Nuclear pore complexes (NPCs) are canonically known to regulate nucleocytoplasmic transport. However, research efforts over the last decade have demonstrated that NPCs and their constituent nucleoporins (Nups) also interact with the genome and perform important roles in regulation of gene expression. It has become increasingly clear that many Nups execute these roles specifically through regulation of chromatin state, whether through interactions with histone modifiers and downstream changes in post-translational histone modifications, or through relationships with chromatin-remodeling proteins that can result in physical changes in nucleosome occupancy and chromatin compaction. This review focuses on these findings, highlighting the functional connection between NPCs/Nups and regulation of chromatin structure, and how this connection can manifest in regulation of transcription. Nuclear pore complexes (NPCs), composed of ~30 distinct Nucleoporins (Nups), are the main mode of nucleocytoplasmic transport in eukaryotic cells. Since early characterization of NPCs via electron microscopy (EM) in the late 1950s, “intranuclear channels” could be seen extending from nuclear pores into the nucleoplasm , facilitWith respect to regulation of chromatin state by NPCs/Nups, perhaps the most is known about the interactions of NPCs and their constituent Nups with various histone-modifying enzymes. Histone modifying enzymes are responsible for depositing post-translational modifications on core histone tails. These modifications can either directly regulate chromatin condensation state, as in the case of acetylation, or provide a signal to recruit other proteins that regulate chromatin compaction or downstream transcriptional processes . While tTranscriptional memory is the phenomenon of enhanced rounds of subsequent transcriptional activation after an initial stimulus-induced transcriptional event, a process previously reviewed extensively ,19. SomeDrosophila, Nup98 was found to similarly interact with a homologous H3K4 HMT, Trithorax (Trx), both physically and genetically, and to regulate expression of Trx target genes [The relationship between Nup98 and H3K4 HMTs is further supported by data in human hematopoietic progenitor cells, where Nup98 interacts with a component of the homologous HMT Set1A/COMPASS complex and is required for the targeting of the complex to promoters . Genome-et genes . The evoet genes , which het genes .Drosophila revealed binding of Nup153 predominantly at active loci, marked by RNA polymerase II (pol II) [Another NPC component Nup153 has similarly been shown to interact with histone modifying enzymes associated with the active chromatin state. Early ChIP-chip experiments in (pol II) . More re(pol II) . The chr(pol II) , which i(pol II) . General(pol II) , and is (pol II) . Additio(pol II) . Togethe(pol II) . Importa(pol II)  (discuss(pol II) . As discIn an attempt to characterize the chromatin landscape at the nuclear pore, one group has recently utilized high resolution structured illumination microscopy (SIM) and sophisticated data analysis software. Importantly, they were able to confirm that areas of open chromatin, or heterochromatin exclusion zones, at nuclear pores, observed in previous EM images, can be reproduced by DAPI stain and high resolution fluorescence imaging in HeLa cells . In furtOne clear theme within the field of nuclear pore proteins, whether in their roles in transport or their roles in regulating chromatin state and gene expression, is that the ~30 Nups comprising the nuclear pore are individual proteins that can have highly unique functions. Although many NPC constituents seem to be involved in regulating transcriptional activation, there are examples where Nups are involved in facilitating formation of repressed chromatin and reducing gene expression levels. One potential explanation for this could be that the Nups bound to condensed chromatin may be promoting the divide or the transition between euchromatin and the adjacent lamina-associated heterochromatin. Another could be that not all nuclear pores in a nucleus perform the same functions, and that a sub-population of nuclear pores may be involved in gene repressive functions. While the reasoning behind this dichotomy is still a mystery, it is becoming increasingly clear that specific Nups have a functional relationship with silenced genes .One of the first studies on this relationship showed an interaction between Nup155 and Histone Deacetylase 4 (HDAC4) in human cardiomyocytes . HDAC4 iHoxA gene, where it was found to promote the Polycomb-associated mark H3K27me3 [Interestingly, not only can different Nups have opposing roles in regulation of chromatin state, but it appears that even the same Nup can have opposing functions depending on cell type or developmental context. Nup153, which as we previous discussed, associates with the CBP/p300 complex to promote gene expression in cardiac tissue, has also been shown to carry out a gene repressive role in mouse Embryonic Stem Cells (mESCs) . In thisH3K27me3 . The mecChromatin remodeling proteins regulate chromatin structure in more direct ways than histone modifiers. While histone modifying enzymes deposit marks on histone tails that can regulate nucleosomal interactions or provide binding platforms for downstream proteins, chromatin remodelers possess an intrinsic enzymatic activity to alter physical interactions between histones and DNA, changing the occupancy or the spacing of nucleosomes. This activity can function through eviction of one or more of the core histones within the histone octamer, a sliding of the histone octamer down the DNA sequence, or a complete removal of the entire octamer to generate what is referred to as a Nucleosome Free Region (NFR) . These rAs described in the previous section, mammalian Nup155 interacts with repressive histone modifiers to facilitate chromatin compaction and target gene repression. Interestingly, its yeast homolog, Nup170p, is also involved in facilitating increased chromatin condensation and repression, but instead appears to employ chromatin remodeling proteins, such as RSC, a chromatin remodeling complex involved among other functions, in telomere maintenance . A genetDrosophila [C. elegans homolog of Elys, Mel-28, has been seen to interact with an accessory subunit of the SWI/SNF chromatin remodeling complex, which is homologous to the Drosophila PBAP complex. Specifically, Mel-28 was found to interact with the component swsn-2.2 [pyp-1, the homolog of another Drosophila chromatin remodeling protein NURF-38, resulting in larval sterility [Multiple studies have now demonstrated the role for an NPC component Elys and its homologs in seeding post-mitotic nuclear pore formation by recruitment of the core Nup107 sub-complex to chromatin ,50. Consosophila . This fuswsn-2.2 , which iswsn-2.2 . A genetterility . NURF-38terility ,58. In hterility , a membeterility . This evC. elegans found a defect in global genome decondensation in the background of mutant replication machinery, but this phenotype was rescued in an Elys mutant, suggesting that Elys may be involved in the crosstalk between replication and chromatin compaction although the precise molecular role of Elys in this process remains unclear [Xenopus sperm nucleus. Here they found that treatment with RNases depleted Elys off of chromatin, and this resulted again in defects in chromatin decondensation [Drosophila cells [Consistent with the reported interactions between Elys and chromatin remodeling proteins, several recent studies revealed a functional role of Elys in regulating global chromatin compaction. One study looking at DNA replication in  unclear . In a suensation . Specifila cells . This dala cells .Above, we have discussed the current knowledge on the interactions of Nups with specific histone-modifying and chromatin remodeling enzymes, as well as cases where Nups have been demonstrated to functionally contribute to deposition of specific histone modifications or to chromatin compaction. In the section below, we examine instances of known functions of Nups in regulation of large-scale chromatin and nuclear organization. Mechanistically, these roles may be similarly based on the known interactions of Nups with chromatin regulatory machinery, or they may involve a unique set of molecular mechanisms. Either way, in the cases presented below, these mechanisms are manifested in chromosome-wide epigenetic processes, in structural elements of the nucleus, and in genome integrity.Drosophila the Dosage Compensation Complex (DCC) binds along the length of the X-chromosome, as is a common theme for DC machinery in all species and is responsible for ~2-fold upregulation of X-linked genes in male flies. The DCC contains a HAT called Males absent On the First (MOF) responsible for depositing the activating histone mark H4K16acetyl, which coats the male X-chromosome and is necessary for transcriptional upregulation [Drosophila embryos, Nups, Mtor, and Nup153 were found to interact with MOF and other DCC components biochemically, as both Nups were recovered as abundant hits in the proteomic characterization of the interacting partners of MOF [Drosophila genome in large domains termed Nucleoporin Associated Regions (NARs), enriched especially at transcriptionally active regions [C. elegans as well, even though DC is accomplished by condensation and down-regulation of the X, rather than activation and transcriptional upregulation [Drosophila dosage compensation has been questioned. A more recent study did not observe an effect of Nup153 or Mtor on X-chromosome expression or recruitment of the MOF complex in Drosophila larval tissues or S2 cells, and the authors proposed a difference in knock-down methods as a potential culprit [Drosophila and humans [C. elegans [Drosophila male X-chromosome [Over recent years, several papers have described the role of Nups in dosage compensation (DC). The unequal number of X chromosomes between male and female organisms requires a process, via which gene expression from the X chromosome is equalized between the sexes, and which different species accomplish utilizing different mechanisms. This level of transcriptional regulation is no small feat, as it requires changing the transcriptional output of an entire chromosome. In gulation . In males of MOF . Upon Nus of MOF . Interes regions . Fascina regions . In anotgulation . One com culprit . Howeverd humans , the int elegans , and theromosome , all supDrosophila spermatocyte nuclei in what the authors termed Mad1-containing IntraNuclear Territories (MINTs) [Drosophila and human cells [Another recent study provided an example of the function of nucleoporin Mtor in large-scale genome organization. Here they discovered that Mad1, a protein normally part of the mitotic spindle assembly checkpoint, was found in post-mitotic and interphase  (MINTs) . Of partan cells ,70. Furtan cells . This fiThe described relationship between Mtor and MINTs, and Mtor’s potential role in DC, support the idea that Mtor plays an evolutionarily conserved role in promoting an active chromatin environment. In further support of this idea, an intriguing recent work has implicated Mtor in the distribution of open chromatin along the nuclear periphery. As mentioned at the beginning of this review, the peripheral chromatin localized to NPCs appears open and euchromatic in nature, relative to the adjacent condensed lamina-associated heterochromatin. One group set out to understand what regulates these heterochromatin exclusion zones (HEZs), and found that the mammalian homolog of Mtor, TPR, was required for their formation . In cellConsistent with the finding that Mtor is important to maintain open chromatin at NPCs, there are multiple studies linking both Mtor and Nup153 with viral genome insertion. One study, using