Although they are organelles without a limiting membrane, nucleoli have an exclusive structure, built upon the rDNA-rich acrocentric short arms of five human chromosomes (nucleolar organizer regions or NORs). This has raised the question: what are the structural features of a chromosome required for its inclusion in a nucleolus? Previous work has suggested that sequences adjacent to the tandemly repeated rDNA repeat units  may be involved, and we have extended such studies by addressing several issues related to the requirements for the association of NORs with nucleoli. We exploited both a set of somatic cell hybrids containing individual human acrocentric chromosomes and a set of Human Artificial Chromosomes (HACs) carrying different parts of a NOR, including an rDNA unit or DJ or PJ  sequence. Association of NORs with nucleoli was increased when constituent rDNA was transcribed and may be also affected by the status of heterochromatin blocks formed next to the rDNA arrays. Furthermore, our data suggest that a relatively small size DJ region, highly conserved in evolution, is also involved, along with the rDNA repeats, in the localization of p-arms of acrocentric chromosomes in nucleoli. Thus, we infer a cooperative action of rDNA sequence—stimulated by its activity—and sequences distal to rDNA contributing to incorporation into nucleoli. Analysis of NOR sequences also identified LncRNA_038958 in the DJ, a candidate transcript with the region of the suggested promoter that is located close to the DJ/rDNA boundary and contains CTCF binding sites. This LncRNA may affect RNA Polymerase I and/or nucleolar activity. Our findings provide the basis for future studies to determine which RNAs and proteins interact critically with NOR sequences to organize the higher-order structure of nucleoli and their function in normal cells and pathological states.The online version contains supplementary material available at 10.1007/s00018-023-04770-3. Ribosomal RNA (rDNA) gene clusters occupy a significant part of the genome, forming repeat regions comparable to centromeres. The total copy number of rDNA repeats varies from 250 to 670 per diploid human genome . The repThe primary 45S pre-rRNA transcript is transcribed from rDNA units by RNA polymerase I (RNA Pol I) and is then processed to produce the mature 18S, 5.8S and 28S RNAs (rRNA) , 10 thatThe apparent regularity of rDNA repeats is consistent with the notion that each ribosome has been considered equivalent to all others. The notion of ribosome uniformity was further reinforced when a 3D structure of ribosomes was established at high resolution  and a reThe organization and sequence variation of human rDNA units is likely to be highly significant, both because NORs are the locus of ribosome biogenesis and because they have also been implicated in processes as varied as cellular stress response, mitosis and cell proliferation, and specific age-related pathology (summarized in ).Given the inferred involvement of NORs in so many important processes, we have recently aimed to characterize the actual structure and variation in human NORs. Using Transformation-Associated Recombination (TAR) cloning , 21, we Sequence analysis of rDNA isolates from the sampled chromosome 21 revealed an unexpectedly high level of heterogeneity in human rDNA, including substantial base substitutions, variation in mono- or dinucleotide run lengths, large insertions, and deletions . The rDNThe possible effects of variants in ribosomal DNA sequence have not yet been studied, but further investigation of the role of rDNA sequence in nucleolar formation as well as function is warranted by reports of various phenotypic effects of genome dosage and/or number of active rRNA genes in health and pathology. For example, it was recently suggested that rheumatic arthritis genomes appeared to harbor significantly less active ribosomal genes compared to controls . AnotherAs for the sequences bracketing rDNA clusters, McStay et al. , 33 haveIt was previously reported that the DJ region, rather than being a passive block of heterochromatin, is transcriptionally active . Three tPan troglodytes) compared to humans . HPRT-positive colonies were selected after 3 weeks of growth in the HAT medium.Loading of the TAR BAC constructs into the unique loxP site of the alphoid18 clone  is descr18 clone . BrieflyHPRT gene . Integrity of the inserted material was confirmed by PCR amplification reaction using diagnostic pairs of primers corresponding to each region of interest .Insertion of TAR BAC constructs was confirmed by PCR using specific primers to detect reconstitution of the tetO array signal on metaphase chromosome spreads. One HAC clone containing each TAR BAC construct was chosen for further analysis.To confirm that the HACs are maintained autonomously in hamster CHO cells, FISH analysis was performed. The images of the HAC carrying different TAR BAC constructs in CHO cells are shown in Fig. S6. The HAC signal colocalizes with the PNA (peptide nucleic acid) FITC-labeled probe for the alphoidR colonies were obtained in one MMCT experiment involving HAC transfer from hamster to human cells. To confirm that alphoidtetO-HACs carrying different TAR BAC constructs propagate autonomously in human HT1080 cells without detectable integration into chromosomes, FISH analysis was performed .MMCT transfer of the HACs carrying different TAR BAC constructs from hamster CHO cells to human HT1080 cells was performed as described in detail previously , 48. Bla5 of HT1080 cells bearing the alphoidtetO-HAC (either HAC/GFP or HAC/rDNA or HAC/DJ) were seeded onto each well of a 6-well plate in 2 ml of growth medium supplemented with 5 μg/ml of Blasticidine S and 1 μg/ml of Doxycycline. Next day, the cells were transfected with 1 μg of tetR-tTAVP64 vector with ViaFect™ Transfection Reagent (Promega) according to the manufacturer’s protocol. Next day, the medium was changed to 10 ml of a fresh medium either with 1 μg/ml of doxycycline or without doxycycline. After 7 days of cultivation, the cells were washed with PBS, trypsinized and seated on the gelatin-covered microscopic slides. Next day, the slides were fixed and stained with the PNA FITC-labeled FISH probe for the tetO sequence in the alphoidtetO array of the HAC and anti-RRP1 antibodies (Nop52) to visualize nucleoli.1.5 × 10tetO repeat (tetO) as well as for a control 5S ribosomal DNA, are listed in Supplementary Table S1. At least three independent ChIP experiments were performed to estimate the level of enrichment.ChIP using antibodies against trimethyl H3K4me3 (Millipore) was carried out according to a previously described method . BrieflyThe images obtained from 3D immuno-FISH with an LSM780 laser scanning confocal microscope (Zeiss) were analyzed using FiJi software. A polygon selection tool was used to measure nuclear and nucleolar areas in human/mouse monochromosomal hybrid cell lines A9 (#13) 89-2 (chromosome 13) and A9hygro14 10F (chromosome 14). The ratios of areas of nucleolus/nucleus were calculated using Excel software.6 HT1080 cells were used per nucleofection. The primers used for the experiment are listed in Table S1.Nucleofection on Lonza 4D nucleofector was performed according to the manufacturer’s protocol. Briefly, SF Cell Line 4D-Nucleofector™ X Kit L (Lonza) was used. 1 × 10U test. p values of less than 0.05 were considered as statistically significant. Data are presented in diagrams as the mean ± SD; error bars correspond to a 95% confidence interval. p-values were generated for the difference in the percentage of nucleolar association. Average percentages were generated from three independent repetitions of each experiment on replicate cultures. GraphPad Prism 9 software was used for statistical analysis.The statistical significance of comparisons between data groups was determined using a two-tailed nonparametric Mann–Whitney http://www.ncbi.nlm.nih.gov/) of AL592188 (NT_167214) sequences that contain the proximal 100 kb end of the DJ region. Annotations from the Ensembl database (https://www.ensembl.org/) for a regulatory build as well as information from “Conservation Track” of the UCSC database (http://genome.ucsc.edu) were also used in the analysis of AL592188 (GL000220) sequences to locate orthologous hits and in primates and look for conservative blocks and regulatory sites or potential functional signals.We used published GenBank annotations (http://genome.ucsc.edu). The conservation scores of each hit or analyzed region were obtained by averaging PhyloP and PhastCons scores (“Conservation Track”), which measures conservation such that only “runs” of conserved sites are considered through the use of the hidden Markov model. BLAST (https://blast.ncbi.nlm.nih.gov/) and BLAT (http://genome.ucsc.edu/cgi-bin/hgBlat) were used to confirm the synteny of the aligned full-length sequences of the isolated human and primate blocks. Multiple alignments of nucleotide sequences were constructed using the program Muscle with default parameters [http://humangen.med.ub.es/tools/RepeatMasker.html) because the numerous low-complexity and repetitive regions in the long DJ sequences obscured the pattern of orthology. All predicted primate transcripts were analyzed using GENSCAN (http://hollywood.mit.edu/GENSCAN.html) and NCBI Orf Finder (https://www.ncbi.nlm.gov/orffinder/).Multiple alignments of 30 mammalian and 100 vertebrate species were retrieved for each analyzed region of interest with a 100-nt extension on both sides from the UCSC Genome Browser (rameters  and editrameters . Pairwisrameters  in pairwhttp://rulai.cshl.edu/dme) and our implementation motif search approach [https://genexplain.com/transfac/). The 5′ ends of the predicted transcripts were computationally folded using programs Afold [http://www.unafold.org/mfold/applications/rna-folding-form.php) to estimate free energy.Modified DME-X  89-2 (chromosome 13) ; A9hygroWe first demonstrated that human ribosomal genes in these hybrid cell lines are transcriptionally silent . Next, we estimated the size of rDNA clusters by Southern blot hybridization analysis  analysis, using primers specific for the human rDNA spacer sequence Table S1). Based on qPCR, the results were consistent with the analysis of restriction digests: A9#22 (γ2) and A9HyTK-22 cell lines carrying chromosome 22 were inferred to contain 2 (95% CI 2) and 9 (95% CI 7–11) human rDNA repeats, respectively, and A9 (#13) 89-2, A9hygro14 10F, A9 (Neo15)-3, and A9 #21-16 cell lines carrying chromosomes 13, 14, 15 and 21 contained 78 (95% CI 48–108), 39 (95% CI 26–53), 17 (95% CI 14–19) and 43 (95% CI 29–57) repeats, respectively  see “” Fig. 11e. NucleWe found that nucleolar association of acrocentric p-arms can occur in mouse background, and this association occurred independently of the amount of rDNA present on the acrocentric chromosomes. For example, the percentage of cells containing an associated nucleolar localization of chromosomes 13 and 21, which contain the highest copy numbers of the rDNA repeat , was 42% (95% CI 37–47%) and 48% (95% CI 42–54%), respectively  89-2 hybrid cell line containing human chromosome 13, which has the highest number of rDNA repeat (78 repeats) but a relatively low percentage of nucleolar localization in the hybrid cell nucleoli (42%).Transcription of the 45S preribosomal RNA genes is mediated by DNA-dependent RNA polymerase I (Pol I). Mouse Pol I transcription fails on human rDNA but can proceed if human TATA-binding protein (TBP)-associated factors (hTAFIs) are provided in the mouse cells . The foup < 0.05; human rDNA is transcriptionally silent vs 95% CI 