Hematopoiesis is a convenient model to study how chromatin dynamics plays a decisive role in regulation of cell fate. During erythropoiesis a population of stem and progenitor cells becomes increasingly lineage restricted, giving rise to terminally differentiated progeny. The concerted action of transcription factors and epigenetic modifiers leads to a silencing of the multipotent transcriptome and activation of the transcriptional program that controls terminal differentiation. This article reviews some aspects of the biology of red blood cells production with the focus on the extensive chromatin reorganization during differentiation. For a long time chicken erythrocyte nuclei have been a classic model object in numerous studies on the chromatin arrangement in interphase cells. Organization of a chromatin fibre and different levels of its compaction, from a 146 bp nucleosome-level units to large structurally distinct chromatin compartments, were studied using nucleated erythrocytes ,3,4,5. IDuring mammalian erythropoiesis, erythroid progenitors proliferate and undergo stepwise morphological changes, producing a pool of nuclear-free reticulocytes . ErythroThe finely regulated differentiation process is accompanied by progressive hemoglobinization and reorganization of membrane and cytoskeletal proteins. Erythroblast chromatin becomes progressively compacted starting from the basophilic stage. Orthochromatic erythroblasts exit the cell cycle, their transcriptional activity is significantly suppressed, except for the regions encoding important erythroid-specific genes, such as globin genes and erythroid cell membrane proteins . FinallyAlthough all vertebrate erythroid cells undergo chromatin condensation, only mammalian erythrocytes are enucleated. Red cells in some non-mammalian vertebrates contain a special linker histone H5 ,19,20. BEx vivo and in vitro culturing of erythroid progenitor cells have expanded our understanding of terminal erythropoiesis. Molecular and signaling pathways have been discovered that play an important role in chromatin condensation, enucleation and reticulocyte maturation. It is now clear that complex epigenetic regulation is involved in the control of transcriptional program in highly specialized erythroid cells, defining their differentiation trajectory.Erythropoiesis is one of the most extensively characterized cell differentiation models, serving as a paradigm for understanding the mechanisms of development and differentiation in other cell types. Epigenetic studies of distinct erythroid populations have shown that chromatin states differ by specific differentiation stages, with clear transitions between some stages, which indicates that stage-specific activation of gene activity during erythropoiesis is a stepwise process involving complex cis-regulation ,23,24,25Post-translational modifications of the flexible histone tails significantly contribute to the chromatin structure and stability. For instance, acetylation of histones by histone acetyltransferases (HATs) destabilizes closed chromatin structure, making DNA more accessible to transcription factors. In contrast, deacetylation of histones by histone deacetylases (HDACs) stabilizes chromatin by strengthening histone–DNA interaction, which is critical for heterochromatin formation. During erythroid maturation expression of histone acetyltransferase Gcn5 gradually decreases, which results in the drop of the global levels of the several histone acetylation markers, especially H3K9Ac, H4K5Ac, H4K12Ac, and H4K8Ac . This isConsistent with these data, HDAC2 level, which gradually increases during erythropoiesis, is critical for chromatin condensation and enucleation. Treatment with pharmacological inhibitors of HDAC2 or HDAC2 shRNA knockdown blocks chromatin condensation and enucleation of cultured mouse fetal erythroblasts . In addiMethylation of histone tails is also an important regulator of chromosome condensation. Setd8  is the sole enzyme that can catalyze monomethylation of histone H4 lysine 20 (H4K20) . Setd8 aExtrinsic signals can also induce changes in histone methylation status during erythroid cell maturation. Binding of EPO with EPO receptor activates Jak2-Stat5 signaling cascade. This appears to promote the expression of Suv420h2, a methyltransferase that adds methyl groups to mono-methylated K20 of histone H4 (methylated by Setd8) to form H4K20me3 . Di- andSpecific histone modifications are necessary for normal chromatin compaction and enucleation in erythroblasts. Collectively these findings suggest the importance of histone post-translational modifications in regulation of global chromatin dynamics during erythropoiesis.One of the hallmark features of mammalian erythroid differentiation is the formation of nuclear openings—extensive areas in the nuclear envelope of early erythroblasts lacking the components of the lamina, nuclear pore complex, and nuclear membrane ,43. DistHistone release in erythroblasts is a unique example of selective transport carried out not through the nuclear pore complex, but through huge openings in the nucleus. The details of this mechanism, as well as why DNA is not released through these openings, are not yet clear. However, the process does not seem to be passive as not all major histones are released.Another protein export pathway acting in late erythroid development is RAN transport machinery. Erythroid-specific nuclear export protein, Exportin 7 (Xpo7), may facilitate migration of some nuclear proteins, including core histones H2A and H3, to the cytoplasm . Xpo7 knDifferentiation from early erythroid precursor cells is characterized by a highly coordinated transcriptional program. It regulates dramatic alterations in their phenotypic features, such as metabolic shifts, decrease in cell size, hemoglobinization, membrane reorganization, and nuclear condensation ,23,24,47Stage-specific patterns of transcriptional activity in erythroid cells were described via global gene expression analysis in morphologically discrete FACS-sorted cell populations . RNA wasIntegration of transcriptomic patterns with dynamics of open chromatin landscape enabled researchers to more accurately understand the mechanisms that underlie HSC fate decisions. A detailed picture of the accessible chromatin landscape and transcription factor binding throughout human erythroid differentiation was obtained by Ludwig et al. . They paCoherence between the dynamic program of transcriptional activity during erythroid maturation and a tissue-specific regulatory DNA landscape are covered below.Changes in DNA methylation pattern play an important role in gene expression, parental imprinting, X chromosome inactivation, and transposable elements. Most promoters and enhancers generally remain unmethylated . Data frThe most prominent methylation losses were observed in regions with initially high methylation levels, such as non-CpG island promoters. Both de novo methyltransferases Dnmt3a and Dnmt3b were significantly down-regulated during differentiation along with upregulation of Gadd45a, a protein involved in active demethylation. Presumably, mechanisms leading to global demethylation may function to promote removal of methylation marks at sites of up-regulated erythroid genes, as Dnmt1 knockdown in fetal liver cells accelerates erythroid gene induction with differentiation.Besides, a global loss in methylation was also detected in imprinted genes and transposable elements—regions that are stably methylated in somatic cells. However, at the same time, global demethylation was not accompanied by an increased transcription of transposable elements, as was shown for the LINE-1 retrotransposon .The ten-eleven translocation (TET) family proteins have been recently documented to play a role in erythropoiesis . The famTissue-specific chromatin folding patterns reflect different patterns of gene expression. How chromatin architecture and its modifications interrelate with gene activity as cell fate decisions are being made continues to be studied. Erythropoiesis represents a convenient model system for studying the molecular mechanisms of gene regulation within the same lineage during commitment. Alpha-globin locus represents a canonical example of developmental stage specific promotor-enhancer dynamics.Chromosome conformation capture-based techniques, in particular Hi-C, have become a useful tool for analyzing the structural and functional relationships in the genome. This group of methods has played an important role in identifying the spatial context in which interactions of distal regulatory elements take place. Studies have revealed functional units of chromatin, including compartments, topologically associated domains (TAD), and chromatin loops ,62,63. CThe relationship between chromatin structure and gene regulation was examined on the in vitro differentiated fetal and adult human erythroblasts . The Hi-In Oudelaar et al. the Hi-C modification called Tiled-C in combination with ATAC and single-cell RNA-seq was used to study the relationship between the formation of structural chromatin interactions, the activation of regulatory elements and gene expression during development . An impoExperiments on chicken HD3 cells have revealed that erythroid-specific transcription outburst of the alpha-globin genes has a strong impact on adjacent non-related genes and chromatin structure of the encompassing TAD. Ulianov et al. have analyzed a 2.7 Mb region of chicken chromosome 14 comprising an alpha-globin gene domain, a set of non-globin genes, and a gene desert . It turnExploration of the tissue-specific organization of α-globin locus has been expanded in work by Chiariello et al. Using Capture-C data from Oudelaar et al. for ESCs and erythroid cells, they found that a striking pattern of chromatin contacts is formed in the latter ,79. WhilThe Hi-C method was used to study global chromatin dynamics in chicken erythrocytes . One of Another Hi-C related study expands the knowledge on chromatin dynamics during differentiation. In work by Zhang et al. a low-input Hi-C variant, tagHi-C, was used to obtain contact maps for 10 major cell types of the hematopoietic lineage . ContactMammalian erythrocytes are highly specialized cells: after lineage commitment, progenitors undergo four to five cell cycles before enucleation. Their morphology changes dramatically during this process, occurring in a relatively short time frame. One of the hallmarks of erythroid differentiation, along with hemoglobinization and autophagic organelle clearance, is nuclear condensation and extrusion. Chromatin condensation associated with transcriptional silencing is a necessary requirement for erythroid enucleation. In this review, we have covered some ways in which chromatin dynamics during erythropoiesis is regulated. In particular, open areas are formed in the nuclear envelope of early erythroblasts, lacking components of the lamina and nuclear membrane. The dynamic nuclear opening is required for the selective release of a fraction of core and linker histones . Remaini


