After overlaying microarray data from human chondrosarcoma, 204 upregulated and 106 downregulated genes were identified as Hh-responsive Gli binding targets. After overlaying published Gli ChIP-on-chip data from mouse, 48 genes were identified as potential direct downstream targets of Hedgehog signaling with shared GLI binding regions in evolutionarily conserved DNA elements. Among these was BMP2, pointing to potential cross-talk between TGF beta signaling and Hh signaling. Our identification of potential target genes that are unique and common to GLI1 and GLI2 in neoplastic chondrocytes contributes to elucidating potential pathways through which Hh signaling impacts cartilage tumor biology.Excessive Hedgehog (Hh) signaling in chondrocytes is sufficient to cause formation of enchondroma-like lesions which can progress to chondrosarcoma. To elucidate potential underlying mechanisms, we identified GLI1 and GLI2 target genes in human chondrosarcoma. Using chromatin immunoprecipitation (ChIP) sequencing and microarray data,  Hedgehog (Hh) signaling is essential for normal embryonic development, governing cell differentiation and patterning . During Hh signaling is activated through binding of extracellular ligand to the transmembrane receptor Ptch. This binding relieves inhibition of a second transmembrane protein, Smo. The Gli transcription factors are then processed through a mechanism that is incompletely elucidated, but that involves other pathway members , 13. TheThe Gli transcription factors are the effectors of Hh signaling, targeting genes that are involved in growth and development. Identifying transcriptional targets of GLI1 and GLI2 in chondrosarcoma can provide mechanistic insight into the role of Hh signaling in tumor pathogenesis. Previous studies have used chromatin immunoprecipitation (ChIP) and tiling arrays coupled with expression arrays to identify Gli transcriptional targets, including Gli3 targets in the developing mammalian limb , 20. ForWith informed consent, a human chondrosarcoma tumor was obtained directly following surgical excision. As previously described , the tumChIP was performed using the ChIP-IT kit (Active Motif) following the manufacturer's protocol. Briefly, cells were fixed with formaldehyde to crosslink and preserve protein-DNA interactions. Protein-DNA complexes were sheared into small fragments using a Sonic Dismembrator (Fisher Scientific) at power level two for eight pulses of 10 seconds interspersed with 30 seconds cooling on ice. ChIP-grade antibodies against GLI1 (R&D AF3324), GLI2 (R&D AF3526), and negative control IgG (Active Motif) were used to immunoprecipitate protein-bound DNA sequences. Crosslinking was reversed using NaCl and protein was digested using Proteinase K. DNA was purified and subjected to sequencing. We did not repeat sequencing experiments with other ChIP-grade antibodies, so the GLI binding regions identified here are specific to R&D AF3324 for GLI1 and R&D AF3526 for GLI2.http://broadinstitute.github.io/picard) to the bigwig format files with bandwidth of 250-bp, approximately the size of sonicated DNA fragments. IgG reads were subtracted from GLI1 and GLI2 reads during peak detection.Sequencing was performed using the Solexa/Illumina Genome Analyzer II. Libraries of single-end reads of 72-base length were prepared for each of three samples: GLI1, GLI2, and IgG. Analysis was conducted following the ENCODE Data Processing Guidelines . Single-hgug4112a.db‘. For screening of transcription factor motifs in gene regulatory regions we implemented the MATCH algorithm [DNA motif analysis in enriched transcription factor binding regions was performed using the Homer program  with thelgorithm  customizlgorithm , 29.Gene ontology pathway enrichment analysis using differentially expressed genes was performed using the David GO term program for transcriptome analysis. GLI/CTCF-targeted differentially expressed genes were identified from the gene neighborhood defined by the two nearest neighbor genes located up- and down-stream, including the whole intergenic region and gene body. Pathway enrichment analysis on enriched transcription factor binding regions was performed using the GREAT GO term program for ChIP-sequencing data analysis. Human-mouse conserved GLI binding regions were identified using mouse Gli1 and Gli3 datasets , 20 convACTB and GAPDH). Gene expression was calculated according to the comparative threshold cycle (Ct) method using the ΔΔCt formula and values expressed as fold change relative to carrier control. Statistical analyses were performed using a one-tailed t-test.With informed consent, three additional human chondrosarcoma tumors were obtained and processed as described above. Cells were treated with 1μM purmorphamine (Hh agonist) or carrier for 24 hours. RNA was extracted from cells using a modified TRIzol (Invitrogen) protocol as previously described  and reveChIP-sequencing was used to identify genome-wide GLI1 and GLI2 binding regions in human neoplastic chondrocytes. After filtering out the negative control IgG reads, 80,029 GLI1 and 172,630 GLI2 binding peak patterns were detected in the GLI1 fraction and GLI2 fraction, respectively. Criteria for subsequent peak selection included: a) coverage intensity score greater than the mean score plus one standard deviation , b) evolde novo motif analysis was performed on bound regions with and without the Gli-consensus binding motif . Of these, 204 genes and 106 genes respectively contained at least one GLI1, GLI2, or GLI1 and GLI2 co-occupied region, suggesting that they are directly bound and regulated by the Gli transcription factors Y(C/T)CH(T/C/A)GGTGG-3’. Since 53% of GLI1 sites, 53% of GLI2 sites, and 38% of GLI1 and GLI2 co-occupied regions were associated with at least one CTCF binding site within a short genomic distance of 250-bp, this suggests that the GLI binding sites are located in gene-dense regions of the genome.Previous research suggests that promoter-centered chromatin interactions can provide a topological basis for transcriptional regulation . CTCF isDe novo motif analysis was performed to identify additional transcription factor binding sites within these regions. We found enrichment for ZIC4, SNAI2, ID4, HIC1, RUNX1, GLI2, and SMAD2/3/4 binding motifs  regulates extracellular matrix turnover by inhibiting proteases and has been previously implicated in inducing apoptosis in chondrosarcoma , 40. We IGFBP5 contains a GLI2 binding site, is upregulated 1.8-fold with Hh inhibition in microarray data, and shows a trend towards downregulation with Hh activation in real-time PCR data  signaling is suggested to play a role in cartilage tumor formation and progression . The insBMP2 is upregulated 2.2-fold with Hh inhibition in the microarray data (Bone morphogenetic protein-2 (BMP-2) has been implicated in enhancing the migration of chondrosarcoma cells –46. Prevray data , containray data , and shoray data . Furtherray data . Given tray data  and seveRather than pursue further validation or mechanistic studies to elucidate the role of these and other candidates, we provide our data as complete lists  Tables iin vitro and in vivo validation experiments are required to confirm these genes as true Hh targets, and to explore their contribution to chondrosarcoma. We provide evidence suggesting that TIMP3, IGFBP5, and BMP2 are direct targets of Gli-mediated Hh signaling with implications for chondrosarcoma pathology, including potential cross-talk between TGF-beta signaling and Hh signaling. The genes identified in this study as potential Gli targets in neoplastic chondrocytes can inform future studies and ultimately provide mechanistic insights into tumor biology.In this study we identified unique and overlapping GLI1 and GLI2 transcriptional targets in neoplastic chondrocytes taken from primary human chondrosarcoma which is known to exhibit activated Hh signaling , 6. Our S1 FigAfter filtering out reads in the IgG fraction, 80,029 GLI1 and 172,630 GLI2 binding peak patterns were detected. The mean signal intensity of the coverage profile of aligned DNA fragments is approximately 206.8 and 89.0, with the standard deviation of 120.6 and 62.0 for the GLI1 and the GLI2 fractions, respectively.(PDF)Click here for additional data file.S2 FigIdentification of transcription factors which showed differential expression by microarray in regions containing both CTCF and GLI motifs (CTCF-GLI binding regions).(PDF)Click here for additional data file.S3 FigThe Gli1 promoter binding regions (right graph) detected in mouse followed the distribution of signal intensity with mean at 3.1 and standard deviation of 1.4. The Gli3 genome-wide binding regions (left graph) detected in mouse followed the distribution of signal intensity with mean at 5.4 and standard deviation of 2.5. For the genome-wide Gli3 dataset (left graph), binding regions with intensity score greater than 3.0, accounting for over 75% of the dataset, were chosen for analyses.(PDF)Click here for additional data file.S4 FigIndependent chondrosarcoma samples  treated with a Hh agonist. Values are the fold change in gene expression relative to that in carrier-treated control .(PDF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.


