We show that notochord-expressed Cpeb1b is required for HSPC development by regulating Hedgehog signaling. Cpeb1b interacts with shha mRNA in the liquid-like condensates and promotes its cytoplasmic polyadenylation. Cytoplasmic polyadenylation of shha mRNA enhances its own translation efficiency and therefore increases the Shha protein level, which facilitates Hedgehog signaling activation.HSPCs have the capacities of both self-renewal and multilineage differentiation and hold great importance for lifelong blood supply. The developmental signals ensure the production of HSPCs through endothelial-to-hematopoietic transition during vertebrate embryogenesis. However, how these signals are accurately regulated to execute cell fate transition remains elusive. In this study, we explore the role of Cpeb1b in HSPC production and uncover its function via cytoplasmic polyadenylation of  shha messenger RNA (mRNA) in the liquid-like condensates, which are induced by Pabpc1b phase separation, is required for cytoplasmic polyadenylation of shha mRNA. Intriguingly, the cytoplasmic polyadenylation regulates translation but not stability of shha mRNA, which further enhances the Shha protein level and Hh signal transduction. Taken together, our findings uncover the role of Cpeb1b-mediated cytoplasmic polyadenylation in HSPC development and provide insights into how posttranscriptional regulation can direct developmental signals with high fidelity to translate them into cell fate transition.During vertebrate embryogenesis, hematopoietic stem and progenitor cell (HSPC) production through endothelial-to-hematopoietic transition requires suitable developmental signals, but how these signals are accurately regulated remains incompletely understood. Cytoplasmic polyadenylation, which is one of the posttranscriptional regulations, plays a crucial role in RNA metabolism. Here, we report that Cpeb1b-mediated cytoplasmic polyadenylation is important for HSPC specification by translational control of Hedgehog (Hh) signaling during zebrafish early development. Cpeb1b is highly expressed in notochord and its deficiency results in defective HSPC production. Mechanistically, Cpeb1b regulates hemogenic endothelium specification by the Hedgehog–Vegf–Notch axis. We demonstrate that the cytoplasmic polyadenylation element motif-dependent interaction between Cpeb1b and  During vertebrate embryonic development, the hematopoiesis occurs through two waves: the primitive wave only generates erythrocytes and myelocytes, and the definitive wave can produce hematopoietic stem and progenitor cells (HSPCs), which have the capacity to give rise to all lineages of blood cells and maintain the entire blood system –3. Durin4Several developmental signals have been reported to be critical for hematopoiesis , 3, 8. A9126A modification  tail length, codon usage, and RNA structure, plays a crucial role in the regulation of gene expression and signaling specificity through controlling metabolism of RNA molecules –20. Recefication , are invfication , 25. CPEcation 25. CPEB prcation 25–31, germcation 25, cellulacation 25, muscle cation 25, and immcation 25. Howevercpeb1a and cpeb1b  and found that cpeb1b displayed maternal expression and was highly expressed in the notochord region from 14 to 24 h post fertilization (hpf) . Moreover, double fluorescence in situ hybridization (FISH) was carried out with cpeb1b and a well-known notochord-specific marker gene shha. FISH result showed that the green cpeb1b signals were colocalized with the red shha signals in the notochord at 14 and 16 hpf , confirming the notochord-enriched expression of cpeb1b. To determine whether Cpeb1b plays a potential role in zebrafish embryonic hematopoiesis, we utilized the knockdown approach by injection of cpeb1b anti-sense ATG morpholino (MO) , whose effectiveness was verified by western blot (WB) . WISH revealed that the primitive hematopoiesis marked by gata1 (erythroid) and spi1 (myeloid) expression at 14 hpf was normal , and time-lapse imaging showed that the blood flow at 32 hpf was not altered in the cpeb1b morphants (MO-injected embryos) compared with control (Movie S1). However, cpeb1b morphants exhibited impaired HSPC production in definitive hematopoiesis marked by the expression of HSPC markers runx1 and cmyb in VDA at 36 hpf (cmyb-marked HSPCs in CHT at 2 days post fertilization (dpf) and HSPC-derived lymphocytes in thymus at 4.5 dpf was also evidently reduced in the cpeb1b morphants (cpeb1b mRNA without the cpeb1b MO binding site (to avoid inhibition by its antisense MO)  rescued this HSPC defect , indicating that the defective phenotype resulted from cpeb1b loss-of-function. To further validate the HSPC phenotype upon cpeb1b knockdown, we observed the living definitive hematopoietic precursors by using the Tg(flk1:mCherry/cmyb:GFP) double-transgenic line and found that the number of flk1 and cmyb double-positive precursors within the VDA region was markedly decreased in the cpeb1b morphants . In addition, we generated a cpeb1b-null frameshift mutant by CRISPR/Cas9 technology to confirm the cpeb1b loss-of-function phenotype. The zygotic mutant embryos were obtained by cross-mating heterozygous mutants , however, we failed to obtain the maternal-zygotic mutant embryos due to the defective germ cell and ovary development in zygotic mutant adult zebrafish, which are similar to that in mouse  cpeb1b MO into wild-type (WT) and cpeb1b zygotic mutants and observed severe HSPC defect, which is similar to that in the cpeb1b morphants, in the cpeb1b mutants injected with LD cpeb1b MO, but not in the wildtype , indicating that maternal effect indeed led to the alleviation of phenotype. Previous studies have demonstrated that HE specification is a prerequisite for HSPC generation during early development (gfi1:GFP) transgenic line and found that the number of gfi1 positive HE cells within the VDA region was decreased in the cpeb1b morphants . Furthermore, WISH showed that there were fewer HE cells in the cpeb1b morphants compared to control  inducible Cpeb1b overexpression system. Strong green fluorescence of green fluorescent protein (GFP)-Cpeb1b was detected from 2 h post heat shock at indicated time points to at least 20 h post heat shock . WISH showed that heat shock induction of Cpeb1b at 10 hpf, but not at 20- or 30 hpf, rescued the HSPC defect in the cpeb1b morphants  for RNA-seq analysis. Gene ontology (GO) analysis revealed that the downregulated and upregulated genes in Cpeb1b-deficient embryos were enriched in various signaling pathways, such as canonical glycolysis, mitogen-activated