Recurrent epigenomic alterations associated with multiple human pathologies have increased the interest in the nuclear receptor binding SET domain protein 1 (NSD1) lysine methyltransferase. Here, we review the current knowledge about the biochemistry, cellular function and role of NSD1 in human diseases. Several studies have shown that NSD1 controls gene expression by methylation of lysine 36 of histone 3 (H3K36me1/2) in a complex crosstalk with de novo DNA methylation. Inactivation in flies and mice revealed that NSD1 is essential for normal development and that it regulates multiple cell type-specific functions by interfering with transcriptional master regulators. In humans, putative loss of function NSD1 mutations characterize developmental syndromes, such as SOTOS, as well as cancer from different organs. In pediatric hematological malignancies, a recurrent chromosomal translocation forms a NUP98-NSD1 fusion with SET-dependent leukemogenic activity, which seems targetable by small molecule inhibitors. To treat or prevent diseases driven by aberrant NSD1 activity, future research will need to pinpoint the mechanistic correlation between the NSD1 gene dosage and/or mutational status with development, homeostasis, and malignant transformation. Gene expression is controlled by temporarily and spatially coordinated modification of chromatin. Hereby, the N-terminal tails of the histone octamers formed by H2A, H2B, H3, and H4 undergo post-translational modifications including methylation, phosphorylation, acetylation, ubiquitylation and sumoylation executed by proteins acting as “writers” of an epigenetic code . Histone−L and NID+L. NID−L interacts with RAR and TR when a ligand is absent, whereas NID+L binds RAR, TR, RXR and ER when a ligand is present, indicating that NSD1 controls repression or activation of target genes by distinct binding to nuclear receptors [NSD1 was discovered in a yeast two hybrid screen for proteins associated with the ligand-binding domain (LBD) of the retinoic acid receptor alpha (RARa). NSD1 was shown to interact directly with the LBD of several nuclear receptors, including the retinoic acid (RAR), thyroid (TR), retinoid X (RXR), and estrogen (ER) receptors. These interactions are mediated by two distinct nuclear receptor interaction domains (NID) in NSD1, NIDeceptors . Similareceptors .The NSD1 gene maps to human chromosome 5q35.3, close to the telomere, with an 8088 bp open reading frame (ORF) . InterroInterrogating public databases suggests ubiquitous NSD1 expression (or its related homologs) in most tissues from various organisms. Somehow higher NSD1 mRNA levels seem to be expressed in normal brain, pancreas, male reproductive tract, and hematopoietic organs such as the bone marrow and lymphoid tissues . Signifi−L and NID+L showed the least identity, with 88 and 83%, respectively [The NSD1 protein contains two NIDs, two proline-tryptophan-tryptophan-proline (PWWP) domains, five plant homeodomains (PHD), an atypical (C5HCH) plant homeo-domain (PHD) finger and a catalytic domain (CD) composed of a pre-SET (AWS), Su(var)3–9, Enhancer-of-zeste, Trithorax (SET) and post-SET domain . The aa ectively   or Multiple Myeloma SET domain protein (MMSET) is located on the short arm of chromosome 4 (4p16.3), a locus targeted by a recurrent t translocation found in up to 20% of patients with multiple myeloma. NSD2 contains a PWWP domain, a SET domain, PHD zinc fingers and a high mobility group (HMG) box with 75% homology to NSD1 [NSD1 is a member of a SET-containing methyltransferase protein family, which contains two additional members, NSD2 and NSD3. Both are significantly smaller than NSD1 due to the absence of the NIDome 4 4p1.3, a loc to NSD1 .NSD1-3 have been functionally characterized as histone methyltransferases (HMT) due to its conserved catalytic SET domain involved in methylation of histone 3-K4, -K9, -K27, -K36, and -K79, and methylation of histone 4-K20 . MembersSeveral, mostly in vitro studies, reported other histones (H4K20) and non-histone proteins as potential NSD1 substrates. Berdasco et al. found that loss of NSD1 by 5′-CpG island DNA hypermethylation interferes with histone lysine methylation not only by decreasing the levels of H3K36me3 but also of H4K20me3 . Lu et aMethylation of histone H3K36 occurs in three states mono-, di- and trimethylation and is primarily described as a hallmark of active transcription. Several KMTs were shown to be recruited by RNA polymerase II and deposit H3K36me3 over gene bodies essential for transcriptional elongation, whereas H3K36me2 is enriched at intergenic regions or promoters ,21.Functional studies have shown that NSD1 catalyzes mono- and dimethylation of H3K36 specifically. NSD2 leads to mono- and dimethylation of H3K36, whereas it prefers to catalyze dimethylation compared to monomethylation. Interestingly, H3K36me2 marks are not only set by NSD1-3 but also by ASH1L (ASH1 Like Histone Lysine Methyltransferase), whereas SETD2  is the only enzyme able to introduce K36 methylation up to the trimethylation stage (H3K36me3) . PreviouNsd1 leads to genome-wide expansion of H3K27me3 not only at PRC2 target genes but also as de novo accumulation within broad H3K27me2 marked domains. Thus, NSD1-mediated H3K36me2 seems crucial to restrict PRC2 activity by preventing uncontrolled deposition of H3K27me3 [Yuan et al. suggested that H2A mono ubiquitination (ubH2A) impairs the enzymatic activity of HMTs including NSD1, indicating another layer of complexity in NSD1 regulation . NotablyIn addition to PRC2, epigenomic regulation by NSD1 also involves DNA methyltransferases (DNMTs), which methylate CpG dinucleotides. In total, there are five different DNMTs, of which three play a role in DNA methylation. DNMT1 is important to maintain methylation during DNA replication and acts in response to DNA damage, while DNMT3A and DNMT3B are responsible for de novo methylation . DNMT3 eDepletion of NSD1 leads to both up- and down-regulation of gene expression, indicating NSD1 functions as transcriptional co-activator and co-repressor. In earlier studies, distinct stretches of the NSD1 ORF sequence were tested for their transcriptional activity by fusing them to a GAL4 DNA binding domain, which identified a region (1084–1400 aa) with a significant repressive activity in vitro. This suggested that NSD1 has a silencing domain that functions autonomously, which might act as corepressor for unliganded TR and RAR ,34. In cSchizosaccharomyces pombe SET2, which contains a SET domain but no PHD or PWWP domains, conferred reduced serum dependence, indicating that the catalytic NSD1 activity is able to modulate serum dependence [Earlier in vitro studies showed that NSD1 overexpression allowed NIH-3T3 fibroblasts to grow in reduced serum levels, whereas vector-transfected control cells did not. Overexpression of pendence .Drosophila melanogaster caused developmental delay and reduced body size at the larval stage, resulting in pupal lethality. Targeted overexpression in various tissues led to significant alterations that rescued RNAi-based NSD knockdown. NSD overexpression enhanced the transcription of pro-apoptotic genes and led to caspase activation. Notably, NSD-overexpression associated wing atrophy was reduced by a loss-of-function mutation in Jun N-terminal (JNK) kinase [Drosophila imaginal discs induced organ atrophy. Interestingly, ectopic expression of the DNA replication-related element-binding factor (DREF) resulted in increased NSD expression [Drosophila larval brain cells. However, pan-glial NSD overexpression also induced caspase-3 cleavage in neuronal cells. Among the various glial cell types, NSD overexpression in only astrocytic glia induced apoptosis and abnormal learning defects in the larval stage. These observations in Drosophila suggested that aberrant NSD expression may result in neurodevelopmental disorders through functional interference with astrocytes [Drosophila larvae. Although the NSD mutant flies survived to adulthood, their fecundity was dramatically decreased. NSD lacking flies also showed neurological dysfunctions, such as lower memory performance and motor defects, and a diminished extracellular signal-regulated kinase activity [To better understand the function of NSD1 in vivo, gain- and loss-of-function studies in various organisms have been performed. Ubiquitous NSD (the fly NSD1 homolog) overexpression in ) kinase . NSD1 ovpression . DREF prtrocytes . In contactivity . CollectNsd1 exon 5 containing the nuclear factor interaction domain. Ubiquitous inactivation  embryos displayed a high incidence of apoptosis and failed to complete gastrulation, indicating that NSD1 is essential for early post-implantation development [f/fNsd1 allele, showed that conditional targeted ablation in primordial germ cells  resulted in male sterility associated with absence of mature spermatozoa and loss of testicular germ cells in adult testis and epididymis. A similar effect was seen when DNMT3A was conditionally ablated in germ cells. Male mutant mice presented with impaired spermatogenesis due to loss of methylation at two out of three paternally imprinted loci in spermatogonia [−/−Nsd1 females are fertile. These studies showed that NSD1 plays a critical role in the maturation of mouse gametes by regulating distinct profiles of H3K36 methylation [Nsd1 mouse allele generated by Losson et al. inactivated the gene in the hematopoietic system. Unexpectedly homozygous ablation during late fetal liver hematopoiesis  resulted in a fully penetrant hematological malignancy phenocopying many aspects of human acute erythroleukemia. Functional studies revealed that lack of Nsd1 impairs terminal differentiation of erythroblasts, which could be rescued by expression of wildtype, but not a catalytically inactive SET-domain NSD1N1918Q mutant. Interestingly, NSD1, but not the inactive mutant, significantly increased the occupancy of the erythroid transcriptional master regulator GATA1 at target genes and their expression. These studies identified NSD1 as a novel regulator of GATA1-controlled erythroid differentiation [Nsd1 allele for targeted activation of the gene in mesenchymal progenitor cells . Ablation of Nsd1 in mesenchymal progenitors resulted in impaired cartilage development, skeletal growth defects, and impaired fracture healing. Chondrogenic differentiation was impaired, which was associated with reduced H3K36me2 marks and lower expression of critical mediators including the SRY-box transcription factor 9 (SOX9). Interestingly, in chondrocytes NSD1 seems to bind the promoter and to control expression of the hypoxia-inducible factor 1alpha , a well-known regulator of SOX9 [Sox9 overexpression rescued the chondrogenic differentiation effects of −/−Nsd1 cells. Collectively, these data suggest that NSD1 controls chondrogenic differentiation by direct (H3K36me2) and indirect (HIF1A) regulation of SOX9 [To gain insight into the biological functions of