GATA4. Our study revealed promising candidate genes in bovine cells by a butyrate-induced condition that might be related to the regulation of rumen development, such as integrins, keratins, and collagens. These results provide a better understanding of the function of butyrate in cattle rumen development and chromatin landscape regulation.Butyrate is produced in the rumen from microbial fermentation and is related to several functions, including cell differentiation and proliferation. Butyrate supplementation in calves can accelerate rumen development. DNA-protein interactions, such as the CCCTC-binding factor (CTCF), play essential roles in chromatin organization and gene expression regulation. Although CTCF-binding sites have been identified recently in cattle, a deeper characterization, including differentially CTCF-binding sites (DCBS), is vital for a better understanding of butyrate’s role in the chromatin landscape. This study aimed to identify CTCF-binding regions and DCBS under a butyrate-induced condition using ChIP-seq in bovine cells; 61,915 CTCF peaks were identified in the butyrate and 51,347 in the control. From these regions, 2265 DCBS were obtained for the butyrate vs. control comparison, comprising ~90% of induced sites. Most of the butyrate DCBS were in distal intergenic regions, showing a potential role as insulators. Gene ontology enrichment showed crucial terms for the induced DCBS, mainly related to cellular proliferation, cell adhesion, and growth regulation. Interestingly, the ECM-receptor interaction pathway was observed for the induced DCBS. Motif enrichment analysis further identified transcription factors, including CTCF, BORIS, TGIF2, and ZIC3. When DCBS was integrated with RNA-seq data, putative genes were identified for the repressed DCBS, including  Various physiological functions of the rumen are regulated by short-chain fatty acids (SCFAs), also called volatile fatty acids (VFAs), which are molecules derived from the rumen microbial fermentation. The main SCFAs produced on the rumen are acetate, propionate, and butyrate. These SCFAs can affect the rumen epithelium integrity and renewal of rumen epithelial cells ,2. In adButyrate is present in relatively low concentrations during rumen fermentation compared to acetate and propionate. However, it involves several important roles, such as cell differentiation, proliferation, and apoptosis, and can cause DNA histone modifications ,5,6,7. PStudies show that butyrate supplementation in young calves has beneficial effects on gastrointestinal performance and growth rates. For example, preweaning calves supplemented with butyrate develop a rumen and mature ruminal epithelium more rapidly . AnotherRecently, Chromatin immunoprecipitation followed by sequencing (ChIP-seq) and Assay of Transposase Accessible Chromatin sequencing (ATAC-seq) have been used to identify regulatory elements in cattle ,15,16,17Millions of bovine regulatory elements have been identified in the last years; however, identifying such regulatory elements in specific tissues and conditions is still lacking or has not been conducted in a more profound aspect. CTCF ChIP-seq studies have been conducted recently in sheep ,26 and c2 flasks, as described in our previous report [The Madin–Darby bovine kidney epithelial cells  were cultured in Eagle’s minimal essential medium and supplemented with 5% fetal bovine serum  in 25 cmCTCF ChIP-seq in bovine cells from two samples (butyrate and control) was performed by Active Motif, Inc. . The DNA integrity was verified using the Agilent Bioanalyzer 2100 , then the DNA was processed, including end repair, adaptor ligation, and size selection, using an Illumina sample prep kit, following the manufacturer’s instructions . The DNA libraries were sequenced (75 bp) on an Illumina HiSeq 2500 platform .https://www.bioinformatics.babraham.ac.uk/projects/fastqc/, (accessed on 14 March 2022)). Then, reads were aligned to the ARS-UCD1.2 cattle reference genome assembly [https://broadinstitute.github.io/picard/, (accessed on 30 March 2022)). The read quality was examined using FastQC v.0.11.9  and a defined window of 200 bp. The DCBS were filtered with a |log2FC| >1 and mapped against the identified CTCF peaks. The CTCF peaks from the two conditions (butyrate and control) were merged by BEDtools v.2.25.0 [2 fold change values and used for the downstream analyses.DiffReps v.1.55.6  was usedv.2.25.0  to generv.2.25.0  with intThe induced and repressed DCBS were annotated with the annotatePeak from the ChIPseeker package . ChIPseep-value < 0.01), upstream regulators , and molecular networks (network score > 20) using 1561 genes from the induced DCBS and 225 genes from the repressed DCBS. Gene ontology (GO) enrichment and KEGG pathways analysis were performed with ShinyGO v.0.76  . The enriched motifs were identified using HOMER v.4.11  from thep-value of 0.05. The analysis was performed for the induced and repressed DCBS jointly. The p-values from BETA (rank product) are estimated by the Kolmogorov–Smirnov test comparing the regulatory potential of upregulated, downregulated, and background genes. Genes with p-values/rank product < 0.05 were considered significant target genes.To investigate gene expression and regulatory networks and compare with DCBS, previously RNA-seq data from butyrate and control conditions  were utilized  to obtaiThe bigwig files from butyrate and the control were generated from MACS2 bedGraph files using the bedGraphToBigWig tool . Then, tChIP-seq libraries were obtained from MDBK cells treated with butyrate and the control. A total of 40,990,109 reads were initially generated for butyrate and 39,610,540 reads for the control, and approximately 90% of the reads were aligned to the ARS-UCD1.2 cattle reference genome assembly  with a tThe CTCF peaks were discovered in the individual samples by the MACS2 (FDR < 0.05) from 47,364,743 clean reads . A totalp-value < 0.05) was initially obtained for the butyrate vs. the control , and ~10% of repressed sites (log2FC ≤ −1)  .The annotation of the 2265 butyrate-induced and -repressed DCBS was done separately . Most ofGO enrichment and KEGG pathway analysis were conducted with ShinyGO (FDR < 0.05) . A totalp-value < 0.01) were identified for the induced DCBS, including growth hormone, macropinocytosis signaling, regulation of cellular mechanics by calpain protease, AMPK, PAK, and others  such as growth factors, kinases, and transcription factors were identified for the induced sites , and for the repressed sites . More details can be found in IPA  was utild others . Eight cd others . Signifip-value ≤ 0.01) and putative transcription factor binding sites (TFBS) in the butyrate-induced and repressed DCBS. Twenty-six and 41 enriched motifs were identified for the butyrate-induced and repressed DCBS, respectively  for the induced sites were BORIS, CTCF, ZIC3, BCL11A, THRB, ZIC2, LRF, ZEB1, NEUROD1, and SCL, and for the repressed sites were CTCF, BORIS, FRA2, FOS, JUN-AP1, ATF3, FRA1, JUNB, AP1, and BATF.The HOMER tool  was emplectively . The topp-value = 0.0343, p-value < 0.05) were identified, including GATA4, RASD1, KANK3, CFAP45 and ZNF395 ). According to ENCODE, our samples produced the recommended number of reads; however, at least two replicates per sample are recommended. ENCODE also recommends the fraction of reads in peaks (FRiP score) as a metric to verify the quality of the ChIP-seq studies, and our results showed a FRiP score of 0.22 for butyrate and 0.16 for the control, which indicates an acceptable quality [ChIP-seq libraries were obtained from bovine cells treated with butyrate and the control. Butyrate resulted in 23,691,050 clean reads, and the control condition in 23,673,693 clean reads. The Encyclopedia of DNA Elements (ENCODE) project guidelines for transcription factor ChIP-seq recommend at least 20 million usable fragments for each sample  and 244 repressed DCBS for the butyrate treatment. We utilized all induced and repressed DCBS for the downstream analysis to identify differences in the biological functions, including annotation, GO, and pathways analyses.Of note, 61,915 CTCF peaks were generated for the butyrate condition, representing 1.27% of the cattle genome, and 51,347 for the control, representing 0.88% of the cattle genome (bosTau9). Our results are consistent with a previous study in cattle rumen tissue where the CTCF peaks identified for weaning conditions represented approximately 0.6% of the cattle genome (bosTau8) , and a sThe annotation of the butyrate-induced and -repressed DCBS showed similar results with most of the induced and repressed DCBS in distal intergenic regions, followed by promoters and introns. The induced and repressed DCBS located primarily on distal intergenic regions show a potential role as insulators, as reported in previous studies in sheep  and humaITGB1, ITGA4, ITGA5, ITGA7, ITGB8), collagens , and other genes related to extracellular matrix or cartilage . The ECM-receptor interaction pathway has a crucial role in maintaining cell and tissue structure and can include collagen, fibronectin, and laminin molecules [GO enrichment revealed important enriched GO terms for the induced DCBS related to cell migration and motility, epithelial cell proliferation, cell adhesion and junction, complex collagen trimers, and growth regulation. We additionally detected a biological relevant KEGG pathway for the induced DCBS, the ECM-receptor interaction. This pathway includes 16 genes such as integrins  or CTCFL is a paralog of CTCF and is involved in methylation events and might be involved in developmental reprogramming and chromatin unfolding ,56. TGIFGATA4, RASD1, KANK3, and ZNF395. Previous studies in mice and quails showed that GATA4 is essential for maintaining intestinal homeostasis and controls functional integrity [GATA4 expression in the intestine [GATA4 expression, showing that acetate and butyrate positively affected the expression of GATA4. RASD1 is part of the Ras superfamily of small GTPases and plays several critical roles, including iron homeostasis, growth hormone secretion, circadian rhythm, and cell proliferation and differentiation [ZNF395 is a novel tumor suppressor gene [DCBS were then integrated with previous RNA-seq data  to identntegrity ,67 and integrity . GATA4 integrity . Anotherntestine . Authorsntiation . The KANntiation . A recensor gene .integrin genes, including ITGB1, ITGA4, and ITGA5 on chromosomes 13, 2, and 5, respectively. This study observed eight induced regions in seven integrin genes . However, no repressed DCBS were in integrin genes. As mentioned before, integrins are crucial for cell adhesion and proliferation and might have a role in bovine rumen development, as shown by previous studies in cattle [keratin genes . Keratins can be found on the rumen surface and result in protection from potential damage [Genomic regions were selected for visualization of genes related to potential roles in rumen development during butyrate supplementation, such as cellular adhesion and cell proliferation. Three regions showing CTCF peaks and induced DCBS were selected for four n cattle ,51. In tl damage . Also, tl damage .Butyrate utilization can accelerate calves’ gastrointestinal tract development and improve feed efficiency and growth. CTCF is a crucial chromatin organizer and plays an essential role in gene expression regulation. Using the butyrate-induced treatment on bovine cells and the ChIP-seq approach, genome-wide characterization of CTCF-binding sites and differential CTCF-binding sites for the butyrate vs. control comparison was successfully performed here. Then, a total of 2265 differentially CTCF-binding sites comprising ~90% of induced sites were further integrated with gene ontology, IPA and KEGG pathways, motif enrichment, and RNA-seq data to reveal relevant biological roles related to the butyrate-induced condition. Gene ontology enrichment showed crucial GO terms for the induced sites, mainly associated with cellular proliferation, cell adhesion, and growth regulation. Our study revealed candidate genes in bovine cells by butyrate-induced utilization that might be related to the regulation of rumen development such as integrins, keratins, and collagens, and transcription factors such as BORIS, ZIC2/3, GATA4, and TGIF2. However, additional studies with larger sample sizes are needed to confirm these findings.