protein kinase cascade, Hh signaling pathway, histone ubiquitination, cellular ion homeostasis, vitamin metabolic process, and others (Dataset S1). Among these altered signaling pathways in GO analysis, the Hh signaling, which was downregulated in Cpeb1b-deficient embryos at 16 and 22 hpf, has been previously demonstrated to regulate HSPC generation in zebrafish and mouse . qRT-PCR showed that the reduced expression of Hh downstream gene gli1 in the cpeb1b morphants was rescued by shha overexpression . On the contrary, inhibition of the Hh signaling by its antagonist cyclopamine, which directly binds to and inhibits Hh signaling coreceptor and transducer Smo , confirming a critical role of Hh signaling in HSPC development. In addition, we noticed that the Cpeb1b-deficiency–induced phenotype was weaker than that in embryos with cyclopamine treatment , implying that not all the Hh member-mediated signaling is inactivated in Cpeb1b-deficient embryos. Taken together, these results above indicate that Cpeb1b regulates HSPC development through Hh signaling.To further determine the timing of Cpeb1b function, we applied orphants A and B, nd mouse . Combineorphants E. To detpression F, and WIpression G and H. ucer Smo , impairevegfa was decreased in the cpeb1b morphants compared with control , indicating that Cpeb1b-deficiency leads to downregulation of Vegf signaling. WB showed that the protein level of NICD was decreased in the cpeb1b morphants , and qRT-PCR showed that the expression of Notch signaling downstream genes hey1 and hey2 was also decreased in the cpeb1b morphants . Next, we took advantage of the Notch reporter line Tg(fli1a:EGFP/tp1:mCherry) to examine Notch activity in ECs and found that the number of fli1a+tp1+ cells in the VDA region was reduced , demonstrating that Cpeb1b-deficiency resulted in attenuated Notch activity. Furthermore, WISH showed that the expression of Notch signaling-related artery genes efnb2a and dll4 was also decreased in the cpeb1b morphants at 26 hpf . By contrast, the expression of another arterial marker tbx20 was relatively normal in the cpeb1b morphants , suggesting that the dorsal aorta still developed in the Cpeb1b-deficient embryos, which is consistent with previous studies in that Notch signaling alteration does not necessarily result in loss of dorsal aorta , implying that the phenotype severity might be dependent on the Hh signaling level. To investigate whether Notch signaling activation can rescue the HSPC phenotype, we utilized a system for HS–inducible overexpression of NICD, which is a dominant activator of Notch signaling. The function of NICD overexpression on Notch signaling activation was confirmed . qRT-PCR showed that the reduced expression of Notch downstream gene hey2 in the cpeb1b morphants was rescued by NICD overexpression , and WISH showed that the HSPC phenotype in the cpeb1b morphants was also rescued by NICD overexpression . Combined with the previous data, these results suggest that the Hedgehog–Vegf–Notch signaling axis is involved in Cpeb1b-mediated regulation of HSPC development.Previous studies showed that Vegf signaling acts downstream of Hh signaling and upstream of the Notch signaling during early development, and this Hedgehog–Vegf–Notch signaling axis is crucial for HSPC generation , 40. Besal aorta , 41, 42.shha (Dataset S2), which is important for Hh signaling induction  , which is similar to that in the shha mutant. Together with the observation that cpeb1b was colocalized with the shha in the notochord region of 16 hpf zebrafish embryo by FISH, we thus focused on shha mRNA for subsequent analysis. The interaction between Cpeb1b and shha mRNA in RIP-seq was further confirmed by RIP-qPCR assay . To determine whether this also occurs in zebrafish embryo, we coexpressed GFP-Cpeb1b and Cy3-shha in embryos and found that GFP-Cpeb1b colocalized with Cy3-shha in a similar granular pattern in the notochord region of 16 hpf embryos (shha mRNA by FISH and utilized the immunofluorescence (IF) to detect the endogenous Cpeb1b. The confocal imaging showed similar result (Movie S2), suggesting that Cpeb1b molecules in these condensates could diffuse and exchange with surrounding dilute solution. Moreover, pairs of the GFP-Cpeb1b droplets could fuse and combine into one droplet , further demonstrating liquid-like characteristics of these condensates. In addition, we performed FRAP on Cy3-shha by using a 561-nm laser and found recovery of Cy3-shha fluorescence within the bleached region (Movie S4), suggesting that Cy3-shha in these condensates could also freely exchange with surrounding dilute solution. Taken together, these results above illustrate that Cpeb1b interacts with shha mRNA in the liquid-like condensates. Previous studies reported that some of the CPEB family members can undergo liquid–liquid phase separation by their prion-like domains (PLDs) . Moreover, we performed in vitro cell-free phase separation assay by using purified Cpeb1b protein, which was labeled with Alexa488, and found that Cpeb1b did not form condensates , indicating no phase separation ability of Cpeb1b itself. Considering that CPEB family proteins interact with poly(A)-binding protein (PABP) family proteins within cytoplasmic polyadenylation complex . To reveal the subcellular localization of Pabpc1b, we cotransfected mCherry-pabpc1b and GFP-cpeb1b plasmids into HEK293T cells. Confocal imaging showed that mCherry-Pabpc1b colocalized with GFP-Cpeb1b in the cytoplasmic condensates . Consistently, mCherry-Pabpc1b also colocalized with GFP-Cpeb1b in punctate pattern in the notochord region of 16 hpf embryos . We analyzed the PLDs of Pabpc1b using the PLAAC algorithm and found that there indeed existed PLDs, which was similar to the ubiquitously expressed human homologous gene PABPC1 . Then, we performed in vitro phase separation assay by using Alexa488-labeled Pabpc1b protein. The imaging showed that Pabpc1b formed spherical condensates in 150 mM but not 1 M KCl condition , and FRAP showed recovery of Alexa488-Pabpc1b fluorescence within the bleached droplets . These results suggest that Pabpc1b was able to undergo phase separation, and the condensates formed by Pabpc1b were sensitive to high ionic strength, which can severely affect electrostatic interactions. To examine the intracellular Pabpc1b phase separation, we transfected mCherry-pabpc1b plasmid into HEK293T cells and found that Pabpc1b alone formed very few of condensates . By contrast, cotransfection of pabpc1b and cpeb1b led to much more condensates , implying that Cpeb1b might promote