NSD1 in mammals, Losson and colleagues have generated mice carrying a floxed elopment . More reatogonia . Moleculhylation . A thirdntiation . Very re of SOX9 . Importa of SOX9 Nsd1. Although they did not find any major morphologic defects in +/−Nsd1 brains, the animals exhibited deficits in social behavior without significant learning or memory deficits. −/−Nsd1 E9.5 embryos had a smaller prosencephalon compared to heterozygous and wildtype animals, with abnormal morphology and aberrant formation of the luminal cavity of the brain [Drosophila and mice showed that NSD1 is essential for normal development and that it regulates a wide variety of cellular functions, of which many seem to be cell type-specific, most likely by controlling the activity of distinct transcriptional master regulators.Piper and colleagues used a CRISPR/Cas9 strategy to inactivate exon 3 of he brain . Taken tNSD1 gene locus have been reported in rare patients with a clinically reversed SOTOS syndrome. These individuals are characterized by short stature, microcephaly, learning disability or mild to moderate intellectual disability, and distinctive facial features. These observations suggest that the NSD1 gene dosage determines the phenotype of these developmental syndromes [Germline lesions  potentially resulting in loss-of-function of the NSD1 protein have been linked to a developmental syndrome called SOTOS . SOTOS iyndromes .Analysis of a cohort of >700 individuals with overgrowth and intellectual disability revealed a putative causal mutation in less than 15 genes in almost half of the individuals . Notably+/− DNA methylation signature encompasses genes that function in cellular morphogenesis and neuronal differentiation reflecting cardinal features of SOTOS syndrome [Analysis of genome-wide DNA methylation of SOTOS syndrome patients revealed a highly specific signature able to differentiate patients with pathogenic NSD1 mutations from controls, benign NSD1 variants and clinically overlapping syndromes. This NSD1syndrome . SOTOS-rsyndrome .+ AML cells of which activating FLT3-ITD mutations are by far the most prevalent, present in about 80% of the cases [HoxA7 and HoxA9 loci and maintains histone H3K36 methylation and histone acetylation, preventing transcriptional repression of the HoxA gene cluster during differentiation. Structure functional analysis indicated that the phenylalanine-glycine (FG) repeats of the NUP98 moiety as well as the NSD1-SET domain are necessary for its transforming activity [NSD1 mutations in AML patients suggesting that not only gain but also loss of NSD1 can contribute to transformation of hematopoietic cells [The first evidence linking NSD1 genetic aberrations to cancer came from cloning of a cytogenetically silent t chromosomal translocation associated with pediatric de novo MDS or aggressive AML that leads to fusion of the N-terminal domains of the nucleopore 98 (NUP98) protein to the C-terminal part (including the SET) of NSD1 . Importahe cases . Reconsthe cases ,59. Funcactivity . Targeteic cells .Nsd1 inactivation again supporting the converting consequences on epigenomic regulation [Analysis of cancer-associated aberrant CpG promoter methylation revealed epigenetic silencing of NSD1 in human brain tumor cell lines associated with reduced H3K36 methylation . While Ngulation ,67.A similar hypomethylated tumor subtype enriched for inactivating NSD1 mutations and deletions was also found in lung squamous cell carcinoma (LUSC). NSD1-altered HNSCC and LUSC correlated at the DNA methylation and gene expression levels, featuring ectopic expression of developmental transcription factors and genes that are also hypomethylated in SOTOS syndrome. Reduced expression of NSD1 was also reported to be part of an epigenetic gene signature able to distinguish non-malignant tumor from tissue of prostate cancer. Surprisingly, metastatic lesions appeared to express significantly higher NSD1 levels than primary tumors . Highly NSD1 that may contribute to cancer through a combination of rare germline variants and somatic loss-of-heterozygosity (LOH). Interestingly, rare germline variants in such genes may contribute substantially to cancer risk, particularly of ovarian carcinomas, but also other cancers [Comprehensive genomic analysis of 21 tumor types originating from >6000 samples revealed that the degrees of overall methylation in CpG island and demethylation in intergenic regions, defined as the ‘backbone’, are highly variable between different tumors . Interes cancers .Researchers also explored the correlation between allele frequency of somatic variants and total gene expression of the affected gene using matched tumor and normal RNA and DNA sequencing data from almost 400 individuals across 10 cancer types. They defined higher allele frequency of somatic variants in cancer-implicated genes. This study revealed that somatic alleles bearing premature terminating variants (PTVs) in cancer implicated genes seemed to be less degraded via nonsense-mediated mRNA decay, possibly favoring truncated proteins. Notably, NSD1 appeared as a gene with more than five somatic variants and PTVs with high allele frequency .Collectively, increased NSD1-SET activity drives a particular hematological cancer, whereas loss-of function mutation or impaired expression characterize a wide variety of mostly solid human cancers .Several strategies have been explored to selectively interfere with NSD1 activity. Earlier work characterized a small molecule methyltransferase inhibitor (BIX-01294) able to modulate H3K9 methylation. BIX.01294 was characterized as a G9a inhibitor by binding to the histone-tail groove in the SET domain . NotablyNSD1 contains several PHD zinc fingers, whereby the PHD-V C5HCH domain serves as a binding site for protein–protein interactions. This region is particularly interesting as it has been shown to be involved in dysregulated Hox gene activation in AML and occurrence of point mutations in SOTOS Syndrome . PHD-V CUsing a luminescence screening platform that quantifies S-adenosyl homocysteine (which is produced during methyl transfer from S-adenosylmethionine used by NSD1 and other HMTs), researchers identified suramin and other scaffolds as potential inhibitors of the enzymatic NSD1 HMT activity . A compuHOXA gene cluster and MEIS1. Notably, BT5 also impaired the clonogenic growth of primary NUP98-NSD1+ AML cells but not leukemic cells carrying an KMT2A-MLLT1 fusion or normal human CD34+ hematopoietic stem and progenitor cells. The discovery of this compound provides a platform for the development of potent and selective NSD1-SET inhibitors [More recently, Grembecka, Cierpicki and colleagues employed a fragment-based screening strategy to identify and optimize first-in-class irreversible small-molecule inhibitors of the NSD1 SET domain . Structuhibitors .It is well established that NSD1 regulates gene expression programs through H3K36 methylation in a complex crosstalk between activating and repressive histone marks, as well as DNA methylation. In addition, NSD1 is a target of recurrent germline or somatically acquired loss and gain-of-function alterations associated with developmental syndromes  and various human cancers. However, many open questions remain; in particular, it is currently poorly understood how a putative loss of function mutation or reduced expression results in the observed developmental and cancer phenotype.Molecular characterization of SOTOS patient-derived DNA confirmed the connection between NSD1 loss-of-function mutations and aberrant DNA CpG methylation . However+/−Nsd1 mice do not develop any pathologies and express normal Nsd1 mRNA and protein levels [NSD1 gene dose in malignant transformation is necessary. It also remains unresolved whether genetic alterations are early or late events in cancer development.As outlined before, predicted loss-of-function mutations or epigenetic silencing of NSD1 have been described in a variety of human cancers. Investigating HNSSC or lung squamous cell carcinomas revealed that mutations did not abrogate NSD1 expression in most samples. Notably, interrogation of the cancer cell line encyclopedia (CCLE) indicates that only a very small number (5/1457) of human cancer cell lines completely lost NSD1 expression at the mRNA level ,81. Currn levels . In addiIn addition, the critical downstream effectors of the tumor suppressive activity of NSD1 remain unknown. Although recent molecular analysis of human HNSCC cancer cell lines with and without NSD1 mutations (generated by CRISPR/Cas9 genome editing) revealed aberrant regulation of genes related to oxidative phosphorylation, MYC, mTORC1 or RAS signaling and other pathways, the impact on the cell biology has not been addressed and no particular transformation effector genes have been validated . In addi+ T cells) as well as low expression of immune checkpoint ligands and receptors  [+ T cell-infiltrated tumor phenotypes (TCIP-H vs. TCIP-L) associated with different clinical outcome. Notably about 20% of TCIP-L tumors carried loss of function NSD1 mutations [Notably, one of the most significantly down-regulated pathways in HNSSC cells, carrying engineered NSD1 mutations, was interferon alpha/gamma signaling . EarlierDCD1LG2) . InteresDCD1LG2) . Anotherutations . These outations ,85.HOX-A gene cluster regulated by the fusion partner like NSD1 that favors transcription by H3K36 methylation [+ hematological malignancies.When fused to the N-terminus of NUP98, the NSD1-SET gains transforming activities in hematopoietic cells, resulting in myelodysplasia and AML, and the presence of a NUP98-NSD1 (and other NUP98-fusions) is often associated with primary resistance to chemotherapy ,87. Funchylation ,89. Thes+ pediatric AML, one has to take into consideration that loss-of-function mutations of NSD1 are much more prevalent in human cancers. Will such NSD1-SET inhibitors also block NSD1’s role as a tumor suppressor? Significantly reduced NSD1 activity may functionally affect transcription factors controlling maturation of hematopoietic cells . In the best-case scenario, some reduction of the NSD1-SET might be sufficient to induce differentiation of NUP98-NSD1-transformed myeloid cells, whereas significant side effects (as observed in gene targeted mice) may only develop upon complete inactivation over a longer time period that will most likely never be reached by such compounds.Although selective NSD1-SET inhibitors are highly relevant for aggressive NUP98-NSD1The future NSD1 research agenda should aim to (i) mechanistically determine the gene dosage–phenotype correlation in germline syndromes with aberrant NSD1 activity, (ii) identify the cellular and molecular mechanisms of malignant transformation by altered NSD1 activity , and (iii) optimize and validate small molecule NSD1-SET inhibitors for therapy of pediatric AML, driven by the NUP98-NSD1 fusion gene, and research for strategies to selectively interfere in situations when reduced NSD1 activity is the driving force.