Fluorescent In-Situ Hybridization (FISH) and molecular assays, showed that genomic integration sites for the HIV-1 viral DNA occur predominantly at active chromatin associated with NPCs, as opposed to peripheral lamin-associated heterochromatin, and that Nup153 was required for this localization . An addiMultiple studies have recently demonstrated a role for NPCs and Nups in silencing of transposable elements (TEs). Piwi, a critical component of the piRNA pathway responsible for silencing TEs, uses complementary piRNAs to seek and target TEs for degradation. Interestingly, genomic targets of Piwi were found to substantially overlap with genomic binding maps of NPCs . A furthMany of the interactions between Nups and chromatin factors, described above, have been shown to fulfill functions in regulation of downstream gene expression. Regulation of gene expression overall has become a well-established function of NPCs and individual Nups. We discuss some of the most recent findings on this topic below, where, in the examples to follow, functional roles of Nups have been linked more directly to transcriptional activation, as opposed to regulation of chromatin structure. In some cases, certain Nups have been shown to play a role in recruitment of specific transcription factors (TFs) or influencing transcription itself, but since regulation of transcription and chromatin structure are intimately intertwined, Nups may affect the transcriptional process via both interactions with TFs and with chromatin machinery. We hope that the above summary of the chromatin-related roles of NPC components will help draw attention to the clear importance of Nups in regulation of chromatin itself, and that these findings may be kept in mind while examining future research as the field of Nups in regulation of gene expression continues to be explored. Early work in this field has established that Nups bind chromatin in multiple cell types, that many of the targets tend to be cell cycle and developmental genes, and that this binding can have an effect on gene expression ,80,81,82Hox genes, which are known to regulate organismal body morphogenesis and cell identity across cell types and organisms [Drosophila to bind and regulate expression of Hox genes [Drosophila MOF-containing NSL complex responsible for depositing active histone mark H4K16acetyl on autosomes. Nup98 was proposed to work in conjunction with the canonical Hox regulator HMT Trx, as reduction of Nup98 was sufficient to reduce expression of Trx targets and Nup98 was found to physically interact with the H3K4 HMT Trx, as discussed above. Interestingly, mammalian Nup98 was similarly found to physically interact with the homologous NSL and MLL complexes in leukemic models [Hox genes, supporting the notion that both MLL and Nup98 normally regulate expression of Hox genes. Overall these studies highlight the role of Nup98 in regulating expression of key developmental Hox genes in both endogenous and disease contexts. Though the mechanism of this regulation is still being explored, Nup98 in other contexts has been shown to associate with architectural proteins and regulate enhancer-promoter looping, as part of transcriptional memory [Hox genes and other targets. In this manner, Nup98 may primarily function in stabilizing a particular transcriptional complex, an idea discussed recently [The theme of Nups binding and regulating cell identity genes has proven robust between cell types and among species. This is particularly intriguing considering the existence of many tissue-specific defects and diseases resulting from Nup mutations and dysfunctions ,84. Perhrganisms . This biox genes . This tac models . MLL is l memory . It is precently .Drosophila enhancers, described above, Nup153 and Nup93 have recently been found to bind super-enhancers in human cells, interestingly predominantly at the nuclear periphery [Multiple reports have recently demonstrated the binding of NPC components to tissue-specific enhancers (reviewed in ). In adderiphery , even theriphery . Super-eeriphery . Strikineriphery . Of speceriphery ,89. WhilOne mechanism behind specificity of function for individual Nups at different genetic targets may lie in differential protein binding partners, especially cell-type/context dependent transcription factors. Such binding partners have been identified for Nup153 in regulation of differentiation in neural progenitor cells (NeuPCs) . SpecifiNups regulating binding or activity of cell-type transcription factors to control transcriptional programs is becoming a common theme in the field. It has also been observed for Nup210, which was shown to recruit muscle TF Mef2C, and its genomic targets, to NPCs in myofiber nuclei to promote expression of genes regulating muscle differentiation . SimilarOver the years, the field has come to learn the pleiotropic nature of NPCs and their constituent Nups, as multiple mechanisms, by which they regulate genomic integrity, mitosis, nuclear organization, transcription, chromatin state and, of course, transport, were discovered. As we have discussed, these proteins have proven to be critical for many roles promoting proper nuclear organization and function, especially with regard to chromatin structure and gene expression. Recently, we have grown to appreciate their importance in cell-type specific gene expression, with certain Nups regulating recruitment of specific transcription factors to their target genes to facilitate developmental transcriptional programs ,90,92. WThere are many remaining questions in regard to the precise functional role of NPC components in regulation of chromatin and transcription. As presented above, different Nups appear to be involved in unique molecular mechanisms, and it will be critical to characterize tissue-specific chromatin binding patterns, interacting partners, and organismal phenotypes of individual Nups in order to fully define the NPC–genome relationship. The apparent ability of certain Nups to promote both gene activation and gene repression, depending on the specific genomic and developmental context, is a particularly interesting question for future study. Comprehending this specificity and the Nup–chromatin relationship in general hinges upon determining the molecular basis of Nup recruitment to chromatin, which remains poorly understood. In the majority of cases, it is unclear how Nups, which lack any obvious DNA or chromatin binding domains, are recruited to their target loci, and how their recruitment is influenced by cell type context or chromatin state. It is similarly unclear whether there is a functional difference between Nup–chromatin contacts of different sub-nuclear locations, at peripheral NPCs versus in the nuclear interior, and whether dynamic Nups can re-localize the chromatin template on and off the NPC. It has been suggested that certain loci contact the nuclear pore during activation and re-localize back to the nuclear interior, once fully activated . However


Arabidopsis thaliana and define organ-specific regulatory sites and binding motifs of TFs at these sites.There is a growing interest in the role of chromatin in acquiring and maintaining cell identity. Despite the ever-growing availability of genome-wide gene expression data, understanding how transcription programs are established and regulated to define cell identity remains a puzzle. An important mechanism of gene regulation is the binding of transcription factors (TFs) to specific DNA sequence motifs across the genome. However, these sequences are hindered by the packaging of DNA to chromatin. Thus, the accessibility of these loci for TF binding is highly regulated and determines where and when TFs bind. We present a workflow for measuring chromatin accessibility in Arabidopsis based on their accessibility to nuclease digestion. By applying this pipeline in Arabidopsis roots, we revealed 41,419 accessible sites, of which approximately half are found in gene promoters and contain the H3K4me3 active histone mark. The root-unique accessible sites from this group are enriched for root processes. Interestingly, most of the root-unique accessible sites are found in nongenic regions but are correlated with root-specific expression of distant genes. Importantly, these gene-distant sites are enriched for binding motifs of TFs important for root development as well as motifs for TFs that may play a role as novel transcriptional regulators in roots, suggesting that these accessible loci are functional novel gene-distant regulatory elements.We coupled the recently described isolation of nuclei tagged in specific cell types (INTACT) and assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) as a genome-wide strategy to uncover accessible regulatory sites in By coupling INTACT with ATAC-seq methods, we present a feasible pipeline to profile accessible chromatin in plants. We also introduce a rapid measure of the experiment quality. We find that chromatin accessibility at promoter regions is strongly associated with transcription and active histone marks. However, root-specific chromatin accessibility is primarily found at intergenic regions, suggesting their predominance in defining organ identity possibly via long-range chromatin interactions. This workflow can be rapidly applied to study the regulatory landscape in other cell types, plant species and conditions.The online version of this article (10.1186/s13007-018-0381-9) contains supplementary material, which is available to authorized users. As sessile organisms, plants can accommodate to changes in the environment by modulating their cellular transcription programs to allow developmental plasticity , which rArabidopsis [The genome regulatory potential relies not only on DNA sequence but also on epigenetic features that dictate the time, place and level of gene transcription. The chromatin structure is highly regulated and dynamic as histones can be evicted from chromatin to expose regulatory sites and allow binding of transcription factors (TFs) and other regulatory proteins to DNA  or be rebidopsis ), ChIP-bcis-regulatory elements (CREs) is a powerful approach for predicting their associated TFs and depicting the gene regulatory network underlying a transcriptome [Arabidopsis [TFs can bind specific DNA sequence motifs. Thus, uncovering these motifs in active criptome , 5. The Arabidopsis [Arabidopsis thaliana allows depicting of organ or cell type-specific chromatin accessibility landscape [Almost all active CREs, including promoters, enhancers, suppressors, and insulators, are located at chromatin accessible sites, which are hypersensitive to cleavage by endonucleases, such as DNaseI or transposase . In manybidopsis . The INTbidopsis , 24  and 6 ml HCl . Seeds were sowed on square Petri dishes coated with 1/8 strength MS (Murashige and Skoog) media pH 5.7 [a pH 5.7  and incuArabidopsis 3-methylcrotonal CoA carboxylase [Arabidopsis thaliana (Col-0) was stably transformed with this construct by floral dip [3 homozygous, single copy, independent transformants were acquired.To generate plants expressing the INTACT , 24 systboxylase . This syoral dip . TransfoFor purifying 100,000–150,000 nuclei, 1 g of fresh tissue was harvested and ground in liquid nitrogen using a mortar and pestle to break the cell wall. To avoid enzymatic activity, all the following steps were performed at 4 °C. The resulting powder was transferred into 20 mL NPB ) and incubated on a rotator at 4 °C for 10 min. The sample was then transferred through a 40-µm mesh and centrifuged for 10 min at 1000 g and 4 °C. The pellet was gently resuspended in 7 mL NPBt (NPB supplemented with 0.1% Triton X-100). Nuclei were then bound to 25 µl of streptavidin-coated Dynabeads  according to the manufacturer’s protocol and washed with NPB. After washing 4–5 times with 1 mL NPBt, the nuclei were resuspended