55–63%; p < 0.05; Pol I transcription active; 1.5-fold increase)  following hTAFI expression Fig. c, consisWe note that the extent of association of human rDNA shown in Fig. To examine the role of DJ and PJ regions as well as rDNA sequences in the association of NORs with nucleoli, we isolated these regions by TAR cloning as circular YAC/BAC molecules  and thentetO-HAC in hamster donor CHO cells following the transfer of the HAC constructs into human HT1080 cells   that have homology to the 5′ and 3′ ends of a region of interest . The TAR1 vector was used to isolate a 54,121 bp fragment containing the 43,754 bp sequence of a complete copy of the rDNA unit (TAR1 construct). The TAR2 vector was used to isolate a 25,621 bp fragment containing ~ 15,265 bp of the transcribed part of the rDNA unit 45S rRNA) (TAR2 construct). The TAR3 vector was used to isolate a 28,601 bp fragment corresponding to the IGS sequence (TAR3 construct). The TAR4 vector was used to isolate a 58,377 bp fragment of the PJ sequence (TAR4 construct). The TAR5 vector was used to isolate a 42,938 bp fragment of the DJ sequence (TAR5 construct)  and the 43 kb DJ fragment  compared to 42% for the control HAC carrying the GFP transgene (Table S6). Surprisingly, the nucleolar association of HACs carrying the 26 kb transcribed (45S) and 28 kb non-transcribed (IGS) parts of the rDNA repeat was also statistically higher compared to the control . In contrast, the nucleolar association of a HAC carrying the 58 kb PJ fragment did not differ from the control . In all cases, the HAC centromere is the same, and we therefore attribute the increase in association to the inserted DNA, on the assumption that any effect of centromeric heterochromatin is the same for the various constructs.To determine the nucleolar association status of the HACs carrying different TAR constructs within interphase cells, we applied 3D immuno-FISH Fig. ”  co-localization with the nucleolus observed in these experiments is predictable. First, the HAC size is significantly smaller compared to the chromosomes that facilitates its penetration into the nucleolus. Secondly, a functional centromere in the HAC as well as in the chromosomes contains large blocks of heterochromatin. It is known that perinucleolar heterochromatin is composed of satellite DNA surrounding NORs [A relatively high percentage of the control alphoiding NORs . TherefoCollectively, our analysis of HACs carrying different rDNA constructs revealed that a single rDNA repeat, its transcribed (45S) and non-transcribed (IGS) parts, and also sequences within the DJ DNA fragment can specify nucleolar association of these HACs.p < 0.0001; 1.5-fold) , in which the 3′ end of the IGS sequence, which includes pre-promoter sequences involved in regulating rRNA transcription, was deleted. 3D immuno-FISH in HT1080 cells revealed a significant reduction of association of this HAC with nucleoli (to the control level)  sequence replacing the CENP-B box in each amplified synthetic dimer [tetO-HAC allows the targeted manipulation of chromatin composition within a single functional centromere in vivo without affecting all kinetochores of the endogenous chromosomes of the host cell.Next, we asked whether, in addition to the effect of transcription regulation of the ribosomal DNA, the modification status of chromatin surrounding rDNA affects NOR association with nucleoli. To address this question, we exploited the alphoidic dimer , 74. Becic dimer . BindingVP64, i.e., tetR fused to the advanced tTAVP64 , that can generate chromatin changes in the HAC kinetochore due to elevation of transcription of the alphoidtetO array which rapidly inactivates the HAC kinetochore [tetO-HAC carrying the 54 kb entire rDNA repeat (HAC/rDNA), the HAC carrying the 43 kb DJ sequence (HAC/DJ) and the HAC carrying the GFP transgene (HAC/GFP). The HACs are propagated in human HT1080 cells. To change the chromatin status of the entire 1.1 Mb alphoidtetO array in the HAC/rDNA, HAC/DJ and HAC/GFP, we transiently transfected the multiple copy vector expressing tetR-tTAVP64 into HT1080 cells bearing the HACs in the non-selective medium either with doxycycline (dox+) to inhibit binding of tetR-tTAVP64 to the alphoidtetO array sequence of the HACs or without doxycycline (dox−) to permit tetR-tTAVP64 binding  and as a control locus, for 5S ribosomal DNA (Table S1) revealed elevation of satellite transcription of the alphoidtetO array accompanied by enrichment in H3K4me3 chromatin , in agreement with previously published data [First, we carried out a control experiment to show any change in the chromatin status of the alphoidhed data . Three iVP64 transfection. As expected, without tetR-TAVP64 transfection no significant difference in HAC association with nucleoli was observed when cells were cultured in dox+ and dox− media      (Table S8). Thus, chromatin changes in the HAC centromere induced by the function of a transcriptional activator do not alter peripheral localization of the HAC in the nucleolus.Finally, we determined sub-nucleolar localization of the HAC/GFP and HAC/rDNA before and after altering their chromatin state to a more open configuration with the tTAAs shown above, sequences within a 43 kb DJ DNA fragment located immediately proximal to the rDNA array specify nucleolar association of the HAC. Therefore, we decided to carefully analyze the proximal 100 kb of the DJ sequence in vertebrate genomes and also consider whether this region is conserved in evolution.The DJ sequences were previously shown to be predominantly confined to acrocentric short arms and are dominated by a large, inverted repeat of > 100 kb, in which a large (~ 40 kb) block of 48-bp satellite repeats, CERs, was identified at the distal end of the DJ sequence . Here weSome conserved blocks were used for further analysis  in close proximity to the rDNA array, and the last five exons located in the IGS region, downstream of the rDNA transcript . The complete rRNA transcript is ~ 13 kb long and overlaps with the third intron of this LncRNA. Consensus folding for multiple alignments of the 5′ end of predicted LncRNA NR_038958 in four primate species is demonstrated in Fig. S13. These results suggest that some of the conserved blocks in the DJ region may be functional and even potentially transcribed. The sequence data described here indicate that all acrocentric chromosomes are in principle capable of producing the LncRNA NR_038958 transcript. Using reverse transcriptase PCR (RT-PCR), we experimentally confirmed the existence of the spliced transcript in HT1080 cells and its absence in the human/mouse hybrid A9#13 89-2 .https://www.ensembl.org/) for at least some cell lines or cultures. These sites are likely functional and may be involved in the regulation and structural determination or support of the DJ sequence architecture. One of the features that may be involved in the regulation of rDNA biogenesis and their transport in nucleoli is the CTCF sites, which are conserved and occur twice in the 92.5–94.5 kb region . The consensus C and G rich motif for the CTCF interactions was found to be highly conserved not only in humans but also in some primate genomes. A list of elements conserved between human and chimpanzee and experimentally validated TF sites in the 92.5–94.5 kb region (in GL000220) is presented in Table S10. This region is located upstream of the predicted LncRNA NR_038958 and may be involved in the regulation of transcription not only of this LncRNA but also in the regulation of expression of overlapped rRNA transcripts.Motif search analysis and prediction of transcription factor (TF) sites  and can also be considered as a promising area for further analysis, given the experimental support for expression in this region. Two additional conserved sequences enriched with potential sites for protein binding are located between 32 and 50 kb . The most common motifs found at the proximal end of the DJ region by the DME-X program are shown in Table S11. This suggests that common motifs with high similarity to known TF sites may be responsible for protein binding and involved in the regulation of rDNA array transcription, replication, and/or transport.To summarize, TF sites, the cluster of CTCF sites, and the LncRNA start (NR_038958) are located immediately adjacent to the rDNA array within the same 10–12 kb region. Therefore, future analysis of this region may reveal factors determining the association of the DJ and NORs with the nucleoli and possibly additional functions.In this study, we have carried out a detailed analysis to clarify parameters involved in the association of the p-arms of acrocentric chromosomes with nucleoli. Earlier McStay et al.  assayed tetO-HAC, which behaves as an extra 47th chromosome with proper segregation and replication in human cells [tetO-HAC remain unchanged after HAC transfer from donor hamster CHO cells to different host mammalian cells [To clarify which parameters of NOR may contribute to association with nucleoli, we exploited the human artificial chromosome, alphoidan cells . It is ian cells . Thus, ttetO-HAC carrying either an entire rDNA unit, its transcribed (45S) or non-transcribed (IGS) parts, DJ or PJ DNA regions propagates in human fibrosarcoma HT1080 cells, which are very similar to non-transformed human cells in their NOR chromosomal organization and activity status [The alphoidy status . Our anay status . ConsideWe assume that inclusion in a nucleolus in mouse and human cells will follow the same rules. A caveat, however, is that the genomic architecture of the mouse rDNA-containing chromosomes is quite different from human acrocentric chromosomes. Normal mouse chromosomes are telocentric, with the rDNA located distal to the centromere. The surrounding satellite environment is also different from the human context. Furthermore, DJ-like sequences are features of primate genomes, while nucleoli are present in all eukaryotes. Still, mouse and human nucleolar structure and activity involve rDNA units with a similar structure ( and unputetO-HAC carrying either a full rDNA repeat (44 kb) or a short proximal DJ fragment (43 kb). As has been shown previously, the majority of the megabase-order alphoid DNA array in the alphoidtetO-HAC is covered by centrochromatin and heterochromatin [tetO-HAC consisting of alpha-satellite repeats contains thousands of tet operator sequence (tetO) in every other alphoid monomer. This provides a unique feature for this HAC: its chromatin status can be changed by tethering the tetR-fusion chromatin modifiers [VP64, which induces open chromatin thereby disrupting the HAC heterochromatin, resulted in reduction of HAC association with the nucleoli. This result suggests that NOR association with the nucleoli may be affected by the status of heterochromatin blocks formed next to the rDNA arrays.To address the question whether the heterochromatin status of NORs is important for nucleolar association of the acrocentric p-arms, we used as a model the alphoidhromatin , 78. Thehromatin , 79, 80.odifiers , 79, 80.In extending such analyses, we were interested in determining the requirements for the inclusion of rDNA repeats in nucleoli. We further capitalized on the use of a set of human/mouse hybrid cell lines, each containing one human rDNA-containing chromosome. We began by checking the rDNA content of the human acrocentric chromosomes in the hybrid cells employed in the study. Our analysis revealed a widely varying distribution of rDNA repeats between acrocentric p-arms that ranges from 2 to 78 repeats. In these hybrid cells, human ribosomal genes are