CYP1A1 has rarely been studied, especially regarding basal transcription. In this study, we first confirmed that the key regulatory elements of porcine CYP1A1 basal transactivation are in the proximal promoter region using promoter truncation analysis via a dual luciferase assay in a porcine kidney cell line LLC-PK1. Two overlapping cis-elements, the xenobiotic response element (XRE) and GC box, in this proximal region potentially play key roles in the basal transactivation of porcine CYP1A1. Furthermore, using electrophoretic mobility shift assay and chromatin immunoprecipitation, the GC box binding protein Sp1 was confirmed to bind to the proximal promoter of porcine CYP1A1, instead of AhR, the XRE binding protein. In LLC-PK1 cells, by knocking down either Sp1 or AhR, the expression of porcine CYP1A1 at the mRNA level and protein level was significantly downregulated, suggesting both proteins are important for porcine CYP1A1 expression. However, promoter activity analysis in LLC-PK1 cells treated with an AhR agonist and antagonist confirmed that AhR does not participate in the basal regulation of porcine CYP1A1 at the proximal promoter. In conclusion, our study revealed that the proximal promoter is the key regulatory region for porcine CYP1A1 basal expression. Although AhR plays an important role in the transactivation of porcine CYP1A1 expression, the key determinant transcription factor for its basal transactivation is Sp1 at the proximal promoter of porcine CYP1A1.Pigs are commonly used as an animal model to evaluate the toxic effects of exogenous compounds. Cytochrome P450 1A1 (CYP1A1) metabolizes numerous exogenous compounds and is abundantly expressed in the liver, kidneys, and intestines. The high amino acid similarity between human and porcine CYP1A1 indicates that they probably have the same metabolic characteristics. Therefore, understanding the regulatory mechanism of CYP1A1 expression in pigs is particularly important for predicting the toxicology and metabolic kinetics of exogenous chemicals. Currently, the transcriptional regulation of porcine  CYP1A1 expression in pigs is instructive in understanding the metabolism of various drugs in humans.CYP1A1 is one of the most important CYP450 family members for metabolizing multiple exogenous and endogenous substrates such as drugs, carcinogens, steroids, and toxicants . The expDrosophila SL2 cells that specific protein 1 (Sp1), aryl hydrocarbon receptor (AhR) and AhR receptor nuclear translocator (Arnt) interacted with each other and bound to the GC box at the promoter to enhance the transcription of CYP1A1  at the promoter of the gene, thereby activating gene expression  and chromatin immunoprecipitation (ChIP) confirmed that Sp1 binds to the proximal promoter of pCYP1A1.In our study, initially, we confirmed that the key regulatory elements for its basal transcription are in the proximal promoter region using truncated promoter analysis by a dual luciferase assay. Two overlapped CYP1A1 (GenBank Accession No. NC_010449.5) was amplified by PCR from the genomic DNA of porcine liver tissues. This fragment was inserted into the pGL3-Basic vector at Xho I and Mlu I sites to generate the -3424-Luc plasmid. Using this plasmid as a template and the same downstream primer, a series of upstream truncated primers were used to amplify fragments of different lengths. These fragments were inserted into the pGL3-Basic vector at Xho I and Mlu I sites to generate the truncated plasmids. Using primers designed for different mutation patterns, ΩPCR was used to construct different mutation vectors using the -43-LUC plasmid as a template. The open reading frames for the expression of Arnt (GenBank Accession No. NC_010446.5), AhR (GenBank Accession No. NC_010451.4), and Sp1 (GenBank Accession No. NC_010447.4) were amplified with the corresponding primers from cDNA that was reversely transcribed from total RNA extracted from porcine liver cells. The open reading frames were inserted into the Xba I and Hind III sites of pcDNA3.1/myc-His(-) A vectors (Invitrogen). The primers used are listed in Supplementary Table S1.A 3.5-kb fragment  from the 5′-flanking region of porcine 2.LLC-PK1 cells  were cultured in M199 medium, and COS7 cells  were cultured in DMEM medium. All media were supplemented with 10% fetal bovine serum , 1% penicillin G/streptomycin (Invitrogen), 1× SITE (Sigma), 0.1 μM dexamethasone and 0.1 μM insulin (Invitrogen). All cell lines were cultivated at 37°C, 5% COTotal RNA was isolated using TRIZOL reagent (Invitrogen). Total RNA was treated with DNase I  to remove the genomic DNA before performing reverse transcription. Thereafter, 1 μg of RNA was reversely transcribed using M-MLV Reverse Transcriptase (Promega), random primer (6mer) and 10 mM dNTPs (TaKaRa).T-ΔΔC method was used to process data and calculate the relative expression of genes. The primers used are listed in Supplementary Table S1.Real-time PCR was performed using the BioRad CFX96 real-time PCR detection system  according to the manufacturer’s instructions. RT-PCR was performed in 20-μL volumes containing SYBR Green I Dye. The following parameters were used: 94.0°C for 2 min, followed by 40 cycles of 94.0°C for 20 s, 50.0°C for 30 s, and 72.0°C for 30 s. The gene expression levels were normalized using GAPDH as a control. The 2According to the manufacturer’s instructions , RIPA lysis buffer containing 1 mM phenylmethylsulfonyl fluoride (PMSF) was used to extract total cellular protein. The protein concentration was adjusted using the BCA Protein Assay Kit (Pierce). Next, 30 μg of total protein was subjected to 10% polyacrylamide gel electrophoresis, followed by transfer to a PVDF membrane (Millipore). The membranes were blocked in a buffer containing 5% skim milk and 0.1% Tween 20 in Tris-buffered saline  for 1 h at room temperature. Next, the membranes were incubated with antibodies overnight at 4°C. Secondary antibodies were incubated for 1 h at room temperature. The bands were detected using the ChemiDoc MP Imaging system . The antibodies used in this work included anti-GAPDH , anti-Sp1 , anti-AhR , and anti-CYP1A1 .Cells were grown in 24-well plates for 24 h to 70–90% confluence. Next, 0.5 μg of the pGL3-basic plasmid containing the promoter and 2.5 ng of the pRL-CMV plasmid were transfected into cells with 1.5 μL of Lipofectamine 3000 (Invitrogen). The transfection reagent was removed, and then 500 μL of medium with 10% FBS was added to each well after 5 h. After 24 h, the cells were lysed, and the luciferase activities were measured using the Dual Luciferase Reporter Assay System (Promega) on a Turner Designs TD-20/20n luminometer (Promega). The dual luciferase reporter assay system was purchased from Promega . The ratio of the firefly luciferase activity to the Renilla luciferase activity represents the strength of the promoter.Supplementary Table S1.All siRNAs were synthesized by GenePharma (Suzhou). The cells were grown in 24-well plates for 24 h to 70–90% confluence, and then 40 pmol of siRNA and plasmid were transfected into the cells with 1.5 μL of Lipofectamine 3000 (Invitrogen). Non-targeting siRNA (scramble) was used as the negative control. The transfection reagent was removed, and 500 μL of medium with 10% FBS was added to each well after 5 h. After 24 h, the cells were lysed, and the luciferase activities were measured. The siRNA sequences used are listed in For overexpression experiments, COS-7 cells were transfected with the constructs of the Sp1 or AhR gene. The Nuclear Extraction Kit  was used to extract overexpressed nuclear protein from COS7 cells. EMSA was performed using the EMSA Assay Kit . The mixtures containing unlabeled probe, nuclear extract (4 μg) and binding buffer were preincubated at 23°C for 10 min. Next, 0.1 pmol of the biotinylated probe was added and incubated at 23°C for 20 min in a total volume of 9 μL. The mixture was subjected to electrophoresis in 4.5% non-denaturing polyacrylamide [acrylamide/bisacrylamide 29:1 (v/v)] gels, followed by the addition of bromophenol blue in a blank hole as an indicator. The gel was transferred to a nylon membrane (+) after the bromophenol blue appeared at approximately 2 cm from the bottom of the gel. The nylon membrane (+) was crosslinked for 2 min under UV light (254 nm). The nylon membrane (+) was then processed with the EMSA Assay Kit , followed by the detection by chemiluminescence . For competition experiments, 100-fold molar excess of unlabeled probe was used. For supershift experiments, 1 μL of anti-Sp1 , and anti-AhR  were used.CYP1A1 promoter in LLC-PK1 cells was analyzed. The antibodies used in this work included anti-histone H3 , anti-Sp1 , and anti-AhR . The primers used are listed in Supplementary Table S1.According to the manufacturer’s instructions , the enrichment of Sp1 and AhR in the P < 0.05 were considered statistically significant.All experiments were performed independently at least three times. All the data are represented as the means ± standard deviation (SD). Statistical significance was assessed by ANOVA. Values of cis-elements that regulate CYP1A1 expression in the porcine CYP1A1 promoter, DNA fragments with different lengths, spanning from the ATG of the pCYP1A1 gene to -3424 bp upstream were fused upstream of the firefly luciferase gene. Each promoter plasmid and reference plasmid, pRL-CMV harboring the Renilla luciferase gene, were co-transfected into LLC-PK1 cells. Normalized luciferase activity indicates the strength of the promoter for transcription activities. As shown in Figure 1A, the removal of DNA fragments from -3424 to -1981 bp led to the apparent incremental change in firefly luciferase activity, suggesting there are negative regulatory elements in this region to inhibit the basal transcription of porcine pCYP1A1. More importantly, the firefly luciferase activity was apparently decreased when DNA fragments from -43 to -28 bp were deleted, from 27- to 1.7-fold that of the normalized basic control. This suggested that the proximal promoter is the key region for pCYP1A1 transactivation and contains positive regulatory elements between -43 and -28 bp .To identify the 1 was used to analyze the candidate cis-elements in the proximal promoter DNA sequence regarding transcriptional regulation. Two cis-elements, GC box and XRE, were found in this -43 to -28 bp region, and they probably play important roles in pCYP1A1 expression. These two cis-elements overlapped in the region, and the core DNA sequences only have one base difference. Therefore, direct deletion of one cis-element to confirm its role in the pCYP1A1 promoter transactivation is not applicable. To verify the critical roles for the two cis-elements in basal transcription, the key binding sites were mutated, and then the strengths of the mutated promoters were analyzed by the dual luciferase assay. The relative luciferase activity was decreased by 4.5-fold in the plasmid with the mutated GC box and 5.6-fold in the plasmid with mutated XRE . This implied either that both cis-elements were essential for the basal transcription or the mutation abolished the function of non-mutated cis element. The double mutations of the GC box and XRE in the promoter region caused the complete loss of basal transactivity because the relative luciferase activity was even lower than that of the reference control. Our data suggest that the mutation of key binding sites may lead to a combination of repressor in this region. Therefore, a mutation assay cannot confirm whether either one of these two cis elements or both are the key players.The MatInspector programFigures 2A,B, siRNA successfully repressed the expression of Sp1 or AhR, respectively. The protein and mRNA levels of pCYP1A1 following the knocking down of Sp1 or AhR were