Inflammation is one of the critical risk factors for colorectal cancer (CRC). However, the mechanisms for transition from colitis to CRC remain elusive. Recently, epigenetic changes have emerged as important regulatory factors for colitis‐associated cancer. Here, a systematic epigenomic study of histone modifications is performed, including H3K4me1, H3K4me3, H3K27ac, H3K27me3 and H3K9me3, in an AOM‐DSS‐induced CRC mouse model. In combination with transcriptomic data, the authors generate a dataset of 105 deep sequencing files and illustrate the dynamic landscape of chromatin states at five time points during inflammation‐cancer transition. Functional gene clusters are identified based on dynamic transcriptomic and epigenomic information, and key signaling pathways in the process are illustrated. This study's results reveal that enhancer state regions play important roles during inflammation‐cancer transition. It predicts novel transcription factors based on enhancer information, and experimentally proves OTX2 as a critical tumor suppressive transcription factor. Taken together, this study provides comprehensive epigenomic data and reveals novel molecular mechanisms for colitis‐associated cancer. The dynamic changes of chromatin states during the transition from inflammation to cancer are studied in a colitis‐associated cancer model. Multiple omics analysis reveal that enhancer state regions play important roles during inflammation‐cancer transition. Novel transcription factors, such as OTX2, are discovered as critical factors for colorectal cancer. Transcription factors, such as NF‐κB, are highly involved in colitis‐associated CRC through promoting a localized inflammatory response and enhancing the growth and survival of tumor cells. However, it remains elusive whether other transcription regulators are involved in the process.Colorectal cancer (CRC) is one of the most common cancers in the world. CRC develops in ≈5% of the adults in the United States, and ≈50% of the patients die from the disease.1 The  Recently aberrant DNA methylation and regulation of enhancer activity have emerged to be important features in CRC. DNA methylomes have been extensively investigated in CRC patients and methylated DNA fragments of specific genes have been developed as diagnosis markers for CRC. Genome‐wide profiling of active enhancers also turns out to be a powerful tool to identify tumor‐specific enhancers and transcription factors. However, profiling of one single chromatin modification does not reflect the complete features of genome loci, and sometimes the information could be misleading. Moreover, patient samples usually hardly provide mechanistic information for disease development, and studies in animal models are urgent to reveal the underlying mechanisms.Epigenetic features frequently change in CRC tissues and multiple epigenetic genes have been reported to be associated with CRC5, 6 To fully understand chromatin functions, a software called ChromHMM was developed to determine chromatin states by considering the impacts of multiple chromatin modifications. Although it is not perfect to describe and explain every chromatin event, it is useful to summarize the genome‐wide chromatin features and predict novel regulators. The approach has been used in the studies in cell lines, human tissues, and animal models. Recent studies have tried to investigate a genome‐wide enhancer state in CRC patient tissues or organoid derived from patient cells. However, it is not clear how dynamic chromatin states contribute to inflammation‐cancer transition in colitis‐associated CRC.Histone modifications are critical marks for the functions and features of certain chromatin elements. H3K4me1 is the mark for primed enhancers; H3K4me3 usually marks transcription start sites (TSS); H3K27ac is distributed on both active enhancers and promoters; H3K27me3 covers transcription repressed regions, and H3K9me3 is for heterochromatin11 To  Combining these data, we generated the genome wide landscape of chromatin states during inflammation‐cancer transition. Our study provides important datasets for CRC studies, and reveals new regulatory mechanisms and potential targets for clinical investigation.In the current study, we performed epigenomic and transcriptome studies in an colitis‐associated CRC mouse model induced by azoxymethane (AOM) and dextran sodium sulfate (DSS).17 Com22.1FigureTo study the epigenomic changes during inflammation‐cancer transition of colitis‐associated cancer, we used an AOM‐DSS induced colitis‐associated CRC mouse model. Colon or tumor tissues were collected at time points of 2, 4, 7, and 10 weeks after AOM injection and the control group was raised to the same time as the 10‐week group. Three mice for each time point were subjected for sequencing study  samples and those at the 7‐ and 10‐week with CRC samples , heterochromatin state regions (dominant H3K9me3), transcription repressed regions (dominant strong or weak H3K27me3), active enhancer state regions (high H3K4me1 and H3K27ac), poised enhancer state regions (high H3K4me1 and low H3K27ac), bivalent enhancer state regions , weakly active enhancer state regions (low H3K4me1 and H3K27ac), active promoter state regions , and poised promoter state regions (high H3K4me3 and H3K27me3) Figure2A. The Then we compared the chromatin states at different time points, we found that all the above chromatin state regions were highly dynamic during inflammation‐cancer transition Figure . Most of2.4FigureAlthough we analyzed the functions of DEGs, it was still difficult to obtain a comprehensive picture of the dynamic change during inflammation‐cancer transition. So, we used maSigPro software to determine functional gene clusters based on their dynamic expression levels. We successfully divided all dynamic genes into four clusters Figure. They we2.5 The dynamic genes were divided into 9 clusters according to their H3K27ac signal on enhancers  values of histone modifications on genes. Because histone modifications around gene body may also regulate gene expression, it is better to integrate the signals on gene bodies and regions close to them. After comparing the analytical results of different ranges, we used the signal within gene body flanked ±2 kb for the following analyses; while for analysis of histone modifications on enhancers, signals close to TSS were excluded . All the above modifications were investigated and we found that the classification with H3K27ac on enhancers was mostly meaningful. It supports the recently raised hypothesis that enhancer activation is one of the important features for cancer10,19 Thes Figure. Genes oy Figure , which hYwhaq, 14‐3‐3) is a cancer‐related gene and selected as a representative to show the dynamic change of chromatin states and histone modifications  were used to represent its chromatin states. A large portion of genes of cluster 3 showed a high level of enhancer state, and we took those showing conversion from quiescent to enhancer state to investigate the relationship between chromatin states and gene expression. Although the expression of some genes was not always correlated with their dominant chromatin state, most of them showed high expression at the cancer stage (7‐ or 10‐week), suggesting the elevated H3K27ac on these genes were associated with tumorigenesis Figure . These sated gene21 ands Figure . H3K27acs Figure .[16]2.6AXIN2 is a typical WNT pathway target gene and was used as a representative gene to show its expression, histone modifications, and chromatin states during transition  play key roles in multiple biological processes, and their functions are tightly related with enhancer activation and regulation. To further explore the molecular mechanisms of colitis‐associated cancer, key TFs specifically involved in each stage were analyzed by motif analysis with the corresponding enhancer regions. The top 10 TFs enriched on variant enhancers of the 10‐week versus control, together with the TFs validated experimentally, are shown , H3K4me1 , H3K27me3 , H3K9me3 , H3K27ac , and OTX2  were purchased from indicated commercial sources. Protein G‐Sepharose beads , AOM , and DSS  were purchased from the indicated companies. PCR primers were custom synthesized by BGI and siRNAs by GenePharma. HCT116 and RKO Cell lines were purchased from Cell Bank of Chinese Academy and cultured under recommended conditions according to the manufacturer's instruction with 10% FBS.Mice were purchased from Beijing HFK Bioscience. All the mice were born and maintained under pathogen‐free condition at ≈20–24 ℃ with a humidity of ≈40–70% and a 12/12‐hours dark/light cycle , with free access of water and food .All the animal operations were following the laboratory animal guidelines of Wuhan University and were approved by the Animal Experimentations Ethics Committee of Wuhan University (Protocol NO. 14110B). No patient study was involved and the consent to participate is not applicable.n = 5 per group). Mice in the experimental groups were given a single intraperitoneal injection of AOM (10 mg kg−1 body weight). Seven days after the AOM injection, the mice were given 2.5% DSS (w/v) in drinking water for 7 days. Then mice of the 2‐week group were sacrificed. The other three groups were fed with distilled water for 14 days and then the 4‐week group was sacrificed. The DSS/water cycle was repeated and mice were sacrificed at the 7‐ and 10‐week, respectively. The control group mice were fed with distilled water for 70 days and sacrificed. The colorectal tissues were divided to distal, middle and proximal fragments, and the distal colon fragments were collected for experiments. Tumors were observed in the mice of the 7‐ and 10‐week groups and only tumors were collected for further analysis for the two groups. A small number of mice did not survive randomly after the whole procedure, then we choose 3 mice of each group for further analysis.The 8‐week‐old C57BL/6J male mice were randomly divided into four experimental groups  and one control group  for 4 min with gentle rotation. After centrifugation at 12 000 rpm, 4 °C for 2 min, the pellet was washed once with digestion buffer , incubated in 630 µL digestion buffer with 1 µL MNase  at 37 °C for 20 min, and quenched with 8 µL 0.5 m EDTA. The resulted mixture was sonicated and the pellet was discarded after centrifugation. 