in 1 mL NPB. To count nuclei, a 20-µl suspension was loaded to a Marienfeld hemocytometer , and visualized with a Nikon Eclipse TS100 light microscope.To remove EDTA, nuclei were washed with a low volume of TDX buffer . Transposition was performed as published  with sev(average cq gDNA − average cq sample) for each primer set. To define the fold change for each library, the average of normalized amplification of all accessible (open) regions was divided by the average of normalized amplification of all inaccessible (closed) regions. qPCR thermal cycles were as follows: 3 min 95 °C; 39X .The enrichment of accessible regions relative to inaccessible regions was measured by qPCR using DNA from the final ATAC-seq libraries. qPCR was performed using the iTaq universal SYBR green supermix . The final volume of each reaction was 10 μl. Primers were designed using the NCBI primer-BLAST. The final concentration of the primers was 0.5 μM. All amplicons were 90 bp long. Each PCR plate contained genomic DNA, and normalization was performed using the following equation: (primer efficiency)The following qPCR primers were used to amplify accessible loci (5′–3′): Set 1: forward: TGGAATACACCAGAGAAAGGATAAC, reverse: GCATAAGTGATTTCATTCTGCGA. Set 2: forward: AGCCCATTCAAGGCCTCACA, reverse: GGCAATTCGAAGTTGAAGGCAT.The following qPCR primers were used to amplify inaccessible loci (5′–3′): Set 3: forward: ATCATATTCTTCACAGTTTGATCCC, reverse: ACATTTCAGGTTGGGAGACAGA. Set 4: forward: CCCAGGGGAATACGGTCAAC, reverse: AAGAGCTTACGAAACTGGAGGT.RNA was isolated from 14-day-old roots using TRIZOL (Life Technologies) reagent and cleaned with RNA Clean & Concentrator™-5 . RNA was quantified by NanoDrop2000 (Thermo Fisher). Libraries were prepared with the NEBNext RNA library prep kit (module E7530-E7490). cDNA was quantified using a Qubit HS DNA kit  and analyzed on a BioAnalyzer or TapeStation. Libraries were sequenced on an Illumina HiSeq 2500 sequencer, and 61 bp were sequenced using a single-end protocol.Arabidopsis genome using bowtie [Arabidopsis genome using TopHat2. To calculate the number of reads on each gene, HT-seq was used, and RPKM was calculated using EdgeR package in the R programming language. GO analysis was performed using the GO Ontology database (release 2017-06-29). Sequencing data of histone modifications ChIP-seq were downloaded (E-MTAB-1663). Reads were aligned to the TAIR10 Arabidopsis genome with bowtie. Only unique mapped reads were used. Peaks were called by applying MACS2 with the following parameters: -g 135000000–nomodel–extsize 143. Analyzed PLT2 ChIP-seq data (GSE79755) were downloaded from [p value was obtained from the normal standard distribution. To calculate the expression of genes near intergenic accessible sites, the nearest gene was identified using annotatePeaks in the HOMER [2 value was calculated for each gene in the group of genes near intergenic root unique accessible sites and in the group of genes near intergenic root nonunique accessible sites. Finally, Student’s t-test was performed.Sequencing reads were aligned to the TAIR10 g bowtie  with theg bowtie  rmdup opg bowtie  with theg bowtie . Leaf DHg bowtie . Leaf RNhe HOMER  package,Arabidopsis thaliana and uncovering active regulatory elements that are key for regulating tissue-specific transcriptional programs. Although chromatin accessibility can be profiled by other methodologies, such as DNase-seq, these techniques are not widely used due to technical limitations. The integrity of isolated nuclei is critical for profiling chromatin accessibility given that their disruption by mechanical shearing reduces the signal-to-noise ratio [In this study, we combined novel methodologies for rapid and efficient measuring global chromatin accessibility in se ratio . Using tse ratio , 22. NonPlant cells have a vacuole, which contains various hydrolytic enzymes, including DNase. Unlike lysosomes in animal cells, which remain intact and are discarded during nucleus isolation, in plants, the vacuole membrane is disrupted and its contents are released, leading to undesirable DNA cleavage. Affinity purification of nuclei by INTACT allows the cellular extract to be rapidly and efficiently discarded. Moreover, to minimize nonspecific DNA degradation due to the nuclease-promoting conditions, we also reduced the tagmentation reaction time see “” sectionPreferential cleavage of accessible sites relative to inaccessible chromatin relies on the ratio between transposase enzyme and nuclei. Excess enzyme would lead to excessively frequent cleavage; thus, enrichment for DNA from accessible sites would be lost. On the other hand, enzyme insufficiency reduces the detection sensitivity . Hence, Arabidopsis, and within this nuclei range.As shown in Fig. Arabidopsis organs in which the chromatin accessibility profile is unknown, we designed a qPCR-based approach to define ATAC-seq library quality [Arabidopsis cell types and organs [Despite its relative simplicity, calibrating and performing ATAC-seq remain challenging. Therefore, we developed a quality control step that enables us to assess the enrichment of accessible chromatin relative to the inaccessible genomic background in the ATAC-seq DNA sample. Its application prior to next-generation sequencing (NGS) saves time and money. To develop such a control that could also be applied in  quality  by assesd organs , 10, 38 d organs  were ampArabidopsis roots, sequenced reads were mapped to the Arabidopsis genome (TAIR10), revealing that it contains only 2.15–1.43% nonnuclear DNA contamination   Fig. . This hiSS) Fig. . This co2FC > 1, p-value < 0.05, RPKM > 1) compared with 5.76% of genes that are significantly upregulated in leaves from this group. We performed GO enrichment analysis on these 476 highly expressed genes. As expected, these genes were enriched with terms associated with root functions, such as response to salt stress  and response to osmotic stress   accessibility profile and retrieved 989 genes with root-unique accessible site at their promoter region (− 1000 bp to + 400 bp). Approximately half (48.13%) of these genes are significantly upregulated in roots . Notably, this divergence was fivefold greater in the root-unique compared with the leaf-unique accessible sites , which is also expressed uniquely in roots (tenfold increase in roots relative to leaves). MYB61 regulates root growth and architecture by controlling multiple aspects of plant resource allocation , 45. TheArabidopsis genome. To test the linkage of intergenic loci to genes we hypothesized that they may represent enhancers of distant genes, we made the naïve assumption that each accessible site regulates the expression of the nearest gene. The vast majority of the genes in proximity to root-unique or nonunique accessible sites are expressed . In addition, the average expression level of genes near root unique or nonunique intergenic accessible sites  is significantly increased compared with the genome-wide average , suggesting that intergenic chromatin accessibility is linked to gene expression in roots . This proportion of intergenic loci is doubled relative to the complete dataset of accessible chromatin (23%) Fig. a, which Consistent with their expected role as putative regulatory elements, intergenic loci are not associated with H3K4me3 or H3K27me3 gene histone marks Fig. c. To furAltogether, focusing on organ-specific gene-distant sites may reveal novel transcription factors that are important for defining root function or identity. In addition, the fact that the potential binding sites of these factors are distant from genes suggests that they may reach their gene targets by chromosome looping .Arabidopsis thaliana genome reveals valuable information about active CREs and the TFs that bind them and further enables study of the relationship between CREs and gene expression.It has been long known that the genomic potential relies not only on the DNA sequence but also on epigenetic features, such as chromatin accessibility to TF binding. Therefore, the chromatin accessibility landscape of the Arabidopsis nuclei [ATAC-seq is a novel technology that can be applied using a small quantity of nuclei , therebys nuclei . Couplins nuclei , 48–50.In addition, we present a rapid qPCR assay for assessing the quality of ATAC-seq libraries prior to high-throughput sequencing. This assay conserves resources and is particularly valuable when calibrating ATAC-seq for novel organisms or cell types . NotablyHigh chromatin accessibility was observed at promoters of expressed genes, which are also decorated with the H3K4me3 histone mark but not with the H3K27me3 mark, which is similar to chromatin accessibility in rice .Identifying sequence motifs enriched in chromatin accessible loci allows identification of active transcription factors and their postulated binding sites, and focusing on organ-specific regulatory chromatin increases the discovery power of organ-specific TFs. Thus, dissecting an organ to specific cell-types is expected to increase our understanding of cell-type specific regulatory DNA elements and their associated transcription factors. This approach for identifying potentially relevant transcription factors is unbiased and global. However, this method needs to be complemented by more direct methods, such as ChIP-seq for measuring transcription factor binding, given that binding at some loci may be indirect. In addition, the motif signature is not similarly abundant for different TFs, and binding at some loci may be indirect .Arabidopsis roots and leaves. However, the proportion of accessible sites at the TSS was reduced by greater than twofold in the root-unique sites. This finding may reflect the fact that promoter proximal accessible sites are correlated with transcriptional activity and that the majority of expressed genes (~ 90%) are shared between the two organs. The high organ-specific expression of transcription factors [Arabidopsis thaliana supports the hypothesis that these regulatory sites communicate with their gene targets by chromosome looping, a concept that is emerging in plant research [Approximately one-fourth of the accessible sites are located within 400 bp upstream of a TSS, where the basal transcription machinery binds. Other accessible sites are distributed downstream and upstream to the TSS within gene bodies and at intergenic regions. The proportional distribution of accessible sites relative to the TSS is similar in  factors  may suggresearch , 55.Arabidopsis by combining INTACT with ATAC-seq. This methodology can be rapidly applied to multiple cell types, plant species and conditions. The resulting chromatin accessibility profile covers various genomic activities. TSS-proximal loci are associated with gene expression levels and histone marks of gene activity. Intergenic accessible loci are primarily enriched with TF binding and TF binding motif sequences. TSS-distant regulatory elements exhibited the highest organ specificity compared with TSS-proximal loci or gene expression. Furthermore, these organ-specific accessible loci are linked to distant genes with organ-enhanced expression, suggesting that they are functional organ-specific cis regulatory elements. Altogether, this finding suggests that organs or cell types are shaped primarily by variation in regulatory chromatin relative to variation in gene expression profiles.We present a robust pipeline to profile accessible chromatin in Additional file 1: Fig. S1. Browser view of a representative locus chosen as a positive QC. Table S1. Mapping and peak calling results for the three biological repeats shown in Fig. Table S2. GO analysis of biological processes of highly expressed genes near root-unique accessible sites. Table S2. Top 30 sequence motifs enriched in the root ATAC-seq peaks. Table S3. TF binding motifs enriched in root-unique ATAC-seq peaks.