intracellular Pabpc1b phase separation. In addition, we knocked down Pabpc1b by pabpc1b MO injection and found that the runx1 expression at 36 hpf was reduced in the pabpc1b morphants compared with control , suggesting that Pabpc1b is also important for HSPC production.To further explore the molecular mechanism of Cpeb1b in HSPC development, we performed RNA immunoprecipitation (RIP)-seq by using Flag-Cpeb1b to identify target mRNAs of Cpeb1b in embryos. Intriguingly, the result showed that Cpeb1b coimmunoprecipitated with nduction , 40. A pou (syu) . ConsistCR assay A. To obs embryos B. Further result C. Previor result –45, thens (PLDs) , 46–48, (PLDs) 46 and surp complex , 25, and complex , we nextc period , which ishha mRNA  , 25, whihha mRNA A, then wPE motif A and perPE motif B and C, PE motif D and E. wn assay F and G, Xenopus and mammals, CPEB-regulated cytoplasmic polyadenylation is reported to rely on the CPEB partner Tent2, which as a noncanonical poly(A) polymerase is response for cytoplasmic poly(A) lengthening , suggesting that these molecules can form a complex together. Then, we examined the poly(A) length of shha mRNA in embryos at different developmental stages by PCR poly(A) test (PAT) assay  length between 16 and 22 hpf was similar , suggesting an important poly(A) length shift between 8 and 16 hpf. Next, we investigated the Cpeb1b-regulated cytoplasmic polyadenylation. The PAT assay revealed that the poly(A) tail length of shha mRNA in the cpeb1b mutants was decreased at 16 and 22 hpf, but not at 8 hpf, compared with that in the WT  assay C 52). G. GXenopun the WT D. By conl stages E. Taken shha mRNA in the control and cpeb1b morphants at 16 hpf by WISH and surprisingly found no difference between the two groups . To examine the stability of shha mRNA, we treated the embryos with α-amanitin for inhibition of polymerase II-mediated nascent mRNA transcription and detected the relative level of shha mRNA in the control and cpeb1b morphants at the indicated time intervals by qRT-PCR. The 18s rRNA, which is transcribed by polymerase I and not sensitive to α-amanitin, was used as an internal control. The qRT-PCR result revealed that Cpeb1b deficiency did not alter the stability of shha mRNA . Next, to explore whether the translational efficiency of shha mRNA was affected, we performed ribosome profiling assays and found that the global and shha mRNA translational efficiency in the cpeb1b mutants was decreased at 16 and 22 hpf, but not at 8 hpf . Consistently, WB analysis showed a decreased endogenous Shha protein level , we showed that in WT embryos, the Shha-Flag expression was reduced in mutant CPE motif groups at 16 and 22 hpf, but not at 8 hpf, compared with that in the WT CPE motif groups  terminator, was in vitro polyadenylated. We respectively overexpressed these mRNAs in the cpeb1b mutant embryos and found that the polyadenylated shha mRNA almost fully rescued the HSPC defect , suggesting a mild somite developmental defect induced by Cpeb1b-deficiency. In addition, the fkd4, which is another downstream gene of Hh signaling , suggesting a mild nervous system developmental defect. However, the pectoral fin development, which is also regulated by Hh signaling .In consideration of the role of Hh signaling is broad and not restricted to HSPC development , 53, we myod , 55 at 1ignaling , 56, expignaling , was norshha mRNA through the CPE motif in the liquid-like condensates, and Cpeb1b-deficiency inhibits cytoplasmic polyadenylation of shha mRNA, further impairing its translation. Altogether, these findings suggest that Cpeb1b-mediated cytoplasmic polyadenylation plays an important role in HSPC development through translational control of Hh signaling  stimulation, further inducing RA-dependent shh transcription  the interaction between Cpeb1b and shha mRNA is dependent on the particular CPE motif and is important for regulating translation but not stability of shha mRNA, contributing to specificity at the molecular level. Although there are many other mRNAs binding to Cpeb1b in the RIP-seq data, based on a series of experiments on phenotype and signaling pathway analysis, we speculate that the shha should be the main and direct target responsible for the HSPC defect in the Cpeb1b-deficient embryos. Moreover, multiple signals besides Hh were altered in Cpeb1b-deficient embryos in our GO analysis. The signals, such as canonical glycolysis, histone ubiquitination, cellular ion homeostasis, response to unfolded protein, and vitamin metabolic process, are involved in physiological-biological activities of glucose homeostasis, histone modification, ion transport, unfolded protein response, and vitamin metabolism regulation. Whether these signals are indeed regulated by Cpeb1b as well as being involved in HSPC development awaits further investigation.In vertebrates, Hh signaling, as a crucial developmental signal, is regulated by various factors to improve the signal transduction accuracy. At the transcriptional level, HNF3β transcription factor binds to the specific HNF3β motif in pression –59. Morecription . At the cription . Besidescription . In addiIn addition, we show that Cpeb1b-deficiency mildly affects the development of nervous system and somite, which is known to be regulated by Hh signaling –56, suggAplysia, the multimerization of ApCPEB, which is induced by its N-terminal PLD, is enhanced by serotonin stimulation and is essential for the maintenance of long-term facilitation by upregulation of local protein synthesis in neurons  polymerase Tent2 in the cytoplasmic condensates under normal conditions. Based on the results of FRAP and granule fusion assays, we find that the molecules in these condensates are dynamic, suggesting liquid-like but not pathological or gel-like characteristics of these condensates. Intriguingly, Cpeb1b does not have PLDs and cannot undergo aggregation by itself, which is different from other CPEB members. Nevertheless, Cpeb1b colocalizes with Pabpc1b and efficiently promotes Pabpc1b’s phase separation ability, which further induces the condensate formation. Although this condensation phenomenon in Cpeb1b-mediated cytoplasmic polyadenylation is evident, the detailed molecular mechanism remains elusive. At the subcellular level, condensation changes the spatial distribution and local quantity of biomolecules Click here for additional data file.Dataset S01 (XLSX)Click here for additional data file.Dataset S02 (XLSX)Click here for additional data file.Dataset S03 (XLSX)Click here for additional data file.Movie S1.The blood flow in the control and Cpeb1b-deficient