30 µL supernatant was taken for checking the efficiency of digestion. Immunoprecipitation was performed with 150 µL sheared chromatin, 2 µg antibody, 50 µL Protein G beads, and 800 µL dilution buffer  overnight at 4 °C. Next day, the beads were washed once with Wash buffer I , once with Wash buffer II , once with Wash buffer III , and twice with TE . The beads were eluted twice with 100 µL elution buffer  at room temperature. The elution was incubated at 65 °C for 6 h and then purified with the DNA purification kit (TIANGEN DP214‐03). Primers for ChIP‐qPCR are listed in Table ChIP assay was performed as previously described.30 BriChIP‐seq libraries were constructed with ChIP and input DNA using VATHS Universal DNA Library Prep Kit for Illumina (Vazyme ND606). Briefly, 50 µL of DNA (8–10 ng) was end‐repaired for dA tailing, followed by adaptor ligation. Each adaptor was marked with a barcode of 8 bp DNA. Adaptor‐ligated DNA was purified by AMPure XP beads (1:1) and then amplified by PCR of 9 cycles with the primer matching with adaptor universal part. Amplified DNA was purified again using AMPure XP beads (1:1) in 35 µL EB elution buffer. For multiplexing, libraries with different barcodes were mixed with equal molar quantities (30–50 million reads per library). Libraries were sequenced by Illumina Nova‐seq platform with pair‐end reads of 150 bp.RNA extraction was performed using Ultrapure RNA Kit . Briefly, ≈40 mg tissues were triturated for 30 s in 1 mL TRIzon provided in the kit, incubated at room temperature for 5 min, added with 200 µL chloroform and shaken drastically. After centrifugation at 12 000 rpm, 4 °C for 10 min, the upper water phase was moved into an adsorption column provided by the kit. The column was then eluted with 50 µL RNase‐free water. RNA‐seq libraries were constructed by NEBNext Poly(A) mRNA Magnetic Isolation Module (NEB E7490) and NEBNext Ultra II Non‐Directional RNA Second Strand Synthesis Module (NEB E6111). mRNA was purified with poly‐T magnetic beads and first and second strand cDNA was synthesized. The resulting cDNA was purified by AMPure XP beads (1:1) and eluted in 50 µL nucleotide‐free water. The subsequent procedures were the same as described in ChIP‐seq library construction, except that the sequencing depth was 20 million reads per library. RNA‐seq libraries were sequenced by Illumina Nova‐seq platform with pair‐end reads of 150 bp.https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) to quality control. Clean data were obtained by removing adapter with Cutadapt . Cleaned reads were aligned in paired‐end mode to mouse UCSC reference genome mm10 with BWA mem . Duplicate reads were removed by samtools rmdup . Only unique mapped reads were used in following work. Peaks were called by MACS2  at false discovery rate (FDR) < 0.01.ChIP‐seq raw fastq data used FastQC  and Multiqc . Cleaned reads were aligned against the mouse UCSC mm10 genome with TopHat2 . The gene annotation file was used UCSC mm10 genome. Differential expression genes were calculated by Bioconductor package DESeq2  at a fold change > 2 and p‐value less than 0.01. The gene expression level was normalized as fragments per kilobase of bin per million mapped reads (FPKM) by Cufflinks .RNA‐seq cleaned fastq data were obtained in the same way as ChIP‐seq data (parameters were “‐u 4 ‐u ‐10 ‐U 4 ‐U ‐10 ‐m 30”). Quality control is done with FastQC .34 The The mapped bed files of all five histone modification markers  across five CRC development stages was binned into non‐overlapped 200‐bp intervals using Bedtools software (version 2.29.2). The whole‐cell extract signal  were used as control data, providing background signal level to adjust the binarization criteria. The model was trained with a range of chromatin states from 10–15, and finally selected the 13 states model in subsequently analysis as it could sufficiently capture the key interactions between all histone modification markers . A gene was assigned to a specific chromatin state when the 200‐bp bins annotated by this state had the highest frequency in ± 2 kb of the gene body region. This highest frequency state was defined as the dominate chromatin state of a gene.To capture histone modifications combination, we used ChromHMM (version 1.11) to get chromatin state by training a hidden Markov model.12 Thes Figure . With th In briefly, the expression of RNA was normalized to TMM by edgeR (version 3.32.1), and then fitted to a polynomial model with degree 4. The goodness‐of‐fit (R2) would be calculated for all genes, and only those with R2 > 0.7 would be identified as dynamic expression genes. Next, a K‐means clustering analysis for these dynamic expression genes was performed using maSigPro, with the param k from three to nine. Four distinct clusters with obvious different expression patterns were gotten at last  implemented in R.37 In t Figure .In H3K27ac signal density dynamic analysis, the gene signal density was normalized to RPM within the region of the gene body ±1.5–10 kb. The dynamic H3K27ac signal density in genes was identified in the same way with RNA dynamic analysis. At last, nine distinct clusters were obtained.http://homer.ucsd.edu/homer/) was used to identify transcript factor motifs, with the size parameter 600 bp.For H3K27ac in each mouse CRC development stage, peaks calling by MACS2 across all replicates were merges to obtain a non‐redundant enhancer region list. Furthermore, the TSS ± 2 kb were removed to exclude an affect from the nucleosome free regions. Then motif enrichment analysis was performed with the regions in all five stages. The findMotifsGenome.pl module in HOMER  generated from mouse embryonic stem cells by Buecker et al. was selected.25 TheκB target genes, Pearson correlation coefficient in R between the gene expression level FPKM and marker's signal density RPM was calculated. In each time point, the gene's FPKM and RPM were averaged across all replicates.To evaluate the regulation of histone markers to gene RNA expression, the average signal density RPM for each marker across TSS ± 1.5 kb, TSS ± 1.5–10 kb and TSS ± 10–100 kb regions around the gene promoter was calculated. For OTX2 and NF‐Differential expression genes detected in the 2‐, 4‐, 7‐, and 10‐week versus control were used to perform gene set enrichment analysis (GSEA) with R packages fgsea (version 1.16.0). Six CRC related pathways and five immune related pathways were selected to classify the sample stages. For the genes with different dominate chromatin state across CRC development stages, the chromatin state change profile between two stages was summarized. New enhancer state genes at 10‐weeks, original from quiescent or promoter state genes, were used in biological process analysis. Genes in each cluster identified by RNA dynamic analysis or H3K27ac dynamic analysis were used to conduct BP and KEGG pathway analysis, which was performed by R package clusterProfiler (version 3.18.1).40 using the alignment file of chromatin markers and state annotation bed files produced by ChromHMM. Histone marker's signal density panel across TSS and gene body were plotted by in house R script, using the density matrix data produced by deeptools (version 3.3.2).UCSC genomic track for histone marks, RNA expression and chromatin state beyond the RefSeq gene model were drawn by karyoploteR,41 usiβ‐actin was used for normalization. The sequences of primers are in Table p‐value was calculated using student's t test.Cells were scraped down and collected with centrifugation. Total RNA was extracted with RNA extraction kit (Aidlab) according to the manufacturer's manual. Approximately 1 µg of total RNA was used for reverse transcription with a first strand cDNA synthesis kit (Toyobo). The resulted cDNA was then assayed with quantitative PCR. p‐value was calculated using student's t test.The cell proliferation was measured using the MTT assay. Briefly, 1000 cells were seeded into 96‐well plate per well. Six well of each group were detected every day. MTT (0.25 µg) was put into each well and incubated at 37 ℃ for 4 h. The medium with the formazan sediment was dissolved in 50% DMF and 30% SDS (pH 4.7). The absorbance was measured at 570 nm. Assays were repeated at least three times. Data were shown as average values ± SD of at least three representative experiments and 5 HCT116 cells were plated in medium without serum or growth factors in the upper chamber with a Matrigel‐coated membrane , and medium supplemented with 10% fetal bovine serum was used as a chemoattractant in the lower chamber. After 36 h of incubation, cells that did not invade through the membrane were removed by a cotton swab. Cells on the lower surface of the membrane were stained with crystal violet and counted. Assays were repeated at least three times. Data were shown as average values ± SD of at least three representative experiments and p‐value was calculated using student's t test.1 × 106 HCT116 cells per site into the flank regions of the mice. Tumor volumes were measured twice a week using calipers. Tumor volumes were calculated as V  =  0.5 × length × width2. After 24 days of injection, the tumors were harvested and weighed.The 5‐week‐old male BALB/C nude mice were purchased from Beijing HFK Bioscience Co. Ltd. Colon cancer model was established by injecting subcutaneously 2 × 10All the deep sequencing data generated in the current study have been submitted to GEO database, with the Acc. NO. GSE178145 (RNA‐seq) and GSE178144 (ChIP‐seq). Publicly available AOM/DSS RNA‐seq data are available under GEO Acc. NO. GSE57533. ChIP‐seq data for CRC patients are accessible at GEO Acc. NO. GSE156614. The remaining data are available within the article, Supporting Information, or available from the authors upon request.The code for all analyses presented in this paper is available from the authors upon request.The authors declare no conflict of interest.L.C., Z.L., and C.Z. contributed equally to this work. L.C. performed RNA‐seq, ChIP‐seq and most of the experiments; Z.L. and C.Z. performed bioinformatics analyses; Q.L. established CRC model and collected tissues; M.W., Z.‐X.C., and L.L. directed the project; M.W. and L.L. provided funding; M.W., L.C., Z.L., and C.Z. wrote the manuscript.Supporting InformationClick here for additional data file.Supporting Table 1Click here for additional data file.