apparently decreased . This suggested that both transcription factors play important regulatory roles in pCYP1A1 expression. However, when only measuring the transcription in the proximal promoter using the relative luciferase assay, a twofold decrease in transactivity was observed in the Sp1-knockdown cells but not in AhR-knockdown cells . These data demonstrated that Sp1, rather than AhR, affects the regulation of the pCYP1A1 proximal promoter. Taken together, the data proved that, in the proximal region of the pCYP1A1 promoter, Sp1 transactivates the basal expression of pCYP1A1, and AhR does not contribute to the proximal DNA transactivation of pCYP1A1.Next, we further confirmed whether Sp1 or AhR plays a key transactivation role in the proximal promoter region by measuring the relative luciferase activity of the (-43/+157) promoter in the cell lines with the knocking down of Sp1 or AhR. As shown in CYP1A1, which is contradicted to the previous reported that AhR affects the activity of the CYP1A1 proximal promoter . Nevertheless, the (-43/+157) promoter was not changed significantly compared with the relative luciferase activity in β-naphthoflavone-treated LLC-PK1 cells with the activity in untreated control at 24 h . Resveratrol inhibits the binding of AhR to the promoter DNA, thereby AhR activation of gene expression is inhibited. When (-43/+157) promoter plasmids were transfected into cells, similarly, there was no significant change in the relative luciferase activity in resveratrol-treated cells for 24 h . In resveratrol-treated LLC-PK1 cells, pCYP1A1 mRNA was decreased by 18-fold relative to that in untreated cells .As mentioned above, AhR expression in cells does not affect the proximal promoter activity of ppromoter . Two dru nucleus . In β-naThe agonist and antagonist for AhR do not significantly affect the relative luciferase activity of the (-43/+157) promoter plasmid. These data further confirmed that the transcription factor that affects the (-43/+ 157) promoter activity is not AhR.CYP1A1. As mentioned above, it is not applicable to verify the key role of these two cis-elements in the regulation of pCYP1A1 by deletion or mutation of the cis-elements. Therefore, we initially confirmed the binding of Sp1 or AhR to the DNA motif in vitro by EMSA. Sp1 or AhR was overexpressed in COS-7 cells. For Sp1, when the probe was incubated with the nuclear protein, probe migration would lag to form a band. A supershift occurred after the addition of the Sp1 antibody, and the band disappeared after the addition of a 100-fold molar excess of the unlabeled probe, but not after the addition of a 100-fold molar excess of unlabeled and mutated probe . For AhR, it is dubious that AhR bound with the probe, and no supershift band was observed . These data indicated that Sp1 binds at the position of -37 to -7 bp of the pCYP1A1 promoter and then transactivates the expression of pCYP1A1. ChIP was used to verify whether Sp1 and AhR bind to the pCYP1A1 proximal promoter. The binding of Sp1 to the porcine CYP1A1 proximal promoter was fourfold greater than that of the negative control, while the binding of AhR to the porcine CYP1A1 proximal promoter was not significantly different from that of the negative control . Taken together, those data proved that Sp1, but not AhR, binds to the proximal region of the pCYP1A1 promoter.Sp1 and AhR bind to the GC box and XRE, respectively, which are located in the proximal promoter region of pCYP1A1 in pigs is not clear. To analyze the conservation of the regulatory mechanisms of CYP1A1 in humans and pigs, it is necessary to clarify the expression regulation mechanism of pCYP1A1.Cytochrome P450 is a superfamily of enzymes known to metabolize exogenous compounds. Among them, CYP1A1 is well-known for its ability to metabolize drugs and other xenobiotic substances . The pigCYP1A1 promoter DNA showed that the proximal region (-43 to -28) is the key determinant region for pCYP1A1 expression. In this region, two cis-elements were identified, but the core binding sequence is overlapped. We also found that these two cis-elements at the human CYP1A1 proximal promoter overlap and play important roles in human CYP1A1 basal transcription . Furthermore, by knocking down either Sp1 or AhR via siRNA, the expression levels of pCYP1A1 at the mRNA and protein levels were significantly decreased, suggesting that both are important in pCYP1A1 basal transcription. However, using EMSA and ChIP, it was confirmed that only Sp1 binds to the GC box in the proximal promoter. Instead, AhR did not bind to this region, although the expression of pCYP1A1 was drastically decreased in si-AhR cells. This finding suggested that, in the proximal promoter region, Sp1 determines the strength of transcription. AhR probably affected the expression of pCYP1A1 in this proximal region, which harbors other functional XRE sites.Truncation analysis of the pCYP1A1. The high induction of CYP1A1 expression by many exogenous compounds like PAHs, PCBs, and HAHs relies on the AhR-dependent pathway (CYP1A1 through AhR is clear. TCDD increases the level of AhR in the nucleus and induces the expression of CYP1A1 in humans and pigs (Cyp1a1 promoter region of mice, thereby enhancing the expression of Cyp1a1 via an AhR-dependent pathway (Studies have shown that AhR is an important transcription factor that participates in the expression of  pathway . Among tand pigs . In addi pathway .CYP1A1 basal promoter activity is unclear. In our study, AhR was also important for the basal regulation of CYP1A1 in pigs. Intriguingly, we found that the DNA region that regulates pCYP1A1 expression is mainly located proximal to the transcription start site, whereas XRE in this region does not participate in the regulation of pCYP1A1. These data are inconsistent with previous studies. Therefore, we performed promoter strength analysis under the condition that AhR was regulated by its agonist or antagonist to further address the effect of AhR on the proximal promoter of pCYP1A1. β-Naphthoflavone has been reported to enhance gene expression by activating AhR, and resveratrol reduces gene expression by inhibiting AhR (CYP1A1 mRNA, suggesting that AhR binds to the promoter of pCYP1A1. Using the MatInspector program to analyze the 3.5-kb promoter DNA, 12 XREs were predicted to be in the promoter region of pCYP1A1, and 10 of them were located in the region of -819 to -2494 nt upstream of the transcription start site. However, when proximal promoter analysis was applied, it showed that neither activation nor deactivation of AhR showed significant effects on the activity of the pCYP1A1 proximal promoter. Our results demonstrate that AhR regulates the expression of pCYP1A1, but it is not involved in the regulation of the proximal promoter of pCYP1A1.In humans, AhR is important for the basal regulation of CYP1A , but howting AhR . Indeed,CYP1A1 rather than AhR. Sp1 participates in the expression of many CYP450 genes, such as CYP1A1, CYP1B1, CYP2J2, CYP3A29, and CYP3A46 (CYP1A1 expression. In humans, Sp1 activates the CYP1A1 promoter (CYP1A1 expression (CYP1A1 is the main cis-element that plays a regulatory role by recruiting Sp1.Considering only the regulation of this proximal promoter, the luciferase assay clearly suggested that only Sp1 transactivates the basal expression of p CYP3A46 . The amipromoter , and phopression . We alsoCYP1A1 not only functions to metabolize exogenous compounds but also functions in the metabolism of endogenous chemicals, such as polyunsaturated fatty acids . CompariCYP1A1 promoter activity, we found that the proximal promoter is very important for the regulation of pCYP1A1 expression. Two cis elements were found in the proximal promoter region: XRE and GC box with the binding of Sp1 and AhR, respectively. However, only Sp1 plays a transactivation role in the proximal promoter region of pCYP1A1. AhR also regulates the expression of pCYP1A1, but it does not function at the proximal promoter.In summary, by analyzing the porcine XX, JJ, WY, and RC conducted the experiments and data analysis. XX and JW wrote this article. YD and JW conceived the study.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.


HOX Transcript Antisense Intergenic RNA) is largely deregulated in epithelial cancers and positively correlates with poor prognosis and progression of hepatocellular carcinoma and gastrointestinal cancers. Furthermore, functional studies revealed a pivotal role for HOTAIR in the epithelial-to-mesenchymal transition, as this RNA is causal for the repressive activity of the master factor SNAIL on epithelial genes. Despite the proven oncogenic role of HOTAIR, its transcriptional regulation is still poorly understood. Here hepatocyte nuclear factor 4-α (HNF4α), as inducer of epithelial differentiation, was demonstrated to directly repress HOTAIR transcription in the mesenchymal-to epithelial transition. Mechanistically, HNF4α was found to cause the release of a chromatin loop on HOTAIR regulatory elements thus exerting an enhancer-blocking activity.The expression of the long noncoding RNA HOTAIR ( HOX Transcript Antisense Intergenic RNA [The lncRNA HOTAIR  is a tenic RNA –6. Consienic RNA , 4, 5, wenic RNA , 7, 8.Reprogramming of epithelial cells relies on the transdifferentiation processes, known as epithelial-to-mesenchymal transition (EMT), and the reverse mesenchymal-to-epithelial transition (MET). EMT/MET plasticity is essential for organogenesis, development, wound healing, and regeneration, and is aberrantly activated in fibrosis, tumor progression, and metastasis . We receDespite the strong correlation between HOTAIR expression, EMT, and tumor progression , 11–13, Several evidence demonstrated the role of the orphan nuclear receptor hepatocyte nuclear factor 4-α (HNF4α) as master regulator of differentiation and epithelium formation in hepatocytes , 16 as wHnf4α knockout  in vitro hepatocyte cells able to undergo EMT/MET dynamics , 24–26, cre mice ), and , as in ref. , by usin-ΔCt method and normalized with respect to the housekeeping gene 18 S (mouse) or L32 (human). The list of primers is shown in Supplementary Table Total RNAs were obtained from liver samples by TRIzol  or from cells by RNAeasy Mini Kit . Reverse transcription was performed by using the iScriptTM c-DNA Synthesis Kit  and qPCR reactions on cDNAs by using GoTaq® qPCR Master Mix . The relative amounts were obtained by 2Cells were lysed in Laemmli buffer, subsequently the proteins were resolved on sodium dodecyl sulfate polyacrylamide gel electrophoresis and transferred to Nitrocellulose membrane 0.45um . The following primary antibodies were used for immunoblotting: α-HNF4α , α-Snail , α-E-cadherin , and α-GAPDH , used as a loading control. The immune complexes were detected with horseradish peroxidase-conjugated species-specific secondary antiserum  then by enhanced chemiluminescence reaction .ChIP analysis was performed as reported previously  by using3 C assays were performed as described previously , 34. AftThe primers used for 3 C sample amplifications were reported in Supplementary Table t test was used for statistical analyses. All the tests were one-tailed and a p value < 0.05 was considered statistically significant (* symbol). Data were obtained from independent experiments performed at least in triplicate and expressed as mean ± SEM.The For liver samples analysis the Mann–Whitney test was used. Data were obtained from six wild-type and six knockout mice and expressed as mean ± SEM.http://www.ensembl.org) and submitted to MatInspector Professional , using the vertebrate matrix library and optimized thresholds, to identify putative HNF4α-binding sites.The regulatory sequences (up to 1 kb upstream of transcription start site) of murine and human HOTAIR