embroys. Time-lapse imaging was performed to observe the blood flow in the control and Cpeb1b morphants. Scale bar, 100 μm.Movie S2.Fluorescence signal recovery of GFP-Cpeb1b droplet. Time-lapse imaging was performed to observe the fluorescence signal recovery of GFP-Cpeb1b droplet in HEK293T cells. A bleaching 488 nm laser pulse was applied. In this representative movie, one condensate was tested, and one condensate recovered. The lapsed time was 420 s. Scale bar, 10 μm.Movie S3.The fusion of GFP-Cpeb1b droplet. Time-lapse imaging was performed to observe the fusion of GFP-Cpeb1b droplet in HEK293T cells. In this representative movie, twenty condensates were showed, and four condensates fused. The lapsed time was 180 s. Scale bar, 2 μm.Movie S4.shha mRNA.Fluorescence signal recovery of Cy3-labeled  Time-lapse imaging was performed to observe the fluorescence signal recovery of Cy3-labeled shha mRNA in HEK293T cells. A bleaching 561 nm laser pulse was applied. In this representative movie, one condensate was tested, and one condensate recovered. The lapsed time was 420 s. Scale bar, 10 μm.Movie S5.Fluorescence signal recovery of Alexa488-labeled Pabpc1b in vitro. Time-lapse imaging was performed to observe the in vitro fluorescence signal recovery of Alexa488-labeled Pabpc1b. A bleaching 488 nm laser pulse was applied. In this representative movie, one condensate was tested, and one condensate recovered. The lapsed time was 420 s. Scale bar, 2 μm.


Drosophila cells and optimize it for mapping 3D epigenomes in human cells robustly. Applying ChIATAC to primary human T cells, we reveal mechanisms that topologically regulate transcriptional programs during T cell activation.Connecting genes to their cis-regulatory elements has been enabled by genome-wide mapping of chromatin interactions using proximity ligation in ChIA-PET, Hi-C, and their derivatives. However, these methods require millions of input cells for high-quality data and thus are unsuitable for many studies when only limited cells are available. Conversely, epigenomic profiling via transposase digestion in ATAC-seq requires only hundreds to thousands of cells to robustly map open chromatin associated with transcription activity, but it cannot directly connect active genes to their distal enhancers. Here, we combine proximity ligation in ChIA-PET and transposase accessibility in ATAC-seq into ChIATAC to efficiently map interactions between open chromatin loci in low numbers of input cells. We validate ChIATAC in  Methods connecting genes to their cis-regulatory elements usually requires millions of input cells. Here the authors combine proximity ligation in ChIA-PET and transposase accessibility in ATAC-seq, reporting ChIATAC, to map interactions between open chromatin loci in low numbers of input cells. Advanced chromatin interaction-mapping methods based on proximity ligation—such as Hi-C7 and ChIA-PET10—have greatly expanded our knowledge of 3D genome organization in human and model organisms. In particular, the inclusion of chromatin immunoprecipitation (ChIP) to specifically enrich protein factor-associated chromatin complexes in ChIA-PET and its derivatives HiChIP11 and PLAC-seq12 efficiently capture chromatin interactions associated with chromatin architectural proteins  and transcription factors (TF) such as RNA polymerase II (RNAPII) and other specific TFs in a genome-wide manner. However, these methods require large numbers of input cells (106–107) for each experiment in order to generate high-quality data, and when applied in studies with a low number of input cells, the resulting data were often of poor quality, mapping only the higher-order chromatin domains and lacking the details of individual interactions between specific chromatin loci14. Thus, they cannot be readily applied in studies of biological and clinical samples of high interest, which often have few cells available and yet require high-resolution data. Meanwhile, chromatin profiling methods such as ATAC-seq15, DNase-seq16, and FAIRE-seq17 map regions of open chromatin genome-wide to identify candidate promoters and cis-regulatory elements that are accessible to trans-regulatory factors. Specifically, ATAC-seq identifies chromatin that is sensitive to digestion by hyperactive Tn5 transposase, which simultaneously cuts genomic DNA and inserts a sequencing adaptor at its cutting site; this direct coupling of ‘tagmentation’ to the digestion of accessible DNA enables high-efficiency construction of DNA sequencing libraries from as few as 500 input cells15. However, ATAC-seq analysis cannot reveal direct interactions between open chromatin loci, and thus could not reflect accurate long-range transcriptional regulation, such as enhancer–promoter interactions.The human genome comprises of 6 billion base pairs and is organized in 23 pairs of chromosomes that fold through long-range chromatin interactions into loops and domains in an ordered but also fluid manner within the confines of the nucleus10. Trac-looping18 is another multi-omic method that uses a bivalent oligonucleotide linker, which favors the formation of a tetramer complex of transposase to tag and cut two accessible chromatin loci that are linearly faraway but spatially in proximity, thus, capturing interactions between open chromatin sites. Ocean-C19 and HiCAR20 are two of the recent methods that either includes FAIRE  steps to separate protein-free DNA from protein-bound material or Tn5 digestion in Hi-C protocol to detect contacts between open chromatin loci. However, these methods still require large numbers (105−106) of input cells in order to obtain quality chromatin interaction data, thus limiting their applications.Here, we sought to develop a method that could efficiently and simultaneously map open chromatin loci and chromatin interactions associated with transcriptional activity using low numbers of input cells. There have been several efforts to combine different chromatin-probing protocols for more efficient and informative multi-omics analysis. ChIA-PET was the first to simultaneously detect TF binding sites (TFBSs) and chromatin interactions associated with the TF of interest21. Here, we report a strategy called ChIATAC that combines in situ proximity ligation for chromatin interaction analysis (ChIA) and the efficiency of transposase-based ATAC approach for chromatin library construction. We show that ChIATAC can simultaneously and robustly identify open chromatin loci and capture chromatin interactions from as few as 1000 input cells per library. To demonstrate the utility of ChIATAC, we used