transcriptionally silent, but acrocentric p-arms are associated with mouse nucleoli, which confirmed the earlier report . What waAs we have shown, a relatively small size DJ region (43 kb) located just next to the rDNA array is involved, along with the rDNA repeats, in the localization of p-arms of acrocentric chromosomes in nucleoli. In our study, we identified LncRNA NR_038958, a transcript starting at the proximal end of the DJ region, whose first two exons are located in close proximity to the rDNA array, and which last five exons are in the IGS region. This LncRNA is present in all acrocentric chromosomes and is located in the same region. The region between 92.5–96.5 (in GL000220) upstream of the LncRNA is enriched in TF binding sites that are conserved between human and primates and that may be involved in the regulation of transcription of this LncRNA as well as in the regulation of rRNA transcripts.The search for DNA binding motifs revealed multiple CTCF binding sites across the 100 kb DJ region located in close proximity to the rDNA array, consistent with data previously obtained . InteresGiven that LncRNA NR_038958 can partially overlap the genomic location of the antisense transcripts, termed PAPAS (“promoter and pre-rRNA antisense”) found earlier in independent studies of mammalian rDNAs, we can assume a cumulative regulatory effect of these two LncRNAs in regulating the epigenetic signature at the rDNA enhancer and promoter, and an effect on RNA Pol I transcription. PAPAS is a long noncoding RNA (LncRNA) that is transcribed in an antisense orientation to pre-rRNA and produces transcripts > 10-kb in size covering the gene body and intergenic regions, including the rDNA promoter and upstream enhancer sequences. PAPAS has been shown to interact directly with DNA by forming a DNA–RNA triplex structure that bind PAPAS to a purine-rich site in the enhancer region, thereby directing the associated CHD4/NuRD (nucleosome remodeling and deacetylation) to the rDNA promoter –87.Sequence identity among the DJ contigs of acrocentric chromosomes allowed us to design an antisense oligonucleotide to target the depletion of the transcript. RT-PCR analysis showed that after its transfection into HT1080 “”, the trDespite the different ordering and identified rearrangements of DJ regions in some genomes of great apes, our comparative analysis showed ~ 96% identity between chimpanzees and humans in the first 100 kb of the DJ sequences. Another group of genomes with conserved blocks within the DJ sequences, especially in the potentially functional and important for regulation region described above, are located between ~ 92.5 kb and the beginning of 45S pre-ribosomal RNA, includes gibbon, gorilla, orangutan, and other Old World monkeys. Sequence alignment analysis in primates showed that there are numerous conserved blocks with almost identical breakpoints and indel locations in the DJ region, even though they originate from different species, including some New World monkeys. Thus, rDNA arrays and DJ sequences remain fairly conserved in primates over evolutionary time. Therefore, we assume that, like in humans, the NORs of great apes should be considered in molecular terms as being comprised of rDNA arrays and associated DJ sequences. This assumption is consistent with our finding that rDNA and DJ sequences are likely to drive nucleolar association of acrocentric p-arms in human.The current findings provide a basis for future studies of each identified parameter and further analysis is required to understand the specific nature of interactions between all these sequences, heterochromatin, and their association with the NOR. This may further facilitate efforts to investigate how rearrangements in rDNA and DJ sequences within acrocentric p-arms or other NOR abnormalities can affect disease susceptibility.Supplementary file1 (DOCX 58004 KB)Below is the link to the electronic supplementary material.


Blood comprises a wide array of specialized cells, all of which share the same genetic information and ultimately derive from the same precursor, the hematopoietic stem cell (HSC). This diversity of phenotypes is underpinned by unique transcriptional programs gradually acquired in the process known as hematopoiesis. Spatiotemporal regulation of gene expression depends on many factors, but critical among them are enhancers—sequences of DNA that bind transcription factors and increase transcription of genes under their control. Thus, hematopoiesis involves the activation of specific enhancer repertoires in HSCs and their progeny, driving the expression of sets of genes that collectively determine morphology and function. Disruption of this tightly regulated process can have catastrophic consequences: in hematopoietic malignancies, dysregulation of transcriptional control by enhancers leads to misexpression of oncogenes that ultimately drive transformation. This review attempts to provide a basic understanding of enhancers and their role in transcriptional regulation, with a focus on normal and malignant hematopoiesis. We present examples of enhancers controlling master regulators of hematopoiesis and discuss the main mechanisms leading to enhancer dysregulation in leukemia and lymphoma. Although between 40% and 50% of human genes are ubiquitously expressed, a subset of genes that determine cell identity are only expressed in a tissue-specific manner.6 These patterns of expression change along hematopoiesis, as cells progressively specialize and commit to certain lineages. To understand why some genes are active and others are silent, ensuring the maintenance of highly specific transcriptional programs, one must look beyond coding sequences, and put the lens on a much less understood part of the genome—regulatory elements.The human hematopoietic system encompasses a wide range of cell types with unique morphologies and functions, involved in processes as disparate as immune defense, nutrient transport, or coagulation. However, like every other organ and tissue in the human body, they all carry the exact same genetic information: 46 chromosomes containing roughly 20,000 protein-coding genes.7 In their seminal publication, they proposed that repressor molecules could bind regulatory elements (operators) on the DNA to regulate the synthesis of proteins through short-lived RNA intermediates. Despite significant advances in the field, this surprisingly prescient model outlined the 2 major modes of transcriptional regulation. On the one hand, molecules that bind the DNA are transcription factors (TFs) that act in trans to control the expression of multiple genes across the entire genome. On the other hand, noncoding DNA regions bound by these factors are cis-regulatory elements (CREs) that are specific to genes in the vicinity. In turn, CREs can be classified into various functional classes, among which enhancers are of particular interest as critical determinants of cell identity.8The concept of gene regulation can be traced back to the model of Jacob and Monod, derived from their studies of the lactose system in bacteria.11This review describes the role of enhancers in transcriptional regulation during hematopoiesis, with a focus on their involvement in malignant transformation. Although key aspects about enhancer biology are presented here, we refer the reader to other excellent reviews for a more in-depth discussion.12 Transcription can be divided into 3 distinct phases: initiation, elongation, and termination. It begins at the transcriptional start site (TSS), located at the 5′ end of a gene, and progresses toward its 3′ end. Upon completion of this process, the product of protein-coding genes, known as mRNA, is imported into ribosomes for translation.13 In this final step, a protein is synthesized by sequentially adding amino acids, following the order dictated by sequences of 3 nucleotides (codons) in the mRNA.14Gene expression starts with transcription, defined as the copying of a DNA sequence into complementary RNA by a member of the RNA polymerase family of enzymes. RNA polymerase (RNA pol) II transcribes all protein-coding and most noncoding genes, whereas RNA pol I and III transcribe ribosomal RNA and certain small noncoding RNAs, respectively.16 The minimal stretch of DNA sufficient to direct this process is known as the core promoter, defined as a 50-bp region around the TSS that docks the preinitiation complex, which consists of RNA poll II together with general transcription factors (GTFs).16 Moreover, the rate of initiation can be modulated by TFs, proteins that bind specific DNA motifs and recruit components of the transcription machinery.18 To achieve this goal, they rely on 2 types of functional domains: DNA-binding domains recognize TF-binding sites (TFBS), whereas effector domains interact with other proteins, including RNA pol II and transcriptional cofactors (which can be either activators or repressors).22 TFBS appear at CREs in dense clusters, arranged with precise order, orientation, and spacing to ensure that TFs can cooperate effectively.17 Various modes of cooperativity, which can involve direct protein-protein interactions,23 DNA-facilitated interactions,24 or other indirect mechanisms, enable a finer control of transcriptional patterns.25Spatiotemporal regulation of gene expression is mediated by CREs, which include promoters, enhancers, insulators, and silencers Figure A. Origin27 Enhancers collaborate in the recruitment of RNA pol II by forming loops with target promoters, which can be located kilobases away in the linear genome  or cohesin that generates loop domains, thereby blocking interaction across domains and favoring those within the same loop.30 Thus, contacts between CREs and their target genes usually take place within these insulated regions, often referred to as topologically associated domains (TADs).31Although core promoters are capable of driving autonomous transcription, they often have low basal activity. In order to reach the expression levels required by the cell, they may thus require input from enhancers.e Figure B.28 In as Figure A.29 Insu33 Enhancers were discovered in the 1980s through the identification of a 72-bp DNA sequence from the SV40 virus that increased transcription of a reporter gene by ≈200-fold, irrespective of distance and orientation.34 The first cellular enhancer was later found in the immunoglobulin heavy chain (IGH) gene locus, within the intron preceding the constant region exons.36 The authors noted the striking tissue specificity of this element, which was only active in B cells. These early discoveries established the key properties of enhancers: (1) they augment gene expression of their target genes; (2) act independently of orientation; (3) can function at large distances; and (4) are often tissue-specific. Furthermore, enhancers preserve their function even in a different genomic context, as shown by reporter assays, which also has implications for disease. Successive studies have consistently confirmed these features, and the importance of enhancers for tissue-specific gene regulation in vivo.38 Moreover, enhancers are modular and can contribute either additively or synergistically to the transcriptional output of their target genes.41 Long-distance interactions are mainly synergistic and confer robustness against comutagenesis, whereas the additivity of short-range enhancers maintains high expression.42Enhancers are DNA sequences of a few hundred basepairs that contain TFBS and increase the level of transcription from their target promoters.43 to more than a million,46 depending on the predictive