and human E-cadherin were obtained from ENSEMBL , vimentin (VIM), and fibronectin (FN1), and negative regulation of the epithelial (and Snail-target) genes E-cadherin (ECAD), HNF1A, and HNF4A . ChIP assays were then performed to investigate both Snail occupancy and the local H3K27me3 status of epithelial promoters. Snail was found bound to its consensus binding sites (E-boxes) on ECAD promoter in both cell lines  has a role in the control of Snail repressive activity.To extend previous studies on the role of HOTAIR in the Snail-mediated repression of epithelial genes, we focused on the in vitro model of colon carcinoma progression represented by SW480 and SW620 cell lines, established, respectively, from a primary adenocarcinoma of the colon and from a secondary tumor from the same patient . HOTAIR F4A Fig. . With reion Fig. . Notablyion Fig. . Moreoveion Fig. . These ones Fig.  but the nes Fig. , in whicnes Fig. . These dThe evidence of HOTAIR induction in EMT and tumor progression , 11 and SNAI1, SNAI2, HMGA2, FN1, VIM) both in MET and in the stable maintenance of the epithelial identity [Hnf4a-null mice  the master factor HNF4α directly represses several master EMT regulators and mesenchymal genes  HNidentity , 23; (iiidentity . Given tidentity ) that HNbERT2cre ) and mattes Fig. , previoutes Fig. . Notablytes Fig. . We nextECAD and HNF1A mRNA, negative regulation of the mesenchymal markers VIM, FN1, and MMP2 mRNAs and of the master factor SNAI1 mRNA  located 150 Kb downstream of the HOTAIR TSS [One of the few-reported observations on HOTAIR transcriptional regulation includes characterization in human breast cancer cells of an enhancer, termed TAIR TSS . The HDETAIR TSS . We therTAIR TSS , Fig. 7cThe main finding of this study is the identification of a molecular mechanism controlling the expression of the oncogene HOTAIR. HNF4α, a master factor of MET and inducer of epithelial differentiation, was found to directly repress HOTAIR transcription thus antagonizing the EMT of both hepatocytes and colon cancer cells. Mechanistically, our data revealed an enhancer-blocking activity of HNF4α by influencing chromatin topology of HOTAIR gene regulatory sequences Figs.  and 8.FiDespite the proven oncogenic role of HOTAIR, its regulation is still poorly understood. HOTAIR is a low-copy lncRNA , which eHnf4a-null mouse model, and HOTAIR induction pairs the HNF4α functional impairment in the TGFβ-induced EMT. Moreover, ChIP analysis revealed that HNF4α directly binds to the HOTAIR promoter and its binding inversely correlates with HOTAIR transcription. The inverse correlation between HOTAIR and HNF4α expression was confirmed in colon cancer cells, with HOTAIR upregulation in EMT-like SW480 cells, expressing low levels of HNF4α, and HOTAIR downregulation in MET-like HNF4α-positive SW620 cells. Moreover, this inverse correlation was observed also in SW480 cells during HNF4α-induced MET and in SW620 undergoing a TGFβ-mediated EMT or after HNF4α silencing. The ChIP data suggest that in this cell type, HNF4α directly binds to the HOTAIR promoter and regulates HOTAIR gene repression.HNF4α is a well-known (i) master factor of epithelial cell differentiation –17, 39; Furthermore, our results integrate the well-established knowledge about the role of HNF4α as a transcriptional repressor with a new function, attributing to this factor an enhancer-blocking activity. Others previously reported on a HOTAIR enhancer able to positively regulate HOTAIR gene expression by DNA looping . Here, bOur data should be considered in line with other dynamic changes of higher-order chromatin structures, previously described for specific loci during differentiation , 43 or iSupplemental Table 1


Plasmodium species express variant antigens which may mediate immune escape in the vertebrate host. In Plasmodium falciparum, the rif gene family encodes variant antigens which are partly exposed on the infected red blood cell surface and may function as virulence factors. Not all rif genes are expressed at the same time and it is unclear what controls rif gene expression. In this work, we addressed global rif transcription using plasmid vectors with two drug resistance markers, one controlled by a rif 5′ upstream region and the second by a constitutively active promoter. After spontaneous integration into the genome of one construct, we observed that the resistance marker controlled by the rif 5′ upstream region was expressed dependent on the applied drug pressure. Then, the global transcription of rif genes in these transfectants was compared in the presence or absence of drugs. The relative transcript quantities of all rif loci did not change profoundly between strains grown with or without drug. We conclude that either there is no crosstalk between rif loci or that the elusive system of allelic exclusion of rif gene transcription is not controlled by their 5′ upstream region alone.All  Plasmodium species which cause malaria in humans still is a challenge for the public health predominantly in underdeveloped countries. Plasmodium falciparum alone is still responsible for 445000 deaths per year, mostly children under five years or pregnant women1. Part of the virulence exerted by Plasmodium is caused by the presence of variant antigens expressed on the surface of the host’s infected red blood cells. Members of the best-characterized family of variant antigens, the P. falciparum erythrocyte membrane protein 1 (PfEMP1), play a central role in immune evasion. PfEMP1 are encoded by approximately 50–60 different var genes2 which are highly recombinogenic4, possibly through specific three-dimensional DNA conformations near breakpoints5, and possess a modular structure6. In order to successfully evade immune mechanisms exerted by the human host, var gene transcription is tightly controlled in a way that normally only one or two var genes are expressed. A number of factors are involved in this control and these include not only sequences in the 5′ upstream regions of var genes8, including untranslated ORFs10, the pairing of var promoters and var introns11, but also specific DNA/chromatin binding factors12 and the involvement of several chromatin modifiers (reviewed in13). Recently, the participation of non-coding GC-rich RNAs in var transcription control was shown14. The current model of var transcription regulation also suggests a specific subnuclear site in which var transcription occurs and to which var loci translocate in order to be transcribed. However, the exact factors and dynamics which orchestrate this process and license one var locus for transcription while excluding all other var loci are largely unknown. Still more elusive is what determines that a var locus and its associated histone modifications switch from an active to a silent state or vice versa.The infection with one of the five Plasmodium species but also in murine species is the pir (Plasmodium interspersed repeat) gene family15, and the biological function of gene products from this family is not well understood. Recent results indicate that their encoded proteins may function at different points of the parasite-host interface16. If results from Plasmodium chabaudi can be extrapolated to all Plasmodium species, pir transcription seems to be reset during mosquito passage and reinfection17 and earlier evidence pointed to transcriptional diversity18 and quick switching in several models20. A recent study implied a specific PIR protein of P. falciparum  as a factor involved in the pathogenic process of erythrocyte rosetting22. Another study revealed that a specific motif in RIFINs promoted binding to leucocyte immunoglobulin-like receptor B1 (LILRB1) or leucocyte-associated immunoglobulin-like receptor 1, thereby inhibiting activation of B-cells and natural killer cells which express the LILRB1 receptor23. This turns evident that at least some RIFINs can be understood as virulence factors. Importantly, VIR proteins of Plasmodium vivax also appear to mediate cytoadherence and participate in pathogenic processes and probably immune evasion25. In P. falciparum, the vast majority of rif genes are localized adjacent to var genes, often in a tandem organization. In version 36 of PlasmoDB, there are 221 genes in the 3D7 strain genome which encode PIR proteins. Of these, 158 are full-length RIFINs, 27 are truncated or defect RIFINs, and the remaining are STEVOR (subtelomeric variant open reading frame) or truncated or defect STEVOR. RIFINs can be categorized into two major groups of rif genes and RIFINs: A and B. These groups differ by a short conserved 25mer peptide sequence in the first half of the protein which is present only in the 97 A-group RIFINs in the P. falciparum strain 3D7 genome26. While the A-group RIFINs seem to be exported to the infected red blood cell (IRBC) surface, B-group RIFINs are believed to remain associated with the vesicular network in the IRBC (Maurer’s clefts). It is still unclear what controls rif transcription, a recent study pointed to the transcription factor AP2-SP27 which somehow seems to influence transcription in blood stage P. falciparum28. While earlier studies indicated that rif and var gene transcription may be controlled by similar factors29, no clear-cut allelic exclusion mechanism could be detected in other studies which specifically addressed rif transcription or switching30. A drawback in the study from Howitt and colleagues29 was that the tested rif promoter controlled the unique drug resistance marker blasticidin deaminase in their construct, turning a considerable baseline activity of the promoter essential in order to obtain transfectant parasite lines. This did not permit a genuinely “switched-off” state of the rif 5′ ups-controlled transgene. In another study, the activity profile of a 5′-rif upstream region appeared more related to var genes31 and no significantly different regulation could be discerned upon activation. Also, no “crosstalk” – understood as the influence of the activity of one promoter on the activity of remaining promoters - between 5′ upstream regions such as occurs in var gene regulation was detectable. In contrast, in the study by Goel and colleagues, phenotypic selection procedures pointed to the expression of a single rif gene in parasites with PfEMP1-independent rosetting22, supporting the view that allelic exclusion and crosstalk may occur. In order to settle the question if there are allelic exclusion and crosstalk between rif 5′ ups regions, we used three different rif 5′ upstream regions in bicistronic transfection plasmids. Previously, this approach was successfully applied on var promoters32. After transfection, we divided transfected parasite lines and in one culture we selected the growth of parasites which actively transcribed a drug resistance marker (human dihydrofolate reductase). Afterwards, we compared rif transcripts between pyrimethamine-derivate sensitive and resistant lines by RNAseq.Another major variant gene family which is not only found in human or primate rif genes and the proteins they encode, RIFINs, is unclear. In order to test if rif genes are expressed in a similarly coordinated way as var genes33, we created bicistronic plasmids similar to those used by Voss7 or Witmer31 and colleagues. In these, one resistance marker gene was controlled by the constitutive plasmodial heat shock protein 86/90 promoter and the other by potentially inducible rif 5′ upstream sequences. We chose three rif upstream sequences (ups) based on previous observations using wild-type parasites of the 3D7 lineage where rif transcripts from these 5′ upstream regions were detected20. This assured that functional promoters were being used. The size (~1500 nt) of the inserted putative promoter sequence was chosen