it to comprehensively characterize the 3D epigenome during T cell activation by T cell receptor (TCR) and interleukin-2 (IL-2).Improving efficiency and reducing the number of input cells for broader application of chromatin interaction assays has been challenging15, we designed a strategy for mapping chromatin interactions that combines the proximity ligation of in situ Hi-C7 and in situ ChIA-PET21 with the Tn5-mediated in situ digestion of ATAC-seq15 for simultaneous mapping of chromatin interactions and open chromatin loci with the goal of reducing the required input cells down to a few thousands or even hundreds, without compromising data quality. We call this method ChIA-ATAC, or in short, ChIATAC. In ChIATAC, cells are crosslinked, and the intact but permeabilized nuclei are subjected to in situ restriction enzyme digestion and followed by proximity ligation with a biotinylated bridge linker, as described in the in situ ChIA-PET protocol21. The nuclei are then processed for in situ transposase-based tagmentation, as established in the ATAC-seq protocol15. The tagged DNA fragments containing chromatin ligation products are isolated by biotin-streptavidin affinity for PCR amplification, and the amplicons (ChIATAC library) are subjected to paired-end-tag DNA sequencing. The sequencing reads are then mapped to the reference genome to reveal chromatin accessibility and interaction  cells as their smaller genome size facilitates method development. The initial results are summarized in  S2 cells, while only 50 thousand (5 × 104) cells were used in ChIATAC, representing a 200-fold reduction of input cells for chromatin interaction analysis. Importantly, the data quality in terms of chromatin contact frequency and peak intensity derived from ChIATAC data were largely comparable with the data of RNAPII ChIA-PET .The successful proof of concept using 28 the outcome due to the large size and complexity of the human genome, and we therefore tested the restriction digestion by one enzyme versus two enzymes (Methods). We initially employed AluI (which has a 4-bp recognition site) for in situ chromatin digestion in Drosophila cells, where it produced an average chromatin fragment size that plateaued at 5500 bp  of ChIATAC peaks between two replicates Fig. , we foun29. Indeed, ChIATAC faithfully captured genome-wide open chromatin loci identified by ATAC-seq  and CTCF ChIP-seq  data. Approximately half  of the CTCF binding sites overlapped with open chromatin sites, while the rest  did not 10, we showed that ChIATAC captured the same higher-order chromatin architectures and domain structures as detected by Hi-C and ChIA-PET  of the RNAPII loops (PET ≥ 15) were found in the ChIATAC data  of the CTCF loops (PET ≥ 15) were enriched by ChIATAC  not identified as enriched in ChIATAC data, 5062  loops overlapped with open chromatin sites, but the PET counts between two anchors in ChIATAC data were below the threshold we used in our analysis pipeline, and 5986  loops had either no anchors or only one anchor associated with open chromatin sites. Overall, the CTCF loops that matched with ChIATAC loops exhibited higher chromatin contact signals than those CTCF loops that were not enriched in ChIATAC data  and ranging down to 1000 (1 K) cells per ChIATAC library  than with fewer cells (5 K and 1 K) -mediated activation of CD4+ T cells and subsequent effects of stimulation by IL-2 on the epigenome landscape and the chromatin folding structures, and how such chromatin modifications might lead to altered gene transcription programs in CD4+ T cells.Given the robustness of ChIATAC for cultured cells, we sought to apply ChIATAC to primary human cells, with a specific focus on characterizing the 3D epigenome and dynamic changes in primary T cells in response to activation by various extracellular signals. Within the human immune system, it is well established that cell identity and function are largely determined by cell-type-specific transcriptional programs that are regulated by a set of lineage-specific TFs+ T cells upon activation, we isolated total CD4+ T cells from a buffy coat from a normal blood donor. The CD4+ T cells were activated through TCR-activation (anti-CD3 + anti-CD28) for 72 h, rested overnight, and then either not stimulated or stimulated with IL-2 for 4 h  of the loci induced by TCR-activation exhibited increased PET counts  of the 4,532 loci repressed by TCR-activation showed decreased PET counts  of the activated open chromatin loci after IL-2-stimulation correlated with increased PET counts  short (<8 kb), and only 15% were long-range contacts (>8 kb); whereas the majority (62%) of chromatin interaction loops in ChIATAC data were long-range  than HiCAR (3 × 104), but the quality of the ChIATAC data was also more robust than the HiCAR data. Specifically, the peaks of open chromatin loci identified by ChIATAC were much stronger than those identified by HiCAR, and the open chromatin loops in ChIATAC data revealed more detailed looping structures between active gene promoters and enhancers than were observed in the HiCAR data  and the resolution of loops is dependent on the binning size ; the other one is peak-based  if the loop anchors are also experimentally enriched as peaks. We compared ChIA-PIPE  and HICCUPS (a popular tool for Hi-C data) as well as Mustache (recently developed for Hi-C and Micro-C data) for calling loops in ChIATAC data (see Methods). As shown  of which showed increased peak signals, while only 60 of them had lower peaks . The most enriched TF motifs after TCR-activation in CD4+ T cells include ETS1  and a range of well-known pioneering factors such as BATF, AP-1, and PU.1  to assess the differential chromatin accessibility and gene expression during the cell-state transition, and further predicted TFs either as putative activators or repressors. Out of the 734 TFs in the diffTF database, 437 TFs showed (Resting vs. TCR-activation) significant differential chromatin accessibility at predicted TFBSs and measurable gene expression. Among them, 138 were classified as activators, 171 as repressors, and 128 were undetermined  cell differentiation40, was predicted to be a putative repressor in response to IL-2 , impairing Th9 differentiation41. Our results suggest a potential epigenetic mechanism as to how IL-2 can affect the Th9 cell differentiation by inhibiting the BCL6. We were also able to identify TFs that have not been reported to be involved in the immune response, and our analysis implicates them as putative activators or repressors  motifs  of 22 genes. Compared to unchanged or