B factor from the human pathogen, Mycobacterium tuberculosis, induces the RNAP holoenzyme oligomerization into a supramolecular complex composed of eight RNAP units. Cryo-electron microscopy revealed a pseudo-symmetric structure of the RNAP octamer in which RNAP protomers are captured in an auto-inhibited state and display an open-clamp conformation. The structure shows that σB is sequestered by the RNAP flap and clamp domains. The transcriptional activator RbpA prevented octamer formation by promoting the initiation-competent RNAP conformation. Our results reveal that a non-conserved region of σ is an allosteric controller of transcription initiation and demonstrate how basal transcription factors can regulate gene expression by modulating the RNAP holoenzyme assembly and hibernation.Self-assembly of macromolecules into higher-order symmetric structures is fundamental for the regulation of biological processes. Higher-order symmetric structure self-assembly by the gene expression machinery, such as bacterial DNA-dependent RNA polymerase (RNAP), has never been reported before. Here, we show that the stress-response σ Biological processes can be regulated via oligomerization of macromolecules into high-order symmetric structures. Here, authors reported high-order structure of RNA polymerase and its role in regulation of gene expression in pathogenic bacterium. To initiate transcription, the core associates with the promoter-specific initiation factor σ (the σ subunit) to form the RNAP holoenzyme (Eσ)2. Upon holoenzyme assembly, the σ subunit domain 2 (σ2) binds to the β‘ subunit coiled-coil region (β‘-CC) at the RNAP clamp domain while domain 4 (σ4) binds to the β subunit flap (β flap). The σ subunit region 3.2, which connects domains σ2 and σ4 . During transcription initiation, the RNAP clamp successively adopts different states, from open (free RNAP) to closed (RPo and transcription elongation complex)13. The open-clamp state allows the DNA template entry into the active site, and the closed state is required to hold the DNA template in the active site. Thus, the clamp conformational dynamics drive promoter recognition and melting during transcription initiation12. The σ2 and σ4 domains impose restraints on the clamp and β flap relative movements and consequently, should affect the basic RNAP functions in a promoter-dependent manner. Lineage-specific σ factors create gene regulatory networks that ensure the rapid adaptation of bacteria to environmental stress and allow pathogenic bacteria to tolerate antibiotic treatment15. For instance, the dormant form of M. tuberculosis (Mtb), the origin of latent tuberculosis, can persist in tissues for decades16. Most Mtb genes are transcribed by RNAP harboring the principal σA subunit and the principal-like σB subunit15 that belong to group I and group II, respectively, and share almost identical promoter binding regions17. It is thought that the σB subunit is responsible for gene transcription during starvation and stress20. However, recent findings showed that the mycobacterial σA and σB subunits are present at similar levels and co-transcribe essential genes during exponential growth15. Two general transcription factors, CarD and RbpA, regulate Mtb RNAP activity in the growth phase and in a gene-specific manner23. Unlike EσA, the activity of which displays loose dependence on RbpA, EσB is deficient in promoter-dependent transcription initiation in the absence of RbpA24. Single-molecule Förster resonance energy transfer (smFRET) analysis showed that RbpA induces the σB conformational change required for the correct assembly of active EσB6. Several solution structures of the Mtb EσΑ holoenzyme and its complexes with CarD, RbpA, and promoter DNA have been solved by cryogenic electron microscopy (cryo-EM)27, and have provided the structural basis for understanding σΑ-dependent transcription initiation. However, the lack of EσΒ structure does not allow dissecting the specific roles of the σA and σB subunits in gene regulation. Here, we use single-particle cryo-EM to determine the structural basis of the intrinsically limited EσB transcriptional activity. We find that after σB association with the RNAP core, the EσB holoenzyme remains trapped in an immature conformation in which the σB C-terminus is unloaded from the RNA exit channel. The immature EσB, deficient in promoter recognition, self-assembles into a 3.2 MDa, octamer the size of which exceeds that of the bacterial ribosome. Thus, σB acts as a bona fide RNAP-hibernation factor that can repress transcription.Transcription is the first and most highly regulated step in gene expression. In bacteria, transcription is carried out by the RNA polymerase (RNAP) core (E) composed of five subunits 28 with a ~5 Å bigger distance between the RNAP β lobe 1 (β-L275) and β‘ clamp (β‘-R214) domains. We then refined the RNAP oligomer cryo-EM map without imposing symmetry at a nominal resolution of 6.13 Å  symmetry . The β clamp contacts were formed by the Actinobacteria-specific insertion in the β‘ subunit  and invariant residues of the β‘ Zn2+ binding domain . Local resolution calculations showed that the σ2-β‘ clamp module was determined at a resolution between 3.6 and 5.5 Å while the remaining RNAP parts were determined at a resolution between 5 and 10 Å  was poorly delimited, possibly due to its high mobility.The Eσion Fig. . The heamentclass2pt{minimσ2B Fig.  that comB protomer structure, we performed local refinement of the octamer C1 -map with masked R1 and R5 protomers which displayed better defined density for σB  aperture of the β‘ clamp were refined at 3.9 and 4.19 Å resolution respectively   with well-defined density of the σΒ C-terminal segment (resolution between 6.5 and 8 Å), and class 2  that lacked density of the σΒ C-terminal segment , stacked between the β lobes and β flaps of the neighboring RNAPs  Fig. . We dete8 Å Fig. . To imprAPs Fig. . Two perAPs Fig. . PotentiA)  displays a closed β flap conformation (rotation angle 80°)32  and negative  regulation of transcription.The β flap domain provides an anchoring point for σ4 and paves the RNA exit channel. In the transcriptionally competent RNAP holoenzyme, the β flap tip faced the β‘ dock  of the RNA exit channel (open flap) and positioned σ4 relative to σ2 at the optimal distance for promoter −10/−35 element recognition  Fig. . The dis)32 Fig.  as well A, free or in complex with ligands: RbpA, CarD, promoter DNA, or fidaxomicin (Fdx), have various clamp states, from open in the Fdx/EσA complex to closed in RPo27. Superposition of the EσB structure with the published models showed that in EσB, the clamp adopted a “fully open” conformation with a rotation angle of 22° relative to σA-RPo , which moved toward the secondary channel rim-helices (β‘ K742-H792) and of the β‘ dock, which moved toward the clamp  that affect clamp dynamics12. We concluded that the fully open-clamp state observed in EσB is characteristic of RNAP inactive state in which the σ subunit regions 3.2 and 4 are unloaded from the RNA exit channel. This immature RNAP conformation may represent an assembly intermediate on the pathway to a transcriptionally active mature conformation of the RNAP holoenzyme.Published cryo-EM structures of Mtb EσRPo Fig.  and a clRPo Fig. . This co15° Fig. . In addiβ‘jaw aa 37–1116, A  was stacked to the β‘ clamp surface in the downstream DNA (dwDNA) channel  was located perpendicular to the clamp inside the dwDNA channel and contacted β lobe 1  in α3-helix that was substituted by alanine (A78) in σΒ. Also, σB-NCR harbored an histidine residue at position 60 (94% of σB sequences) and a leucine residue at position 62 (98% of sequences) that were conserved in σΒ, but not in σA. Hydrophobic interaction of σB-L62 in the a2-helix with σB-L76 in the a3-helix created a bridge that can stabilize the helix-turn-helix domain of σΒ NCR.Structural sequence alignment of σ2A Fig.  showed hder Fig. . An aligB octamer and dimer structures revealed four principal intersubunit interfaces to hold the RNAP protomers together: β flap-σB, β‘ZBD-σB, β‘i1-σB and σBNCR-σBNCR , σB NCR  and σB subregion 2.3  made contacts with residues R69, R67 and I73 in β‘-ZBD. Of these residues, σB Y57 (σA Y258), σB H60 (σA Q261), σB D131 (σA D336), and σB Y132 (σA Y337) were located at the RbpA-binding interface  also interacted with residues in β‘i1 . Finally, R81 (σA R286) and R74 (σA R279) from two adjacent σB NCR faced each other and could make π-stacking interactions37 through guanidinium groups stabilized by N71.Analysis of the EσNCR Fig. . All thebpA Fig. . The invace Fig. . Thus weB oligomerization 8). Octamer formation occurred starting from RNAP concentrations of 0.1 μM which is several orders of magnitude lower than the bulk RNAP concentration in bacterial cells estimated at 5–28 μM39. These results, suggest that RNAP octamer assembly may occur in vivo. Next, we explored the capacity to form octamers by the Mtb RNAP core, Mtb EσΑ and a chimeric RNAP holoenzyme assembled from Mtb σB and E. coli RNAP core (Eco EσB). Analysis of the negatively stained images and SEC profiles showed that none of these proteins could form octamers in our experimental conditions , should interfere with the σANCR-σANCR interactions and hinder oligomerization. Next, we asked whether RbpA and CarD affect EσB oligomerization  to explore the conditions for Eσion Fig. . Analysiers Fig.  migratinons Fig. . Althougons Fig. . Thus, wion Fig. . As RbpAion Fig. . Indeed,ion Fig. . As CarDion Fig. . Yet, SEB octamer structure, the σB subregions 2.3 and 2.4 interact with the β flap. To explore whether the β flap and its binding partner σ4 affected octamer assembly, we constructed RNAP mutants in which residues 811-825 in the β flap tip (Mtb EΔFTσB) and residues 252–323 in the σB domain 4.2 (Mtb EσBΔ4.2) were deleted. Analysis of the SEC profiles  inhibited octamer formation  to affect RNAP-DNA binding directly. It may stabilize an overall fold of σ domain 2, and thus stimulates its interaction with the promoter −10 element.Run-off transcription assays performed with the mutant Eσter Fig. . The Y57act Fig. . FurtherΑ subunit cannot induce octamer formation  between residues 71 and 72 of σB (σB 71Ω72)Fig. . Analysiion Fig. .B 71Ω72 and two complementary methods: single-round run-off transcription assay24 and fluorescent assay to follow RPo formation kinetics in real-time42. To minimize the RNAP dependence on RbpA, we used as template the sigAPext-10 promoter that forms RPo by EσB without RbpA24. We monitored run-off RNA synthesis at different time points after mixing RNAP with promoter DNA.  displayed ~3-fold higher transcriptional activity than EσB (octameric state). In the presence of RbpA (monomeric state), EσB and EσB 71Ω72 showed similar transcriptional activity. Therefore, we concluded that insertion in σB NCR stimulates transcription initiation possibly by inhibiting octamer formation. As the σB NCR residues 71 and 72 are located too far from the promoter, they cannot affect initiation directly through interaction with promoter DNA, as shown for E. coli σ70 NCR43.Oligomerization captures RNAP in the inactive state and is expected to inhibit transcription, while its suppression should stimulate transcription. To assess the oligomerization effect on transcription initiation, we used σNA. Fig. . WithoutsigAPext-10 promoter with the Cy3 dye tethered to the guanine at position +2 of the non-template DNA strand24. Next, we followed Cy3 fluorescence increase upon RNAP binding to the promoter, which is a characteristic of RPo formation  and reflected isomerization of the closed promoter complex (RPc) to RPo42. All three kinetics of RPo formation by RNAPs in the monomeric state  displayed similar fractional amplitudes and rate constants for the intermediate and slow phases. The kinetic constants of RPo formation by RNAP in the octameric state (EσB) were different  than EσB 47. We speculate that the EσΒ octamer may serve as a storage of hibernating EσΒ that can be rapidly converted to the active form by RbpA during stress. EσΒ octamer