In this study, Eckersley-Maslin et al. investigated the upstream maternal factors that initiate zygotic genome activation (ZGA) in either a Dux-dependent (a transcription factor expressed in the minor wave of ZGA) or Dux-independent manner. They performed a candidate-based overexpression screen, identifying developmental pluripotency-associated 2 (Dppa2) and Dppa4 as positive regulators of 2C-like cells and transcription of ZGA genes, and their results suggest that Dppa2/4 binding to the Dux promoter leads to Dux up-regulation and activation of the 2C-like transcriptional program, which is subsequently reinforced by Zscan4c. The molecular regulation of zygotic genome activation (ZGA) in mammals remains an exciting area of research. Primed mouse embryonic stem cells contain a rare subset of “2C-like” cells that are epigenetically and transcriptionally similar to the two-cell embryo and thus represent an in vitro approximation for studying ZGA transcription regulation. Recently, the transcription factor Dux, expressed in the minor wave of ZGA, was described to activate many downstream ZGA transcripts. However, it remains unknown what upstream maternal factors initiate ZGA in either a Dux-dependent or Dux-independent manner. Here we performed a candidate-based overexpression screen, identifying, among others, developmental pluripotency-associated 2 (Dppa2) and Dppa4 as positive regulators of 2C-like cells and transcription of ZGA genes. In the germline, promoter DNA demethylation coincides with expression of Dppa2 and Dppa4, which remain expressed until embryonic day 7.5 (E7.5), when their promoters are remethylated. Furthermore, Dppa2 and Dppa4 are also expressed during induced pluripotent stem cell (iPSC) reprogramming at the time that 2C-like transcription transiently peaks. Through a combination of overexpression, knockdown, knockout, and rescue experiments together with transcriptional analyses, we show that Dppa2 and Dppa4 directly regulate the 2C-like cell population and associated transcripts, including Dux and the Zscan4 cluster. Importantly, we teased apart the molecular hierarchy in which the 2C-like transcriptional program is initiated and stabilized. Dppa2 and Dppa4 require Dux to initiate 2C-like transcription, suggesting that they act upstream by directly regulating Dux. Supporting this, ChIP-seq (chromatin immunoprecipitation [ChIP] combined with high-throughput sequencing) analysis revealed that Dppa2 and Dppa4 bind to the Dux promoter and gene body and drive its expression. Zscan4c is also able to induce 2C-like cells in wild-type cells but, in contrast to Dux, can no longer do so in Dppa2/4 double-knockout cells, suggesting that it may act to stabilize rather than drive the transcriptional network. Our findings suggest a model in which Dppa2/4 binding to the Dux promoter leads to Dux up-regulation and activation of the 2C-like transcriptional program, which is subsequently reinforced by Zscan4c. Activation of transcription from the embryonic zygotic genome is a key concerted molecular and developmental event occurring in two waves at the one- to two-cell stage in mice and the four- to eight-cell stage in humans  and Dppa4 are small putative DNA-binding proteins expressed exclusively in preimplantation embryos, pluripotent cells, and the germline . These sIn order to identify new positive regulators of ZGA transcription, we performed a screen in ESCs, identifying 12 chromatin and epigenetic factors that increase the percentage of 2C-like cells within a population. Among these were Dppa2 and Dppa4. We investigated the regulation of these two proteins, revealing that promoter DNA demethylation during the germline cycle coincides with their expression in vivo, including in the oocyte. Knockdown of either Dppa2 or Dppa4 reduces 2C-like cells as well as expression of ZGA transcripts. Furthermore, knockout of Dppa2 and/or Dppa4 is sufficient to completely abolish this cell population. Importantly, this phenotype can be restored upon re-expression of both Dppa2 and Dppa4 but not Zscan4c, confirming that these two proteins are necessary to activate expression of ZGA transcripts. Furthermore, we show that both Dppa2 and Dppa4 bind and activate Dux. Notably, Dux is required for Dppa2 and Dppa4 to activate the 2C-like state and ZGA transcription. Therefore, Dppa2 and Dppa4 act as master activators of a ZGA transcriptional program by directly regulating the ZGA transcription factor Dux.In mice, ZGA takes place in two waves: a minor wave that occurs predominantly at the paternal pronucleus in the zygote and a more substantial major wave that takes place in the two-cell embryo. Unfortunately, these stages of development are not easily manipulated on the scale required for high-throughput screens. To circumvent this, we took advantage of a spontaneously occurring rare subpopulation of primed mouse ESCs that express transcripts usually restricted to ZGA, including the MERVL endogenous retrovirus and Zscan4 cluster . These “Supplemental Fig. 1A). Of the 22 candidates investigated, 12 promoted a 2C-like state by both flow cytometry and qRT–PCR. Following Zscan4c, Dppa4 was the strongest-scoring screen candidate, with its closely related and interacting partner, Dppa2, also among the screen hits, leading us to investigate these two genes further. Importantly, analysis of an independent microarray data set . Of the two factors that did promote expression of ZGA transcripts, Gata3 was similarly identified in our candidate-based screen, indicating that our bioinformatic preselection of candidates enriched substantially for potential ZGA regulators.We first performed an in silico screen for potential positive regulators by selecting epigenetic and chromatin regulators that are expressed in the oocyte and/or zygote . Candidadata set  in whichSupplemental Tables 1, 2). Consistently, the 12 screen hits also up-regulated genes that are similarly up-regulated following Dux overexpression . As all three of these genes are also up-regulated in 2C-like ESCs , this could suggest that positive feedback loops act to reinforce the 2C-like state. Supporting this, analysis of published ChIP-seq (chromatin immunoprecipitation [ChIP] combined with high-throughput sequencing) data .To validate the 12 screen hits, we performed RNA sequencing (RNA-seq) of the GFP-positive and GFP-negative sorted cells following transient transfection of the relevant GFP fusion construct. Transcriptome analysis confirmed an up-regulation of 2C-like transcripts  in the Gpression , Caf-1 kpression , or LINEng) data  revealedSupplemental Fig. 2E), illustrating the specificity of repeat up-regulation.One of the hallmarks of 2C-like ESCs and preimplantation embryos is the up-regulation of repetitive elements, including the MERVL endogenous retrovirus . We therSupplemental Fig. 2F). In all cases, the transcripts up-regulated by Dppa2, Dppa4, Zscan4c, or other screen hits, including Bahd1, Eya1, Hdac9, and Sp110, were similarly up-regulated in the mid to late two-cell stage during embryogenesis , confirming that these transcripts are activated during ZGA. Other screen candidates, such as Gata3, Irf1, Tox3, and Trp63, up-regulated not only 2C-like transcripts but also other non-ZGA transcriptional networks .One-hundred-ninety-five genes, including the 2C-like transcripts, were similarly up-regulated by Dppa2, Dppa4, and Zscan4c  reprogramming. Up-regulation of 2C-like transcripts at intermediate stages of iPSC reprogramming has been reported previously . ConsistDppa2/4 locus is demethylated , which coincides with their expression in the gonads . This is in contrast to 2C-like gene promoters that are more highly methylated compared with all gene promoters in sperm . During preimplantation, there is a second wave of DNA demethylation across the entire Dppa2/4 locus . To further investigate the link