Runx1 is a large, complex gene that is expressed from two alternative promoters under the spatiotemporal control of multiple hematopoietic enhancers. To dissect the dynamic regulation of Runx1 in hematopoietic development, we analyzed its three-dimensional chromatin conformation in mouse embryonic stem cell (ESC) differentiation cultures. Runx1 resides in a 1.1 Mb topologically associating domain (TAD) demarcated by convergent CTCF motifs. As ESCs differentiate to mesoderm, chromatin accessibility, Runx1 enhancer-promoter (E-P) interactions, and CTCF-CTCF interactions increase in the TAD, along with initiation of Runx1 expression from the P2 promoter. Differentiation to hematopoietic progenitor cells is associated with the formation of tissue-specific sub-TADs over Runx1, a shift in E-P interactions, P1 promoter demethylation, and robust expression from both Runx1 promoters. Deletion of promoter-proximal CTCF sites at the sub-TAD boundaries has no obvious effects on E-P interactions but leads to partial loss of domain structure, mildly affects gene expression, and delays hematopoietic development. Together, our analysis of gene regulation at a large multi-promoter developmental gene reveals that dynamic sub-TAD chromatin boundaries play a role in establishing TAD structure and coordinated gene expression.The transcription factor RUNX1 is a critical regulator of developmental hematopoiesis and is frequently disrupted in leukemia.  RUNX1 is a large and complex gene with two alternative promoters and multiple hematopoietic enhancers. Here the authors show that unlike smaller genes Runx1 becomes sub-compartmentalized during differentiation and gene activation. This subcompartmentalization partially depends on CTCF binding at promoter-proximal CTCF sites and transcription. Runx1 is best known for its critical role in the de novo generation of the hematopoietic system and maintenance of normal hematopoietic homeostasis4. Disruption of RUNX1 in humans leads to several hematopoietic disorders, including acute myeloid leukemia5 and familial platelet disorder with associated myeloid malignancy (FPD-AML)6. All members of the RUNX family bind the same canonical DNA motif (YGYGGT) and their tissue-specific functions are thought to be governed largely by their specific expression patterns7. Runx1 transcription is tightly regulated, with changes in gene dosage and expression level affecting both the spatiotemporal onset of hematopoiesis and hematopoietic homeostasis11. Runx1 is transcribed from two alternative promoters, the distal P1 and proximal P2 that are differentially regulated and generate different transcripts and protein products13 (reviewed in de Bruijn and Dzierzak1). During hematopoietic development, Runx1 expression initiates from the P2 promoter and gradually switches to the P1 promoter with the majority of adult hematopoietic cells expressing P1-derived Runx117. The Runx1 promoters do not confer tissue specificity and several distal Runx1 cis-elements have been identified that mediate reporter gene expression in transient transgenic embryos in Runx1-specific spatiotemporal patterns21. However, the combinatorial regulation of Runx1 at different stages of hematopoiesis is currently unclear, as are the mechanisms through which the tight and dynamic spatiotemporal control of Runx1 expression is achieved. A better understanding of Runx1 regulation may yield insights into potential avenues for therapeutic targeting of RUNX1 in a variety of hematological disorders, as recently highlighted by growth inhibition in a leukemia cell line upon loss of the Runx1+ 23 enhancer22.Runx1/AML1 is a member of the RUNX family of transcription factors (TFs), which are key to many developmental processes26. Specific interactions achieved through chromatin folding, particularly enhancer–promoter (E-P) interactions, are thought to be a key component of spatiotemporal gene regulation28. Many insights into principles of transcriptional regulation have come from studying a few relatively small gene loci, including the globin genes. However, genes encoding developmentally important TFs, including LIM-Homeobox, Hox, Eomes, Sox, and Sonic Hedgehog (Shh), often lie in larger regulatory domains and are frequently flanked by gene deserts29. Indeed, studies of developmental regulators, such as Shh, have revealed exceptionally long-range enhancer–promoter interactions30, suggesting that specific regulatory mechanisms may be at play at these large developmental loci in addition to the basic regulatory principles established at smaller genes. One aspect that remains unclear is whether large-scale chromatin conformation changes may be required to coordinate complex developmental expression patterns at larger genes. A known factor important for the regulation of chromatin conformation is CCCTC-binding factor (CTCF)31. CTCF, along with the loop extruding factor cohesin, mediates the establishment and maintenance of both E-P interactions and TAD structure34. Interestingly, Runx1 was mis-regulated in zebrafish after perturbation of CTCF/cohesin37, suggesting that Runx1 regulation may depend on chromatin structure. Elucidating Runx1 transcriptional regulatory mechanisms is expected to contribute to a better understanding of the chromatin conformation changes employed by complex multi-promoter genes during development.The 3D conformation of DNA in structures such as topologically associating domains (TADs) delimit the activities of enhancers in vivoRunx1 chromatin landscape in four-dimensions, i.e., in 3D space over time, in an in vitro mouse ESC differentiation model of developmental hematopoiesis. Using high-resolution chromosome conformation capture (Tiled-C)38, we report the presence of a pre-formed 1.1 Mb TAD spanning the Runx1 locus in mouse ESCs that is conserved in human and forms prior to gene activation. Upon differentiation, accessible chromatin sites emerge within the TAD over known enhancers, CTCF sites, and candidate cis-regulatory elements. These regions interact with the Runx1 promoters in a developmental stage-specific manner. Notably, an increased interaction of the P1 and P2 promoters within cell-type-specific Runx1 sub-TADs is seen. These sub-TADs are bounded by highly conserved promoter-proximal CTCF sites, the role of which is poorly understood. Here, we use a machine learning approach and CRISPR/Cas9-mediated deletion to examine the importance of promoter-proximal CTCF binding for the Runx1 chromatin landscape. Deletion of either the Runx1 P1 or P2 promoter-proximal CTCF site partially disrupts TAD structure, while E-P interactions appear unaffected. Runx1 levels show a decreased trend at the mesoderm stage, concomitant with significant changes in mesodermal gene expression indicative of a delay in hematopoietic differentiation. Together, we find that sub-TAD chromatin boundaries form dynamically within the large and complex Runx1 regulatory domain during differentiation and are involved in coordinating gene expression and hematopoietic differentiation.Here, we characterize the Runx1 locus . In this model, we assessed chromatin conformation (Tiled-C), along with gene expression (poly(A)-minus RNA-seq to capture nascent transcripts) and chromatin accessibility (ATAC-seq) over hematopoietic differentiation  cultures. Upon further differentiation in EHT media these gave rise to phenotypic HPCs with blood progenitor morphology and in vitro clonogenic potential  plot , transient expression of mesodermal genes , and increasing levels of hematopoiesis-associated genes  .To investigate dynamic changes in 3D chromatin confirmation in the ion Fig. . Flk1+ mlot Fig. . This wa2b) Fig. . Runx1 ePCs Fig. 17.Fig. 1Runx1 regulatory domain, we performed Tiled-C, a targeted method that generates Hi-C-like data at specific loci38, with probes against all DpnII fragments in a 2.5 Mb region centered on Runx1. PCA of individual Tiled-C replicates showed a clear developmental trajectory  . Ten accessible peaks unique to mesoderm corresponded to previously identified enhancers 47 , while insulation of the main TAD (a measure of intra-TAD interactions) decreased slightly . To determine promoter-specific enhancer interactions, we compared virtual Capture-C profiles across the Runx1 locus using the P2 and P1 promoters as viewpoints , specific increased interactions between the P2 promoter and the −327, −322, −303, −181, and −171 enhancer elements in the gene desert, and the +3, +23, and +110 enhancers in the Runx1 gene body , in line with the absence of P1-derived Runx1 expression . Insulation of the main TAD slightly decreased further as cells differentiated from mesoderm to HPCs , while CTCF-CTCF interactions between the boundaries of the TAD were not different from mesoderm . Alongside these changes at the main TAD-level, two sub-TADs spanning the Runx1 gene were strengthened significantly in HPCs . We next compared how specific E-P interactions changed between mesoderm and HPCs using virtual Capture-C plots of the Tiled-C data. Compared to mesoderm, total E-P interactions increased in HPCs for the P2 promoter and there was a trend of increased overall E-P interactions for P1 . Both P1 and P2 showed specific increases in E-P interactions with −59, −43, −42, +23, and +110 enhancers . The role of promoter-proximal CTCF has not been widely explored. To examine whether the deeply conserved P1 and/or P2 promoter-proximal CTCF sites  to predict chromatin interactions at the Runx1 locus in mESCs. The deepC model was trained on Hi-C data from mESCs59, withholding mouse chromosome 16 containing Runx1. The overall Runx1 TAD predicted by deepC agreed well with the TAD observed in Tiled-C data from mESCs  nor was any individual E-P interaction . Together, our results show that despite perturbed chromatin architecture resulting from the absence of conserved promoter-proximal CTCF sites, specific Runx1 E-P interactions are maintained.In HPCs, both P1 and P2 promoters primarily interacted with enhancers lying within the tissue-specific sub-TADs Fig. . As thesRunx1 P1, is associated with promoter activity . No changes were observed in alternative P1 or P2 promoter usage after deletion of promoter-proximal CTCF sites . Notably, expression of several mesodermal markers (including T and Eomes) was higher in P2-CTCF-KO mesoderm compared to wild type, while several hematopoietic markers and Runx1 target genes were downregulated 62. GO analysis of genes downregulated by P2-CTCF-KO were associated with biological processes including “response to growth factor” and “blood vessel remodeling”, while upregulated genes were associated with terms including “mesoderm development” and “gastrulation” . Collectively, this indicates that loss of the P2-proximal CTCF binding site caused a delay in in vitro hematopoietic differentiation, providing functional support for a mild decrease in P2-derived Runx1 transcription at or prior to the mesoderm stage.Since CTCF binding close to promoters genome-wide, including at tes Fig. . PCA of tes Fig. . Howevertes Fig. . Indeed,Runx1 chromatin architecture in four-dimensions, i.e., the three-dimensional folding of chromatin over developmental time. Tiled-C38 analysis of the Runx1 regulatory domain provided an unprecedented high-resolution view of Runx1 chromatin architecture during in vitro differentiation from mESC through Flk1+ mesoderm to differentiating HPCs. Our detailed dissection of Runx1 transcriptional regulation during developmental hematopoiesis sheds light on regulatory mechanisms of complex large developmental genes. We found that Runx1 resides in a preformed, transcription-independent, and evolutionarily conserved main TAD that is present throughout differentiation  it is plausible that a similar dependency on the +23 enhancer may exist in other leukemic cells64. Of note, a recent report exploring GWAS studies for SNPs in RUNX1 regulatory elements found just one mutation in the +23 enhancer and this was predicted to be pathogenic65. This suggested that there is strong selection pressure to conserve the +23 enhancer in normal hematopoiesis. However, further studies are required to elucidate the dependency on Runx1 enhancers in