disassembly leads to a burst in the effective RNAP concentration and consequently should boost transcription yields  is important for the viral life cycle regulation51. Yet, only two cases of regulation that implicate self-assembly of the cellular gene expression machinery into supramolecular structures have been thoroughly described: dimerization of ribosomes in bacteria53 and dimerization of RNAP I in yeast57. In both cases, dimerization was induced by nutrient deprivation and employed as a regulatory mechanism to control ribosome biogenesis and protein synthesis during cell hibernation. Recently, it has been proposed that dimerization of the Bacillus subtilis RNAP core in complex with the HelD helicase is a hibernation mechanism58. There is an amazing convergence in the mechanisms of RNAP inactivation between the evolutionary distant yeast RNAP I and Mtb EσΒ. Like in Mtb EσΒ, in inactive RNAP I dimers, the clamp adopts an open state56. Furthermore, like RbpA, the eukaryotic initiation factor Rrn3, interacts with the RNAP I regions involved in dimer formation and converts RNAP I dimers to initiation-competent monomers59 Thus, RNAP oligomerization controlled by transcription factors emerges as a general regulation mechanism for gene repression in the different kingdoms of life. An exciting direction for future studies will be to explore RNAP octamer formation in live cells and to determine its function.To our knowledge, no structure of octamers formed by RNAPs has been described up to date. Early biochemical studies reported formation of octamers by the E. coli cells transformed with the pMR4 plasmid and purified by Ni2+-affinity chromatography17 followed by purification by anion-exchange chromatography on MonoQ 5/50GL . In brief, 15 g of bacteria were resuspended in 200 ml of lysis buffer , 0.1 mg/ml lysozym). Cells were disrupted by sonication and the lysate, cleared by centrifugation at 9,000 g , was loaded on 5 × 5 ml HisTrap FF columns (GE Heathcare) equilibrated with 40 mM Tris-HCl pH 7.9, 500 mM NaCl, 5% glycerol, 0.2 mM β-mercaptoethanol. Mtb RNAP core was eluted with 300 mM imidazole. Mtb RNAP sample was dialyzed at 4 °C overnight against buffer A . Next, RNAP sample was dialyzed at 4 °C for 2 h against buffer B  and loaded on MonoQ 5/50GL column (GE Heathcare) equilibrated with buffer B. Mtb RNAP core was eluted in linear gradient of NaCl (200–480 mM). Collected peak fractions were pooled, concentrated by Amicon® Ultra-15 Centrifugal Filter Unit (Millipore), supplemented with 20% glycerol, and stored at −80 °C. The 6xHis-tagged E. coli RNAP core was expressed in BL21 DE3 E. coli cells transformed with the pVS10 plasmid and purified as described above for Mtb RNAP. The gene encoding for Mtb CarD (Rv3583c) was PCR-amplified from H37Rv genomic DNA  and cloned between the NdeI and HindIII sites into the pET28a vector under the N-terminal 6xHis-tag. The 6xHis-tagged Mtb CarD, RbpA, and the σA subunit were expressed and purified by chromatography on HisTrap HP  Ni2+-affinity columns as described. The 6xHis-tagged Mtb σB subunit, σB in which residues 252–323 were deleted (σBΔ4.2), and σB with the insertion in NCR (σB71Ω72) were purified by chromatography on HiTrap TALON  columns. To construct the mutant σB 71Ω72, residues N71 and R72 of the σB subunit were replaced by six σA residues (segment 272-KLPAAQ-277) using the Quick Change Lightening site-directed mutagenesis kit (Agilent). Residues 811-825 in the Mtb RNAP β flap were deleted using Quick Change II XL site-directed mutagenesis kit (Agilent). Variants of the wild-type sigAP and sigAPext-10 (harboring the T-17G-16T-15G-14 motif) promoters 5’-end-labeled with fluorescein and the sigAPext-10 promoter internally labeled with Cy3 at position +2 of the non-template DNA strand were prepared as described24. Sequences of primers used for CarD cloning and for sigAP promoter fragments preparation are provided in Supplementary Table 2The 6xHis-tagged Mtb RNAP core was expressed in BL21 DE3 B holoenzyme, 3.4 μM Mtb RNAP core and 3.74 μM σB in transcription buffer  were incubated at 37 °C for 5 min. Next, samples were dialyzed in 10 μl drops on 0.025 μm MF-Millipore membrane filters (VSWP) against dialysis buffer  at 22 °C for 45 min. About 3 μl of sample  was spotted on a Quantifoil R2/2 200 Mesh holey carbon grids which were glow-discharged for 10 s using the PELCO easiGlow system (Ted Pella). Grids were flash-frozen in liquid ethane using Vitrobot Mark IV (FEI) at 20 °C and 95–100% of humidity.To assemble the Eσ−/Å−2/s and a total electron dose of 49.6 e−/Å−2 over a nominal defocus range from −0.5 to −5.0 µm.Data were collected using a spherical aberration (Cs) - corrected Titan Krios S-FEG instrument (FEI) operating at 300 kV acceleration voltage and equipped with a Gatan K2 Summit direct electron detector . Automatic image acquisition was carried out using the EPU software (FEI) in a super-resolution mode at a nominal magnification of ×105,000 with a pixel size of 0.55 Å. Movies (31 frames) were collected at an exposure rate of 6.2 e60. Movie sums were used for contrast transfer function (CTF) estimation with Gctf61. A 3064 dose-weighted movie sums were used in the subsequent image-processing steps. About 100 particles comprising monomers and oligomers were manually picked in cryoSPARC62 and subjected to 2D classification to create templates for automatic picking.Movie frames were aligned, dose-weighted, binned by two, and averaged using Motioncor2A total set of 721,752 particles that included RNAP monomers underwent several 2D classification rounds. A cleaned dataset of 153,953 particles was used in the ab-initio reconstruction to compute the initial model. The ab-initio model was used as reference for the 3D heterogeneous refinement and classification. Two 3D classification rounds produced a cleaned set of 55,008 particles that were used for the homogeneous refinement at 4.19 Å. Then, the local non-uniform refinement resulted in an improved cryo-EM map refined at 4.08 Å.C1-map at a nominal resolution of 6.13 Å. The dataset of 115,457 particles was used for the non-uniform refinement with imposed D4 symmetry to compute the D4-map at a nominal resolution of 4.39 Å. The dataset of 115,112 subtracted particles and the masked C1-map were used for the local non-uniform refinement to calculate the maps of the RNAP monomer and RNAP dimer at a nominal resolution of 3.84 Å and 4.36 Å, respectively The dataset of 115,112 subtracted particles underwent 3D heterogeneous refinement using the R1-R5 RNAP dimer map as reference. The 3D classification produced two RNAP dimer classes with different conformations: class 1, which included 66,519 particles, resolved at 4.38 Å, and class 2, which included 48,593 particles, resolved at 6.75 Å.A dataset of 254,380 particles that included RNAP oligomers underwent several 2D classification rounds to produce a clean dataset of 115,112 particles. The best class averages that included 82,893 particles were used in the reference-free ab-initio heterogeneous reconstruction to produce the initial model. The homogeneous non-uniform refinement of the initial map using 115,112 particles without applying symmetry resulted in a D4-map of the EσB octamer at resolution of 6.3 Å. Then, each particle 2D image was replicated and 3D-rotated according to the D4 point group symmetry and the re-projected density of all but one EσB protomer was subtracted. The resulting expanded dataset of 753,528 subtracted particles was used in alternate cycles of asymmetric 3D classification and 3D local refinement focused on the region occupied by a single EσB protomer. Refinement was first focused on the RNAP core density devoid of the β‘ clamp. A D4-map of the octamer, from which the focused region was masked out, was used for the signal subtraction. The focused region of the RNAP core, which represented the least resolved peripheral zones in the D4-map of the EσB octamer  3D refinement to compute the A holoenzyme (PDB ID 6FBV) were used as starting model. The σΑ subunit was replaced by σB using homology modeling in Modeller63. The model was fitted to cryo-EM maps in UCSF Chimera64 and was manually modified in Coot65. Several cycles of real-space refinement, using secondary-structure restrains and geometry optimization, were performed in Phenix66 using the R1-R5 RNAP dimer and R1 RNAP protomer maps. To improve the σΒ subunit model, it was real-space refined separately in Phenix with the RNAP octamer D4-map. The final EσΒ model was assembled and modified in Coot. The R1-R5 RNAP dimer model was assembled from two copies of EσΒ rigid body refined in Phenix. The EσΒ octamer model was built by applying NCS operators to the EσB protomer model in Phenix followed by modification in Coot.The coordinates of the Mtb Eσ67.100–400 nM RNAP core was mixed with threefold molar excess of the σ subunit in the transcription buffer described above. When indicated, RbpA and CarD (3-fold molar excess) were added to the RNAP core. Samples were incubated at 22 °C for 10 min. The reaction mixtures were dialyzed for 1 h, as described for the cryo-EM samples. Then, 3 μl of mixture was spotted on a Formvar/Carbon copper 200 mesh grids (Electron Microscopy Sciences) glow-discharged for 10 s. Grids were stained with uranyl acetate (1% w/v). Images were collected using an 120 kV JEOL 1200 EX II EM equipped with an EMSIS Quemesa 11Mpixels camera with a nominal magnification of ×50,000 and pixel size 2.86 Å. Particles were counted using the EMAN2 e2boxer moduleΑ, σB variants, RbpA and CarD in 120 μl of transcription buffer were incubated at 24 °C for 1 h. Mtb E was first mixed with RbpA and CarD and then supplemented with the σB subunit. To test the effect of RbpA on the octamer dissociation, Mtb E was incubated with σB overnight at +4 °C, then supplemented with RbpA and incubated at 24 °C for 1 h. Next, a 100 μl of the sample was applied to Superose® 6 Increase 10/300 GL column (Cytiva) equilibrated with 10 mM Tris-HCl pH 8.0, 150 mM NaCl, 5 mM MgCl2, 5% glycerol and run at 0.5 ml/min flow rate.To assess oligomeric states of RNAP, about 200 pmole of E and Eσ holoenzymes formed with twofold molar excess of σB and 300 nM RbpA in 10μl of transcription buffer and incubated at 37 °C for 5 min. 50 nM of promoter DNA was added and incubated at 37 °C for 10 min. Transcription was initiated by adding 50 μM/each of ATP, GTP, CTP, 5 μM of UTP, and 0.5 μM of [32P]-UTP, and performed at 37 °C for 5 min. In single-round kinetics run-off assays, 200 nM RNAP core was mixed with 600 nM σB with or without 600 nM RbpA in 10μl of transcription buffer and incubated at 37 °C for 5 min. Samples prepared without RbpA were incubated at +4 °C overnight to reach the maximum yield of RNAP octamer. After the addition of 100 nM of sigAPext-10 promoter, DNA samples were incubated at 37 °C for 1, 2, 3, 5, 10, or 20 min. Transcription was initiated by adding 100 μM/each of CTP, GTP, ATP, 10 μM of UTP, 0.5 μM of [32P]-UTP, and 0.1 mg/ml poly(dI-dC). Reactions were incubated at 37 °C for 3 min. RNA transcripts were analyzed by denaturing 18% PAGE/7 M urea gels. Gels were scanned with a Molecular Dynamics STORM Imager and quantified by ImageQuant software.In multiple-round transcription assays, 100 nM RNAP core was mixed with 300 nM σsigAPext-10 promoter in a transcription buffer containing 0.1 mg/ml BSA. The final RNAP concentration was 25 nM and the DNA concentration was 5 nM. Data were collected at 30 °C for 20 min. Two consecutive shots were performed and averaged. Each dataset was normalized to the fluorescence signal value at equilibrium and plotted as the fluorescence fold change (FC), where FC = (F–Fo)/Fo. Fo is the signal for DNA alone and F is the signal for RNAP-bound DNA. Values from two experiments were averaged and fitted using the Grace software (v. 5.1.25) with the triple-exponential equation FCt = A0 + Α1· exp(-k1· t)+ Α2· exp(-k2· t) + Α3· exp(-k3· t) where FCt is the total fluorescence change.Data were acquired using a SF-61 DX2 stopped flow spectrophotometer (TgK Scientific UK) with a shot volume of 100 µl, excitation at 535 nm and emission at 570 nm. 200 nM RNAP core was mixed with 1 μM of σ subunit with or without 1 μM RbpA in 100 μl of transcription buffer and incubated at 37 °C for 5 min. Samples prepared without RbpA were incubated at +4 °C overnight. Protein samples were diluted 4-fold in transcription buffer containing 0.1 mg/ml BSA immediately before mixing with promoter DNA. Experiments were initiated by mixing equal volumes of 50 nM RNAP and 10 nM Cy3-labeled Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Reporting Summary