approaches employed and the number of tissues surveyed. Despite the disparity of these figures, in all cases they greatly exceed the number of promoters detected. Nevertheless, the repertoire of enhancers active in each lineage is only a fraction of this number. Together with the fact that most binding events of TFs take place at enhancers, this points to a pivotal role for enhancers in the regulation of tissue-specific gene expression and cell identity.8 Indeed, enhancers in conserved regions are key regulators of development and disease48 and enhancer activity strongly correlates with gene expression in genome-wide studies.51 In the hematopoietic system, this notion is further supported by the fact that clustering of chromatin accessibility classifies cell types better than gene expression.52 More recently, multimodal single-cell approaches have demonstrated positive correlation between CRE accessibility and gene expression, with enhancer activation in early hematopoietic stages preceding transcription in more differentiated cells.54 Moreover, use of a Venus-YFP reporter in embryonic stem cells (ESCs) undergoing hematopoietic specification provided functional evidence that tissue-specific enhancers were associated with expression of genes in the same stage.55 A recent publication using bacterial methylation labeling showed coordinated enhancer and gene activity throughout enterocyte differentiation.56Recent estimates of the number of potential enhancers in the human genome range from a low of 40,000CEBPA offers a clear example of tissue-specific regulation, with different enhancers active in each tissue that expresses said gene, and complete absence of enhancer activity in tissues where CEBPA is silent  the pool of TFs available in a particular cell type, and (b) the accessibility of their binding sites at a given enhancer.22 For instance, binding sites for the ETS, C/EBP, and NF-κB families are accessible in monocyte-specific enhancers, whereas neuronal enhancers are enriched for RFX and SOX proteins.43 Cooperative binding of TFs further narrows both tissue and genomic specificity of developmental enhancers.59 On the one hand, the requirement for simultaneous engagement of multiple TFBSs at enhancers prevents transcriptional noise due to spurious recognition of short motifs. On the other hand, it allows a finer control of transcriptional patterns during differentiation, as specific combinatorial patterns are uniquely expressed in specific cell types. Thus, in hematopoietic stem and progenitor cells (HSPCs), a heptad of TFs  frequently colocalize at CREs of key hematopoietic genes and act in concert to regulate their expression.61 At least 4 of these regulators establish protein-protein interactions that stabilize their DNA-binding and facilitate complex formation.The myeloid master regulator t Figure .57 Other62 This type of enhancer is particularly common in plastic cell types that undergo phenotypic adaptations upon changes in the environment, like macrophages, T cells, or neutrophils. For example, macrophages stimulated with TLR4 ligands activate preexistent enhancers that control genes involved in inflammatory responses.65 During macrophage differentiation, these enhancers are primed by combinations of LDTFs, such as PU.1 or C/EBPβ,67 and become fully activated upon stimulation by TFs such as NF-κB, IRFs, and AP-1.65 Similarly, acquisition of a regulatory phenotype by CD4+ T cells following TCR stimulation largely results from activation of preestablished enhancers by newly attached FOXP3.68 Although most inducible enhancers seem to be previously primed during development, a fraction of them, known as latent enhancers, are created de novo upon reception of external stimuli.68 Those are roughly 10% of all enhancers induced during macrophage differentiation, but <1% in regulatory T cells. Inducible enhancers are critically dependent on cohesin.69Although binding of lineage-determining TFs (LDTFs) establishes the repertoire of tissue-specific enhancers in a cell, not all of them are immediately active. Some of them, known as inducible enhancers, require binding of additional TFs in response to internal or external signals.74 and recruit chromatin remodelers76 to make the region accessible to other TFs and epigenetic modifiers. Cirillo and colleagues first coined the term “pioneer factors” to describe FOXA (HNF3) and GATA4, after demonstrating they bind nucleosome arrays and open compacted chromatin,77 but multiple other LDTFs have a similar function in the hematopoietic system, including C/EBPβ,78 GATA1,80 and PU.1.66 These factors direct the selection of primed enhancers that are ready for further activation (see81 for a review on chromatin priming), exhibit reduced DNA methylation82 and are flanked by nucleosomes with lysine 4 monomethylation at histone 3 (H3K4me1).83Enhancer states can be classified as inactive, primed, poised or active, each of which is associated with distinct epigenetic marks . Inactiv84 which is associated with transcriptional silencing and is established by the polycomb repressive complex 2.85 The role of H3K4me1, primarily deposited by MLL3/4 methyltransferases,86 is uncertain, but it may contribute to increased responsiveness to activating signals87 and serve as a molecular memory of previous stimulation in the case of inducible enhancers.65 This mark is thought to be a key mechanism in the acquisition of inflammatory memory, or trained immunity, which depends on the opening of chromatin domains by TFs like AP-1.89 On the contrary, it is plausible that H3K4me1 prevents de novo DNA methylation at poised enhancers, as shown for a similar mark (H3K4me3) at bivalent promoters that also harbor H3K27me3.90Poised enhancers are a category of primed enhancers associated with lineage specification marked by both H3K4me1 and H3K27me3,33 The histone acetyl transferases (HATs) CREB-binding protein (CBP) and p300 deposit acetylation marks like histone H3 lysine 27 acetylation (H3K27ac)91 and H3K9ac,92 which neutralize the positive charge of lysine residues, thereby decreasing their affinity for DNA and destabilizing the nucleosome to increase chromatin accessibility.93 Indirectly, acetyl groups act as docking sites for bromodomain-containing proteins such as the switch/sucrose non-fermentable (SWI/SNF) chromatin remodeler,95 leading to the displacement of nucleosomes and increased chromatin accessibility.96 Moreover, the acetylating activity of CBP/p30099 facilitates the recruitment of RNA pol II and GTFs at enhancers101 to initiate transcription. Analogously to gene promoters, this results in the production of enhancer RNAs (eRNAs),102 which are often bidirectional and whose biological function remains obscure  flanked by intrinsically disordered tail domains (histone tails).114Histone posttranslational modifications (PTMs): Histone tail domains contain a large number of sites that can be target of PTMs, which modulate the charge of the tail and thus alter the electrostatic interactions supporting chromatin structure.115 The existence of histone tail PTMs has been known since 1964, when Vincent Allfrey showed that acetylation and methylation are incorporated after synthesis of the polypeptide chain.116 Despite the strong association between histone PTMs and gene expression, their role in transcriptional regulation may be more limited than originally thought. Experiments in drosophila revealed that gene activation occurs in the absence of H3K4 methylation117 and that point mutations in H3K27 only lead to a loss of repression, suggesting that acetylation mainly antagonizes H3K27me3.118Histone code: the histone code hypothesis proposed by C. David Allis and Brian Strahl suggested that histone tail domains encode a language that could be read, written, or erased by specific proteins.119 Examples of readers are bromodomain-containing proteins that bind acetylated lysines,120 whereas HATs like p300 are writers that mediate acetylation.121 In contrast, histone deacetylases (HDACs) are erasers that removes acetylation.122 Another prediction of this hypothesis was that PTMs may be interdependent and act in combination, which has been confirmed by the integration of multiple chromatin marks into so-called chromatin states.123 These inferred functional associations are a result of specific recognition by reader proteins that contain motifs able to distinguish residues based on their methylated stated and surrounding sequence.Histone variants: These are paralogues of the so-called canonical histones, with differences that can range from a few amino acids to 50% of their sequence.124 Some examples include H2A.Z and H3.3, both of which are associated with enhancers. While canonical histones assemble into nucleosomes behind the replication fork, variants are incorporated during the cell cycle, in a replication-independent manner.125 The replacement of canonical histones by their variants changes the properties of nucleosomes and their interaction with remodelers and other proteins, thus having an effect on gene expression.Nucleosome-free regions: Nucleosome eviction or destabilization in nucleosome-free regions is a critical requirement for the binding of TFs to cis-regulatory elements and initiation of transcription.111 These accessible chromatin regions are susceptible to digestion by nucleases, and as such they are also known as DNase hypersensitive sites (DHS).126 Chromatin accessibility is facilitated by several processes, including the replacement of canonical histones with histone variants, the eviction or repositioning of histones by chromatin remodelers, and the covalent modification of histones.127Enhancer-derived RNAs: eRNAs are generally bidirectional, unspliced, and nonpolyadenylated,102 although a recent study in single cells concluded that this bidirectionality is an artifact of bulk data.128 Three main models have been proposed to explain the role of eRNA in gene regulation, reviewed in more depth.33 First, both the transcription of enhancers and the resulting eRNAs are nonfunctional and merely a byproduct of high RNA pol II concentrations. Second, the act of transcription participates in the remodeling of chromatin, by carrying histone transferases or opening up chromatin, although the resulting eRNAs would be irrelevant. Third, eRNAs themselves have a function, such as the stabilization of enhancer-promoter looping, the binding of TFs, or the sequestration of transcriptional repressors. Although these different possibilities are not mutually exclusive, a recent study provided convincing evidence that, at least in some instances, enhancer transcripts are required for physical interaction between enhancers and promoters.12910 These can be broadly classified as follows:Starting with the seminal article of Banerji et al in 1981, the first efforts to identify enhancers relied on reporter assays that exploited the capability of these elements to augment gene transcription, regardless of cellular context, distance, or orientation. While successful, this approach was limited by its low throughput, the inability to determine whether enhancers are active in vivo and in which cell types or tissues. Therefore, more scalable methods to detect novel enhancers have been developed and are currently in use.112 The ability to produce bidirectional transcripts has also been exploited to detect active putative enhancers.130 Among the various epigenetic marks, H3K27ac is the best predictor for validated active regulatory regions,131 although eRNA discriminates better between genes with high or low expression.132 Such methods have been employed extensively