repressed chromatin loci, these 22 genes showed a significant increase in chromatin accessibility, chromatin looping, and expression Fig. , bottom.RL1 Fig. , right aifs Fig. , which a+ T cells and the changes caused by TCR-activation and IL-2-stimulation. Importantly, our initial analysis demonstrated that 3D epigenomic activation in chromatin accessibility and chromatin interaction looping is strongly correlated with the altered gene expression, thus elucidating a likely topological involvement of regulatory mechanism in gene transcription. The rich datasets generated in this study are also a valuable resource for further dissecting the mechanistic understanding of transcriptional regulatory programs of key genes along with the processes of CD4+ T cell activation.Overall, our ChIATAC data provided comprehensive coverage of the 3D epigenome in CD4+ T cells, perhaps owing to the establishment of new open chromatin regions after TCR-activation, whereas IL-2-stimulation did not result in additional changes , and these long-range interactions were not observed after TCR-activation and IL-2-stimulation  after TCR-activation may indicate the rewiring of chromatin interactions, which results in a transition from condensed and suppressed chromatin structures to gene-centric chromatin domains with increased chromatin accessibility to TFs and connectivity between promoters and enhancers for activated transcription.To further explore the potential topological involvement of transcriptional regulation in T cells, we investigated the dynamic changes of 3D epigenome during TCR-activation and following stimulation with IL-2. As shown, TCR-activation significantly increased the number of open chromatin peaks and associated chromatin loops, whereas the subsequent IL-2 stimulation had only a minor impact on both peaks and loops Fig. . The oveges Fig. . Substanges Fig. . In restion Fig. , perhaps34. Among the chromatin loci (n = 7117) that were more accessible following TCR-activation, the chromatin accessibility was largely maintained in the CD4+ cells after subsequent IL-2-stimulation  had increased chromatin accessibility specifically stimulated by IL-2 , whose gene expression did not respond to TCR signaling but was specifically induced by IL-2-stimulation , which showed a progressive increase of gene expression after TCR-activation and IL-2-stimulation , a gene that is potently induced by IL-2. Indeed, our analysis showed that CISH specifically responded to IL-2 (60-fold) as measured by RNA-seq but marginally and insignificantly (1.4-fold) to TCR-activation  in a stepwise and progressive manner, probably due to a sharp surge (5.2-fold) of chromatin accessibility induced by IL-2 at a distal STAT5-bound enhancer more than 40 kb downstream . It encodes a protein that is involved in the induction of hematopoietic differentiation in normal and myeloid leukemia cells and is known to be induced by IL-2 significantly47. The expression of LIF in CD4+ T cells was increased 64-fold by TCR-activation and was further induced over 2000-fold by IL-2 . Another advantageous feature of ChIATAC is its selective enrichment for transcription regulatory interactions between gene promoters, enhancers, and super-enhancers without the ChIP step as is used in ChIA-PET, HiChIP, and PLAC-seq. This is mostly because ChIATAC robustly captures chromatin interactions between open chromatin loci analogous to ATAC-seq for highly efficient mapping of open chromatin loci, and most open chromatin loci are highly associated with active transcription23. Lastly, because the critical experimental steps including restriction digestion followed by proximity ligation and transposase fragmentation plus sequencing adaptor addition are all performed in situ without breaking up individual cells or nuclei, the ChIATAC method can be further adapted to various single-cell platforms for developing single-cell ChIATAC.The most critical technical advance in ChIATAC is the incorporation of the transposase-based in situ chromatin fragmentation and sequencing adaptor insertion in one reaction step for highly improved efficiency in chromatin DNA library construction, as previously demonstrated in ATAC-seq+ T cells isolated from an individual blood donor and their ex vivo activation by TCR-activation and IL-2-stimulation, we explored potential topological mechanisms of transcription regulation by extracellular signals—here the effects of TCR-activation followed by IL-2-stimulation, mimicking what occurs during the immune response. Combining ChIATAC data for 3D epigenomic features and RNA-seq data for transcriptional output, we traced the dynamic changes of chromatin modification of IL-2-specific genes during the cellular transformation from quiescent to cellular activation in CD4+ T cells. Our preliminary analyses are consistent with a topological model in which the chromatin structures are activated by TCR and followed by IL-2 for additional activation in terms of increased chromatin accessibility, enhanced chromatin connectivity, and enhanced transcription. This topological model appeared applicable to IL-2 inducible genes: although RNA-seq did not show upregulation in response to TCR-activation alone, but the surrounding chromatin structures were still significantly modified, with increased chromatin connectivity between open chromatin loci. This observation suggests a possible topological explanation for the previously proposed epigenetic priming model, in which an imposed chromatin modification converts a closed state to an open one during cellular differentiation, resulting in a latent epigenetic state that does not immediately lead to increased gene expression49, but cells are nevertheless primed for rapid response upon subsequential inductions50. Here, our analysis using ChIATAC data provides evidence that epigenetic priming may also represent the establishment of long-range chromatin interactions between the target gene promoters and essential enhancers that are not by themselves yet sufficient to activate the desired transcription. The CISH locus best exemplified this epigenetic priming in action, with TCR triggering a significant chromatin modification, resulting in the establishment of a new chromatin interaction between the CISH promoter and its enhancer that did not exist in the resting state of CD4+ T cells. However, such establishment was not sufficient to activate CISH transcription, and additional IL-2-mediated STAT5 activation and binding to the CISH enhancer appear to be required to drive CISH transcription  cells (derived from a primary culture of late-stage