What is not known is how the szl transcription achieves its Bmp4 synexpression pattern. To address the molecular details of szl transcription control, we cloned a promoter of size 1566 base pairs for szl (bps) from the Xenopus laevis genomic DNA. Luciferase and eGFP reporter gene results of this szl promoter (−1566 bp) in its activation and repression patterns by Bmp4/Smad1 and a dominant negative Bmp4 receptor (DNBR) were similar to those of the endogenous szl expression. Reporter gene assays and site-directed mutagenesis of the szl promoter mapped an active Bmp4/Smad1 response element (BRE) and a cis-acting element, which competitively share a direct binding site for Ventx1.1 and Ventx2.1 . Smad1 and ventx2.1 alone increased szl promoter activity; in addition, the binding of each protein component was enhanced with their coexpression. Interestingly, Ventx1.1 repressed this reporter gene activity; however, Ventx1.1 and Ventx2.1 together positively regulated the szl promoter activity. From our analysis, Ventx2.1 binding was enhanced by Ventx1.1, but Ventx1.1 inhibitory binding was inhibited by co-injection of Ventx2.1 for the VRE site. The inhibitory Ventx1.1 co-injection decreased Smad1 binding on the szl promoter. In a triple combination of overexpressed Smad1/Ventx1.1/Ventx2.1, the reduced binding of Smad1 from Ventx1.1 was recovered to that of the Smad1/Ventx2 combination. Collectively, this study provides evidence of Bmp4/Smad1 signaling for a primary immediate early response and its two oppositely behaving target transcription factors, Ventx1.1 and Ventx2.1, for a secondary response, as they together upregulate the szl promoter’s activity to achieve szl expression in a Bmp4 synexpression manner.Sizzled (Szl) is a secreted frizzled protein, having a sequence homology with the extracellular cysteine-rich domain (CRD) of the Wnt receptor, ‘Frizzled’. Contrary to the other secreted frizzled like proteins (Sfrps),  For theszl is a Bmp4 synexpression gene and its levels are dependent on the spatial distribution of the Bmp4 gradient, defined as a high concentration in the ventral region, transitioning to a lower concentration in the dorsal region [Xenopus embryo, research has demonstrated that Szl is initially abundant in the animal cap and the ventral marginal zone at the mid-blastula transition stage and during/after gastrulation, with its functional target, chordin, being almost completely repressed [szl expression via a probable Smad1 binding element [szl promoter have not been reported, although transcriptional regulatory sites for other Bmp4 target genes, including the ventx family members, have been described [szl transcription, involvement of a secondary response for other Bmp4 target synexpression genes, including ventx family genes, has not been addressed. Here, we performed a detailed szl promoter analysis for presence of a Smad1 binding cis-acing element (BRE) as well as a Ventx1.1/2.1 response element (VRE).Sizzled (Szl) belongs to the family of secreted soluble signaling antagonistic proteins (Sfrps) that are structurally related to the membrane bound Wnt receptor, Frizzled . Differel region . The funl region . For theepressed . There h element ,19,20. Hescribed ,22. In aszl promoter containing Bmp4-signaling regulatory cis-acting elements. The isolated promoter of 1566 bps in size had a transcription pattern that was similar to that of the endogenous szl in gastrula of Xenopus embryos. We identified for the first time that the isolated promoter contained a Smad response cis-acting element (BRE) and a Ventx response element (VRE), modulating szl transcription. Additionally, we found that Ventx1.1 alone suppressed szl expression and its promoter activity; however, Ventx2.1 alone had the opposite effect of increasing the relevant expression and promoter activity. Each Ventx1.1 and Ventx2.1 alone recognized the same Vent response element (VRE) located at the proximal region of szl promoter. Interestingly, the combination of both ventx1.1 and ventx2.1 overexpression enhanced szl promoter activity more than that of ventx2.1 overexpression alone. Inhibitory Ventx1.1 coexpression enhanced activatory Ventx2.1 binding on the VRE site. Ventx2.1 also reduced inhibitory Ventx1.1 binding on the same VRE, leading to overall stimulation of szl promoter activity. In addition, inhibitory Ventx1.1 reduced Smad1 binding on the BRE site. The triple combination of Smad1/Ventx1.1/Ventx2.1 recovered the Ventx1.1 mediated reduced binding of Smad1 to the level of Smad1/Ventx2.1 combination. Collectively, these results demonstrate that szl promoter contains direct binding cis-acting elements of Smad1, Ventx2.1 and Ventx1.1 for Bmp4 synexpression, which together positively modulate szl transcription in gastrula Xenopus embryos.In the present study, we isolated the szl is a Bmp4 synexpression gene and its transcription is dependent on the Bmp4 gradient, indicating that szl transcripts accumulate in ectoderm and in the ventral lateral marginal zone [szl, ventx1.1 and ventx2.1 through RT-PCR analysis. We found that szl transcription start from stage 8 at the ventral side of the embryo where Bmp4 signaling is abundant , dnbr  or smad1 (1 ng/embryo) mRNAs were individually injected to the animal pole region of one-cell stage embryos. The qRT-PCR analysis of Bmp4 target genes including szl, ventx1.1, ventx2.1, gata2  at stage 11. The isolated RNA samples were balanced with ornithine decarboxylase (odc), a house-keeping gene which is used for equal loading control in RT-PCR experiments. As expected, Bmp4 and its intracellular signal mediator Smad1 overexpression increased szl transcription of the resultant AC (szl mRNA level by treating embryos with dnbr (a dominant negative Bmp-type 1a receptor) mRNA. The dominant negative Bmp-type 1a receptor, which lacks the intracellular kinase domain [ventx1.1, ventx2.1 and gata2 behaved similarly to the szl expression pattern. Bmp/Smad1 overexpression also enhanced xbra, a pan-mesodermal marker [ventx1.1 via a physical interaction with Smad1 [Bmp4 is the dominant signaling of the ventral side of embryo initiated from early onset of mid-blastula transition stage , and ovenal zone ,26,27. Wabundant . To examopoiesis ), and xbe domain ,30, inhie domain ,31,32,33l marker ,35 whichth Smad1 .szl, a 1566 bp 5′-flanking region of szl.L from translational start site (TLS) was cloned into pGL3-luc+ (pGL3-eGFP+ reporter gene vectors (szl(-1566) promoter construct was injected (40 pg/embryo) to the one-cell stage embryos, and the reporter assays at the designated stages were performed as shown in szl(-1566)-luc+ promoter activity was enhanced by Bmp4  (pGL3.luc+(bambi:-3073) (pGL3.eGFP+(bambi:-3073) . Data from RNA expression patterns  , pGL3.lui:-3073)  and pGL3i:-3073)  promoterpatterns , eGFP impatterns e and thel stages c indeed pression ,37,38. Bszl, vent2, bambi and bmp7, their transcription is regulated in a phospho-Smad1 dependent manner [szl promoter has not been addressed. To determine whether Bmp4/Smad1 is directly involved in synexpression of szl, a protein synthesis inhibition experiment with cycloheximide (CHX) was performed. Bmp4 mRNA (1 ng/embryo) was injected to the one-cell stage embryos and the animal caps were dissected at stage 8. The animal cap explants (ACs) were then cultured in L-15 media until stage 11 in the presence or the absence of CHX in order to determine whether szl is an immediate early (primary) or a secondary response gene to Bmp4. RT-PCR showed that the expressions of szl and a known Bmp4 direct target gene, ventx2, were maintained in the ACs treated with Bmp4 mRNA in presence of CHX (xbrachyury (xbra) disappeared in the CHX treated condition.It has been known that for Bmp4 synexpression genes, including t manner ,39; howee of CHX . By compszl(-1566) promoter, serially-deleted promoter constructs from the cloned szl(-1566) region were made , (-1019), (-716), (-530) and (-370), were positively up-regulated by either Bmp4 or Smad1 (bmp4/smad1 mRNA co-injection ((-312) (-223) and (-197), did not respond to either Bmp4 or Smad1 ectopic expression  response remained even in the smallest construct of szl, namely szl(-197) (szl(-197) may contain negative regulatory element(s), which is addressed in -370 and -312 bps of Xenopus laevis with that of Xenopus tropicalis indicated that the promoter region contained a putative conserved consensus sequence  promoter construct containing a mutated BRE from -370 to -312 bps was made and then tested to determine whether the putative BRE was a functioning site for Smad1 mBRE promoter constructs were injected at the one-cell stage and the reporter gene assays were performed at stage 11. To examine whether the putative BRE was the responding site for Smad1, the constructs with or without Smad1 overexpression were examined in reporter assays at stage 11 (szl(-370), but it was completely abolished with the mutated szl(-370)mBRE construct. Direct binding of Smad1 on the 5′-flanking region of endogenous szl promoter was then examined for gastrula embryos with a quantitative ChIP-PCR experiment, using an anti-Flag antibody immunoprecipitation against injected 3Flag-Smad1 mRNA from the total chromatin of gastrula embryos. The results showed that Smad1 directly bound within the 5′-flanking region of the endogenous szl promoter (szl promoter contains a direct Smad1 binding site (BRE) required for Bmp4 synexpression.To determine the location of Bmp4/Smad1 response elements (BREs) within the ere made a. The cozl(-197) , suggeststage 11 e. Smad1 Szl transcription was positively regulated via direct binding of Smad1 on BRE site of szl promoter, in concordance with the expected results for szl synexpression with Bmp4, as Smad1 is a direct transcription factor mediating Bmp4 signaling. To determine the secondary response elements of Bmp4 signaling on the szl promoter, we examined the effects on szl transcription of two direct targets of Bmp4 signaling, the ventx genes ventx1.1 and ventx2.1. Each promoter of these ventx genes contains a direct binding site of BRE, which is essential for their transcription in response to Bmp4 signaling [szl expression of whole embryos or not, szl(-1566)eGFP (szl-GFP) plasmid (40 pg/embryo) was injected at the one-cell stage with either ventx1.1 or ventx2.1 or ventx1.1/ventx2.1 mRNA together (each at 0.5 ng/embryo). The embryos were then grown until stage 11 to detect their intensity of eGFP fluorescence signal. Ventx1.1 co-injection decreased eGFP intensity  promoter, the serially-deleted szl promoter constructs were examined for response changes. The constructs were injected with or without ventx1.1 mRNA (0.5 ng/embryo) to the one-cell stage embryos and reporter gene assays were performed at stage 11. The relative reporter gene activities showed that all eight serially-deleted promoter constructs of szl(-1566) to (-197) were more than five-fold down-regulated by ventx1.1 (szl(-1566) to (-197) constructs were about four-fold up-regulated by ventx2.1 (szl(-1566)luc+, was then selected for examining the combination effects of ventx1.1/ventx2.1. As expected, ventx1.1 injection decreased the relative reporter gene activity of szl(-1566)luc+ (ventx1.1) bars) and ventx2.1 increased the reporter activity (ventx2.1) bars). Similar to the results of the eGFP and RT-PCR experiments, ventx1.1/ventx2.1 mRNAs when together injected displayed the highest relative reporter gene activity (about seven-fold increase). Ventx2.1 alone injected embryos showed a four-fold increase when compared to