by consortia like ENCODE or Roadmap, on account of their exceptional scalability and their ability to measure enhancer-associated signal in their genomic context across multiple tissues. Nevertheless, the predictions upwards of 1 million putative enhancers contain numerous false positives, whereas enhancers characterized by atypical marks  may be missed.Biochemical annotations: the biochemical features of active enhancers described in the previous section have been exploited to detect putative enhancers on the basis of annotations from various molecular biology techniques . These i134 or self-transcribing active regulatory region sequencing (STARR-seq).38 In CRE-seq, the putative enhancers are inserted upstream of a minimal promoter in barcoded plasmids, whereas in STARR-seq they are inserted in the 3′ UTR of the reporter gene, avoiding the need for barcodes. These techniques can be applied in an unbiased manner or in combination with biochemical annotations. Their main appeal is that they directly test for the intrinsic ability of an enhancer to increase expression, which constitutes the functional basis of their definition. On the other hand, these early MPRAs rely on a single promoter and are conducted outside the original cellular and genomic contexts, ignoring the influence of factors such as enhancer-promoter (E-P) compatibility, chromatin looping, or the available TF repertoire. In recent years, strategies that overcome some of these drawbacks have been developed. For example, in site-specific integration fluorescence-activated cell sorting followed by sequencing, putative enhancers coupled with a reporter are integrated into the HPRT locus of ESCs, ensuring a constant and accessible chromatin environment.135 Differentiating cells are next sorted based on reporter expression and candidate regions enriched in populations with high reporter signal are considered functionally active enhancers. Despite its advantages, this approach is still constrained by the use of a single promoter, and the dependency on ESC differentiation trajectories.Massively parallel reporter assays (MPRAs): validating predicted regions as bona fide enhancers requires functional characterization, proving they can indeed increase transcription from a reporter gene. This task can be accomplished using MPRAs, such as CRE analysis by sequencing (CRE-seq)10 Targeted enhancers can be deleted with Cas9,136 repressed with dead Cas9 (dCas9) either on its own or fused to a repressor like KRAB (CRISPRi),137 or activated by dCas9 with a transcriptional activator, such as VP64 (CRISPRa).138 In most studies so far, the technique has been applied to a single gene, identifying gRNAs that are enriched in a fraction of cells with phenotypic changes related to that gene. It can also be applied to determine which specific regions of a putative enhancer region are essential for gene regulation, as shown for a MYB binding site in a relocated GATA2 enhancer.139 More recent approaches harness the power of single-cell (sc) sequencing to determine which enhancers are perturbed in each cell and their corresponding transcriptomic profiles.141 These have received various names, but can be collectively referred to as scCRISPR-seq.142 The main strength of CRISPR-based screens is that they assay for changes in the expression of genes while targeting their putative enhancers in their cellular context, thus overcoming shortcomings of the previous 2 approaches. On the negative side, they are expensive and can be hampered by the low efficiency of gRNAs at certain regions, and by the presence of shadow enhancers that mask the effect of targeting a single enhancer. Furthermore, they are only applicable to cells that grow in culture, of which not all are amenable to genetic manipulation.Targeted genome editing screens: techniques based on clustered regularly interspaced short palindromic repeats (CRISPR) are a relative newcomer to this field, but their potential is becoming increasingly clear. In CRISPR-based screens, guide RNAs (gRNAs) targeted against a collection of enhancers are delivered to a pool of cells and those gRNAs associated with changes in the expression of genes of interest are identified.CEBPA resulted in loss of CEBPA expression and neutrophil depletion, establishing such region as a bona fide enhancer critical for neutrophil commitment.57 Nevertheless, such experiments are very costly and limited to a single candidate, so they are exclusively employed for validation. Alternatively, expression quantitative trait loci (eQTLs) located inside enhancers may act as an indirect confirmation that such regions control gene expression in humans.In vivo validation: only experiments in entire organisms can confirm the role of an enhancer in physiological conditions, not only in the control of gene expression, but also in cellular processes like differentiation. For example, deletion of an H3K27ac-marked region +42 kb downstream of 143These methods have their own strengths and weaknesses Table , so theyBox 2:We present here some of the most popular technologies used to detect signals typically associated with enhancers. This list is not meant to be exhaustive.ChIP-seq: This is a technique whereby DNA bound by a protein of interest is immunoprecipitated with specific antibodies and subsequently sequenced.144 Following alignment to a reference genome, the sequencing reads exhibit enrichment in the shape of peaks at the genomic regions bound by the target protein. An alternative that requires smaller amounts of starting material and provides higher signal-to-noise ratio is CUT&RUN, in which antibodies directed against proteins of interest are recognized and bound by protein A-micrococcal nuclease (MNase) for directed cleavage.145DNAse-seq and ATAC-seq: DNase-seq relies on the principle that open chromatin regions are susceptible to digestion by nucleases to identify nucleosome-free regions as peaks enriched for sequencing reads, known as DHS.147 Narrow depressions in these peaks correspond to TF footprints protected from DNAse degradation by associated proteins. More recently, the ATAC-seq has gained prominence as an alternative to DNAse-seq.148 This technology probes DNA accessibility with hyperactive Tn5 transposase, which inserts sequencing adapters into open chromatin regions.3C/4C/Hi-C: chromosome conformation capture (3C) uses proximity ligation together with formaldehyde crosslinking, followed by restriction enzyme digestion, to detect long-range chromatin interaction between any pair of genomic loci (1 versus 1).149 In circular 3C (4C), a second round of digestion and ligation is used to increase resolution, and an inverse PCR captures interactions between the locus of interest and the rest of the genome .151 When followed by sequencing, this method known as 4C-seq.152 In Hi-C, the digested DNA is labeled with biotin, enabling the enrichment for ligation products with streptavidin pull-down and creating genome-wide contact maps that reflect chromatin organization .153 A powerful alternative to Hi-C is Micro-C, which harnesses MNase digestion to achieve higher resolution.15432 At the stage of initiation, some of these proteins contribute to the assembly and the stabilization of the PIC and the recruitment of RNA pol II, as is the case of the Mediator complex155 and p300/CBP.156 However, some core promoters autonomously recruit high levels of RNA pol II and their limiting factor is elongation. In these cases, their cognate enhancers are likely to display high levels of proteins involved in pause-release, such as BRD4104 and p300/CBP.156 Finally, while transcriptional burst size is a fixed property of the core promoter, the frequency of these bursts can be increased by developmental enhancers.157Enhancers fine-tune gene expression by transmitting regulatory input to promoters in the form of TFs and transcriptional cofactors, which modulate the transcriptional output at multiple levels.159 or 24 kb using only functionally tested enhancers.141 In contrast, the limb-specific enhancer of SHH is located 1 Mb away for its target gene,37 whereas the hematopoietic enhancer of MYC is 1.7 Mb downstream.160 Enhancer-mediated promoter activation is made possible by chromatin looping, which was first proposed in the 1980s,161 but only confirmed almost 2 decades later by pioneering work on the globin gene.162 Another key piece of evidence was the observation that forced looping of an enhancer with a promoter led to gene expression.163 Strikingly, live imaging of E-P loops in Drosophila embryos further confirmed that physical proximity between enhancer and promoter was correlated with transcriptional activation.164 While E-P interactions are necessary for gene expression, they are not sufficient, as they can exist before activation.165 Thus, other factors are involved, such as the existence of a suitable TF repertoire in the cell or E-P biochemical compatibility (see next section). These preformed contacts could facilitate the rapid activation of transcription upon the reception of external stimuli or differentiation cues.One of the most puzzling aspects in enhancer biology is their ability to activate remote genes. The majority of enhancers are located within 200 kb from their target promoters, with a median distance of 120 kb,168  transcriptional output may be explained by a multiplicative model.Nevertheless, even forced contacts between an enhancer and a promoter are not always sufficient to activate transcription, suggesting they must be compatible as well.158 or (b) correlations between features of promoters and putative enhancers, such as open chromatin, transcription, or H3K27ac.51 Chromatin conformation data in 1% of the human genome showed that only 27% of putative enhancers interact with the nearest TSS, or 47% if only expressed genes are considered.158 This is similar to estimates based on pairwise expression correlation, which linked 40% of enhancers to their closest TSS.43 However, CRISPR-based perturbation of regulatory regions coupled with measurement of gene expression revealed that these approaches are also of modest value.189 The results fit better with an activity-by-contact (ABC) model whereby the effect of an enhancer on gene expression depends on its activity and the contact frequency with a given promoter. Based on this model, predictions can be improved by combining data on open chromatin (ATAC-seq), enhancer activity (H3K27ac), and chromatin interactions (Hi-C). In addition, machine-learning computational tools have been developed to predict E-P relationships based on various genomic features, such as EAGLE.190The requirements for biochemical and structural compatibility caution against assigning an enhancer to the closest promoter. Alternative methods to identify E-P interactions include the use of (a) chromatin interactions derived from 3C technologies, especially Hi-C or promoter-capture Hi-C,192 Contrary to conventional enhancers, which have a clear functional definition, SEs were identified based on bioinformatic analysis of ChIP-seq data  binding levels measured by ChIP-seq. After plotting these values, regions to the right of the inflection point of the curve were considered as SEs. Since then, they have been also defined based on other epigenetic features associated with active chromatin, particularly H3K27ac.193 Other similar entities, partially but not completely overlapping, have been proposed independently, such as stretch enhancers194 or locus control regions.195Super-enhancers (SEs) are clusters of enhancers characterized by very high levels of transcriptional activators and