observing the distance to adjacent ORFs . When testing the copy number of the hDHFR gene, we observed that the transfectant line containing the PF3D7_0200700 5′ rif ups showed only one copy. In contrast, the hDHFR gene in a freshly transfected parasite line containing the Photinus luciferase encoding plasmid pCLH (a derivate of pDC1034 where the chloramphenicol acetyltransferase was changed for a luciferase coding sequence from pGL2 (Promega)) appeared in approximately three copies per cell , we conducted a Southern blot analysis using a digoxigenin-labeled bsd-gene fragment as a probe. The observed pattern indicated that recombination occurred at the hsp86/90 locus and not at the PF3D7_0200700 rif 5′ locus . In parasites that were not grown in the presence of WR99210, few hDHFR transcripts from the modified PF3D7_0200700 locus were detected (RPKM ~3), corroborating previous qPCR results. In contrast, higher RPKM values for hDHFR as the most abundantly detected rif transcripts were observed in parasites grown in the presence of WR99210. This indicates that the hDHFR-controlling rif promoter can be either active or inactive, pre-requisites of a variant gene promoter. Also, the RPKM values of the modified PF3D7_0200700 were in the same range as other simultaneously active rif promoters . When the relative rif transcript quantities from other loci were compared between parasites grown under WR99210 pressure or not, no profound changes were found. This can be interpreted that the activity of the modified PF3D7_0200700 rif promoter did not influence transcription from other loci. Such a result is in contrast with similar experiments using var promoters where the activity of a var 5′ ups led to a substantial silencing of the remaining genomic var loci7. When analyzing the RPKM values of all transcripts , we observed that only one rif B type transcript was detected in slightly elevated levels in both treated or untreated parasites, while several rif A-type transcripts were present  and Giardia lamblia36 to Plasmodium. Each parasite seems to have developed different molecular mechanisms to ensure that antigenic repertoires are not prematurely exhausted. In Giardia trophozoites, an RNAi-based mechanism enables the translation of a single variant surface antigen per parasite37. In Trypanosoma brucei, selective variant surface antigen (VSG) production is controlled at the transcriptional level and also through genetic recombination. Single vsg genes are transcribed by RNA Polymerase 1 at a specific subnuclear expression site38 and the activation of vsg expression sites is associated with specific chromatin modifications (reviewed in39). Var gene expression in P. falciparum is tightly controlled at the transcriptional level in ring-stage parasites40 and all but one or two sites remain silenced. Silencing of sites is associated with a number of specific chromatin modifications, mainly at histone H3 which - when trimethylated at lysine 9 - recruits heterochromatin protein 112, initially perceived as a landmark of silenced chromatin in different cell types41. A still not answered question is why not all var sites are silenced and the reason for this possibly lies in the concentration of ncRNAs transcribed from a number of GC rich regions present in the nucleus which somehow seem to coordinate gene counting14. Overproduction of members of these ncRNAs lead to the simultaneous transcription of var genes – an effect which is also observed when histone deacetylases SIR2A and SIR2B are repressed or deleted42. Here, we tried to interfere with the transcription of members of the rif gene family using an approach that was successfully applied to monitor var gene transcription. Interestingly, from three different constructs, only one presented a variable transcription activity, which may be considered as a pre-requisite of the corresponding RIFIN to function in antigenic variation. For the other two constructs, which also did not show integration at genomic sites, we found either a permanently activated or silenced status. Notably, all tested 5′-upstream regions have several, almost completely identical regions in the genome but only one of the rif genes controlled by these identical regions seemed transcriptionally active to the same degree as the transgene . This var locus – PF3D7_0400200 – is annotated as a pseudogene and consists only of exon 2. PlasmoDB predicts also the presence of the var intron, which itself is also a promoter. It is unclear if RNA from this site is involved in rif transcription regulation. Our data do not support co-regulation of rif and var genes. Of note, the material analyzed in our study may also not permit any conclusion about rif-var co-regulation, since RNAs from middle/late trophozoite stage parasites were employed. Normally, var transcription has ceased in trophozoites 20 h post reinvasion43. It must also be reinforced that the shown RNAseq results are unique for this specific experiment. It may be expected that the rif genes which appear transcribed in the current samples change over time due to switching and that in another experiment different, dominant rif transcripts are detected. Additionally, it is unclear if the observed rif transcripts occurred in the same parasites or if they originated from different parasites, concomitantly with the activated PF3D7_0200700 locus in all parasites. Also, it appears that the untreated sample was slightly advanced in the erythrocytic cycle since a number of schizont related genes such as MSPs showed more transcripts in the sample not treated with WR99210 compared to the treated sample . Given the ambiguous results for both rif 5′ ups PF3D7_0900500 and PF3D7_1300400 which are either not integrated or may have been rearranged during the transfection procedure, no further conclusions can be drawn why constructs containing these 5′ ups led to the observed results of permanent silencing or activity, respectively.Based on our data, it may be postulated the chromosomal context surrounding rif promoted hDHFR was partially lower than in the related study from Howitt29 or Witmer31 and colleagues. This may be due to the fact that we used low concentrations of blasticidin for selection. Howitt and colleagues used 2 or 10 µg/ml blasticidin and copy numbers at 2 µg/ml were in the same range or slightly higher than in our episomal constructs. Witmer and colleagues also used 2.5 µg/ml blasticidin but their plasmid backbones contained the TARE/rep20 element, known to improve plasmid segregation44. When we compared results of the hDHFR marker transcript in the transgenic PF3D7_0200700 parasite line growing or not in the presence of WR99210, we found smaller discrepancies between the “on” and “off” in qPCR than in RNAseq. The reason for this may lie in the differing range of linearity of both techniques, although this was not specifically tested for.Here, the copy number of plasmids encountered in parasite lines bearing most probably episomal forms of rif gene family, specifically of the RIFIN A subset, is most probably not controlled by a mechanism related to allelic exclusion as is valid for var genes and that almost 100% sequence identity in rif 5′ ups regions is not sufficient to predict promoter co-activation or silencing. However, not all rif genes are transcribed meaning that there still must be some kind of controlled activation and repression. Considering the results from Guizetti and colleagues14, it may be postulated that ncRNAs are also involved in the activation of rif loci, with the difference that these ncRNAs allow for activity from multiple loci – similar to what is seen for var genes when certain ncRNA from GC rich regions are overexpressed14. From the study of Guizetti and colleagues, it is not clear what influence the var relevant ncRNAs had on rif gene transcription although these authors speculated that a co-regulation could happen. Importantly, there are ncRNAs for most rif loci with yet elusive function45. A specific transcription machinery in the periphery of the nucleus was postulated for var genes48. To date, it is unclear if rif genes are also transcribed from the same machinery. This could be elucidated by RNA FISH or other adequate methods to monitor nuclear substructures, and the created parasite line may be useful for this kind of experiment. It also still remains elusive if the B subfamily of rif genes is differentially regulated, given the fact that we found only one B-type rif gene activated in our cultures.As a central result, we showed that transcription of the 2, 5% CO2, 5% O2 atmosphere or in candle jars as described earlier49. Human blood and plasma were obtained from the local blood bank and ethical clearance for using this blood for this research was granted by the Ethics Committee of the Institute of Biomedical Sciences at the University of São Paulo (No. 842/2016). The medium was changed daily or every two days when parasitemias were low (<0.5%). Parasitemias were checked by Giemsa-stained thin blood smears. For transfection, the protocol suggested by Hasenkamp et al.50 was used. Essentially, 150 µl of cytomix-washed fresh red blood cells were electroporated in a BioRad Gene Pulser at 310 V, 960 µF with 40 µg purified plasmid and later mixed with 2*107 plasmagel-purified51 schizont stage parasites. On day 2 after transfection, Blasticidin (Sigma) was added at 2.5 µg/ml to the medium. At day 6 after addition of the drug, no more viable parasites were visible and the medium was changed every two days until the appearance of parasites on days 17–25 post-transfection.Parasites (strain NF54) were cultured under biological level 2 conditions at 5% hematocrit in human B+ blood supplemented with 0.5% Albumax 1 (Invitrogen) or 10% human B+ plasma in RPMI and 0.23% sodium bicarbonate under a 90% N52 was inserted. The blasticidin-deaminase coding sequence was excised from pBMNL106P-PpLuciBlast53  and inserted into the vector. Then, the hsp86 terminator sequence was inserted from pPF86 via SalI and BamHI. In this plasmid, the hDHFR resistance cassette from pRESA-GFP-HA54 was inserted via EcoRI/EcoRV inserting in EcoRI/SmaI. This plasmid was used to exchange the Calmodulin promoter for a 5′ upstream region from three rif genes which were previously shown to be transcribed in wild-type 3D7 cultures20. The putative rif promoter regions were amplified using oligonucleotides (forward/reverse) ctcgagatataaatttgtaaaaaccatgtg/ggatccttaattgtgatacgtatattatttaatg , ctcgagtattatatttttatatataattattcgtg/ggatccatttaatgtgatacttatattattttatg , and ctcgagatgtaatatattattatgttaatattc/ggatcctattgtgatacgtatattattttatg . The amplified fragments were 1400 to 1500 nt and the identity of the sequences was confirmed by semiautomatic sequencing in an Applied Biosystems 7550 sequencer. An outline of the different rif 5′ upstream region containing plasmid is given in Fig. The bi-cistronic plasmid used here is based on the pTZ57 (Thermo/Fermentas) backbone, where a cassette containing the hsp86 promoter fragment (BglII-NcoI) from pPF8651 and subsequent Sorbitol lysis55 and then harvested after another reinvasion. harvested in ring, trophozoite or schizont stage forms. Harvested IRBC were treated with 0.1% Saponin for 10 min at RT and then pelleted at 12000 g/4 °C for 5 min, washed once in 1 ml PBS and then resuspended in a volume of 100 µl using TE. Afterwards, 1 ml Trizol (Invitrogen) was added and the sample was stored at −80 °C until use. Total RNA was prepared following the Trizol protocol provided by the manufacturer. Final total RNA was dissolved in 20 µl RNAse free water and stored at −80 °C until use.After outgrowth of parasites resistant to 2.5 µg/ml Blasticidin, parasites were split into two parallel cultures and cultivated in RPMI/Albumax supplemented