that of control samples (ventx2.1) and fourth (ventx1.1/ventx2.1) bars). These data together indicated that the putative cis-acting response element(s) for both Ventx1.1 and Ventx2.1 (VRE(s); Ventx response cis-acting element(s)) may be located within the shortest -197 bps region of szl TLS. DNA sequence analysis was then performed to find a putative Ventx binding element within the szl(-197) region. We examined whether the promoter region contains the core consensus residues (AAAT or ATTT) between the -196 and -191 bps of the proximal region of szl promoter. The szl promoter region contains a putative conserved consensus sequence  promoter construct containing the putative VRE site was mutated to identify whether the putative VRE was a functioning site for Ventx1.1 and/or Ventx2.1, or both. Taken together, the results showed that two direct target transcription factors (Ventx1.1 and Ventx2.1) of Bmp4 signaling oppositely modulate but together upregulate szl transcription, indicating that szl transcription is directly modulated by Bmp4/Smad1 signaling as well as by a secondary response using Bmp4 target transcription factors for Bmp4 synexpression.ignaling ,40. To ected ACs b. We obscted ACs . To dete-197 and -1 bps (AAATTT to GGGTTT)  or mutated szl(-370)mVRE promoter constructs were injected (40 pg/embryo) with and without ventx1.1 or ventx2.1 mRNA (0.5 ng/embryo) at the one-cell stage. The reporter gene assays were then performed at stage 11. For the mutated szl(-370)mVRE, the Ventx1.1-mediated as well as Ventx2.1- and Ventx1.1/Venx2.1-mediated relative luciferase activities of wild type szl(-370) construct were completely abolished (szl(-370) had all disappeared in the single VRE mutated szl(-370)mVRE construct  directly and specifically interacts with the C-terminal of Ventx2.1 in an additive fashion in transcriptional activation of Ventx2.1 [szl transcription. To examine Smad1 and Ventx1.1 and/or Ventx2.1 combined effect on szl transcription, we injected smad1 mRNA alone and in combination of ventx1.1 and/or ventx2.1 at the one-cell stage of Xenopus embryos. Animal caps were then dissected and maintained in L-15 medium. RNAs were isolated from the ACs and the qRT-PCR analysis was then performed. The results showed that szl mRNA expression was enhanced either by smad1 or ventx2.1 and reduced by ventx1.1  promoter construct was then measured after injection alone and with smad1, ventx1.1 and ventx2.1 mRNAs. The luciferase activity results were similar to those of quantitative RT-PCR  of the szl promoter contains cis-acting elements responding to Bmp4/Smad1 signaling as a BRE for a primary response. There was also another cis-acting element, one jointly responding to Ventx1.1 and Ventx2.1 as a VRE for a secondary response, confirming the binding of these two Bmp4 targets acting on the szl promoter. Interestingly, Ventx1.1 alone functions as a repressor  and on the ventral marginal region, but not in dorsal marginal region of normal Xenopus laevis embryos. At the present time, we do not know that Smad1, Ventx2.1 and Ventx1.1 were expressed in the same cells of Xenopus embryos. However, genes of both ventx2.1 and ventx1.1 are the direct targets of Bmp4/Smad1 [szl is also expressed during blastula and gastrula Xenopus embryos. Synexpression genes of Bmp4/Smad1 signaling including ventx2.1 and ventx1.1 may not be exclusively expressed in ventral cells of embryos at least until early gastrula stage since Ventx2.1 has been reported as an activator transcription factor on ventx1.1 promoter working together with Smad1. The regulation differences and synexpression for various Bmp4 synexpression genes in the same cells remain to be investigated; these include the genes whose promoters have been cloned in the present study (bmp7 and bambi1)  transcription factors (TFs) including Gata2 and Xbra are also involved.We demonstrated that eriments . Recentlsing CHX . They aldization . In the ignaling . We specVentx2.1 ,42,43,44and xbra . It is np4/Smad1  and are  bambi1) . On modugata2 [ventx2.1 and itself [ventx2.1 and szl . Consistent with this observation, Sander et al. reported that ventx1.1/ventx2.1 double knockdown by morpholinos downregulates szl expression, indicating that szl is the downstream target gene of Ventx transcription factors [szl promoter and Ventx1.1/Ventx2.1 together positively modulate the expression of szl, a Bmp4 synexpression gene.One interesting observation of this study was the stimulatory transcriptional effect of Ventx1.1 when co-expressed with Ventx2.1 . Ventx1.gata2 , ventx2.d itself . The inh and szl b in the ression. . In the  factors . Whang e factors . However factors ,51. The ventx2.1 promoter [szl could be such a target of Smad1/Ventx2.1 complex, with szl mRNA expression and reporter activity assays, as well as Smad1 and Ventx2.1 binding all showing positive combination effects  cycle and 18 °C ambient temperature, by authorized personnel and according to the guidelines of the Institute of Laboratory Animal Resources of Hallym University for laboratory animal maintenance.This animal study was conducted in accordance with the regulations of the Institutional Animal Care and Use Committee (IACUC) of Hallym University . All the research members attended both the educational and training courses for the appropriate care and use of experimental animals at our institution in order to receive an animal use permit. Adult pSP64T.bmp4, pSP64T.dnbr, 3F.pCS4.smad1, 3F.pCS4.ventx1.1 and 6Myc.pCS2.ventx2.1 were linearized with restriction enzymes EcoR1, Not1 and Acc65I and mRNA was made through in vitro transcription using a MEGA script kit . All transcribed mRNAs were diluted in DEPC treated water and quantified at 260/280 nm wavelength using a spectrophotometer . Aliquots of 0.5, 1 ng/5 nL were made and stored at −80 °C for further use.Various constructed cDNA were obtained by transformation of DH5alpha competent bacterial cells. The introduced cDNA clones including Xenopus blood were used for PCR amplification of szl promoter (−1566 bp), bmp7.1 (−3143 bp)  and bambi (−3073)  having a Kpn1 restriction site at the forward and a Xho1 site at the reverse primer for the szl and bmp7.1 promoters and having a Kpn1 restriction site at the forward and a Nhe1 at the reverse primer for bambi promoter. We amplified each promoter region by PCR cloning using the listed primers (szl promoter (−1566 bp) was subcloned into pGL3.luc+ and pGL3.eGFP+  basic vectors. The cloned szl promoter (−1566 bp) was generated with the reverse primer sequence starting at −8 from TLS to guarantee including all the regulatory sequences for the transcription start of szl based on the deposited szl.L mRNA sequences  which contains 5′UTR of 7 bps [Isolated genomic DNA from  primers . The ampof 7 bps .pGL3.luc+ and pGL3.szl(−1566)eGFP+ constructs for fluorescence detection.In addition, seven serially deleted constructs of various sizes were amplified from the −1566 bp fragment on the basis of mapping the potent Bmp signaling response elements and were cloned into Xenopus Resource Center for Research was the source of adult Xenopus laevis. Five hundred units of human chorionic gonadotropin hormone (HCG)  was injected to female Xenopus leavis in order to induce enough embryos. Freshly chopped male sperm was used for in vitro fertilization of the embryos in 1/20X MMR solution for 30 min. Embryos were de-gelled and subjected to various DNA and mRNA microinjections at the one-cell stage around the sperm entry point into the animal hemisphere. The injected embryos were grown and maintained in 30% MMR solution up to the required specific developmental stage for the experiments.Korea szl(−1566)eGFP and bambi(−3073)eGFP constructs were injected (40 pg/embryo) with or without dnbr (1 ng), ventx1.1, ventx2.1 mRNAs (0.5 ng each) per embryo at the one-cell stage and into the animal hemispheres. Green fluorescence was evaluated using a stereo microscope with royal blue light adapter , and photographs were captured using a Nikon D810 camera .The Animal cap explants (10 AC/sample) of injected embryos were dissected at the early blastula stage, cultured in L-15 media in a 96-well plate, and harvested at the specific stage, followed by further experiments.Total transcribed RNA during a specific required stage was isolated from whole embryos using the TRIzol reagent  and approximately 10 animal cap explants were used. The purified RNA was treated with DNase 1 to remove genomic DNA impurities. SuperScript IV  kit was used for cDNA preparation from 2 µg RNA for each sample.All RT PCR and Chromatin immunoprecipitation assays samples were subjected to qPCR analysis using Biosystems StepOnePlus Real-Time PCR System with Kapa Syber Fast qPCR Master mix. All values were normalized to ornithine decarboxylase (ODC), a house keeping gene of Xenopus embryos which is present all around the embryonic developmental. Graphs were made using threshold cycle (Ct) values, ΔCT, ΔΔCT and relative fold change expression method.szl (−1566 bp) or its serially deleted constructs, mutated BRE and VRE constructs, or the bmp7.1 and bambi constructs along with various indicated exogenous mRNA. Five sets of three embryos were collected at a specific stage and homogenized in lysis buffer (10 µL/embryo). Reporter gene activity was quantified using luciferase assay system (Promega) following the manufacturer’s instructions by luminometer . Specific RT-PCR primers were used to amplify markers genes. (Embryos were injected with s genes. .szl full-length promoter with specific mutagenesis primers (Mutations for Smad1 response element (BRE) and Vent response element (VRE) sites were carried out by using the Muta-Direct site-directed mutagenesis kit , following the manufacturer’s instructions. Mutagenesis PCR was performed from 40 pg/5 nl  primers .HA.pCS4.smad1, 3F.pCS4.ventx1.1 and 6Myc.pCS2.ventX2.1 mRNAs at the one-cell stage either alone or together. Around 200 embryos/ sample at a specific stage were then collected following the reported protocol [Embryos were injected with protocol . Anti-Fl3flag.ventx1.1 and myc.ventx2.1 constructs mRNAs, separately and co-injected. All samples were collected at stage 11, and after removing MMR solution through spin down, embryos were homogenized in IP lysis buffer and followed the protocol as described in Kumar et al. (2018) [Equal amounts of embryos were injected at one-cell stage with . (2018) . The homt-test or ANOVA were applied for statistical analysis. p ≤ 0.05 for *, p ≤ 0.01 for **, p ≤ 0.001 for ***, p ≤ 0.0001 for ****, ns (not significant) were the assignments for significance.GraphPad Prism 8  and MS Excel  were used for plotting the graphs. Unpaired two-tailed Student’s