normal hematopoiesis and leukemia. The 4D regulatory interactions at Runx1 described here were missed in previous reports67 as those lacked the required high-resolution, nor included a developmental time series.In the present study, we used a cutting-edge 3C-based method to reveal dynamic changes in the ion Fig. . Within 70, the overall 1.1 Mb Runx1 TAD formed prior to differentiation and in the absence of virtually any gene transcription. The mechanism behind its establishment is likely CTCF/cohesin-mediated loop extrusion74 as a predominant convergence of CTCF motifs was observed at the main Runx1 TAD boundaries, similar to what was found at other TADs77. In addition to these preformed chromatin structures, increasing CTCF-CTCF interactions were observed upon Runx1 activation that might reflect a higher rate or processivity of loop extrusion in the Runx1 TAD, as was recently also observed for α-globin38. Alternatively, increased TF binding could be driving the specific increases in chromatin interactions that were observed over differentiation79. Two tissue-specific sub-TADs formed over differentiation, leading to a sub-compartmentalization of the Runx1 gene itself that was correlated with promoter activation. This agrees with recent findings at alpha-globin, where gene activation is correlated with sub-TAD strengthening38, indicating that common mechanisms underlie chromatin architecture changes during transcriptional activation at different sized gene loci. However, we also observed differences in chromatin structures between smaller and larger genes, in that sub-compartmentalization within a gene is not generally seen at smaller genes, such as α-globin, which reside entirely within one tissue-specific sub-TAD80. This difference might simply reflect the smaller size of the α-globin domain compared to the larger size of the Runx1 regulatory domain . The sub-TAD encompassing the entire α-globin regulatory unit was shown to represent a discrete functional unit that delimits enhancer activity23. We did not see evidence for this in Runx1 as E-P interactions were not significantly changed upon sub-TAD perturbation by deleting promoter-proximal CTCF sites. However, residual sub-TAD structures may still have provided a framework within which specific regulatory interactions could take place81. Promoter-proximal CTCF site deletion facilitated new interactions with CTCF sites distal to the deleted CTCF sites, leading to expanded loop domains at Runx1. Namely, deletion of P2-CTCF led to increased interactions between upstream regions and the centromeric end of the TAD up to a cluster of CTCF sites close to Clic6  recently observed at genes highly expressed in hematopoietic cells82. The fact that P1 and P2-CTCF sites are not in a convergent orientation, and the fact that sub-TADs/GADs form within the gene-body of actively transcribed genes, suggests that instead of being caused by a CTCF-dependent mechanism like loop extrusion, these structures may be dependent on a combination of factors including transcriptional processes82, TF binding79, and clustering of like histone modifications83. Indeed, our data indicate that, as reported for other promoters86, the Runx1 promoters may function as chromatin boundaries in a CTCF-independent manner, which would explain the residual sub-TADs and E-P interactions, as well as the expanded chromatin interactions observed in P1/P2-CTCF-KO cells. Together, our findings suggest that loop extrusion and transcription-related mechanisms may act in concert to produce dynamic chromatin structures during differentiation.In line with TADs at other developmentally regulated lociRunx1 P2 promoter-proximal CTCF binding site resulted in a developmental delay in hematopoietic mesoderm as shown by increased expression of early mesodermal markers at the expense of later hematopoietic ones. Although studies in cell lines indicate that CTCF sites are required for TAD formation87, interestingly, promoter-proximal CTCF sites have been suggested to play a role in E-P interactions and gene transcription92. Therefore, a plausible explanation for the observed differentiation delay could be that promoter-proximal CTCF loss leads to a later or perturbed onset of Runx1 expression, as Runx1 is well known to promote hematopoietic commitment93. Although Runx1 expression in the total mesodermal cell population was not significantly altered, a decreased trend was seen. This surprisingly robust Runx1 expression and alternative promoter usage upon promoter-proximal CTCF-site loss may reflect the residual sub-TADs still found which could be attributed to redundant CTCF sites not targeted in this study (redundancy between CTCF sites has been observed before94), or the Runx1 promoters themselves. An alternative explanation could be the relatively asynchronous development of cells in culture, where some cells may have had enough time to restore Runx1 expression levels. A more substantial phenotype may be seen in a Runx1-heterozygous background, similar to what was observed in mouse embryos carrying an attenuated Runx1 P2 allele and a non-functional Runx1 allele, where the compound phenotype was more severe than that of a homozygous attenuated P216. Finally, compared to in vitro differentiation, promoter-proximal CTCF-site loss may be more detrimental in vivo, where Runx1 levels are subject to tight spatiotemporal control and changes to Runx1 levels or dosage lead to knock-on effects on differentiation timing95. Together this indicates that even subtle changes in Runx1 levels, such as the trend seen in P2-CTCF-KO mesoderm, have the potential to alter hematopoietic developmental dynamics. This underlines that Runx1 requires an exceptionally fine-scale spatiotemporal transcriptional control and isolation from neighboring regulatory domains to support its pivotal role in development. Given that Runx1 has important functions in development and human disease96, an increased understanding of dynamic cis-regulatory mechanisms underpinning its regulation will be vital to future efforts to develop potential therapeutic approaches to manipulate RUNX1 expression in human blood disorders.Interestingly, deletion of the 97 were cultured in GMEM medium supplemented with 100 mM non-essential amino acids, 100 mM sodium pyruvate, 10% FCS, 2 mM L-glutamine, 100 µM β-mercaptoethanol , and 1% Leukemia Inhibitory Factor (prepared in house). Cells were passaged using 0.05% trypsin (Gibco) every 2–3 days. The 416B mouse immortalized myeloid progenitor cell line98 was cultured at 2–8 × 105 cells/ml in Fischer’s medium with 20% horse serum and 2 mM L-glutamine .E14-TG2a mESCs99 in StemPro-34  supplemented with 40X defined serum replacement, 2 mM L-glutamine (Gibco), and 0.5 mM ascorbic acid, 0.45 mM monothioglycerol (Sigma). mESCs were seeded at a density of 5 × 104 cells/ml into SP34 medium plus BMP-4 . At day 3, bFGF and Activin A were added . At day 4, single-cell suspension was generated from embryoid bodies using 0.05% trypsin. FACS-isolated Flk1+ mesodermal cells were cultured at 5 × 104 cells/cm2 in SP34 plus SCF (Peprotech) and VEGF (R&D), 10 ng/ml each. After a further 3 days of culture, adherent and suspension cells were treated with 0.05% trypsin and analyzed.Differentiation of mESCs was performed using a modified serum-free protocolCells were stained in PBS plus 10% FCS with the antibodies listed in Supplementary Table Unsorted cells at day 6 (4 + 2) of differentiation were cultured in MethoCult 04434 (Stem Cell Technologies) in 35 mm dishes. Colonies were counted after 10 days.Cells were plated into glass-bottom 24-well plates (ibidi) and fixed after culture for 10 min with 4% paraformaldehyde (Sigma), permeabilized, and labeled using antibodies (Supplementary Table 100 containing two sgRNAs and confirmed by sequencing. mESCs were transfected with 5 µg plasmid using Lipofectamine 2000 (Invitrogen) and puromycin selected (1 µg/ml). Single colonies were isolated by limiting dilution101. To detect larger on-target deletions104, PCR amplification was done . Reactions were performed in duplex, amplifying from an internal control and a test region in every reaction. Internal control was located on mouse chromosome 4 . Test regions were amplified directly over the targeted region to detect loss of allele (LOA) and at 100 bp and 1 kb up- and down-stream from sgRNA target sites (Supplementary Table 102. Reactions (22 µl) contained 11 µl QX200 ddPCR EvaGreen Supermix (Bio-Rad), 25–50 ng genomic DNA purified using DNeasy Blood and Tissue Kit (Qiagen), 250 nM each of internal control primer, and 125 nM each of test primer. Standard reagents and consumables supplied by Bio-Rad were used. Ratios between test and internal control amplicons was determined in QuantaSoft software (Bio-Rad). Ratios were normalized to the mean ratio of three test amplicons located on different non-targeted chromosomes  to determine relative copy numbers of the test amplicons.To further rule out the presence of undesired complex genotypes4 and 1 × 106 cells using a low-input protocol108. Cells were cross-linked using 2% formaldehyde for 10 min. DpnII (NEB) digestion was performed shaking overnight at 37 °C. Ligation was performed overnight at 16 °C. Samples were treated with RNAse A (Roche) for 30 min at 37 °C and decross-linked using Proteinase K (Thermo Fisher) overnight at 65 °C. Digestion efficiency was quantified by qPCR . Probe sequences were stringently BLAT-filtered to exclude repetitive sequences, and synthesized in-house38. A pooled capture reaction was performed on 1 µg of each indexed 3C library. Washing of captured material was done using Nimblegen SeqCap EZ hybridisation and wash kit (Roche) and captured sequences were isolated using M-270 Streptavidin Dynabeads (Invitrogen). PCR amplification was performed for 12 cycles. Amplified DNA was purified and a second capture and PCR amplification step were performed. Libraries were sequenced on two Illumina NextSeq high-output 150 cycle runs (paired-end).Tiled-C was performed on between 7.7 × 1038. Fastqs were analyzed using the CCSeqBasic CM5 pipeline109 (https://github.com/Hughes-Genome-Group/CCseqBasicF/releases). Individual samples were analyzed before merging biological replicates. PCR duplicate-filtered bam files containing uniquely mapping reads were converted to sam files (samtools) and then into sparse raw contact matrices . ICE normalization was done using HiC-Pro (2.11.1)111 and matrices were imported into R (3.6.0). Matrices were plotted  with a threshold between the 90th and 95th percentile. PCA was done on log normalized counts 112. Merged ICE normalized contact matrices were scaled to the mean number of total interactions  across samples using custom R scripts113. Virtual Capture-C plots were generated by sub-setting the matrices on individual viewpoints of interest. E-P contacts were quantified in count and ICE-normalized matrices from the viewpoint of the bin containing each promoter and bins overlapping previously published Runx1 enhancers  and chromosome 17 from training. Training was done in two stages. First, a convolutional neural network was trained to predict chromatin features given a 1 kb DNA sequence input. The chromatin features cover open chromatin, transcription factor binding, including CTCF, and histone modifications using publicly available DNase-seq, ATAC-seq, and ChIP-seq peaks across a range of cell types. Second, a neural network using a convolutional module followed by a dilated convolutional module was trained to predict Hi-C data given 1 Mb of DNA sequence input. The convolutional filters of the first network are used in the transfer learning to seed the filters of the convolutional module. Promoter-proximal CTCF site deletions were modeled by mutating the region spanning CRISPR/Cas9 deletion alleles that were confirmed by sequencing and predicting the chromatin interactions of the reference and deletion alleles.Predictions of chromatin architecture were performed using deepC3 to 2.5 × 106 cells using QIAzol (Qiagen). Total RNA was extracted using miRNeasy Mini kit (Qiagen). RNA integrity was determined using a 4200 TapeStation RNA ScreenTape (Agilent). Ribosomal RNA was depleted from 2.5 µg total RNA per sample of undifferentiated mESC and 416B cells using the RiboMinus™ Eukaryote System v2 (Invitrogen). A poly A selection module (NEB) was used to extract poly A minus RNA and was eluted directly in First Strand Synthesis Reaction Buffer. cDNA was synthesized using the NEBNext Ultra directional library prep kit. Adapter ligation and 8–15 cycles of PCR were performed. Libraries were sequenced on Illumina NextSeq high-output 75 cycle kit (paired-end).RNA was isolated from 1 × 10114. PCR duplicates were removed using picard-tools (2.3.0) MarkDuplicates. Counts per million (CPM)-normalized bigwig files were generated using deeptools (2.2.2 and 3.0.1)115. A blacklist file was used to exclude mapping artifacts. Bigwig files were converted to bedGraph (ucsctools (373)) and imported into R. Mean CPM was calculated for each merged sample. Reads were assigned using subread (2.0.0) featureCounts116. For poly(A)-minus RNA-seq data reads were assigned to both exons and introns. Assigned counts were imported into R and analyzed using DESeq2 (1.24.0)112. Sample clustering was performed on log normalized counts. Differential expression analysis was done using DESeq2 . Volcano plots were made using EnhancedVolcano (1.2.0)117. GO terms were calculated using goseq (1.36.0)118 and KEGG.db (3.2.3)119. Gene expression was visualized using plotCounts and ggplot2 (3.3.0)120. Promoter-specific counts were quantified from over a 5 kb window downstream of each TSS  using bedtools (2.25.0)121.Fastq files were mapped to the mouse genome (mm9) using STAR (2.6.1d)Runx147 and a hsp68-mCherry-Runx1 +23 enhancer-reporter transgene in the Col1a1 locus). Libraries were generated as previously described122. 