with either 2.5 µg/ml Blasticidin/2.5 nM or 5 nM WR99210 or solely 2.5 µg/ml Blasticidin. After 4 reinvasion cycles, parasites were synchronized by plasmagel floatation56 using 5× Hotfire Pol SYBR Mix (Solis Biodyne Inc.) on an Eppendorf realplex2 thermocycler. In order to monitor the hDHFR transcription controlled by rif upstream regions, the following oligonucleotides were employed: forward 5′-ctggttctccattcctgagaag/reverse 5′-ttgtggaggttccttgagttct. These oligos were predicted using Primer3 online software57 using the same settings as used for the design of var oligos and the internal control oligonucleotide pair for the amplification of seryl tRNA ligase (PF3D7_0717700)58. Relative transcript quantities were then calculated by the 2−ΔCt method59 using the seryl tRNA ligase transcript as endogenous control. The performance of the hDHFR oligonucleotide pair does not differ from seryl t-RNA ligase specific oligos (data not shown). To test for integration of plasmids, genomic DNAs (gDNA) were prepared from parasite cultures using the Promega genomic DNA preparation kit and aliquots of the gDNAs were tested combining forward and reverse real-time PCR oligos for hDHFR (see above) and blasticidin deaminase . PCRs were performed using Thermo/Invitrogen Elongase with the following thermocycling program: 94 °C, 40 s; 54 °C, 40 s; 65 °C, 4 min, over 30 cycles.Total RNA was converted to cDNA using the previously published protocolP. falciparum genome available in the Ensemble Genome database (Release 26) and to generate gene reads count table used in the following pipelines. Two packages built in Bioconductor60 were used for further analysis: edgeR61 and limma62. The first was used to filter and normalize the data set, while linear modeling and empirical Bayes to assess differential expression were performed with the limma package. Finally, the RPKM values of trophozoite-derived cDNA from cultures which were treated with WR99210 or not were loaded in MS Access and filtered for product ID containing “rif”, and the corresponding RPKM values for each rif gene were plotted against their ID.Total RNA was isolated from the harvested trophozoite-stage parasites with Trizol reagent following the manufacturer’s instruction. The concentration of the isolated RNA was quantified using a Nanodrop device  and the integrity of the RNA was measured by a 2100 Bioanalyzer . Paired-end sequencing cDNA libraries were constructed from two samples (grown with or without 2.5 nM WR99210 for 6 reinvasions) using a TruSeq RNA Sample Preparation Kit v2 low sample (LS) protocol , based on the manufacturer’s instructions. RNAseq was conducted in an Illumina NextSeq500 sequencer following the recommendations of the provider using mid output flow cells and a total of 10 million reads per sample. CLC Genomics Workbench 7.01 platform was used to remove the adapter and assess reads quality from the raw reads. The same platform was used to subject reads to the reference PF3D7_0200700 parasites, using the Wizard® Genomic DNA Purification Kit (Promega). 5 μg of each gDNA and 25ηg of plasmid DNA (pDNA) from the pTZ57PF3D7_0200700 construct, were digested using SpHI (Thermo Fisher Scientific). The probe was amplified using standard PCR conditions with digoxigenin-dUTP from DIG High Prime DNA Labeling and Detection Starter Kit I (Roche Diagnostics), using the Blasticidin deaminase cassette from the pTZ57PF3D7_0200700 construct as a template. The oligonucleotide primers used were 5′- atgggaaaaacatttaacatttc-3′ and 5′-aacacaaaacaatctggtgcat-3′. The Southern procedure was performed following the protocol provided by the manufacturer of the labeling kit (Roche), using Hybond N membranes  and a hybridization temperature of 44 °C. All washings steps were performed at room temperature.Genomic DNA was isolated from the WT (NF54) and NF54::pTZ57Supplementary FiguresSupplementary Dataset 1


We found that the ONECUT transcription factor sequence motif was strongly associated with differential chromatin accessibility between iNeurons and fibroblasts. All three ONECUT transcription factors associated with this motif  induced a neuron-like morphology and expression of neuronal genes within two days of overexpression in fibroblasts. We observed widespread remodeling of chromatin accessibility; in particular, we found that chromatin regions that contain the ONECUT motif were in- or lowly accessible in fibroblasts and became accessible after the overexpression of ONECUT1, ONECUT2 or ONECUT3. There was substantial overlap with iNeurons, still, many regions that gained accessibility following ONECUT overexpression were not accessible in iNeurons. Our study highlights both the potential and challenges of ONECUT-based direct neuronal reprogramming.Remodeling of chromatin accessibility is necessary for successful reprogramming of fibroblasts to neurons. However, it is still not fully known which transcription factors can induce a neuronal chromatin accessibility profile when overexpressed in fibroblasts. To identify such transcription factors, we used ATAC-sequencing to generate differential chromatin accessibility profiles between human fibroblasts and iNeurons, an  Reprogramming of somatic cells directly into neurons has previously been achieved by overexpression of transcription factors (TFs)  and by TChromatin accessibility is a key feature of cell type identity. Accessible chromatin, or open chromatin regions (OCRs), are highly cell type-specific and are strongly correlated with where TFs bind to the DNA . TF DNA in vitro neuronal model system. We generated ATAC-seq profiles for iNeurons and human fibroblasts and used ATAC-seq fragment count as a proxy for chromatin accessibility. We found that ONECUT1, ONECUT2 and ONECUT3 were the TFs most strongly associated with differential chromatin accessibility, and that individual overexpression of these TFs in fibroblasts resulted in induction of neuronal characteristics and rapid remodeling of chromatin accessibility within 2 days.In general, however, the TFs that can induce chromatin accessibility associated with neurons are not fully known. Here, our aim was to identify additional TFs that can induce chromatin accessibility associated with neurons when overexpressed in fibroblasts. It has previously been shown that overexpression of Neurog2 differentiates human induced pluripotent stem cells (hiPSCs) into functional neurons (iNeurons) . Here, wThe fibroblasts lines  were culiNeuron differentiation was performed as described previously . BrieflyThe validation experiments consisted of overexpressing OC1/2/3 in human adult skin fibroblasts and were performed as follows. On day –2, 20 000 fibroblasts were plated in 1 ml fibroblast medium in each well of a twelve wells plate (Corning). On day –1, cells were transduced with either only the Bclxl, OC1, OC2 or OC3 vector or the Bclxl vector in combination with the OC1, OC2 or OC3 vector . TransduCells were fixed in ice-cold 4% (mass/vol) paraformaldehyde in PBS, permeabilized with 0.2% Triton X-100 in PBS, incubated with blocking buffer consisting of 10% (vol/vol) goat serum in PBS, incubated with the primary antibodies rabbit anti-ONECUT3  and mouse anti-TUBB3  in 5% (vol/vol) goat serum in PBS at 4°C overnight, incubated with the conjugated secondary antibodies (Invitrogen) in 5% (vol/vol) goat serum in PBS at RT for 1 h, incubated with 0.01% (vol/vol) Hoechst (Invitrogen) in PBS at RT for 10 min, and finally mounted onto slides with fluorescence mounting medium (Dako). Imaging was performed using an Axio Imager Z1 (Zeiss). CellProfiler  was used2 and 0.2% [vol/vol] IGEPAL, in Milli-Q water/PBS [1:1]) to the cell pellet (iPSCs and fibroblasts) or to the cells on the plate (iNeurons), followed by mechanically dissociating the cells using a pipette. Nuclei were pelleted, washed, and incubated with the Tn5 transposase in a shaking heat block at 37°C/650 rpm for 1 h. The reaction was stopped by adding 5 μl clean-up buffer (0.9 M NaCl and 0.3 M EDTA [pH 8] in nuclease-free water), 2 μl proteinase K (10 mg/ml) and 2 μl 5% SDS. DNA was purified using normal-phase 2× AMPure bead purification (Beckman Coulter), PCR amplified for 8 PCR cycles, size-selected using reverse-phase 0.55× AMPure bead purification, purified using a Qiaquick column (Qiagen), PCR amplified for another eight PCR cycles, and again purified on column. Sequencing was performed on an Illumina NextSeq 500 using HighOutput kit v2 for 75 cycles (paired-end 2 × 43 bp). The number of mapped ATAC-seq reads can be found in In short, nuclei were isolated by adding 500 μl lysis buffer  and RNA-seq library preparation was performed using the SMARTer Stranded Total RNA Sample Prep Kit  (Clontech). Sequencing was performed on an Illumina NextSeq 500 using HighOutput kit v2 for 75 cycles (paired-end 2 × 43 bp). The number of mapped RNA-seq reads can be found in iNeuron-Fibroblast union: A reduced union CR set made by combining the iNeuron and fibroblast MACS2 peaksets and merging overlapping peaks to one peak.ATAC union: A reduced union CR set made by combining the Bclxl, OC1+Bclxl, OC2+Bclxl, OC3+Bclxl, fibroblast, iPSC and iNeuron MACS2 peaksets and merging overlapping peaks to one peak.DNase union: A union set of CRs with DNase I accessibility in at least one of 127 ENCODE/ROADMAP cell types.We used three different union CR sets:design ∼ cell line + cell type, to take into account both cell line and cell type. We considered CRs/genes differentially upregulated if the Benjamini-Hochberg-adjusted P-value < 0.01 and the log2(fold change) > 1. Similarly, we considered CRs/genes differentially downregulated if the Benjamini-Hochberg-adjusted P-value < 0.01 and the log2(fold change) < –1.Both differential chromatin accessibility and differential gene expression were determined using DESeq2 . As inpuOC1-up, OC2-up and OC3-up; less accessible in OC1+Bclxl, OC2+Bclxl or OC3+Bclxl compared to Bclxl as respectively OC1-down, OC2-down and OC3-down; more accessible in iNeurons than in fibroblast as iN-Fib up; less accessible in iNeurons than in fibroblasts as iN-Fib down. We defined the differentially expressed gene sets in the same way.Using these criteria, we defined the following sets of differential accessible CRs: more accessible in OC1+Bclxl, OC2+Bclxl or OC3+Bclxl compared to Bclxl as respectively Detailed Materials and Methods can be found in the supplementary materials.2(1+FPKMiNeuron) – log2(1+FPKMfibroblast), on the presence of a TF motif M using a simple linear regression model: cis-bp database , ONECUT2 (OC2) and ONECUT3 (OC3), are associated with the CUT_Homeodomain_Average_9 motif and two TFs, CUX1 and CUX2, are associated with the CUT_Homeodomain_Average_6 motif. We generated RNA-sequencing (RNA-seq) data for the same biological samples to determine whether a complete lack of gene expression may be used to rule out one of these TFs as binding to the motif in iNeurons. This was not the case: all three ONECUT TFs were among the highest expressed TFs in iNeurons and were not expressed in fibroblasts Figure  and F. CWe selected OC1, OC2 and OC3 (OC1/2/3) as candidate chromatin remodeling factors for further experimental validation and characterization.We used a doxycycline-inducible lentiviral construct to overexpress the ONECUT factors individually in three human fibroblast lines Figure . PreviouWe found that OC1/2/3 overexpression induced a neuron-like morphology as early as two days after induction in fibroblast medium Figure , both wiOC1-up, OC2-up and OC3-up; (ii) CRs that were less accessible after OC1, OC2 or OC3 overexpression in fibroblasts as respectively OC1-down, OC2-down and OC3-down; (iii) CRs that were more accessible in iNeurons than in fibroblast as iN-Fib-up; (iv) and CRs less accessible in iNeurons than in fibroblasts as iN-Fib-down.We next investigated whether the morphological changes were accompanied by changes in chromatin accessibility. We characterized chromatin accessibility with ATAC-seq two days after induction of OC1/2/3. As a control, we performed ATAC-seq of fibroblasts only overexpressing Bclxl Figure . We usedWe found that chromatin accessibility was extensively remodeled following OC1/2/3 overexpression Figure . RespectOC1-up) were also upregulated by OC3; vice versa, 50% of regions (OC3-up) upregulated by OC3 were also upregulated by OC1  were also shared between the ONECUT factors  > 2) following overexpression of respectively OC1, OC2, OC3  gained accessibility following OC1/2/3 overexpression Figure . 