between promoter DNA methylation and Dppa2/4 expression, we investigated transcriptome data from embryonic day 8.5 (E8.5) embryos that lacked the de novo DNA methyltransferase Dnmt3b, which is primarily responsible for establishing DNA methylation at promoter regions  undergo a wave of DNA demethylation, which is then re-established in the mature gametes before a second wave of DNA demethylation takes place after fertilization in the preimplantation embryo . This corresponded to 94% and 85% reduction in protein levels for Dppa2 and Dppa4, respectively , potentially due to protein destabilization. Dppa2 siRNA also led to a 22% reduction in Dppa4 protein levels . To further investigate the transcriptional changes occurring after Dppa2 or Dppa4 knockdown, we performed RNA-seq. The majority of differentially expressed transcripts were down-regulated, overlapped with 2C-like transcripts . In addition to ZGA transcripts, there was milder down-regulation of a second group of genes in the knockdown samples that contained many lineage markers such as the gametogenesis genes Syce1, Sohlh2, and Mael , indicating that the same set of ZGA transcripts is being regulated by Dppa2 and/or Dppa4 irrespective of how they are defined. Importantly, transcript levels of the Dux transcription factor were barely detected following Dppa2 and Dppa4 knockdown , consistent with the knockdown experiments. The absence of Zscan4c was validated at the protein level by Western blotting , grew at a similar rate, and were able to be passaged for >20 generations (data not shown), consistent with previous reports , suggesting that the three genotypes are largely indistinguishable transcriptionally. Similar to the knockdown experiments, we also observed a second group of misregulated genes in the knockout ESCs that included many lineage-specific genes, including Mael, Syce1, and Sohlh2, consistent with previous findings . While the majority of genes, including the 2C-like genes, Mael, Syce1, and Sohlh2, showed at least a trend toward down-regulation in both siRNA knockdown and CRISPR knockout, there were other genes that were up-regulated and down-regulated specifically in the knockout cells compared with siRNA knockdown and vice versa . These genes may be sensitive to either the dosage of Dppa2/4 or the duration of Dppa2/4 depletion and thus may represent secondary adaptive effects of Dppa2/4 deletion. Despite these differences, the 2C-like genes were down-regulated by both approaches. Therefore, Dppa2 and Dppa4 are necessary for ZGA transcript expression in ESCs.The intersection of differentially expressed genes from either Dppa2findings . HoweverSupplemental Fig. 6A) up-regulated the 2C-like cell fraction by flow cytometry , suggesting that Zscan4c requires Dppa2 and Dppa4 to enhance the 2C-like cell state. Importantly, reintroduction of both Dppa2 and Dppa4 resulted in a substantial increase in the MERVL::tdTomato-positive cell fraction . While Dppa2 and/or Dppa4 were able to induce expression of the 2C-like transcripts in wild-type cells, this ability was abolished in Dux knockout cells . Furthermore, Dppa4 similarly bound to Dux in P19 embryonal carcinoma cells but not in 3T3 fibroblasts . Thus, Dppa2 and Dppa4 directly bind to Dux in PSCs, consistent with when Dux is expressed. We next investigated whether Dppa2 and Dppa4 bind to other genes that are differentially expressed in Dppa2−/− or Dppa4−/− ESCs. There was a strong enrichment for both Dppa2 and Dppa4 at the promoters of the non-2C-like genes , again confirming a separate role for Dppa2 and Dppa4 in regulating non-ZGA transcripts in ESCs. Importantly, Dppa2 and Dppa4 did not bind to the transcriptional start sites (TSSs) of other 2C-like transcripts , which are direct targets of the Dux protein itself . Indeed, flow cytometry analysis of the MERVL::tdTomato reporter revealed that Dux overexpression is able to induce the 2C-like state in both wild-type and Dppa2−/−Dppa4−/− ESCs . Single-MERVL::tdTomato and double-MERVL::tdTomato/Zscan4c::eGFP reporter cell lines were described in E14 mouse ESCs were grown under standard serum/LIF conditions . Cells were transfected with a single guide targeting Dppa2 and/or Dppa4 and FACS (fluorescence-activated cell sorting)-sorted after 24 h into single cells, and clones were screened by surveyor assay and genomic DNA PCR. Successfully targeted clones were validated by Western blotting. Dppa2 single-knockout clones (clone 5 and clone 12) used in this study were generated using a guide RNA targeting Dppa2 exon 2 (ACCTTAGACCACACACCACCAGG), Dppa4 single-knockout clones (clone 23 and clone 29) were generated with a guide RNA targeting Dppa4 exon 2 (CTGCAAAGGCTAAAGCAACGGGG), and Dppa2/Dppa4 double-knockout clone (clone 43) was generated using a guide targeting Dppa2 exon 3 (TAACTTGAGTACGGATGGCAAGG) together with the guide RNA targeting Dppa4 (as above).CRISPR knockout ESCs were performed as described previously . Guide RRNA was isolated using Qiagen RNA–DNA allprep columns or TriReagent (Sigma) and treated with DNase I (Ambion DNA-free DNA [1311027] or Thermo Fisher RNase-free [EN0525]) following the manufacturer's instructions. cDNA was generated using 0.5–1 µg of RNA , and qRT–PCR was performed using Brilliant III SYBR master mix . Relative quantification was performed using the comparative CT method with normalization to CycloB1 levels. Primer sequences are available on request. Opposite strand-specific polyA RNA libraries were made using 1 µg of DNase-treated RNA at the Sanger Institute Illumina bespoke pipeline and sequenced as single-end 50-base-pair (bp) reads using the Illumina HiSeq 2500 Rapid Run platform.Candidate 2C-like ZGA regulators were selected based on the following criteria. First, genes expressed in oocytes/zygotes (reads per kilobase per million [RPKM] > 1 in http://www.bioinformatics.babraham.ac.uk/projects/seqmonk). Strand-specific quantification was performed using mRNA probes and cumulative distributions matched across samples. Differentially expressed genes were determined using DESeq2  and intensity difference filter , with the high-confidence differentially expressed genes defined as the intersection between the two statistical tests. For Dppa2/Dppa4 single- and double-knockout transcriptome analysis, as there was only one double-knockout ESC clone, differentially expressed genes were defined independently in Dppa2-knockout and Dppa4 knockout ESCs, and the two lists were combined to get the “Dppa2−/− or Dppa4−/−” differentially expressed genes.Raw FastQ data were trimmed with Trim Galore  and mapped to the mouse GRCm38 genome assembly using Hisat2 version 2.0.5. Data were quantitated at the mRNA level using the RNA-seq quantitation pipeline in SeqMonk software  with several homologs and pseudogenes present (dux repeat (AM398147.1). Read counts were normalized to the total read count of the sample.The mouse red mice . In the  present . To miniFor alignments to repetitive regions in the genome, we constructed artificial repeat genomes. Repeat annotations were downloaded from the University of California at Santa Cruz (UCSC) browser  and filtered for long instances of MERVL, MaLR, IAP, and LINE1 elements as well as major satellites see . The lenWestern blotting was performed using 50 µg of protein extracted using detergent buffer  containing a protease inhibitor cocktail  and quantified by Bio-Rad protein assay dye reagent. Proteins were resolved using 4%–12% SDS-PAGE gels  and blotted on PVDF membranes. Following blocking in 5% skim milk/0.01% Tween/PBS, membranes were incubated with primary antibodies for 3 h to overnight. Secondary horseradish peroxidase-conjugated secondary antibodies  were incubated for 1 h, and detection was carried out with enhanced chemiluminescence (ECL) reaction . The primary antibodies used were anti-Zscan4 , anti-Dppa2 , Dppa4 , and anti-HSP90 .