2–5 × 104 differentiated cells were FACS-isolated, resuspended in cold lysis buffer, and incubated for 10 min on ice. Cells were centrifuged, supernatant discarded, and resuspended in 10 µl transposition mix. Samples were incubated for 30 min at 37 °C and quenched using 1.1 µl 500 mM EDTA. Reactions were centrifuged and incubated at 50 °C for 10 min. A total of 13 cycles of PCR were performed as in Buenrostro, Giresi, Zaba, Chang, and Greenleaf122 with transposition reaction as a template. PCR reactions were purified using MinElute PCR purification kit (Qiagen). Libraries were sequenced using Illumina NextSeq 75 cycle kit with paired-end reads. Fastq files were mapped to the mouse genome (mm9) (NGseqBasic VS2.0)123. PCR duplicate-filtered bam files from individual samples (four mesoderm replicates from two experiments and two hematopoietic replicates from one experiment) were merged and filtered to remove reads mapping to chrM, ploidy regions, or the Runx1-Venus targeting construct , and only reads with short (<100 bp) insert sizes were retained. RPKM-normalized bigwig files were generated using deeptools (2.2.2 and 3.0.1)115. DNaseI-seq data in undifferentiated mESCs were downloaded from GEO (GSM1014154)42 and analyzed as ATAC-seq data were. Peaks were called from a single merged bam file for each sample using MACS2124 .ATAC-seq libraries were generated in differentiated E14-TG2a-RV mESCs (stably transfected with a Venus reporter at the 3′ end of 6 cross-linked 416B cells were lysed and sonicated using a Covaris ultrasonicator. Sonicated chromatin was diluted using dilution buffer and 50 µL was removed as the 5% input control. 2 µL CTCF antibody (Supplementary Table CTCF ChIP was conducted using Millipore ChIP agarose kit (Millipore). 1 × 1040 was downloaded from GEO (GSE28247). Fastq files were mapped to the mouse genome (mm9) (NGseqBasic VS2.0)123. De novo CTCF motifs were identified in CTCF ChIP-seq data using meme (4.9.1_1)23. CTCF peaks were called using MACS2125 with parameters -p 0.02 using input track as a control. 2000 peaks were sampled using bedtools (2.25.0)121 and flanking regions were extracted from the sampled peaks. Sequences of sampled peaks and flanking regions were retrieved and a background file was generated using fasta-get-markov -m 0. A de novo motif file was generated using meme with options -revcomp -dna -nmotifs 1 -w 20 -maxsize 1000000 -mod zoops. De novo motifs were identified in CTCF peaks using fimo with options -motif 1 -thresh 1e-3.CTCF ChIP-seq was performed in 416B cells and publicly available E14 mESC data126. Genomic DNA (gDNA) was extracted from 1 to 5 × 106 cells using DNeasy Blood and Tissue Kit (Qiagen) and 250 ng gDNA, or Universal Methylated Mouse DNA Standard (Zymo Research) was bisulfite converted using EZ DNA Methylation-GoldTM Kit (Zymo Research). Nested PCR primer sets . Reads were mapped to an in silico bisulfite converted genome using bismark/0.20.0127. Percentages of methylated CpG dinucleotides were determined using bismark methylation extractor. Bedgraph output files were filtered on CpG dinucleotides with coverage greater than 100 reads and imported into R. Average methylated CpG dinucleotide percentages were plotted over each region using ggplot2.DNA methylation analysis was performed as previously describedp < 2 × 10−16) and so non-parametric two-sided Kruskal–Wallis test with Dunn’s post hoc comparisons test was applied. Post hoc testing with Dunn’s test was applied when Kruskal–Wallis test was significant and p-values were adjusted using the Holm method or the Benjamini–Hochberg method. A significance threshold of p < 0.05 was used for all statistical tests.All statistical tests were performed in R and were two-tailed. Tiled-C contact data were non-normal (Shapiro–Wilks test, Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


CKMT2, SLC25A4, and ACO2), or even overlapping a neighboring gene . Surprisingly, the 3′ end of the 1.38 Mb PRKN (PARK2) gene (involved in mitophagy and linked to juvenile Parkinson’s disease) displayed skeletal muscle/myoblast-specific enhancer chromatin, a myoblast-specific antisense RNA, as well as brain-specific enhancer chromatin. We also found novel tissue-specific RNAs in brain and embryonic stem cells within PPARGC1A (PGC-1α), which encodes a master transcriptional coregulator for mitochondrial formation and metabolism. The tissue specificity of this gene’s four alternative promoters, including a muscle-associated promoter, correlated with nearby enhancer chromatin and open chromatin. Our in-depth epigenetic examination of these genes revealed previously undescribed tissue-specific enhancer chromatin, intragenic promoters, regions of DNA hypomethylation, and intragenic noncoding RNAs that give new insights into transcription control for this medically important set of genes.Striated muscle has especially large energy demands. We identified 97 genes preferentially expressed in skeletal muscle and heart, but not in aorta, and found significant enrichment for mitochondrial associations among them. We compared the epigenomic and transcriptomic profiles of the 27 genes associated with striated muscle and mitochondria. Many showed strong correlations between their tissue-specific transcription levels, and their tissue-specific promoter, enhancer, or open chromatin as well as their DNA hypomethylation. Their striated muscle-specific enhancer chromatin was inside, upstream, or downstream of the gene, throughout much of the gene as a super-enhancer ( Striated muscle consists of skeletal muscle (SkM), the largest organ in the body, and heart muscle, whose malfunction is responsible for approximately 30% of deaths globally . This tyThe progenitor cells for SkM formation and repair are myoblasts, which, upon differentiation, can develop into multinucleated myotubes or fuse with multinucleated muscle fibers . PostnatMost of the energy required for muscle contraction comes from oxidative phosphorylation rather than from glycolysis . CardiacGiven the central role of epigenetics in differentiation, homeostasis, and disease, in general, and to striated muscle in particular ,23,24,25+ RNA-seq database [MYL2 was the sole exception). Our last transcription criterion was to require a ratio of TPM in SkM to TPM in aorta database  that inch tissue ) >3, whi−9; 27 genes) and transit peptide: mitochondrion  consistent with a previous transcriptomic and proteomic study of striated muscle [AGAP2, MYOM1, and TNNC1, from further consideration because, they are only weakly associated with mitochondrial function. The remaining genes in these two gene sets were combined  are overrepresented among the 97 genes. GO analysis using DAVID  that encode subunits of the mitochondrial cytochrome c oxidase [COX6A2 TPM: SkM, 2284 and heart, 1593; COX7A1 TPM: SkM, 704 and heart 584). COX6A2 has the highest specificity for SkM of all the striated muscle/mitochondria-associated genes. The specificity of COX7A1 for striated muscle is also high but lower than that of COX6A2, which is reflected in the epigenetic profiles of these two genes (COX5A and COX10) were preferentially expressed in SkM and heart but with less specific transcription and epigenetics than for COX6A2 and COX7A1  and heart (both left ventricle and right atrium) had promoter chromatin (red segments) throughout the n spleen . In addi tissues . In the e repair , displayCOX6A2 in aorta  had more DNaseI hypersensitivity and enhancer chromatin upstream of the gene than did most other non-striated muscle tissues  but less than in SkM and heart. Aorta also differed from striated muscle in its DNA methylation profile in this gene region. We used two quantitative measures of differential DNA methylation. One of these shows regions that had significantly lower methylation than in the same genome as a whole [COX6A2 had negligible levels of DNA methylation over much of the CpG-rich region (CpG island) that covered this small gene in all tissues. However, there was significantly less DNA methylation at the 5′ end of the gene and immediately upstream in SkM and heart compared with aorta and other tissues . In addition, DNA hypomethylation in SkM and heart extended from upstream of COX7A1 to the 3′ end of the downstream gene, CAPNS1 . CAPNS1, which encodes a subunit of cysteine proteinase, is broadly expressed with no specificity for SkM  encoding the specificity-determining subunit of MyoD has negligible expression in 52 examined adult tissues [COX6A2 and of COX7A1  encodes a Krebs cycle enzyme [COQ10A and CS are only 0.7 kb apart. Like COQ10A, CS is expressed at its highest levels in SkM and heart but with insufficient specificity to meet our criteria for preferential expression in striated muscle  is adjacent to the 3′ end of its broadly expressed neighbor CHKB (Choline Kinase Beta). CPT1B encodes an enzyme that is required for transport of long-chain fatty acids from the cytoplasm to the mitochondria while CHKB codes for an enzyme involved in phospholipid metabolism [CPT1B TSS is only 0.6 kb from the 3′ end of CHKB , which is consistent with CHKB being linked to myopathies [CPT1B RNA and CHKB RNA were seen for many tissues in addition to SkM and heart  highly express exons from both genes despite only the CHKB 5′-region displaying promoter chromatin (CHKB through CPT1B (CHKB-CPT1B) that is predicted to be a noncoding RNA , SLC25A4/ANT (Solute Carrier Family 25 Member 4), ACO2 (Aconitase 2) encode mitochondrial proteins involved in transfer of phosphate from ATP, translocation of ATP from the mitochondrial matrix to the cytoplasm, or interconversions in the TCA cycle. They are highly expressed in SkM and heart (TPM > 250) and have higher expression than in 34 other tissue types  intronic transcripts  .ed gene) A. Their PRKN is another striated muscle and mitochondria-associated gene VDAC1 , and DNA hypomethylation in SkM and heart than did heterologous tissues, findings that are consistent with striated muscle displaying the highest expression of this gene , is another striated muscle/mitochondria-associated gene involved in Parkinson’s disease [ disease . PGC-1α  disease ,45. Much disease ,47,48,49 disease ,46. Desp disease , the corPPARGC1A were enhancer chromatin segments, DHS, DNA hypomethylation, and myoblast or cardiomyocyte TF binding sites that were consistent with the SkM-, heart-, liver-, or brain-associated usage of these promoters  at the PPARGC1A for brain-specific isoforms [+ RNA-seq