21 599 3 Figure . In cont3 Figure . Thus, oOC1-up, OC2-up and OC3-up CRs containing a ONECUT motif . We found that the OC1/2/3 conditions were more similar to each other and to fibroblasts than to iNeurons Figure . Thus, wSecond, we compared the chromatin accessibility changes induced by OC1/2/3 overexpression, denoted by Δ, to the difference in chromatin accessibility between iNeurons and fibroblasts, denoted by Δ. For all three ONECUT factors, overexpression resulted in enhanced chromatin accessibility at CRs more accessible in iNeurons than in fibroblasts  > 1 and Δ > 1 in Figure OC1-up, OC2-up, OC3-up and OC1-down, OC2-down, OC3-down) with the set of CRs differentially accessible between iNeurons and fibroblasts . We found substantial overlap between CRs upregulated by the ONECUT factors and CRs upregulated in iNeurons relative to fibroblasts . We found that CRs differentially more accessible following OC1/2/3 overexpression  were more likely to overlap with CRs accessible in iNeurons than with CRs accessible in ROADMAP DNase-seq samples, including neuronal or brain samples from ROADMAP . As there is currently no large systematic characterization of chromatin accessibility in a wide range of tissues by ATAC-seq, we created a union (‘DNase union’) of OCRs identified by DNase-seq of 53 different tissues and cell types in the ENCODE and ROADMAP projects ,29. To rP Figure . HoweverOC1-up, OC2-up and OC3-up) are associated with a specific cell lineage, we focused on lineage specific OCRs (LSOCRs). We grouped ENCODE/ROADMAP DNase-seq samples on cell lineage (according to ENCODE/ROADMAP annotations) and added iNeurons as a separate lineage. We then defined LSOCRs as CRs that are accessible in only one lineage (see Methods). LSOCRs that gained accessibility following OC1/2/3 overexpression were not restricted to a single lineage  in fibroblasts overexpressing either Bclxl (control), OC1 and Bclxl, OC2 and Bclxl or OC3 and Bclxl at the same time point as the ATAC-seq data (2 days after induction) Figures  and 6A. We characterized overall similarity of the gene expression using Pearson correlation coefficients of the quantile normalized log-transformed gene expression fragment counts FPKMs). After two days of OC1/2/3 overexpression, gene expression was more similar to that in fibroblasts than to that of iNeurons Figure . The ovePKMs. AftOC1-up, OC2-up and OC3-up) were enriched for pathways involving neuronal function or development   were highly similar to those associated with genes downregulated in iNeurons relative to fibroblast (iN-Fib-down) and included cardiovascular and cell motility pathways  Figure , but als) Figure . The neus Figure . Overexps Figure . In conty Figure  Pathwayspathways .To investigate whether OC1/2/3 overexpression induced the expression of genes expressed in a specific tissue or cell type, we determined for >8000 GTEX  RNA-seq OC1/2-up CRs and the genomic regions of downregulated genes were enriched for OC1/2-down CRs  and H3K4me1 (associated with enhancers)  Figure iN-Fib-up-specific ONECUT-motif-CRs were depleted for motifs associated with SMARCC1/SMARCC2, IRF proteins, SP1–9, ZBTB7B, FOX proteins and a motif associated with both NR1D1/NR1D2 and RORA/RORB/RORC, compared to those shared with OC1-up, OC2-up and OC3-up  and fibroblasts. All three ONECUT factors induced a neuron-like morphology and expression of neuronal genes within two days after overexpression in fibroblasts. We observed widespread remodeling of chromatin accessibility; in particular, we found that chromatin regions that contained the ONECUT motif were in- or lowly accessible in fibroblasts and became accessible after the overexpression of a ONECUT factor. There was substantial overlap with iNeurons, still, many regions that gained accessibility following ONECUT overexpression were not accessible in iNeurons. Genome-wide, chromatin accessibility and gene expression did not become more similar to that of iNeurons.TFs that can bind and open nucleosomal DNA at their cognate binding sites are known as pioneer factors . ExampleiN-Fib-up ONECUT-motif-CRs that did not gain accessibility after OC1/2/3 overexpression, supports the involvement of co-factors  that maThe sequence data are available from GEO under accession number GSE120131.gkz273_Supplemental_FileClick here for additional data file.


More than 98% of the human genome does not encode proteins, and the vast majority of the noncoding regions have not been well studied. Some of these regions contain enhancers and functional non-coding RNAs. Previous research suggested that enhancer transcripts could be potent independent indicators of enhancer activity, and some enhancer lncRNAs (elncRNAs) have been proven to play critical roles in gene regulation. Here, we identified enhancer–promoter interactions from high-throughput chromosome conformation capture (Hi-C) data. We found that elncRNAs were highly enriched surrounding chromatin loop anchors. Additionally, the interaction frequency of elncRNA-associated enhancer–promoter pairs was significantly higher than the interaction frequency of other enhancer–promoter pairs, suggesting that elncRNAs may reinforce the interactions between enhancers and promoters. We also found that elncRNA expression levels were positively correlated with the interaction frequency of enhancer–promoter pairs. The promoters interacting with elncRNA-associated enhancers were rich in RNA polymerase II and YY1 transcription factor binding sites. We clustered enhancer–promoter pairs into different groups to reflect the different ways in which elncRNAs could influence enhancer–promoter pairs. Interestingly, G-quadruplexes were found to potentially mediate some enhancer–promoter interaction pairs, and the interaction frequency of these pairs was significantly higher than that of other enhancer–promoter pairs. We also found that the G-quadruplexes on enhancers were highly related to the expression of elncRNAs. G-quadruplexes located in the promoters of elncRNAs led to high expression of elncRNAs, whereas G-quadruplexes located in the gene bodies of elncRNAs generally resulted in low expression of elncRNAs. In cis cription . LncRNAsd lncRNA , can regrference . In addiin trans . For insr hnRNPU . Moreoveth SHARP .trans by mediating the recruitment of cohesin proteins  . Enhanceproteins . In prinproteins . R-loopsproteins , predomiproteins . These fPrevious studies provided great advances in our understanding of the functions of elncRNAs. However, some studies roughly coupled enhancers to their closest genes, which has been proven to be an imprecise method for identifying the target genes of enhancers. DNA is highly compacted in the nucleus, resulting in a complicated three-dimensional genome conformation. Currently, the developed powerful Hi-C technology has been used to profile the three-dimensional chromatin structure in diverse organisms and cells . As enhaIn this study, we comprehensively characterized elncRNAs by analyzing the human chromatin structure. Using Hi-C data, chromatin loops and enhancer–promoter interactions were identified in the GM12878 cell line. Our study was intended to resolve the following issues: 1) whether chromatin loops are associated with elncRNAs in the genome-wide range; 2) whether enhancer–promoter interactions are influenced by elncRNAs in the genome-wide range; and 3) the relationship between elncRNAs and transcription factor binding sites (TFBSs). We found that chromatin loops and enhancer–promoter interactions were highly associated with elncRNAs. By analyzing the relationship between elncRNAs and TFBSs, we found that elncRNAs are capable of affecting TFBSs on both local enhancers and target promoters. Our findings suggest that elncRNAs influence enhancer–promoter interactions in different ways.The protein-coding and lncRNA genes in the human genome were downloaded from the GENCODE  and NONCGenomic regions of enhancers in the GM12878 cell line were derived from a previous study . EnhanceBowtie2  data of the GM12878 cell line were generated by Core et al. (GEO accession number: GSE60456) . GRO-seqBowtie2 . We usedBowtie2 .tophat  <0.05; fold change >1.5) (The paired-end RNA-seq data of the GM12878 cell line (GEO accession number: GSE90223) were generated by Thomas Gingeras’ group of the ENCODE Consortium . RNA-seqtophat . We usedassembly  and cuffge >1.5) . As repoge >1.5) ; therefoge >1.5) .It has been proven that active transcriptional regulatory elements can be identified from GRO-seq data by dREG . In addifit-HiC, as proposed by Hi-C reads and Hi-C interaction matrixes of the GM12878 cell line generated by Rao et al. were downloaded from the GEO repository under accession number GSE63525 . Using tWe designated pairs that consisted of elncRNA-associated enhancers and their target promoters as elncRNA-associated enhancer–promoter interaction pairs. Other enhancer–promoter interaction pairs were defined as non-elncRNA pairs.p < 1 × 10-500) were selected as candidate proteins  on a specified enhancer/promoter (j); the specified structuring factor (i) belongs to the structuring factors (X) in j) belongs to previously identified enhancer–promoter pairs (Y); xij represents the raw signal value of the specified structuring factors (i) on specified enhancer/promoter (j); µi equals the average signal value of the specified structuring factor (i) of all enhancers/promoters (Y); and δi indicates the standard deviation of the specified structuring factor (i) in all enhancers/promoters (Y).Here, https://web.stanford.edu/group/sherlocklab/cluster.html) was used to cluster interaction pairs. The Pearson correlation was set as the distance measurement as described previously . Furthermore, the relative density of elncRNAs surrounding chromatin loop anchors was significantly higher than that of other lncRNAs . The relative density of elncRNAs in the central regions of chromatin loops was slightly but significantly lower than that of other lncRNAs . We next calculated the enrichment of loop anchors with elncRNAs , suggesting that elncRNAs at loop anchors potentially reinforce the interactions of loop anchors, which may help to maintain chromatin loop structures. The distribution of the architectural proteins including CTCF, SMC3, and RAD21 around loop anchors is shown in t-test, p > 0.001), indicating that the high interaction strength of elncRNA-containing loop anchors does not arise from these architectural proteins. We found that YY1 ChIP-seq peak counts around elncRNA-containing loop anchors were significantly higher than those around other loop anchors . Using CLIP-seq, YY1 was found to be capable of interacting with nascent enhancer RNA at the active enhancer regions where it is bound to DNA . These results suggested that the highly abundant TFBSs on elncRNA-containing loop anchors promoted the transcription of elncRNAs. As feedback regulatory elements, elncRNAs on loop anchors can facilitate the loop anchor interactions by recruiting TFs such as YY1.Moreover, the chromatin loop anchors containing