chromatin modifications, often involved in the regulation of cell identity genes and oncogenes.a Figure .191 In t196 Genes under the control of SEs are enriched for lineage-specifying TFs and oncogenes, whose dysregulation may be due to the acquisition of novel SEs in tumor cells.191Although the exact number varies across tissues and cell types, an analysis of H3K27ac data from 86 human tissues revealed that cells have an average of 678 SEs, with an average length of 36345 bp, versus 5154 bp of normal enhancers.197 Disruptions of these boundaries result in dysregulation of nearby genes that can lead to cancer.198 The individual components of SEs often interact with each other through cohesin loops and establish functional interdependence.199 The individual components may act additively, redundantly, or synergistically.201 Dissection by genetic manipulation revealed that disruption of constituent enhancers enriched in chromatin interactions (hub enhancers) destabilizes the whole SE, suggesting a hierarchical model of organization.201The majority of SEs (84% in ESCs) are contained within CTCF-bound cohesin loops that confine their activity to specific target genes, contrary to normal enhancers (48% in the same study).202 Transitions along the hematopoietic continuum are accompanied by modifications in the epigenetic landscape, which collectively govern the transcriptional program of cells: chromatin becomes open or closed, DNA is methylated or demethylated, histones tails are modified, and chromatin interactions are lost or gained. In turn, these changes are instructed by a handful of master regulator TFs that dictate fate choices and maintain cell identity, and whose expression is exquisitely regulated.203Hematopoiesis is a tightly regulated process that ensures a steady supply of blood cells of multiple lineages, originating from a pool of hematopoietic stem cells (HSCs) that progressively specialize into progenitor cells and finally into functioning mature phenotypes.205 Importantly, variants associated with those traits are enriched at related cell-type-specific enhancers; for example, coagulation phenotypes are linked to SNPs enriched at enhancers active in megakaryocytes. Furthermore, these polymorphisms modify known motifs of hematopoietic TFs and are associated with changes in chromatin accessibility. In animal models, perturbation of various hematopoietic enhancers also leads to dramatic blood phenotypes, such as neutropenia and HSC depletion in mice lacking a Cebpa enhancer,206 failure to generate HSCs in a murine model with a deleted Gata2 enhancer,207 and reactivation of fetal hemoglobin production upon editing of the Bcl11a enhancer.136As drivers of cell-type-specific gene expression, enhancers are a key part of this process. In keeping with this notion, single-nucleotide polymorphisms (SNP) that affect blood traits and diseases are frequently located in candidate enhancer regions, explaining between 19% and 46% of heritable variation.In the next sections, we describe how the enhancer landscape changes during hematopoiesis and highlight some key examples of enhancers of master regulators.208 On the one hand, the blank slate model posits that differentiation requires de novo formation and activation of regulatory regions as cells progress toward more specialized stages. Alternatively, the multilineage priming model proposes that multiple differentiation trajectories are available in early progenitors and they progressively become restricted. The latter was formulated on the basis of results from single-cell RT-PCR in HSPCs, which revealed coexpression of lineage-specific markers at low levels before commitment to a single lineage.209 Crucially, myelo-eyrthroid genes were circumscribed to common myeloid progenitors (CMPs), whereas genes linked to the T and B lymphoid lineages were only present in common lymphoid progenitors (CLPs).210Different models have been put forward to explain the emergence of lineage-specific transcriptional programs during hematopoiesis.212 However, this phenomenon is primarily limited to promoters, whereas open chromatin regions at enhancers are frequently created de novo during differentiation.211 Similarly, profiling of H3K4me1, H3K4me2, H3K4me3, and H3K27ac showed that hematopoietic lineage commitment is accompanied by widespread change in the chromatin landscape.213 Up to 90% of the enhancers change state, of which 60% are active only in HSCs and a specific lineage, as predicted by multilineage priming. The rest, however, are established de novo during differentiation. While enhancer decommissioning is a gradual process, de novo formation mostly occurs at key transitions, with CMPs and granulocyte-monocyte progenitors (GMPs) accounting for a large fraction of newly formed enhancers in myelopoiesis.213 Furthermore, the acquisition of different histone marks takes place in a sequential manner, typically starting with H3K4me1/2 at poised enhancers in early progenitors and following with H3K27ac as soon as transcription starts.The advent of next-generation sequencing made it possible to discriminate between these 2 possibilities. Seemingly confirming the existence of multilineage priming, single-cell ATAC-seq showed that chromatin is more accessible in HSCs and it becomes increasingly condensed as differentiation progresses.211 Nevertheless, even newly formed enhancers are primed before their final activation in later stages of hematopoiesis, as shown by the fact that H3K4me1 is present at enhancers of multipotent progenitors before they become fully active or repressed in a lineage-restricted manner.214 In keeping with this notion, H3K4me1-based clustering grouped progenitors with their respective terminally differentiated cells, contrary to RNA-seq.213 Likewise, a study combining ATAC-seq and RNA-seq in 16 major blood cell types confirmed that chromatin accessibility in HSCs/MPPs preceded associated transcriptional changes in later stages.52 The authors also demonstrated that chromatin accessibility at distal regions, but not at promoters, is a better predictor of cell type than gene expression.Altogether, the emerging consensus is that hematopoiesis follows a hybrid model of increasing restriction of multilineage priming and de novo enhancer activation.215 Expression of master regulators is often sufficient to direct differentiation into a particular lineage and even force reprogramming of a committed cell into a different lineage.202 Several of these master regulators make up the aforementioned heptad of TFs, which concomitantly bind CREs associated with genes involved in hematopoietic development, including genes encoding for themselves.61 Although all 7 TFs frequently colocalize in HSPCs, specific combinations of different heptad members are restricted to individual progenitors, where they dictate fate choice and regulate lineage-specific gene expression.216 Indeed, chromatin accessibility at merely 9 enhancers bound by this heptad can be used to predict cell identity at early stages of hematopoiesis.212 Interestingly, heptad binding may precede the formation of E-P loops in more mature cells, supporting the notion that commitment is a gradual process.216Changes in the activity of enhancers during hematopoiesis are linked to their occupancy by TFs, particularly the so-called master regulators that act as primary determinants of cell fate. These often function as pioneer factors, reshaping chromatin to facilitate the binding of other TFs.Although the implementation of lineage-specific programs involves alterations in hundreds or thousands of enhancers, those that control master regulators are of special interest, as they induce and maintain other cell-type-specific enhancers. We present here a few representative examples.SPI1) is involved in both myeloid and lymphoid development, as it is required for the formation of GMPs and CLPs, but not erythrocytes and megakaryocytes.218 Low levels of PU.1 induce B-cell differentiation, whereas high levels promote myelopoiesis at the expense of other lineages.221 Within the myeloid lineage, higher levels favor macrophage over granulocyte commitment, with haploinsufficiency resulting in increased neutrophil numbers.222 Although PU.1 remains expressed in early T-cell precursors up to the DN2 stage, its downregulation is necessary for terminal T-cell maturation.223 The significance of PU.1 in these various processes stems from its role as a pioneer factor: in macrophages-specific enhancers, it initiates nucleosome remodeling, followed by deposition of H3K4me1 and H3K27ac.66PU.1 (encoded by SPI1 gene (−14 kb in mice) and is necessary to sustain adequate levels of PU.1.224 Accordingly, ablation of this enhancer, termed upstream regulatory element (URE), results in 80% loss of PU.1, with loss in HSC function and failure in terminal myeloid differentiation that give rise to leukemia.226 Nonetheless, the fact that loss of the −15 kb enhancer affects all blood lineages indicates it is a general hematopoietic enhancer. Precise transcriptional fine-tuning in each cell type is achieved through the collaboration with other upstream CREs, including a −12 kb enhancer that is specific for myeloid cells, but not B cells.227 Activation of this −12 kb enhancer is indirectly driven by the binding of C/EBPα at the URE228 together with PU.1 itself, which establishes an autoregulatory loop.229 In B cells, it is thought that the binding of lymphoid TFs such as FOXO1 and E2A to the URE is sufficient to elicit transcription of PU.1 without activation of the −12 kb, yielding the lower levels required for that differentiation trajectory.The transcription of PU.1 is under strict regulation by distal enhancers Figure A. One ofCEBPA gene, is a master regulator of myelopoiesis, required for GMP formation,231 granulopoiesis,233 and monopoiesis.234 Indeed, overexpression of CEBPA is sufficient to enforce a myeloid program in lymphoid progenitors235 and reprogram B cells into macrophages.236 First expressed in early myeloid progenitors,206 C/EBPα directs differentiation into GMPs while blocking erythroid development.237 At the GMP stage, C/EBPα acts as a regulatory switch: while high levels can set off granulocyte differentiation by activating genes such as GFI1 or CEBPE, low levels direct monopoiesis.238 These effects involve the binding of C/EBPα to both preformed and de novo enhancers during differentiation, including that of PU.1, which suggests a role as a pioneer factor.240C/EBP alpha (C/EBPα), encoded by the CEBPA in myeloid cells is primarily driven by interaction of its promoter with an enhancer located +42 kb downstream (+37 kb in mouse), which is uniquely active in blood tissues241  TFs, whose name derives from their ability to bind the (A/T)GATA(A/G) consensus sequence, also denoted as WGATAR.GATA2 expression levels must be maintained. Transcription of GATA2 is controlled by a number of enhancers that also act as GATA switch sites, including an intronic +9.9 kb enhancer (+9.5 in mice), several proximal enhancers and a distal −110 kb (−77 in mice) enhancer252  and acute myeloid leukemia (AML).258In keeping with its essential role in hematopoiesis, a fine control of 2 Figure C. While IKZF1) is the founding member of the zinc-finger TF family that bears the same name. Ikaros is a master regulator of lymphopoiesis, as demonstrated by the complete lack of B cells, fetal T cells, natural killer cells, and CLPs in mice with a homozygous mutation in Ikzf1; they produce adult T cells, although in very small numbers.261 Ikaros primes HSCs for subsequent lymphoid development and upregulates this program in