Drosophila melanogaster embryos) were cultured in Express Five® SFM  with 1:100 L-Glutamine  at 27 °C.2, and ambient oxygen levels as recommended by the Coriell Institute of Medical Research.This is a B-lymphoblastoid cell line, originally obtained from Coriell Institute for Medical Research. The cells were cultured in RPMI 1640 , supplemented with 15% fetal bovine serum . The cells were cultured at 37 °C, 5% CO+ T cells were purified by EasySep Human CD4+ T cell isolation kit .An anonymized buffycoat was obtained from the Blood Bank in National Institutes of Health. Buffy coat cells were harvested as a by-product of volunteer-donor blood units and were distributed in an anonymized manner. They meet the criteria for exemption from need for informed consent and IRB review as defined in 45CFR46 and their distribution abides by all NIH guidelines for human subjects research. Human CD4+ T cells were cultured in RPMI1640 medium supplemented with 10% FBS/penicillin-streptomycin in a 37 °C incubator and activated by 2 μg/ml of plate-bound anti-CD3  and 1 ug/ml of soluble anti-CD28  for 72 h.The isolated primary CD4IL-2-stimulation: The above TCR-activated T cells were rested overnight. Two hundred International Units of IL-2 were added to the cells for 4 h.g and the supernatants were removed. Cell pellets were either used for an experiment directly or first stored at −80 °C .Harvested cells were crosslinked by 2% formaldehyde  for 20 min at room temperature, the reaction was quenched by adding 0.125 M glycine and incubated at room temperature for 10 min. Cell pellets were washed once with DPBS . The formaldehyde-crosslinked cells were then crosslinked using 2 mM EGS (ethylene glycol bis(succinimidyl succinate))  for 45 min at room temperature. Double-crosslinked cells were quenched by 0.125 M glycine again at room temperature for 10 min and washed once with DPBS. Cells were centrifuged at 2500 × ATAC assay. Cells were first lysed by 100 μl 0.1% SDS FA buffer  at 4 °C for 1 h. Cells were spun down and permeabilized by 10 μl 0.1% SDS at RT for 2 h. The reaction was quenched by adding 2.5 μl 20% Triton X-100 and incubated at 37 °C for 20 min. Cells were then in situ digested by AluI  or AluI+HpyCH4V  restriction enzymes at 37 °C for at least 2 h or overnight by adding 2 μl AluI/ 1 μl AluI + 1 μl HpyCH4V, 5 μl 10× Cutsmart buffer , 25.5 μl ddH2O. Restriction enzyme digested chromatin DNA was A-tailed by 0.6 μl 1 mM dATP, 1 μl Klenow Fragment (3′→5′ exo-) , and 1 μl BSA (2 mg/ml)  at 37 °C for 1 h. The reaction is stopped by incubating at 65 °C for 20 min. In situ ligation is then performed by the addition of 20 μl 5× Quick ligation buffer , 1 μl T4 DNA ligase , 3 μl 2 ng/μl bridge linker , and 23.4 μl ddH2O for at least 4 h at room temperature or overnight at 16 °C. Cells were spun down and washed once with ATAC-RSB buffer with Tween-20 . Cells were centrifuged at 2500 × g for 5 min and resuspended in 50 μl transposition mix , 19 μl DPBS). Transposition reactions were incubated at 37 °C with agitation for 1 h. The DNAs were purified using DNA Clean & Concentrator-5 , eluted in 50 μl Buffer EB , and incubated with streptavidin M280 beads  at RT for 1 h at room temperature. Beads were washed five times with 0.5% SDS/2× SSC buffer and twice with 1× B/W buffer  then resuspended in Buffer EB. DNA was amplified by adding 25 μl NEBNext® High-Fidelity 2× PCR Master Mix , 5 μl Illumina Nextara XT i7 index primer, and 5 μl Illumina Nextara XT i5 index primer with the following cycling conditions: 72 °C for 3 min, 98 °C for 30 s; 9–12 cycles of 98 °C for 10 s, 63 °C for 30 s, and 72 °C for 40 s; 72 °C for 5 min; 4 °C hold. PCR products were purified using 1× Ampure beads  and size selected with 0.8× Ampure beads. This final library was sequenced using paired-end sequencing (2 × 150 bp) on an Illumina NovaSeq 6000. Fastq files were generated and demultiplexed with the BCL2Fastq (Illumina). A step-by-step protocol is included in Supplementary Note 1000 to 50,000 FA-EGS-crosslinked cells were used as starting material to perform the ChI21. The ChIA-PET libraries were sequenced by paired-end sequencing (2 × 150 bp) on an Illumina NovaSeq 6000.In situ ChIA-PET libraries with 20 μg antibodies against RNAPII  or CTCF  were constructed using 10,000,000 FA-EGS-crosslinked cells from GM12878 cell cultures, following the in situ ChIA-PET protocol51. Briefly, 50,000 cells were harvested and lysed in 50 μl ATAC-RSB buffer with NP-40 and Tween-20  on ice for 3 min, and immediately centrifuged at 500 × g for 10 min at 4 °C. The nuclei pellets were washed once with ATAC-RSB buffer with Tween-20  resuspended in 50 μl of transposition buffer  and incubated at 37 °C for 30 min. Transposed DNA was purified with the DNA Clean & Concentrator-5. This final library was amplified by PCR and sequenced by paired-end sequencing (2 × 150 bp) on an Illumina NovaSeq 6000.ATAC-seq was performed following Omni-ATAC protocol+ T cells or CD4+ T cells with TCR-activation or IL-2-stimulation. RNA libraries were prepared using KAPA RNA HyperPrep Kits with RiboErase (HMR) . This final library was sequenced by paired-end sequencing (2 × 100 bp) on an Illumina NovaSeq 6000.Total RNA was extracted using the RNeasy Mini Kit  from primary total CD422 and mapped to the human hg38 reference genome. MACS252 was used to call peaks and the peak intensity from MACS2 output was normalized with ‘-SPMR’ option . Significant loops were first called by ChIASig53 with PET ≥ 3 (PET distance > 8 kb) and FDR < 0.05. The loops were further filtered by anchor support; only significant loops with both anchors supported by peaks were retained. Both ChIATAC and ChIA-PET data can be visualized on Juicebox as 2D contact maps by using Juicer tools32 v1.22.01 with built-in normalization options  to create ‘.hic’ file. The 2D contact maps were shown after KR normalization.ChIATAC and ChIA-PET share the same bridge-linker, and final library structure (adapter-tag-bridge-linker-tag-adapter). The ChIATAC data output is also very similar to ChIA-PET data (producing peaks and loops simultaneously). Thus, ChIATAC and ChIA-PET data were processed using the ChIA-PIPE pipelinehttps://github.com/FelixKrueger/TrimGalore) to remove adapters and the portion of the reads with low quality (–stringency 3 -q 20 -e .20 --length 15). Trimmed reads were aligned to the hg38 genome HISAT254 v.2.1.0. We used HTSeq55 to quantify mapped reads (MAPQ > 30) to protein-coding genes of GENCODE v36, with parameters for reverse strandedness (–s = reverse). Using the transcript quantifications from HTSeq for those genes, we performed differential gene expression analysis with R package DESeq256. Lowly expressed genes with baseMean <10 in DESeq2 were filtered out. Genes with absolute log2 fold change above 1 and FDR < 0.001 were defined as differentially expressed genes.Reads were trimmed using Trim Galore!  