Interpreting the functional impact of noncoding variants is an ongoing challenge in the field of genome analysis. With most noncoding variants associated with complex traits and disease residing in regulatory regions, altered transcription factor (TF) binding has been proposed as a mechanism of action. It is therefore imperative to develop methods that predict the impact of noncoding variants at TF binding sites (TFBSs). Here, we describe the update of our MANTA database that stores: 1) TFBS predictions in the human genome, and 2) the potential impact on TF binding for all possible single nucleotide variants (SNVs) at these TFBSs. TFBSs were predicted by combining experimental ChIP-seq data from ReMap and computational position weight matrices (PWMs) derived from JASPAR. Impact of SNVs at these TFBSs was assessed by means of PWM scores computed on the alternate alleles. The updated database, MANTA2, provides the scientific community with a critical map of TFBSs and SNV impact scores to improve the interpretation of noncoding variants in the human genome. Several computational tools, such as SIFT2 and Polyphen3, are well established for the assessment of the deleterious impact of coding variation on protein functions yet interpreting the functional impact of noncoding variants continues to be challenging4.Understanding the relationship between DNA sequence variation (genotype) and observable traits and diseases (phenotype) is one of the central paradigms of the post-genomics era. While most analyses have focused on the ~2% of the genome that codes for proteins, genome-wide association studies have shown that up to 88% of disease- and trait-associated variants are located in the 98% of the genome that is noncoding5 can be used to evaluate nucleotides under purifying selection, and experimental data such as histone modifications6, chromatin accessibility8, and DNA methylation9 are used to identify biochemically active DNA, which is indicative of regulatory capacity.Recently, bioinformatics methods have been developed for scoring the impact of noncoding variants based on their pathogenicity and regulatory capacity . These m10. Genomic locations at which TFs interact with DNA are defined as TF binding sites (TFBSs). They are typically short (6–10 bp) and often exhibit degeneracy. Chromatin immunoprecipitation combined with sequencing (ChIP-seq)11 provides in vivo TF-DNA interactions at ~200–300 bp resolution. These ChIP-seq regions are expected to encompass the 6–10 bp fragments corresponding to TF-DNA interactions (TFBSs). The ReMap database12 is a publicly available resource providing an atlas of such regions obtained from 2,829 uniformly processed human ChIP-seq data sets.Transcription factors (TFs) are sequence-specific DNA-binding proteins that regulate gene transcription13. PFMs can be converted into probabilistic computational models, namely position weight matrices (PWMs), which can be used to predict TFBSs on any DNA sequence (reviewed by Wasserman and Sandelin14). Several databases of PFMs exist15, including the recently updated JASPAR database16, which stores manually-curated and non-redundant DNA-binding profiles such as PFMs for TFs across six taxonomic groups.The DNA sequences bound by a given TF can be represented as position frequency matrices (PFMs), which count the number of occurrences of each nucleotide within the TFBSs for that TF17, it is expected that some will alter the binding of TFs to DNA19. Therefore, it is imperative to develop methods that prioritize noncoding variants based on their impact on TF-DNA interactions. In 2015, we developed MANTA, a Mongo database for the analysis of TFBS alterations, to study the impact of regulatory mutations in B-cell lymphomas20. The database stores TFBSs in ChIP-seq regions predicted using PWMs derived from the JASPAR database, as well as the potential impact on TF binding of all possible single nucleotide variants (SNVs) that could occur at these TFBSs  for 227 human TFs for which we had binding profiles in JASPAR16. Each ChIP-seq data set was paired with one or more PFMs associated to the ChIP’ed TFs from the JASPAR CORE vertebrates collection  to identify the best PWM score on the alternate allele. Note that we only kept the best match per SNV. We then computed the distribution of PWM scores for all these SNVs and calculated the corresponding mean, m, and standard deviation, sd. For each SNV, the final impact score was calculated as the Z-score of its TFBS score, S, within the distribution of alternate PWM scores at that TFBS (i.e. (S−m)/sd). Users can refer to the webinar video describing the original MANTA database (http://www.cisreg.ca/Webinars/JASPAR_BioPython_MANTA.flv). Therefore, for each SNV, MANTA stores its associated reference and alternate TFBS PWM scores and locations, along with the computed impact score.For each TFBS, we computed the impact on TF binding of all possible overlapping SNVs as described in the manuscript describing MANTA20 . First, 18. For each event, allelic imbalance was calculated as the number of ChIP-seq reads mapped on the alternate allele divided by the total number of reads mapped at that position (23 to convert them to the hg38 assembly (the conversion process failed for 12 coordinates).We downloaded ChIP-seq data for 35,703 TF-binding events at heterozygous sites in GM12878 and HeLa cells for 36 different TFsposition . The cooMANTA2 is freely distributed as a GitHub repository at https://github.com/wassermanlab/MANTA2.The Mongo database dump of MANTA2, is deposited as a tarball on Zenodo (Data Citation 1).12 and JASPAR16, respectively, and is summarised below.The quality and technical validation of the ChIP-seq data and TFBS predictions is described in the 2018 manuscripts of ReMap12. ChIP-seq reads were aligned to the human genome using bowtie2  with default parameters. The quality of all ChIP-seq datasets was assessed based on metrics developed by the ENCODE consortium27.ReMap ChIP-seq datasets were uniformly processed using a well-established pipelineie2 ref.  (version16: the TFBS Perl module22 (version 0.7.1) and FIMO28, as distributed within the MEME suite29 (version 4.11.2). FIMO is one of the best performing tools for scanning DNA sequences with PWMs to predict TFBSs30. To scan the human genome with the BioPerl TFBS module, PFMs were converted to PWMs and predictions with a relative score ≥0.8 were kept. In preparation for the FIMO scan, PFMs were reformatted to MEME motifs and motifs that matched with a P-value <0.05 were kept. For quality control, TFBS predictions that were not consistent between the two methods were filtered out. Such consistency ensures, for instance, technical validation for the coordinates of the TFBS predictions.JASPAR TFBSs were predicted by scanning the human genome using two different methods23. For 15 randomly selected TFBSs (of different TFs) from MANTA2 we manually checked that: 1) the TFBS overlapped a ReMap ChIP-seq region associated with that TF; 2) the JASPAR PFM matched the start, end, and strand stored for that TFBSs; and 3) the stored SNVs for that TFBS had the expected impact on TF binding. Moreover, we assessed the usefulness of MANTA2 impact scores on an external dataset of heterozygous TF-binding events18. As expected, the allelic imbalance calculated for ChIP-seq reads (see Methods) significantly correlated with the impact scores from MANTA2  or download MANTA2 from GitHub (see Code availability in the Methods section). The script “search_manta2.py” provides programmatic access to MANTA2. It requires the following inputs:MANTA2 can be accessed either programmatically or via its web interface. To access the database programmatically, users must first clone (The name of the MANTA2 database in the MongoDB system (option “-d”)The name of the server where the MongoDB system is hosted (option “-H”)A user with “read” privileges to the MANTA2 database (option “-u”)The password for that user (option “-p”)A file containing a list of variants in “VCF”, “BED” or “GFF” format (option “-i”)Non-mandatory options include:The format of the input variant file The name of a file to output the results )As a usage example, the MANTA2 database hosted by the Wasserman lab can be accessed as follows: “python search_manta2.py -d manta2 -H manta.cmmt.ubc.ca -u manta_r -p mantapw -i <variant file>”.A variant file can be obtained by executing the shell script: “bash ./examples/get_VCF_example.sh”.i.e. “chr20.vcf”) contains high-confidence SNP, small indel, and homozygous reference calls on chromosome 20 from the Genome in a Bottle (version 3.3.2) sample HG001 ;the TF name and associated JASPAR profile ID;the start, end and strand, as well as the absolute (raw) and relative scores for both the reference and alternative TFBSs;and the impact score.Users who plan on performing large numbers of searches should create a local build of the MANTA2 database. Instructions are provided in the “README.md” file of the GitHub repository.http://manta.cmmt.ubc.ca/manta2. Similar to the “search_manta2.py” script, the server requires as input a list of variants in VCF, GFF, or BED format (see help page), and it returns all TFBS predictions potentially impacted by these variants as a tab-separated values table. The table can be sorted on any column by clicking on the column header.The MANTA2 database hosted by the Wasserman lab can also be accessed via a dedicated web server at How to cite this article: Fornes, O. et al. MANTA2, update of the Mongo database for the analysis of transcription factor binding site alterations. Sci. Data 5:180141 doi: 10.1038/sdata.2018.141 (2018).Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Human leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1), an immunoinhibitory receptor, is expressed on most types of hematopoietic cells and some tumor cells. LAIR-1 plays an inhibitory role in immune cell maturation, differentiation, and activation. LAIR-1 is also involved in some autoimmune diseases and tumors. However, the mechanism controlling the regulation of the LAIR-1 gene is still unknown. In order to elucidate the molecular mechanisms involved in LAIR-1 regulation, in the present study, we cloned and characterized the promoter region of LAIR-1 gene using a series of truncated promoter plasmids in luciferase reporter assays. Our results show that the basic core promoter of LAIR-1 is located within the region -256/-8 relative to the translational start site. Our further studies indicate that five ETS transcription factors: ELF-1, ETV-4, ETV-3L, ETS-1 and ETS-2, can up-regulate the LAIR-1 basic promoter activity. Of these, ETS-2 is the most effective transcription factor. Moreover, ETS-2 was confirmed to interact directly with the basic promoter of LAIR-1. This study presents the first description of regions/factors capable of up-regulation the promoter activity of LAIR-1. This new knowledge contributes to understanding of the molecular mechanisms involved in LAIR-1 associated immune regulation and diseases. On peripheral blood mononuclear cells, LAIR-1 surface expression is greatly stimulated by treatment of the cells with PHA, while TGF-β and IL-15 treatment can reduce the PHA-induced up-regulation of LAIR-1expression  (1: 500) (ab14826) followed by HRP–conjugated goat anti-mouse antibody (1: 6000) incubation. Protein bands were detected by an ECL kit  according to the manufacturer's instructions. The immunoblot of GAPDH was used as a loading control.TM magnetic beads (Bangs laboratories. Inc). The beads were added to the cell lysates and incubated overnight. The chromatin-antibody complex was then precipitated using a One-Day Chromatin immunoprecipitation kit (Millipore) and digested with proteinase K and RNase to remove the proteins and RNAs. The CHIP DNA was analyzed using PCR amplification. The primers flanking the LAIR-1 gene core promoter were: 5’-ACG GTC ATC TGC CTC TAA GC-3’ (forward) and 5’-CAC CAA TGC AAG GAC AGA ACT C-3’ (reverse). The resultant PCR products were analyzed by 2% agarose gel electrophoresis.Jurkat and COC1 cells were used for CHIP experiments. The proteins were cross-linked to the DNA by treating cells with 1% formaldehyde for 10 minutes. The cross-linking reaction was then terminated by the addition of glycine to a final concentration of 0.125 M. The cells were lysed, and cross-linked chromatin was sonicated using a Biorupter (Diagenode) to generate DNA-fragments of approximately 200 to 1000 bp in length. Anti-ETS-2, which was used to precipitate the chromatin fragments were pre-bound to BiomagNuclear extracts were prepared from Hela cells using a nuclear protein preparation kit . Hela cells were used because of high expression of ETS-2 . EMSA as


Corynebacterium ammoniagenes is an important industrial organism that is widely used to produce nucleotides and the potential for industrial production of coenzyme A by C. ammoniagenes ATCC 6871 has been shown. However, the yield of coenzyme A needs to be improved, and the available constitutive promoters are rather limited in this strain.rpl21) exhibited the strongest activity among the 26 identified promoters. Furthermore, type III pantothenate kinase from Pseudomonas putida (PpcoaA) was overexpressed in C. ammoniagenes under the control of Prpl21, CoA yield increased approximately 4.4 times.In this study, 20 putative DNA promoters derived from genes with high transcription levels and 6 promoters from molecular chaperone genes were identified. To evaluate the activity of each promoter, red fluorescence protein (RFP) was used as a reporter. We successfully isolated a range of promoters with different activity levels, and among these a fragment derived from the upstream sequence of the 50S ribosomal protein L21 (PC. ammoniagenes and should be valuable in current platforms for metabolic engineering and synthetic biology for the optimization of pathways to extend the product spectrum or improve the productivity in C. ammoniagenes ATCC 6871 for industrial applications.This study provides a paradigm for rational isolation of promoters with different activities and their application in metabolic engineering. These promoters will enrich the available promoter toolkit for  Corynebacterium ammoniagenes (formerly known as Brevibacterium ammoniagenes) is a Gram-positive, non-pathogenic soil bacterium with high guanine–cytosine (GC) DNA content. Due to the divergent evolution of C. ammoniagenes, different strains are used to produce different metabolites. For example, C. ammoniagenes ATCC 6872 is used in the production of nucleotides and nucleosides [C. ammoniagenes ATCC 6871 shows a relatively high synthesis capacity of coenzyme A (CoA), which is a ubiquitous and essential cofactor found in all three domains of life and is involved in numerous metabolic pathways [leosides , while Cpathways .C. ammoniagenes genome has helped to identify key enzymes for diverting carbon flow from metabolic pathways to other products [C. ammoniagenes genes has been achieved through the development of effective transformation protocols and cloning vectors [C. glutamicum endogenous cryptic plasmids that have incorporated E. coli elements for transfer between the species [E. coli promoters or C. ammoniagenes native promoters to express foreign proteins in C. ammoniagenes [C. ammoniagenes, the activities are quite low [Sequencing of the products , 6. Howe vectors . Most ve species –10. Almoniagenes –13. Althuite low .C. ammoniagenes, it is necessary to screen endogenous promoters. Paik and coworkers isolated 22 representative promoters from the genome of C. ammoniagenes ATCC 6872 and the activity of overexpressed chloramphenicol transacetylase from the strongest promoter IJ73 was 2.85 U [C. ammoniagenes ATCC 6872 using the endogenous promoter CJ1 [C. ammoniagenes ATCC 6871 (see text), probably due to the divergent evolution of C. ammoniagenes genomes. For instance, the sequence identities of promoters IJ59 and IJ73 from C. ammoniagenes ATCC 6872 with the homologous promoters from C. ammoniagenes ATCC 6871 are 93 and 89%, respectively. Therefore, due to the importance of CoA, it is necessary to find promoters that are effective in C. ammoniagenes ATCC 6871.To efficiently engineer oter CJ1 . Howeverdnak in Gluconobacter oxydans and Pgro in Corynebacterium glutamicum are promoters of molecular chaperones [rpl21 was found to be the strongest promoter, which was used in the biosynthesis of CoA, increasing the yield by 4.4 times.Endogenous promoters can be obtained by genomic dissection or promoter trapping et.al . Nonetheaperones , 19. In C. ammoniagenes ATCC 6871 cells grown in LB medium and fermentation medium to the exponential phase (OD600nm ≈ 2.0) were collected and sent to Mega genomics  for RNA-seq. A total of 2411 genes were identified from the transcriptomic data. Considering that there are many cases in which genes are in the same operon, genetic loci analysis was performed and the results showed that 1508 genes in 547 operons were expressed. In general, genes in the same operons share a common promoter, so the first gene in each operon was selected. Thus, the total number of remaining genes was 1450 (2411–1508 + 547). Transcription abundance analysis was used to select 71 genes with transcription levels in the top 100 in both RNA-seq profiles. Sequences upstream of the top 20 genes were predicted and scored using the online promoter prediction tool as described below. The annotations and RPKM values for these genes are shown in Table C. ammoniagenes ATCC 6871 genome (Accession Number: NZ_CP009244)  were identified and their promoters were predicted as described in materials and methods. The information of these genes and transcriptomic RPKM values are also listed in Table n. The sequences of the 26 promoters are listed in Additional file Previous studies have shown that most promoters of molecular chaperones exhibit high transcription levels in prokaryotes, so all 6 annotated molecular chaperones in the C. ammoniagenes ATCC 6872 were aligned against the genome of C. ammoniagenes ATCC 6871 by BLAST and were cloned into pXMJ190 to give pXMJ190-CJ1 and pXMJ190-IJ59 [C. glutamicum may also be active in C. ammoniagenes [. Thus, a strong endogenous C. glutamicum promoter named Pgro (the promoter of groES gene) was cloned as pXMJ190-Pgro [tac promoter and conserved SD sequence was also selected and cloned into pXMJ190 as pXMJ190-Ptac [C. ammoniagenes ATCC 6871.For a comprehensive comparison, two conserved homologous promoters CJ1 and IJ59 that are active in 190-IJ59 , respectniagenes . Thus, a190-Ptac . The pXMC. ammoniagenes ATCC 6871 strains harboring pXMJ190, pXMJ190-CJ1, pXMJ190-IJ59, pXMJ190-Pgro, pXMJ19-Ptac and pXMJ190-Pn series plasmids on LB plates containing 20 μg/ml chloramphenicol. Red fluorescence was observed by microscopy, with different intensities in different colonies, indicating that there was variable expression of RFP from the 26 putative promoters  from genes with high transcription levels, Ptmr, Pnat, PatpG, PgpdI, Pacn are essentially inactive, while PgroELA from the 6 molecular chaperone promoters was also inactive. Meanwhile, four strong promoters, including the Prpl21 with 43,433 RFU/OD intensity and followed by PdnaK , PgroELB (8166 RFU/OD) and Prpl10 (6490 RFU/OD) were identified whose fluorescence levels were consistent with those observed on plates. Thus, a range of promoters with different transcriptional activities, including four strong promoters, were identified and can be used directly in further applications. According to the obtained data, only two promoters (Prpl21 and Prpl10) from the 20 genes with high levels of transcription had strong activities, while two promoters (PgroELB and PdnaK) sourced from the six molecular chaperone genes exhibited relatively high activities, which may indicate that isolating promoters from molecular chaperones may be a more efficient strategy. Although most of the promoters identified from the RNA-seq profiles exhibited low level expression or were silent, the red fluorescence intensity of Prpl21 was almost 2.3 times that of the highest promoter (PdnaK) derived from upstream regions of the molecular chaperones. This suggests isolating promoters from genes with high transcription levels may yield strong promoters.To quantify the activities of the cloned promoters, growth-normalized fluorescence intensities were measured using a microplate assay and the data are shown in Fig. gro (5872 RFU/OD) was slightly higher than the Ptac (5683 RFU/OD) promoter but still lower than promoter Prpl10 (6490 RFU/OD). This demonstrates the promoters