elncRNAs displayed significantly higher loop anchor interactions . These results suggested that elncRNAs not only influenced loop anchors locally but also potentially affected the target loop anchors through higher-order chromatin structures.We used Hi-C interaction pairs to select the loop anchors that interact with elncRNA genes (FDR <0.001); these anchors were defined as elncRNA-target loop anchors. Interestingly, the elncRNA-target loop anchors were also rich in YY1 ChIP-seq peaks and the merged TF ChIP-seq peaks . Moreover, the expression levels of the target genes of elncRNA-associated enhancers (average FPKM = 58.97) were significantly higher than those of other enhancers , suggesting that the stable interactions of elncRNA-associated enhancer–promoter pairs lead to high expression levels of the target genes.The average interaction frequency (49.32) of elncRNA-associated enhancer–promoter pairs was significantly higher than that (39.28) of other enhancer–promoter pairs . The expression levels of the target genes of high expressed elncRNA-associated enhancers (average FPKM = 64.47) were also significantly higher than those of low expressed elncRNA-associated enhancers .The elncRNAs were divided into two equal groups with high and low expression levels using the FPKM values; the 50% with the lower FPKM were defined as low expressed elncRNAs, and the 50% with the higher FPKM were defined as high expressed elncRNAs. The interaction frequency (52.88) of high expressed elncRNA-associated enhancer–promoter pairs was significantly higher than that of low expressed elncRNA-associated pairs .Using the signal values of structuring factors on enhancer–promoter pairs, we clustered elncRNA-associated enhancer–promoter pairs into 10 groups , we founTo produce elncRNAs, it is reasonable that RNA POLII and YY1 were highly accumulated around elncRNA-associated enhancers. ElncRNA-associated enhancers in clusters 2 and 3 have much higher RNA POLII and YY1 signal values than other enhancers  of elncRNA enhancer–promoter pairs contained architectural protein binding sites including CTCF, SMC3 and RAD21. Most elncRNA enhancers contained RNA POLII, which can mediate chromatin interactions and is highly related to elncRNA transcription. YY1, HDGF, GATAD2B, and GABPA were also enriched in parts of elncRNA-associated enhancers. These structuring factors potentially facilitate some elncRNA-associated enhancer–promoter interactions. In addition to the TFs, G-quadruplex sequences, which were highly associated with chromatin structures, were found to be enriched in cluster 8 of elncRNA-associated pairs.To investigate whether the cluster results were influenced by the number or the choice of structuring factors, we used different numbers of structuring factors to cluster enhancer–promoter interaction pairs . The elnt-test, p = 2.56 × 10-14), suggesting a critical role of TFs in enhancer–promoter interactions. However, the elncRNA-associated enhancer–promoter pairs in cluster 6, which were rich in HDGF binding sites, displayed significantly lower interaction frequency  than other elncRNA-associated enhancer–promoter pairs. It has been reported that the N-terminal PWWP domain of HDGF is required for DNA binding . We suspected that the formation of G-quadruplexes in this cluster serve as a compensation for the low expressed elncRNAs. And the elncRNA-associated enhancer-target genes in cluster 4 and cluster 6 express significantly lower than other enhancer-target genes , because enhancer–promoter interaction pairs in cluster 4 and cluster 6 were mainly mediated by HDGF and GABPA. HDGF has been reported to function as a transcriptional repressor (Even though elncRNA-associated enhancer–promoter interaction frequency (cluster 8) was the highest, the elncRNAs in cluster 8 were expressed significantly lower than other elncRNAs . We showed the ChIP-seq peaks of all merged TFs, YY1, and RNA POLII around the target genes of enhancers in the GM12878 cell line, respectively , suggesting that elncRNAs can influence some proteins, especially for YY1 and RNA POLII, on the target promoters (in trans) . Moreover, G-quadruplex sequence counts around TSSs of high expressed elncRNAs were significantly higher than those of low expressed elncRNAs .It has been reported that G-quadruplexes show hallmarks of dynamic epigenetic features in chromatin primarily found in regulatory, nucleosome-depleted regions and correlate with high expressed genes . Becauset-test, p = 7.13 × 10-29). Because G-quadruplexes on the gene body may stall elongation of RNAPOLII, high enrichment of G-quadruplex sequences on gene bodies will lead to the low expressed level of elncRNAs. However, G-quadruplex sequences on promoters are highly related to chromatin accessibility, and G-quadruplexes can recruit transcription factors to promoters, which can further promote the expression levels of elncRNAs. We inferred that high abundant G-quadruplex sequences in elncRNA promoters facilitated the steady expression of elncRNA.We clustered the elncRNAs into two groups . The expression levels of genes interacting with high expressed elncRNA associated enhancers (average FPKM = 64.47) were also significantly higher than those of genes (average FPKM = 55.79) interacting with other enhancers . Our results suggested that the high expression levels of target genes of elncRNA-associated enhancers might arise from the high enrichment of TFBSs including YY1 on the target promoters . It was found that elncRNA-associated enhancers in cluster 2 have much higher RNA POLII signal values than other enhancers  and the Key Research and Development Program of Jiangsu Province (BE2016002-3).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.


NIN-LIKE PROTEIN (NLP) transcription factors are master regulators of nitrate-inducible gene expression in higher plants. NLP transcription factors contain a nitrate signal-responsive domain in the amino-terminal region, an RWP-RK-type DNA-binding domain in the middle, and a Phox and Bem1 (PB1) domain at the carboxy terminus. Although the PB1 domain of NLP transcription factors appears to mediate protein-protein interactions associated with nitrate-inducible gene expression in higher plants, its precise role in nitrate-inducible gene expression has not previously been characterized.nlp6 nlp7–1 double mutants. Surprisingly, however, the ability to transactivate nitrate-responsive promoters in protoplast transient expression assays was similar between wild-type and mutant forms of NLP7, suggesting that the PB1 domain was not required for transcription from naked DNA.Yeast two-hybrid assays with the PB1 domain of the Arabidopsis transcription factor NLP7 revealed NLP-NLP interactions that required the core amino acid residues  within the PB1 domain. Consistent with previous speculation on redundant and overlapping functions between different Arabidopsis NLP transcription factors, NLP-NLP interactions were observed between a variety of combinations of different NLP transcription factors. Furthermore, a mutated form of NLP7 that harbored amino acid substitutions at K867, D909, D911, and E913 required a far higher level of expression than wild-type NLP7 to restore nitrate-responsive gene expression and growth of in planta. The PB1 domains of NLP transcription factors may act on gene expression from chromosomal DNA via homo- and hetero-oligomerization in the presence of nitrate.Protein-protein interactions mediated by the PB1 domain of NLP transcription factors are necessary for full induction of nitrate-dependent expression of target genes The online version of this article (10.1186/s12870-019-1692-3) contains supplementary material, which is available to authorized users. Plants acquire nitrogen (N) from soils in the form of nitrate and ammonium ions, which are assimilated into amino acids and then used to generate N-containing organic molecules such as chlorophylls, nucleotides, and proteins. Nitrate is a major form of inorganic N in upland oxidative soils, where the majority of higher plant species are found, and nitrate supply is often a limiting factor for plant growth . NitratePlants have regulatory mechanisms that sense nitrate and/or nitrogen status and then modulate gene expression to fine-tune metabolism and growth in response to nitrate availability and internal nitrogen demand –8. NitraNLP genes (NLP1–9). The high similarities between the amino acid sequences of different NLP transcription factors suggest that they have redundant and overlapping functions in nitrate-inducible gene expression, although some NLP transcription factors may have somewhat different physiological roles. NLP7 appears to play a dominant role in Arabidopsis, as single mutations in NLP7 cause significant decreases in the expression levels of some nitrate-inducible genes and reduce nitrate-dependent growth promotion  and stratified at 4 °C for 3–4 days. Plates were placed horizontally in a growth chamber set at 23 °C with continuous illumination (60 μmol m− 2 s− 1) for 4 days. Seedlings were then transferred to vertical test plates  and incubated for 5 days. To avoid direct contact between shoots and the medium [− 1 MES-KOH, pH 5.7, 0.5% sucrose, and 0.5 mM ammonium succinate) in a plastic dish. After stratification at 4 °C for 3–4 days, the dishes were transferred to 23 °C under continuous light (60 μmol m− 2 s− 1). After 4 days, seedlings were treated with 10 mM KNO3 for 1 h before sample collection, followed by RNA extraction and RT-qPCR.For the measurements of shoot fresh weight, and determinations of transcript and protein levels, seeds were sown on plates containing 0.5× MS [half-strength Murashige and Skoog (MS) salts , 0.5 g Le medium , the agaNLP7 promoter  was amplified by PCR, digested with HindIII and NcoI, and cloned into pJD301 to generate the plasmid pNLP7pro-LUC. All the primers used are listed in Additional file NLP7 coding sequence, together with the sequences encoding six copies of the MYC tag and the NOS terminator, was excised from p35SC4PPDK-NLP7-MYC6 [GUS gene, and the NOS terminator. The resulting binary plasmid was introduced into Agrobacterium tumefaciens strain GV3101 (pMP90) [nlp6 nlp7–1 double mutant. T2 generation lines showing 3:1 segregation for hygromycin resistance were selected, and used to generate homozygous lines, selected at the T3 generation.A 3 kb DNA fragment of the LP7-MYC6 . The twoLP7-MYC6  to repla (pMP90) , which wRNA extraction, reverse transcription, and quantitative PCR (qPCR) were performed as described previously . Primers4 protoplasts in this study. nlp6 nlp7–1 seeds were placed on a urethane sponge moistened with 0.1× MS solution supplemented with 2 mM CaCl2 , and incubated under continuous illumination for 1 day and then in the dark for 2 days. Etiolated nlp6 nlp7–1 seedlings were then grown hydroponically in 0.1× MS solution supplemented with 2 mM CaCl2 in the light for 20 days. Protoplast isolation and transfection of 2 × 104 protoplasts with reporter plasmid (6 μg), effector plasmid (0.1 μg), the internal control plasmid UBQ10-GUS (2 μg), and the empty plasmid (12 μg) were all as described previously. Transfected protoplasts were incubated in WI medium overnight in the dark.The protoplast co-transfection assay using hydroponically grown, N-starved Col plants was performed as previously described , with thSample preparation, SDS-PAGE, and immunoblot analysis were all performed as described in Liu et al. .Additional file 1:Figure S1. The non-conserved amino-terminal region of NLP7 is a transactivation domain. Figure S2. Clones obtained in a Y2H screen with NLP7 (aa. 116–959) as bait. Figure S3. Effects of mutations in the PB1 domain on nitrate-induced gene expression. Table S1. List of primers used in the study. (PDF 66 kb)