to remove adapters and that portion of the reads with low quality (--stringency 3 -q 30 -e .20 --length 16). Trimmed reads were aligned to the hg38 genome with BWA-MEM57. Duplicated reads were removed with gatk MarkDuplicates (Picard) (https://gatk.broadinstitute.org/). We then retained the reads with mapping quality above 30 and filtered out supplementary alignment with samtools flag ‘-F 2048’.Reads were trimmed using Trim Galore!  between two contact matrices for every chromosome. We show the chromosome-length weighted average.HiCRepn = 12,721) ± 1 kb genomic regions in Drosophila S2 cells and ATAC-seq peaks  ± 2.5 kb genomic in human GM12878 cells were assessed. Heatmap was generated by the output from the function ‘computeMatrix’ in deepTools60 v3.5.1.The epigenomic signals from publicly available data at ChIATAC peaks . Compartment score is based on PCA1 computed with 200-kb bin size using ‘hicPCA’ function. The insulation score was computed with 25-kb bin size using ‘hicFindTADs’ function.The compartment score and insulation score were assessed by HiCExplorerWe assessed noise level around a peak by calculating the ratio between SPMR on the peak region and its flanking regions. The flanking regions were composed of 500 bp from the leftmost and 500 bp from the rightmost of the peak region. The noise level is defined as the average SPMR of flanking region divided by that of peak region.32 v1.22.01 with -KR options at 10,000 bp resolution. The Z-score of the central pixel relative to all the pixels in the lower left (LL) corner was used to examine the peak signal enrichment.The Aggregate Peak Analysis (APA) was done by using Juicer tools62 v3.4.1. The trimmed mean of M-values approach (TMM) method was used to normalize compositional differences between libraries. To calculate the library size, we sum up the reads that overlap consensus peaks in each sample (Reads in Peaks). Peaks with FDR < 1% and absolute log2 fold change > 1 were defined as differentially accessible regions.Differential chromatin accessibility analysis was carried out by using R Bioconductor package DiffbindSignificant loops with PETs > 10 were used for analysis. All loop anchors from two replicates of the comparing conditions were collected, and a list of unique anchors was generated by merging the overlapping anchors into larger regions. These unique anchors were indexed and anchor pairs for each loop were identified. A unique ID was then assigned to a consensus loop. A table that contains PET counts of unique consensus loops was generated for each library. We used DESeq2 to normalize the PET counts of consensus loops from the four libraries being compared and computed the differential loops based on the PET counts. Interactions with absolute log2 FC > 1 and FDR < 0.01 were defined as differential interactions.36 v4.11. Visualizing motif positions and motif distribution analysis was done by using ‘annotatePeaks.pl’ function.The genomic regions with increased chromatin accessibility after TCR-activation or IL-2-stimulation were examined for enriched motifs of known transcription factors by using ‘findMotifsGenome.pl’ function in HOMER softwareATAC 1D chromatin accessibility and RNA-seq data were used for each condition. Pairwise comparisons using diffTF38 between (1) Resting vs. TCR-activation; (2) TCR-activation vs. IL-2-stimulation) were performed. We classified putative transcriptional activators and repressors based on adjusted p value < 0.2, stringency = 0.001, and raw p value < 0.2, stringency = 0.001 for (Resting vs. TCR-activation) and (TCR-activation vs. IL-2 stimulation), respectively.diffTF classifies TFs based on the assumption that increasing the level of an activating TF increases chromatin accessibility at its target sites while increasing the level of a repressing TF decreases it. For each TF, diffTF calculated the Pearson correlation between the expression level of each TF and the chromatin accessibility across all the peaks with predicted TFBS for a particular TF. If the median of the resulting correlation coefficients was sufficiently positive, diffTF considers it an activator, if sufficiently negative as a repressor, and if it was not significantly different from the background, diffTF calls it undetermined. Two replicates of ChI+ T cells were downloaded from Lai et al.18 and we used the liftOver utility to convert from hg18 to hg38. The interaction distance between two tags was examined by using PETs from GSM2326181_CD4_Activated_TrAC-Looping_rep1-tech1. PETs up to 1 kb were normalized by reads per million and used to generate Trac-loop one dimensional (1D) coverage track. We filtered out PETs below 1 kb then using the remaining interactions we generated a hic heatmap with Juicer tools v1.22.0132. Significant loops from GSE87254_DHS1K_stim_3PETs_fdr were filtered with PET distance > 8 kb and used to generate Trac-loop chromatin interaction track.Trac-loop data from TCR-activated CD420. The raw data were processed using the Nextflow pipeline (https://nf-co.re/hicar) to get the 1D coverage. The interactions  from Wei et al20. were used for characterizing the chromatin loops.HiCAR is another method that can detect open chromatin loci and chromatin interactions. The HiCAR data from GM12878 cells were downloaded from Wei et al.22 to cluster PETs in the vicinity and HiCAR using a bin-based loop-calling method, i.e., MAPS63. Thus, we further compared several common loop-calling methods, i.e., Mustache35 and HICCUPS32  and HICCUPS  called similar number of loops as reported previously. Eventually, we found that ChIA-PIPE is the most suitable loop-calling method for ChIATAC data.We further benchmarked ChIATAC and HiCAR for both: (i) Peak and intensity of open chromatin loci; (ii) Chromatin interactions among open chromatin sites. The majority (67–70%) of ChIATAC and HiCAR peaks overlapped  with -k KR -f 0.1 option.HiCCUPS35 was used for loop calling in ChIATAC data (bin size: 10 kb and 5 kb) with -pt 0.05 -norm KR option.MustacheNo statistical method was used to predetermine sample size. No data were excluded from the analyses. The experiments were not randomized.Further information on research design is available in the Supplementary InformationReporting SummaryDescription of Additional Supplementary FilesSupplementary Data 1