brain profile was available, namely for hippocampus from an 80-yo, but this RNA analysis was done without strand separation. This sample displayed many exon-like transcribed regions similar to those of the two fetal samples in the 0.3-Mb region downstream of the distal TSS  that are not expressed preferentially in SkM or heart  while ESC cells predominantly express the read-through CHKB-CPT1B transcript initiated at the CHKB promoter  but still have considerable levels of CHKB RNA  encode subunits of cytochrome c oxidase, the terminal enzyme of the electron transport chain [COX6A2 and COX7A1 have paralogs on different chromosomes, COX6A1 and COX7A2, respectively. COX6A1 and COX7A2 encode similar polypeptides to those of COX6A2 and COX7A1, but they have a much broader tissue expression profile and lack specificity for striated muscle [COX6A2 is exceptionally high  for their increased energy needs in myotubes. This change in energy needs is accompanied by mitochondrial clearance via mitophagy followed by mitochondrial biogenesis to provide mitochondria that are more active in OXPHOS during myoblast differentiation [PRKN RNA before or after differentiation [PRKN in myoblasts vs. heterologous cell types. Moreover, the Parkin pathway has been implicated in mitophagy in myoblasts as well as in SkM [PRKN and the myoblast-specific AS transcription in this region upregulate PRKN transcription, as generally observed for some other enhancer regions that generate unidirectional poly(A)+ lncRNAs [The prominent and varied functions of Parkin and PGC-1α are reflected in the intricate and tissue-specific transcriptomics and, in our study, in the epigenomics of their genes. At the 1380-kb -studied  ~100 kb ed [PRKN  is involntiation . Althougntiation , we founs in SkM . It is l lncRNAs .PRKN gene displayed tissue specificity, most notably for brain. Enhancer chromatin in various subregions in the last three introns of PRKN as well as the SkM/heart-specific enhancer chromatin immediately downstream of the TSS promoter  in addits region . We propischemia ,84,85,86RNA levels  for human tissues were from the GTEx RNA-seq database V8 , which cThe 18-state Roadmap Epigenomics  chromatihttps://portal.genexplain.com/  for predicted binding sites within DNaseI hypersensitive sites in left ventricle. The position weight matrix (PWM) for HAND1 binding sites was for HAND1::E47; MYOD1 also can heterodimerize with E47 to give MyoD TF [MyoD, GATA4, and TBX5 binding sites in myoblasts were determined from UniBind data tracks  in the UCSC browser for hg38 . The car MyoD TF .PRKN/PARK2 gene or within the gene neighbor of a studied gene . In addition, novel intragenic antisense lncRNAs were found within PRKN in myoblasts and skeletal muscle and within PPARGC1A/PGC-1α in embryonic stem cells. This study exemplifies the need to look beyond canonical promoters to understand the regulation of expression of genes, in general, and these 27 striated muscle-associated genes, in particular.Genes associated with mitochondrial function, structure, biogenesis, or mitophagy are overrepresented among the category of genes preferentially expressed in both skeletal muscle and heart. Many of these genes are of great importance to metabolism, health, aging and physiological changes. The tissue-specific epigenetic profiles of these genes often paralleled their expression profiles and indicated some unexpected locations of positive regulatory elements, such as, in the gene body 1.28 Mb downstream of the 5′ end of 1.38-Mb


Ribosomal RNA synthesis is the rate-limiting step in ribosome biogenesis. In eukaryotes, RNA polymerase I (Pol I) is responsible for transcribing the ribosomal DNA genes that reside in the nucleolus. Aberrations in Pol I activity have been linked to the development of multiple cancers and other genetic diseases. Therefore, it is key that we understand the mechanisms of Pol I transcription. Recent studies have demonstrated that there are many differences between Pol I transcription in yeast and mammals. Our goal is to highlight the similarities and differences between the polymerase-associated factors (PAFs) in yeast and mammalian cells. We focus on the PAF heterodimer A49/34 in yeast and PAF53/49 in mammals. Recent studies have demonstrated that while the structures between the yeast and mammalian orthologs are very similar, they may function differently during Pol I transcription, and their patterns of regulation are different. Ribosome biogenesis is the process that produces the machinery responsible for synthesizing all the proteins in a cell. This process is extraordinarily complex. Ribosome biogenesis requires the coordination of all three nuclear RNA polymerases . RNA polEarlier dogma stated that the rate of Pol I transcription in cells was constant, and there was no regulation of this process. Over many years, research has shown that many pathways that regulate cell growth also play roles in regulating rDNA transcription. Both oncogenes and anti-oncogenes, such as c-Myc and Rb, contribute to the regulation of transcription by Pol I ,7,8. FurIn 1975, Fromageot’s lab identified two forms of yeast RNA polymerase I . The difThe sequences of the yeast and mammalian orthologues do not demonstrate significant identities. However, focusing on A49/PAF53 and A34/PAF49, the structures predicted for the mammalian proteins are strikingly similar to those of the yeast protein. This is illustrated in TFIIF has multiple roles in Pol II transcription. It has been reported to reduce non-specific interaction of Pol II with DNA  and stabInterestingly, the tWH domains of TFIIE and A49 both lie upstream of the transcription initiation site, and the linker domains of TFIIF and TFIIE appear to span the polymerase cleft in a manner similar to the HTH of A49. In Pol I, the structure of the tWH and linker domains of A49 appear to be more dynamic than those of TFIIE, as they were not visible in the majority of the cryo-EM images captured in the past ,42,43,44S. cerevisiae A49-Δ strain grew slowly at 30 °C and not at all when grown at 25 °C. In contrast, the S. cerevisiae A34-Δ strain grows at normal rates at either temperature. These observations imply that A49 can be incorporated into the core polymerase in the absence of A34. The production of a polymerase devoid of A49 when A34 is deleted demonstrates that the polymerase has a decreased stability in vitro. Thus, A34 helps stabilize the association of A49 with Pol I. Studies in yeast have demonstrated that A49 can be recruited to the polymerase independently of A34. For example, the deletion of the heterodimerization domain does not affect proliferation [A34/PAF49 and A49/PAF53 form a heterodimer complex in both in vitro and in vivo settings. It has also been hypothesized that these proteins function as a heterodimer. In Fromageot’s 1975 paper, they demonstrated that upon purification of RNA polymerase I, there were two forms: Pol IA and Pol IB . The differation ,38. HoweUntil recently, it has been difficult to perform similar studies on the mammalian RNA polymerase I system, due to an inability to knock out PAF53 and/or PAF49. A CRISPR study performed by our lab discovered these difficulties . When PAS. cerevisiae report that the A49/34 heterodimer is not essential for cell proliferation or cell viability [S. pombe (fission yeast), is also required for wild-type levels of cell growth [A long-standing question in the field of RNA polymerase I transcription is the necessity of the heterodimer. That is, are A34/PAF49 and/or A49/PAF53 essential for rDNA transcription, cell proliferation, or cell viability? Many studies performed with iability ,45,46. Tl growth . When Nal growth . TherefoMuramatsu’s lab was the first to report that PAF53 and PAF49 are required for specific transcription ,20. The To determine if PAF53 or PAF49 are essential for rDNA transcription, our lab utilized an auxin-inducible degron system, in which the endogenous PAF could be targeted for rapid degradation in <1 h ,48,49. WThe overall conclusion that both PAF49 and PAF53 are essential for rDNA transcription, and that cell proliferation shifts the paradigm that results from experiments investigating RNA polymerase I transcription in yeast could be used to understand Pol I transcription in mammals . Our demonstration that PAF49 is essential for growth and transcription while its ortholog, yeast A34, is nonessential, highlights the importance of further studying Pol I transcription in mammals.As mentioned above, both the yeast and mammalian heterodimers play an essential role in facilitating rRNA synthesis. Specifically, in yeast A49 is required for specific transcription, while A34 seems to be dispensable. Alternatively, both PAF53 and PAF49 are essential to promote rDNA transcription in mammals. A major question in the field of Pol I transcription is how do the PAFs help facilitate specific rDNA transcription?Currently, the majority of studies focusing on the function of the PAFs have been performed in yeast. These have focused on the main steps in transcription: initiation, elongation, and termination.I48, a subunit of SL-1 [Just like in the Pol II and Pol III systems, Pol I relies on general transcription factors, which help it bind to the promoter and form a transcription-competent initiation complex. In yeast, those GTFs include a core factor (CF) and upstream activation factor (UAF). In mammals, the GTFs are selectivity factor-1 (SL-1) and upstream binding factor (UBF). In both the yeast and mammalian systems, the TATA-binding protein (TBP) in CF and SL-1 are essential for recruiting Pol I to the rDNA promoter. Before Pol I binds to the promoter, it must first form a complex with Rrn3, a polymerase-associated factor that is released once transcription has been initiated . It has  of SL-1 ,20. Mult of SL-1 ,53,54. P of SL-1 . Further of SL-1 . Cramer’ of SL-1 . Upon fu of SL-1 . Our curS. cerevisae have demonstrated that the heterodimer act as built-in Pol I elongation factors. Cramer’s lab reported that A49/34 is required for normal elongation activity of Pol I in vitro [RNA polymerase I processivity during elongation plays a key role in successfully synthesizing a complete rRNA gene. Similarly to Pol II and Pol III, Pol I recruits elongation factors that help it remain on the DNA until a termination signal is reached . Studiesin vitro ,56. ΔA34In both yeast and mammals, there are termination factors that bind to the 3’ end of the rDNA gene ,58. DuriIt has been reported that there is post-transcriptional regulation of the mammalian PAFs at several levels. In their initial reports of PAF53 and PAF49, Muramatsu’s laboratory reported that they could identify two populations of Pol I, one that contained the PAF53/49 heterodimer and one that did not ,20. HannThe second question is significant, because studies in yeast suggest that while the heterodimer may play significant roles in rDNA transcription, it is not essential ,46,50,63Penrod et al. found that ectopic co-expression of PAF53 and PAF49 in HEK293 caused an increased accumulation of both proteins when compared to ectopic expression of each protein individually [While there are similarities between the yeast and mammalian Pol I systems, it is important that we understand the differences between yeast and mammalian Pol I transcription. Understanding these differences will aid in future studies targeting Pol I transcription in different disease models. In this review, we highlighted some key differences between the yeast and mammalian PAF heterodimers. Importantly, we demonstrated that while A34 is completely dispensable in yeast Pol I transcription, PAF49, its ortholog, is required for mammalian Pol I transcription. We also highlighted the differences between yeast A49 and mammalian PAF53. Specifically, the tWH of A49 is sufficient to rescue rDNA transcription in yeast, but the tWH of PAF53 does not rescue transcription in mammals. This infers that recruitment of the heterodimer may differ between yeast and mammals. Lastly, we have observed that levels of PAF49 and PAF53 in the cell are co-regulated, while there is no evidence that demonstrates the same regulation between A34 and A49.