ChIPBase has identified ∼151 187 000 regulatory relationships between ∼171 600 genes and ∼3000 regulators by analyzing ∼55 000 ChIP-seq datasets, which represent a 30-fold expansion. Moreover, we de novo identified ∼29 000 motif matrices of transcription factors. In addition, we constructed a novel ‘Enhancer’ module to predict ∼1 837 200 regulation regions functioning as poised, active or super enhancers under ∼1300 conditions. Importantly, we constructed exhaustive coexpression maps between regulators and their target genes by integrating expression profiles of ∼65 000 normal and ∼15 000 tumor samples. We built a ‘Disease’ module to obtain an atlas of the disease-associated variations in the regulation regions of genes. We also constructed an ‘EpiInter’ module to explore potential interactions between epitranscriptome and epigenome. Finally, we designed ‘Network’ module to provide extensive and gene-centred regulatory networks. ChIPBase will serve as a useful resource to facilitate integrative explorations and expand our understanding of transcriptional regulation.Non-coding RNAs (ncRNAs) are emerging as key regulators of various biological processes. Although thousands of ncRNAs have been discovered, the transcriptional mechanisms and networks of the majority of ncRNAs have not been fully investigated. In this study, we updated ChIPBase to version 3.0 ( Eukaryotic genomes produce various types of RNAs, including mRNAs, microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and other ncRNAs . Transcriptional regulation of ncRNAs and protein-coding genes (PCGs) plays an important role in many biological processes, and their dysregulation is frequently involved in the tumorigenesis of many human cancers and the development of various diseases ,2. ThereChromatin immunoprecipitation followed by sequencing (ChIP-seq) precisely delineates the genome-wide interaction profiles between genes and various transcriptional regulators. Tremendous amounts of ChIP-seq data have been generated by thousands of independent studies and several consortium projects, such as the ENCODE  and NIH To systematically explore the transcriptional regulation of thousands of ncRNAs and PCGs and their relationships with human cancers and diseases, we updated ChIPBase  to versiWe collected a total of ∼55 420 ChIP-seq datasets from the ENCODE project , ReMap dArabidopsis thaliana) from GENCODE  upstream and 1, 2, 5 and 10 kb downstream from the TSSs as the examined regulatory domains for various types of genes. Then, we intersected ChIP-seq peak regions with these regulatory domains to generate transcriptional regulatory relationships.2 of the fragments per kilobase million (FPKM) value. Coexpression profiles between ChIP-seq factors and various types of genes were calculated according to the Pearson correlation coefficient (Pearson's r) as well as the P value in a t-test (Student's t-test).All expression data were normalized by taking logZ-score of each peak signal to enable comparisons across biological samples. Then, we merged all peak regions within the same condition (e.g. same cell/tissues/treatment) if they overlapped by using the ‘bedtools merge’ program with the parameters ‘-c 4,5,6 -o first,mean,first’. We used the ‘bedtools intersect’ program to find overlap between H3K4me1 and H3K27me3 peaks within the same circumstance for poised enhancer identification. Similarly, we found the overlaps between the H3K4me1 and H3K27ac peaks for active enhancer identification. Based on the active enhancers, we referred to previous methods for identification of super-enhancers  genotype data of the HapMap project (release 28)  . All theTo investigate the potential connections between epitranscriptome and epigenome, we systematically explored the distributions of RNA modification coordinates around histone modification regions. We downloaded RNA modification sites of humans and mice from the ENCORE databases , includiTo enable extensive exploration of the transcriptional regulation of the genes of interest, ChIPBase v3.0 performs genome-wide analysis of ChIP-seq data with multiple types of genes, including different types of ncRNA genes and PCGs.Arabidopsis thaliana. Through conjoint analysis with 55 421 curated ChIP-seq datasets from ∼5000 cell lines or tissue types, we identified ∼41 796 020 transcriptional regulatory relationships between lncRNAs and TFs, ∼5 762 250 between miRNAs and TFs, ∼12 739 900 between other ncRNAs and TFs, and ∼90 889 220 between mRNAs and TFs . We calculated the percentage of interaction in each sample and provide detailed information about each interaction relationship. In ChIPBase v3.0, we construct a novel ‘EpiInter’ module, in which users can select the RNA modification and histone modification to browse detailed information of interest, including the locus, ChIP-seq coverage and so on  ChIPBase v3.0 constructs a novel ‘Enhancer’ module to identify tens of thousands of associations between potential enhancer RNAs (eRNAs) and three types of enhancers from various cell lines or tissues. By enabling a comprehensive characterization of eRNAs in various tissues, we believe that the ‘Enhancer’ module will be a valuable resource for understanding the functions and mechanisms of eRNAs. (f) ChIPBase v3.0, for the first time, links transcriptional regulation to disease development by integrating a large number of disease-related SNV and SNP sites. ChIPBase v3.0 constructs a novel ‘Disease’ module to display the correlations between transcription factor binding regions or motifs and somatic mutations across human tissues and diseases. The vast amounts of variation data collected from ICGC, GWAS, and COSMIC datasets will help researchers to study the influences and functions of transcription factor binding motifs in various genes involved in human diseases. (g) We constructed a ‘Network’ module to provide extensive and gene-centred regulatory networks, allowing researchers to decode more information on transcriptional regulation more quickly for the gene of interest. (h) We also constructed an ‘EpiInter’ module to explore the potential connections between the epitranscriptome and epigenome. (i) We offer the optimized module ‘Batch-download’ to download all files at once more conveniently. (j) ChIPBase v3.0 provides a variety of interfaces and graphic visualizations to facilitate analysis of the massive numbers of DNA-binding protein binding sites, motifs, expression profiles, and regulatory networks in normal tissues and cancer cells. Overall, ChIPBase v3.0 provides biologists with better analysis resources to investigate the transcriptional regulatory mechanisms of ncRNAs and PCGs across different biological conditions that underlie the functions of transcription factors and histone modifications.In this study, we developed ChIPBase v3.0 to decode the encyclopedia of transcriptional regulation of ncRNAs and PCGs by integrating thousands of multiomics sequencing datasets. Different from other ChIP-seq databases that mainly focus on collecting ChIP-seq data and providing genomic profiles of ChIP-seq peaks, ChIPBase v3.0 has a core theme of transcriptional regulation, as it focuses on research regarding ncRNA and PCG functional networks. Compared with the previous version, ChIPBase v3.0 has significant advances and improvements in many aspects, including data amounts, features and function (Table 1 and Table With the progress of ChIP-seq technology, an increasing number of types of DNA-level sequencing technologies have been developed and applied, and we hope to collect the resulting new types of data in the future to make our database more complete. We will also integrate the new high-throughput data generated from CLIP-seq and Ribo-seq technologies as well as RNA modification, miRNA target and other data. We will continue to improve the computer server performance for storing and analysing the new incoming data and will continue to develop more tools to conduct a comprehensive analysis of transcriptional regulation.https://rnasysu.com/chipbase3/. The ChIPBase data files can be downloaded and used in accordance with the GNU Public License and the licences of primary data sources.ChIPBase v3.0 is freely available at gkac1067_Supplemental_FileClick here for additional data file.


Triplex-forming oligonucleotides (TFOs) can bind to the major groove of double-stranded DNA with high specificity and affinity and inhibit gene expression. Triplex-forming oligonucleotides have gained prominence because of their potential applications in antigene therapy. In particular, the target specificity of triplex-forming oligonucleotides combined with their ability to suppress oncogene expression has driven their development as anti-cancer agents. So far, triplex-forming oligonucleotides have not been used for clinical treatment and seem to be gradually snubbed in recent years. But triplex-forming oligonucleotides still represent an approach to down-regulate the expression of the target gene and a carrier of active substances. Therefore, in the present review, we will introduce the characteristics of triplex-forming oligonucleotides and their anti-cancer research progress. Then, we will discuss the challenges in their application. Numerous gene diseases are related to genome mutations, so the therapeutic strategies that enable targeted editing in genetic disease treatment have attracted more attention . TriplexRNA interference (RNAi) is an effective mRNA-level intervention technology, but it does not change the genetic code, and gene silencing is transient. In comparison, the advantage of TFOs lies in their ability to target and permanently modify disease-specific genes . Paquet 2+, Ca2+, and Zn2+) to enhance triplex stability (+) bind to DNA with AT and GC base pairs to form the canonical base triads T:AT and C+:GC with duplex DNA  or multidrug resistance (MDR) also can be the target gene.in vitro transcription of the c-myc gene  in breast cancer cells  to the 3′ end of TFOs via histidine to induce DNA double-strand breaks (DSB) when brought close to the DNA strand by TFOs. The formed 99mtechnetium-coupled TFOs also bind to the TTS to form stable triplexes and inhibit bcl-2 gene transcription in vitro, indicating that TFOs are a promising carrier for gene-radiotherapy and may provide an additional therapeutic method for cancers with bcl-2 overexpression (The B cell lymphoma-2 (bcl-2) is one of the most important endogenous anti-apoptotic factors and is located on human chromosome 18q21 . Bcl-2 opression . In addipression . Tanigucpression .The human EGF-like receptor 2 (HER2) is functionally implicated in the pathogenesis of human breast cancer and is an important prognostic and predictive marker in breast cancer . HER2 isin vitro. They found that Ets2-targeting TFO can act as a selective transcriptional repressor of Ets2 transcription in human prostate cancer cells, suggesting that the triplex formation was the functional mechanism of the anti-transcriptional activity of the Ets2-TFO (E26 oncogene homolog 2 (Ets-2) is a member of the ETS transcription factor family and is located on human chromosome 21q22. The abnormal expression of Ets2 exists in various cancer types, including prostate, breast, and thyroid cancers. It may contribute to the occurrence and progression of tumors by activating the expression of multiple genes that promote cell proliferation and invasion or prevent apoptotic cell death. Carbone and colleagues found a potential TTS located −40 to −65 relative to the transcription start site in the Ets2 promoter, which contains a region that can be bound to transcription factors of the Sp family. Sp1 sites may be critical for promoter activity of the Ets2 gene. They designed a pyrimidine-rich Ets2-targeting TFO, which has high affinity and specificity for the TTS, for inhibiting the bind of Sp1/Sp3 transcription factors and Sp1 site Ets2-TFO . The preEts2-TFO .Some of the genes involved in EMT or MDR have also drawn the concerns of many researchers. EMT is a process that epithelial cells lose the apical-basal polarity and cell-cell adhesion and then transit to invasive mesenchymal cells. It is well-known that EMT plays an important role in cancer progression, metastasis, and even drug resistance . The c-mThe experiments described in the previous section have shown that TFOs can be used as antigene agents to control the activity of the tumor-associated gene. But many challenges remain, particularly efficient uptake of TFOs into the nucleus, stability once inside the cell, and specific, high-affinity binding to TTS in a cellular environment.+ concentrations, which has restricted their use as gene-targeting agents. Moreover, a quick degradation of TFOs also is a big drawback. Therefore, modifications are necessary for the TFOs design. Rusling introduced the nucleobase 6-amino-5-nitropyridin-2-one (Z) to take the place of cytosine in pyrimidine-rich TFOs to overcome the pH dependence of triplex formation , transcription activator-like effector nucleases (TALENs), and CRISPR/Cas9 platform . In shor125I, pyrene, and psoralen, can be conjugated or labeled with TFOs to target specific sites in the genome based on the sequence-specific action of TFOs , which could be used as an ideal delivery system and would allow systemic injections of TFOs. Therefore, TFOs as an anti-gene technique for cancer therapy still have great attraction and application prospects and need further research and exploration.