lymphoid-primed multipotent progenitors (LMPPs), mediating their transition into CLPs.263 Ikaros is also critical in later stages of B-cell specification and commitment265 and in T-cell differentiation.266 Mechanistically, Ikaros binds to enhancers and promoters and recruits chromatin remodelers such as NuRD,267 activating genes that drive lymphopoiesis while antagonizing those that participate in myeloid development and in multipotency.269The DNA-binding protein Ikaros  and at least 7 enhancers, most of them intronic (D through J).271 According to the model proposed by the Georgopoulos lab  has been identified in a parallel reporter assay.272 This regulatory element exhibits open chromatin in HSCs and lymphoid precursors, allowing the binding of lymphopoietic TFs. Its deletion reduces, yet not abolishes, Ikzf1 expression in a murine T cell line, confirming the involvement of this SE in the transcriptional control of Ikaros in T cell development.The precise regulation of b Figure D, induct274 Thus, generation of pro-B cells can proceed without PAX5, but those cells fail to progress into subsequent stages and express genes from alternative lineages.275 As an essential driver of B-cell identity, it is exclusively expressed in cells of this lineage, ranging from pro-B cells to mature B-lymphocytes.276 Its continued presence is necessary to preserve their phenotype, as deletion of Pax5 in mouse models allows cells to dedifferentiate into uncommitted progenitors.277 PAX5 directly binds enhancer regions and recruits chromatin remodelers and histone modifiers to activate or repress its target genes.278PAX5 is a crucial TF for stable B-cell commitment that activates genes specific of B cells and abrogates alternative lineages, following the previous specification of CLP cells dictated by the TFs TCF3 (E2A) and EBF1.PAX5 itself is controlled by a tissue-specific enhancer located in intron 5 of the gene, which is bound and activated by PU.1, IRF4, IRF8, and NF-κB279  and, less frequently, IGK in t and IGL in t.281 In 1983, 2 groups independently identified the murine Igh enhancer and proposed its human homolog was involved in the abnormal expression of the translocated MYC,36 which was confirmed in human-derived Manca cells only a year later.282 This stunning realization set the precedent for decades of discoveries that have cemented enhancer dysregulation as a key driver of carcinogenesis. In particular, SEs have garnered special attention in later years, given their frequent involvement in the regulation of cell identity genes that are also dysregulated in cancer.191 A general overview of the role of enhancers and SEs in cancer is available in other excellent reviews.285 Here, we focus on alterations involving enhancers primarily in the context of hematological malignancies.The first report of enhancers involved in malignant transformation was in Burkitt lymphoma with translocations relocating the oncogene The various mechanisms of enhancer dysregulation described in the literature can be grouped into the following categories: enhancer hijacking, point mutations and small insertions/deletions (indels), focal amplifications, and epigenetic modulation of enhancers. Representative examples of each of these mechanisms are provided in Table 297 This is usually the consequence of structural variants that juxtapose a gene to an active enhancer,299 namely translocations, interstitial deletions, and inversions. The earliest known example of this phenomenon is the previously mentioned repositioning of the IGH enhancer to MYC in lymphomas with t.282 In AML with inv(3) or t, the adoption of a GATA2 enhancer relocated to 3q26 causes overexpression of EVI1 with concomitant GATA2 haploinsufficiency , t and t, respectively.301Also known as enhancer adoption, enhancer hijacking occurs when aberrant expression of a gene is driven by an enhancer that would normally control the transcription of another gene, resulting in altered patterns of gene expression that frequently contribute to tumorigenesis.LMO2, possibly driven by an enhancer in the CAPRIN1/NAT10 locus.198 Inactivation of CTCF is also necessary to enable contacts between TLX3 and a relocated BCL11B enhancer in T-ALL with t.302 Conversely, CTCF-dependent loops mediate the interaction of EVI1 with the translocated MYC enhancer in AML with t,303 indicating that chromatin conformation ultimately drives enhancer adoption.Aside from structural variants, enhancer hijacking can also stem from the loss of TAD boundaries that would otherwise preclude the interaction between an enhancer and a promoter. In T-cell acute lymphocytic leukemia (T-ALL), deletions of CTCF binding sites in TAD boundaries cause overexpression of TAL1, leading to its overexpression in roughly 5% of pediatric T-ALLs.287 In contrast, an enhancer located 330 kb away from PAX5 is disrupted by somatic mutations in 8% cases of chronic lymphocytic leukemia (CLL), 29% of diffuse large B-cell lymphoma (DLBCL) and 5% of mantle cell lymphoma (MCL).288Alterations in enhancers and promoters can modify the binding of TFs, RNA-binding proteins, and micro RNAs, leading to transcriptional changes at the genes under their control. A paradigmatic example is the hotspot for insertions that create a de novo super-enhancer upstream of 291 which were later shown to involve a hematopoietic SE 1.7 Mb downstream of MYC.289 Focal amplification of a region 730 kb downstream of BCL11B causes the generation of a hyperactive enhancer driving overexpression of this gene in a subgroup of lineage-ambiguous stem cell leukemias.292Amplifications increase the number of copies of an enhancer, augmenting its ability to bind TFs and recruit transcriptional machinery, and possibly turning it into a SE. Surveys of copy number alterations in adult and pediatric AML identified focal amplifications of the 8q24.21 region in 3%–4% of cases,305 suggesting aberrant enhancer activation that enables the implementation of oncogenic transcriptional programs. However, it is challenging to pinpoint which of these events are truly leukemogenic, rather than a consequence of the altered differentiation status. One of such driver epimutations is the inactivation of the CEBPA +42 kb enhancer in AML with t,296 stemming from the recruitment of HDACs and other repressors307 by the RUNX1-ETO oncoprotein. In T-ALL, mutated NOTCH1 overactivates a T-lineage-specific enhancer of MYC, a well-known oncogene.293Activation and decommissioning of enhancers is an integral part of cellular differentiation and the transcriptional response to external stimuli. However, dysregulation of these processes can lead to aberrant expression of critical genes involved in cell identity and function, ultimately resulting in leukemogenesis. These so-called epimutations are often secondary consequences of other oncogenic events, many of which affect transcriptional and epigenetic regulators in hematopoietic malignancies. Indeed, mutationally-defined AML subtypes exhibit markedly different chromatin landscapes,CCR4, not linked to any specific genetic lesion.308 While some of these may be a consequence of transformation, it is tempting to speculate that others are drivers of leukemogenesis.Nevertheless, primary epimutations that confer selective advantage may also arise independently, in a similar fashion to genetic lesions. A large-scale study in adult T-ALL identified >100 tumor-specific SEs near known oncogenes, including Our understanding of transcriptional regulation has dramatically improved in the last few decades, boosted by new technological developments such as high-throughput sequencing or genome editing. In this conceptual framework, enhancers have emerged as critical regulators of tissue-specific expression patterns that control cell identity and the response to external stimuli. As such, they play central roles in hematopoietic differentiation, turning on and off as cells progress toward their fate. Dysregulation of this tightly regulated process results in the enforcement of aberrant transcriptional programs that lead to cancer. Various mechanisms, including enhancer hijacking and de novo enhancer formation, may contribute to this process by inducing the transcription of oncogenes or silencing tumor suppressors.143 This deep learning model accurately predicts enhancer activity and, strikingly, can be used to design de novo synthetic enhancers. Even so, the generalization of this model to humans is limited, so it may be necessary to train new models using human data. More importantly, it fails to take into account determinants of E-P compatibility, and other layers of epigenetic regulation beyond sequence features, such as chromatin interactions, DNA methylation, or histone modifications. The development of algorithms that successfully integrate this information to model enhancer activity in vivo promises to be an exciting area of research in coming years.Despite tremendous progress, many open questions remain. At a fundamental level, we do not know what elements are minimally required for enhancer formation, how they organize and what rules govern their cooperation or competition. Analysis of thousands of enhancer sequences across multiple cell types or organisms may eventually reveal the so-called enhancer grammar. This is the approach used by DeepSTARR to unveil essential TF motifs and basic syntax rules, such as position or distance, in Drosophila.137 or CRISPRa.138 Another relevant question is how these alterations cooperate with coding mutations. For example, double mutations of CEBPA in AML cooccur with allele-specific expression of GATA2, resulting from simultaneous silencing of its promoter with hyperactivation of a distal −110 kb enhancer.309 Does this epimutation favor leukemogenesis induced by CEBPA lesions?So far, relatively few examples of enhancer dysfunction have been reported in hematological malignancies, most of which involve hijacking by gross structural variants. It is likely those are only the tip of the iceberg. The diminishing costs of whole genome sequencing, together with clever computational tools that exploit ChIP-seq, Hi-C, and other related techniques, will uncover other genetic lesions that create or perturb enhancers. Epigenetic events, primary or secondary, may be more challenging to discriminate from normal changes that occur during differentiation, but single-cell technologies may help in these efforts. Any findings must be validated in suitable models, not only to confirm the affected regions are bona fide enhancers that regulate their cognate promoters, but also that they are involved in tumorigenesis. Genome editing with CRISPR/Cas9 can reproduce genetic aberrations, but sequence-independent epimutations may be better modeled with CRISPRiEVI1 overexpression, which has a dismal prognosis. Instead of targeting aberrantly expressed TFs, many of which have long been considered undruggable due to their disordered structure and lack of enzymatic activity, it may be possible to perturb the oncogenic enhancers that control their expression. The growing knowledge of enhancer biology can thus be exploited to identify key transcriptional and chromatin regulators that are amenable to pharmacological intervention.Finally, oncogenic enhancers and the proteins they recruit constitute attractive therapeutic opportunities. There is an urgent need for effective treatments against malignancies that remain largely refractory to current strategies, such as AML with RM-L and RD wrote the article.The authors have no conflicts of interest to disclose.This work was supported by the Dutch Cancer Society (KWF) and Oncode.