Recent advances in RNA sequencing technologies helped to uncover the existence of tens of thousands of long non-coding RNAs (lncRNAs) that arise from the dark matter of the genome. These lncRNAs were originally thought to be transcriptional noise but an increasing number of studies demonstrate that these transcripts can modulate protein-coding gene expression by a wide variety of transcriptional and post-transcriptional mechanisms. The spatiotemporal regulation of lncRNA expression is particularly evident in the central nervous system, suggesting that they may directly contribute to specific brain processes, including neurogenesis and cellular homeostasis. Not surprisingly, lncRNAs are therefore gaining attention as putative novel therapeutic targets for disorders of the brain. In this review, we summarize the recent insights into the functions of lncRNAs in the brain, their role in neuronal maintenance, and their potential contribution to disease. We conclude this review by postulating how these RNA molecules can be targeted for the treatment of yet incurable neurological disorders. The sequencing of the ∼3.1 billion base pairs of the human genome marked the completion of the Human Genome Project in April 2003 after a little over 10 years of research. One of the main findings of this large scale project was that only a fraction of the genome encoded in total ∼22,300 protein-coding genes, whereas the remaining fraction was considered “junk DNA” . Since tRemarkably, the majority of our DNA generates a large number of lncRNAs . By defiTUG1 and MALAT1)  around their transcription start sites . Consist MALAT1) . LncRNAs MALAT1) . The higXist (X-inactive-specific transcript) was one of the first lncRNAs identified when it was isolated in the early 1990s from a female placental complementary DNA library screening  correlates with the organisms’ complexity and genome size  has been identified as a striatal-specific lncRNA and proposed to play a neuroprotective role against mutant Huntingtin (HTT), a protein implicated in Huntington’s Disease function. Genome-wide association studies and comparative transcriptomic analyses link lncRNA deregulation and dysfunction to multiple human diseases, including a wide range of neurodevelopmental, neuropsychiatric, and neurodegenerative conditions . The ideHowever, the association of altered expression of specific lncRNAs in brain disorders is not hard proof of biological relevance, and functional studies investigating the role of these lncRNAs are still needed. Since lncRNA function is intrinsically influenced by their subcellular localization , we willcis (close to their transcription sites) or in trans (regulation is exerted at distant loci). Alternatively, they can act as molecular decoys, sequestering specific chromatin modulators from the promoters of target genes. Finally, they can directly interact with DNA and generate DNA-RNA hybrid structures, such as R-loops, which ultimately influence chromatin accessibility and remodeling   can dissociate PRC2 from the SMN promoter and increase SMN expression in both in vitro and in vivo SMA models  could represent a valuable therapeutic approach for severe SMA cases characterized by very low SMN levels (Two independent studies identified hy (SMA) . SMA is n levels . KnockdoA models . CombiniN levels .HTT gene. The repeat expansion results in the production of a mutant neurotoxic form of the HTT protein that triggers a progressive degeneration of cortical and striatal neurons. Although the mechanisms behind neuronal loss in HD are not yet completely understood, aberrant chromatin remodeling and transcriptional dysregulation seem to represent key features in the pathogenesis  is a polyglutamine (PolyQ)-related disorder caused by an expanded CAG repeat (>36) in the first exon of the ogenesis . For insogenesis . The HARpatients . The exppatients . These iand MEG3 , and TUGG3 , a severe neurodevelopmental disorder caused by a maternal deficiency of the imprinted gene UBE3A , which has been implicated in Alzheimer’s Disease (AD) pathology. AD is the main cause of dementia worldwide and two hallmarks of this neurodegenerative disorder are the accumulation of extracellular amyloid-β (Aβ)-containing plaques and intracellular neurofibrillary tangles composed of hyperphosphorylated and aggregated Tau protein within the patients’ brains  including transcription and splicing factors. For example, ’ brains . LRP1 pr’ brains . Modulatobserved . HoweverFMR1 gene  or the related disease Fragile X-associated Tremor/Ataxia Syndrome (FXTAS) is caused by the presence of a triple CGG repeat motif in the 5′ untranslated region (5′-UTR) of the MR1 gene . Unaffecogenesis . Intrigund FXTAS . One of carriers . Previoupoptosis , was obsdiseases .C9orf72 gene represents the most common genetic cause of Frontotemporal Dementia (FTD) and Amyotrophic Lateral Sclerosis (ALS), two devastating neurodegenerative disorders commonly designated as c9FTD/ALS (C9orf72 RNA are widely distributed across the CNS of these patients (The presence of hexanucleotide GGGGCC (G4C2) repeat expansions in the 9FTD/ALS . While tpatients . A potenpatients . Ultimatpatients .DISC1  aggregates within Lewy bodies or Lewy neurites and degeneration of dopaminergic neurons, particularly in the substantia nigra. While most PD cases are sporadic, familial forms of the disease can occur and result from mutations in a group of genes that include LRRK2, PARK2, PARK7, PINK1 or the SNCA gene itself (PINK1-AS stabilizes the expression of a PINK1 splice variant (svPINK1) in vivo through the formation of an RNA duplex  is a neurodegenerative disorder generally characterized by the accumulation of α-synuclein -dependent mechanism  sequences – referred to as MIR-NATs – associated with protein-coding genes tied to neurodegenerative disorders has revealed a new class of lncRNAs that mediate gene regulation at the translational level through a MIR-dependent mechanism . One of try site .NEAT1 and MALAT1  are two human lncRNAs conserved within the mammalian lineage which regulate key nuclear functions  splicing factors, while NEAT1 is a structural component of nuclear bodies called paraspeckles, also composed by multiple proteins with reported roles in transcription and RNA processing  patients , FUS and C9orf72 genes are linked to the onset of fALS  is still elusive, mutations in  of fALS . Both TDcontrols . The forcontrols .NEAT1 in human HD postmortem brain patients and in a mouse model of HD  delivery system designed to activate the expression of paternal UBE3A for at least 17 months ameliorated disease phenotype in AS mice and provided proof of concept that this approach is therapeutically relevant  and CRISPR-activation (CRISPRa), has brought the exciting possibility of transcriptionally silence or activate lncRNA expressing loci, and clearly demonstrate that these tools will be crucial for a better understanding of lncRNA biology . One wayrelevant . Onasemndiseases . While rdiseases . For insdiseases . Thus, fThe possibility of modulating RNA expression with oligonucleotides provides a relatively straightforward strategy to impact virtually any RNA of interest and to target previously “undruggable” portions of our genome . At the Remarkably, both ASO- and siRNA-based strategies have been proven successful in reducing the expression of several lncRNAs with potential roles in neurological disorders . HoweverSMN-AS1, BDNF-AS, SHANK2-AS, and UBE3A-ATS). Since there is still a considerable lack of therapeutic approaches to upregulate gene expression, inhibition of these transcripts with siRNAs or ASOs  might be of particular interest to increase the expression of genes found downregulated in CNS disorders  rather than modulating its expression levels may represent an alternative therapeutic approach. An increasing body of evidence suggests that the function of many lncRNAs is largely mediated by their interaction with RBPs or protein complexes. Thus, a promising therapeutic option for targeting lncRNAs is the use of steric hindering antisense oligonucleotides or small molecules that affect these interactions by either (1) blocking the RNA-binding domain of the protein, or (2) directly binding to and disrupting secondary and tertiary structures in the lncRNA molecule  Figure .The variety of lncRNA binding partners and their unique structural features offer exceptional opportunities to target these RNAs using small molecules. Importantly, the development of new RNA sequencing techniques and structure determination assays such as SHAPE , SHAPE-MMALAT1 has been proposed to contain a bipartite triple helix at the 3′ end and single-point mutations that destabilize this structure have been shown to reduce MALAT1 levels in cells, implying a crucial role for this structure in enabling MALAT1 expression   . Recentlt of SMA , and Braa for HD . Both Ridulators . Other sd for PD , Mitoxanopathies , and at ectively .Supported by their characteristics including high cell- and specificity and dynamic regulation of specific cellular pathways at the transcriptional and post-transcriptional level, lncRNA-based therapies could bring important clinical advantages. These include their superior potential as new targets, reduced toxic effects derived from off-target mechanisms, and the possibility to have a biologically meaningful effect with lower compound doses due to their lack of translation, fast turnover, and general low expression levels . The facHowever, there are still some challenges to overcome in the field of lncRNAs research. First and foremost, more basic research is needed to address the exact roles of lncRNAs in the brain and identify their related disease-relevant signaling pathways. Second, and related to the first point, further investigation is needed to develop therapeutic strategies that efficiently alter lncRNA transcript levels or repress their function(s) using ASOs and siRNAs provided that the delivery of these molecules to the CNS is tackled. Though impressive progress occurred in the past years regarding the use of oligonucleotide-based therapies, a deeper appreciation of lncRNA structural features and their interactions with DNA, RNA and proteins will open the exciting possibility of targeting these RNAs using small molecules with unprecedented specificity as agonists or antagonists. On the long term, development of orally available, brain-penetrant lncRNA-targeting small molecules could represent a new therapeutic modality for genomic imprinting diseases, neurodevelopmental and neurodegenerative diseases. As new RNA-targeted therapeutic strategies continue to emerge, we believe that unraveling the functional roles of lncRNAs will pave the way to transform lncRNAs originally perceived as “junk” DNA to a therapeutic treasure for patients affected by CNS diseases.RP, AS, and Cd’Y were responsible for the conception of the article. RP did the scientific literature review, created the figures, and wrote the first draft of the review. Cd’Y contributed to the scientific literature review. AS and Cd’Y critically revised the entire review. All authors approved the final version.Cd’Y was employed by company Janssen Pharmaceutica N.V. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.