Last decade has witnessed an exploration of non-coding transcripts pervasively transcribed from active enhancers in diverse contexts, referred to as enhancer RNAs (eRNAs). Emerging evidence unequivocally suggests eRNAs are an important layer in transcriptional regulation. In this mini-review, we summarize the well-established regulatory models for eRNA actions and highlight the recent insights into the structure and chemical modifications of eRNAs underlying their functions. We also explore the potential roles of eRNAs in transcriptional condensates.Enhancers are a class of  Among tIn this mini-review, we outline current models for eRNA actions in transcriptional regulation. In addition, we highlight recent findings concerning eRNAs secondary structure and post-transcriptional modifications in bestowing diverse functional features of eRNAs. Finally, we discuss an emerging paradigm of transcriptional condensates wherein eRNAs partaken and contribute.The well-appreciated model for enhancer action is that chromatin loops form between enhancers and cognate promoters bringing these two elements into physically close proximity, which involves the participation of cohesin complex, and transcriptional coactivator Mediator complex . Li et aPSA eRNA stimulates transcription through forming a complex with the positive elongation factor (P-TEFb)  . Congrue(P-TEFb) . Besides(P-TEFb) . hnRNPL (P-TEFb)  and impi(P-TEFb) . In thisAnother important paradigm of eRNA functions is that eRNAs can trap transcription factors and transcription co-activators, and enhance their binding to local chromatin . Sigova Lastly, eRNAs can modulate chromatin state. Depletion of eRNAs has been shown to decrease chromatin accessibility at enhancers and cognate promoters . BesidesAs mentioned above, caution needs to be taken to discern whether eRNAs function in a transcript-dependent or -independent manner. 7SK. AR-eRNA, through competitive binding with P-TEFb, can help release P-TEFb from the inhibitory complex (7SK snRNP) and promotes effective transcription elongation  motif, whose secondary structure is akin to the 3′ end of the small nuclear RNA ongation . On the ongation .DRReRNA  is a well-studied pro-myogenic eRNA, which is transcribed from an enhancer region of the myogenic master TF, MyoD  intermediates (in situ conformation sequencing), which can map RNA-RNA interactions in situ in an unbiased manner, and discovered MALAT1 interaction with highly transcribed nascent RNAs. Similarly, in this study, researchers also revealed extensive interactions between eRNAs and promoter upstream antisense RNAs (uaRNAs), which can be leveraged to infer enhancer-promoter connections. Intriguingly, modulating such interaction between eRNAs and uaRNAs influences chromatin looping . Mechanistically, m6A erasure upon Mettl3 knockout stabilizes the carRNAs, rendering the following recruitment of active TFs  and repelling of repressive factors , thus tunes the nearby active chromatin state and stimulates downstream transcription.N6-methyladenosine (m6A) methylation, the most abundant RNA internal modification, has been shown to deposit on chromatin associated RNAs, including eRNAs . NotablyThe effects of m6A methylation on nuclear nascent transcripts and the transcription process could vary depending on different cell contexts. The recent two findings, on the contrary, show that m6A modification protects eRNAs from nuclear degradation, enhances the recruitment of m6A machinery components on enhancers and promoters, and stimulates effective transcription progress  Lee et . In one In the other study, In addition to m6A modification, enrichment of 5-methylcytosine (m5C) marked eRNAs were found at a set of enhancers upon metabolic stress . Under tRecent studies have shown liquid-liquid phase separation (LLPS) occurs at super-enhancers, which compartmentalizes crowded transcription regulators  and promotes the formation of transcriptional condensates . ConsideBased on current findings, we can extrapolate eRNAs play a broad role in controlling the formation, dissociation, and dynamics of transcriptional condensates at enhancers and/or cognate promoters via scaffolding multivalent interactions between condensate components . First, Despite the substantial progress of eRNA studies, much more efforts are warranted in delineating their functions and underlying mechanisms, considering the heterogenous nature in terms of their expression, length, secondary structures, and post-transcriptional modifications. For instance, our understanding of eRNA structures is poorly explored. To tackle this situation, more structural studies  are anticipated to uncover intramolecular secondary structures crucial for distinct properties of eRNAs. Equally important is the cataloging a more comprehensive list of eRNA binding partners . Analyses of such data can provide insights into how eRNAs interact, and whether common sequence motifs or structural features of eRNAs exist conferring the interaction specificity. It will be also important to further explore the recently identified intermolecular RNA-RNA interactions and RNA-chromatin interactions, which present an intriguing possibility that eRNAs potentially participate in nuclear compartmentalization . Besides


Nucleophosmin 1 (NPM1C+) was thought to be a primary driving event in acute myeloid leukemia (AML) that reprograms leukemic-associated transcription programs to transform hematopoietic stem and progenitor cells (HSPCs). However, molecular mechanisms underlying NPM1C+-driven leukemogenesis remain elusive. Here, we report that NPM1C+ activates signature HOX genes and reprograms cell cycle regulators by altering CTCF-driven topologically associated domains (TADs). Hematopoietic-specific NPM1C+ knock-in alters TAD topology leading to disrupted regulation of the cell cycle as well as aberrant chromatin accessibility and homeotic gene expression, which results in myeloid differentiation block. Restoration of NPM1 within the nucleus re-establishes differentiation programs by reorganizing TADs critical for myeloid TFs and cell cycle regulators that switch the oncogenic MIZ1/MYC regulatory axis in favor of interacting with coactivator NPM1/p300, and prevents NPM1C+-driven leukemogenesis. In sum, our data reveal that NPM1C+ reshapes CTCF-defined TAD topology to reprogram signature leukemic transcription programs required for cell cycle progression and leukemic transformation.C-terminal mutation of  NPM1 results in cytoplasmic sequestration of NPM1C+ protein that maintains a unique expression pattern of HOXA/B genes and MEIS1 oncogene by directly binding to chromatin target sites to facilitate AML leukemogenesis [NPM1C+-driven gene regulatory networks and leukemogenesis remain elusive. Since wild-type (WT) NPM1/NPM1C+-associates with CTCF and may influence CTCF-mediated loops by anchoring for CTCF cluster [C+ mislocalization may alter CTCF-mediated gene expression. We test whether mislocalization of NPM1C+ to cytoplasm alters CTCF-mediated three-dimensional (3D) topologically associated domains (TADs) by Hi-C comparing mouse bone marrow (BM) Lin-cKit+ (LK) stem- and progenitor-enriched cells purified from WT and NPM1C+-KI animals induced for NPM1C+ expression for 4-months  gene , or treated OCI-AML3 cells with 50 nM XPO1 inhibitor (XPO1i), selinexor, for 3 days to block the NPM1C+ cytoplasmic export, and test if restoration of nuclear NPM1 reversed NPM1C+-associated HOX expression signature and TAD formation. Immunofluorescent staining confirmed that XPO1i or NPM1OE resulted in nuclear localization of NPM1 and enhanced its colocalization with CTCF . NPM1OE altered 96 TADs defined by CTCF boundaries. Among those, 55 TADs were decreased, while 41 TADs were increased by NPM1OE  were significantly impaired as early as 3 hr upon blocking NPM1C+ cytoplasmic localization, while the CTCF mediated looped interactions encompassing CEBPA/G genes were increased immediately upon blockage of NPM1C+ cytoplasmic translocation (Fig. CEBPA genes were only upregulated upon 24 hr and 3 days XPO1i treatment, respectively (Fig. To further support that NPM1 nuclear relocalization is in part inducing genome TAD reorganization, we performed time course experiments by treated OCI-AML3 cells with XPO1i for 0, 1, 3, 6, 24, and 48 h. We observed a significantly increase in nuclear localization of NPM1 WB Fig.  and immu WB Fig. , C. Timeely Fig. , suggestCDKN1A and CDKN2B by associating with NPM1 and p300, while in MYC transformed cancer cells, association of MYC and MIZ-1 repels NPM1 and p300 leading to aberrant proliferation [NPM1OE, these interventions promoted MIZ-1 interacting with NPM1 in nucleus compared to untreated OCI-AML3 cells (Fig. CDKI and CEBP genes, was significantly increased (Fig. NPM1OE (Fig. C+ regulates CDKI and CEBP genes upon nuclear retention of NPM1 because the antibody used recognized both forms.It has been proposed that MIZ-1 activates its target genes including feration , 11. We lls Fig. , bottom.lls Fig. . RT-qPCRsed Fig. E, S4B. Csed Fig. –E, while1OE Fig. , G. As a1OE Fig.  while H31OE Fig.  comparin1OE Fig. , HoweverCDKN1A and CEBPA genes are consistently enhanced by XPO1i treatment (Fig. c+/NPM1 were targeted to distinct chromatin sites to differentially activate oncogenic vs myeloid differentiation pathway. Given that NPM1 interacts with MIZ-1 and chromatin bound CRM1/XPO1 recruits NPM1C+ onto HOX cluster [C+ to the intended chromatin targets, respectively. In addition, HOX associated lncRNAs, HOTTIP and HOXBLINC, are aberrantly activated in NPM1C+-AML cells that may also play a role in NPM1C+-driven oncogenic HOX gene expression [Although NPM1 antibody that we used cannot distinguish WT from mutant protein and their role in CDKI and CEBP gene regulation, analyzing Bru-seq data of WT and XPO1i treated OCI-AML3 cells from recent published data  also revent Fig. , support cluster , 12. It pression , 13, 14.NPM1C+ AML cells affects leukemogenesis and survival of AML mouse models in vivo, we transplanted 1 × 106 WT, NPM1OE OCI-AML3 cells into NSG mice. All animals transplanted with WT OCI-AML3 cells died around 38 days after transplantation, while mice that received OCI-AML3 cells with NPM1OE survived between 54–58 days (Fig. NPM1C+, perhaps blocking NPM1C+-driven TAD topology and signature gene expression and restoring cell cycle control and myeloid differentiation.Consistent with upregulation of CDKIs along with myeloid TFs, CEBPA and CEBPD, nuclear retention of NPM1 promoted OCI-AML3 cell differentiation seen by increased expression of myeloid-specific surface markers CD11b and CD14 Fig. –C. Furthays Fig. . Thus, nSupplementary Information-NPM1