that work well in one species or homologous strains may not possess the same characteristics in another.When it comes to the known promoters, the promoter CJ1 had some certain activity (4171 RFU/OD), the IJ59 (2866 RFU/OD) promoter had almost non activity, and the activity of PC. ammoniagenes ATCC 6871 [C. ammoniagenes carries a type I coaA which is highly regulated by CoA and its derivatives. In contrast, type II and III enzymes are insensitive to CoA and its thioesters [Pseudomonas putida (PpcoaA) was selected and overexpressed by the control of the strongest promoter Prpl21 in C. ammoniagenes ATCC 6871 [It has been reported that CoA, a ubiquitous and essential cofactor in biochemical reactions, can be produced by TCC 6871 . In the TCC 6871 . Bacteriioesters , 28, theTCC 6871 , 30.PpcoaA. As shown in Fig. rpl21-PpcoaA-RFP, suggesting that RFP and PpcoaA were successfully co-expressed. By measuring the red fluorescence intensity, the strain harboring pXMJ190-Prpl21-PpcoaA-RFP had up to 7560 RFU/OD. This value was lower than that observed when RFP expressed alone under the control of Prpl21, possibly due to the long distance from the transcription initiation site and the increased cellular burden caused by co-expression of two proteins. The expression of RFP and PpcoaA was also be observed by SDS-PAGE. As shown in Fig. PpcoaA were overexpressed and that the Prpl21 promoter functioned well in C. ammoniagenes. Furthermore, three crucial substrates (pantothenic acid (2 mM), L-cysteine (2 mM), ATP (6 mM)) were added to the reaction mixture containing a certain number of bacterial cells (OD600 nm ≈ 40) at 39 °C. Coenzyme A production increased to a satisfactory yield of approximately 315 U/mL in 6 h . The results indicated that PpcoaA was successfully overexpressed under the control of promoter Prpl21 and increased the anabolic flow of CoA. To further improve the CoA production, the RFP gene was removed from the plasmid pXMJ190-Prpl21-PpcoaA-RFP for eliminating the burden of RFP expression in cells. With the PpcoaA overexpressed alone in C. ammoniagenes, the CoA production was reached 332 ± 13 U/mL, which was slightly increased than the PpcoaA and RFP co-expressional system.Considering there are no direct enzyme assays for type III pantothenate kinase, RFP was co-expressed with C. ammoniagenes ATCC 6871 is a producer of CoA, however, its genetic operation has been rarely reported, and its industrial application potential still needs to be improved. In order to further increase the production of CoA, endogenous promoters from C. ammoniagenes ATCC 6871 were screened in this study. Firstly, 20 putative promoters based on genes with high transcription levels and 6 promoters upstream of molecular chaperones were identified and characterized for transcriptional activity by using RFP as the reporter gene. Among the 26 putative promoters, 20 with different transcriptional activities were isolated including 15 from the high transcription level genes and 5 from molecular chaperone genes. The output efficiency demonstrates that isolating promoters from molecular chaperones (5/6) might be a more efficient strategy than using RNA-seq (15/20). Therefore, isolating promoters from molecular chaperone genes is more effortless and cost-effective than RNA-seq. These results may ascribe to that the RPKM values of the genes only represent the abundance of RNA and do not equivalent to its promoter activities, which might be caused by multiple factors, such as the codon usage of genes, copy numbers of genes, the half-lives of mRNA and limitations inherent in transcriptomics [iptomics –24. It trpl21) identified from RNA-seq was almost 2.3 times than the highest promoter (PdnaK) derived from molecular chaperone genes, so isolating promoters based on the genes transcriptional data may be more likely to yield promoters with highest activity. To our best knowledge, Prpl21 from the upstream sequence of the 50S ribosomal protein L21 is the strongest C. ammoniagenes ATCC 6871 promoter reported so far. The promoters obtained in this work will enrich the available promoter toolkit for C. ammoniagenes and should be valuable in current platforms for metabolic engineering and synthetic biology for the optimization of pathways to extend the product spectrum or improve the productivity in C. ammoniagenes ATCC 6871.Nevertheless, we should note that the red fluorescence intensity of the highest promoter . E. coli Top10  was cultivated in Luria-Bertani (LB) broth or on LB plates with 2% (w/v) agar at 37 °C as a host for transformation. C. ammoniagenes ATCC 6871 grown in NCM medium at 30 °C was used as the transformation host for E. coli/Corynebacteria vectors used in this study. After transformation by electroporation (1.8 kV), transformants were plated on BHIS plates with 20 μg/mL chloramphenicol at 30 °C. Fermentation medium  was used to cultivate strains producing CoA. Cultivation for expression analysis was performed in at least biological duplicates.The C. ammoniagenes genomic DNA was isolated using a genomic DNA isolation kit . Kits for plasmid isolation, extraction of DNA from agarose gels and PCR product purification were also purchased from Tiangen . I-5 2 × High-Fidelity Master Mix and Trelief™ SoSoo Cloning Kit were purchased from Tsingke  and used for routine molecular biology applications.tac promoter and lac operator were removed. A gene encoding red fluorescent protein (RFP) was inserted into the MCS to form a probe-vector named pXMJ190  in a cold sterile electroporation cuvette (1 mm electrode gap) and pulsed immediately with a MicroPulser electroporator . The electroporator was usually set at a voltage of 1.8 kV. Cells were subsequently resuspended in 0.9 mL of BHIS, heated at 46 °C for 6 min and withdrawn immediately for recovery by incubating for 3 h at 30 °C and then plated for selection of transformants.To increase transformation efficiency, recipients were grown in 100 mL of NCM medium at 30 °C until an ODC. ammoniagenes and the top 20 genes were selected. All of the genes were identified from the genome and their promoters were predicted as below. Six annotated molecular chaperones in the genome were sorted and their promoters were predicted as outlined below. According to previous studies, the promoter-5′-UTR junction influences mRNA and protein levels [The transcriptional levels of genes can be estimated by Reads Per Kilobase per Million mapped reads (RPKM), so the genes were ranked by RPKM value based on transcriptional data from n levels , 33. Thehttp://www.fruitfly.org/seq_tools/promoter.html) [Promoter sequences were predicted using the Neural Network Promoter Prediction online tool (er.html) . The proer.html) . For corer.html) , 37.C. ammoniagenes ATCC 6871 and C. glutamicum ATCC 13032 genomic DNA with the corresponding primers. Oligonucleotide primers used in this work are listed in Additional file E. coli TOP10 and then transformed into C. ammoniagenes ATCC 6871 for subsequent analysis.Promoters were amplified from C. ammoniagenes strains harboring various vectors were grown overnight on LB plates containing 20 μg/ml chloramphenicol. Fluorescence was observed using a LUYOR-3430 stereo microscope with a fluorescence excitation source  set at 501 nm and matching lenses to detect RFP. Pictures were captured with a camera.To evaluate RFP expression under the control of the various promoters, 600 nm of approximately 1.0. The excitation wavelength for RFP was set at 554 nm and emission was set at 586 nm. Fluorescence intensities were normalized by OD600 nm and were used to indicate the activities of the promoters. Bacteria harboring pXMJ19-Ptac were induced with 1 mM IPTG.For more accurate comparisons, the fluorescence intensities of bacteria harboring different plasmids were measured using a Synergy H4 microplate reader . In order to exclude other interfering factors, harvested cells were washed once with PBS (pH 7.4) and then resuspended in PBS (pH 7.4) at an ODP. putida KT2440 (PpcoA) and RFP were co-expressed under the control of the strongest promoter Prpl21. The PpcoaA gene was amplified by PCR from the genomic DNA of P. putida KT 2440, and the Shine-Dalgarno sequence for translation of RFP was calculated using the RBS calculator online tool (https://www.denovodna.com/software/). All primers used in this section are listed in Additional file rpl21-PpcoaA-RFP was constructed with Gibson assembly and positive colonies were confirmed by DNA sequencing . Recombinant plasmids were transformed into C. ammoniagenes ATCC 6871 for further experiments.To further examine the function of the isolated promoters, a type III pantothenate kinase from C. ammoniagenes strains were precultured in 10 mL LB medium at 30 °C and shaken at 220 rpm for 24 h. Ten percent of the culture was inoculated in a 250 mL shake flask containing 100 mL fermentation medium. After 24 h cultivation, cell samples were harvested by centrifugation at 12,000 rpm for 10 min. Forty micrograms of cell lysate were loaded per lane. The PpcoaA and RFP expression was analyzed by 15% (v/w) polyacrylamide gel electrophoresis (PAGE) with cell-free extract under denaturing conditions. Mini-Protean III Electrophoresis System  was utilized to perform the operation. Coomassie Brilliant Blue R-250  was utilized to stain protein on the gel.0; and then 0.01 mL of the phosphotransacetylase (30–40 U/mL) solution was added, mixed well and the highest absorbance within 3 to 5 min was taken as E1. Finally, another 0.01 mL of phosphotransacetylase solution was added, mixed well and the absorbance was read as E2. The number of CoA units per milliliter was calculated as U = (2E1-E0-E2) × 5.55 × 413.Coenzyme A content was determined according to the modified phosphotransacetylase method , 39. AllAdditional file 1: Table S1. Primer sequences used in this study. Table S2. Comparison of different promoter activities in C. ammoniagenes ATCC 6871. Table S3. The sequences of identified promoters.


Mycoplasma, up to several tens of thousands in many higher organisms. The first observations indicating that the nucleus had some kind of organization were made over a hundred years ago. Understanding of its significance is both limited and aided by the development of techniques, in particular electron microscopy, fluorescence in situ hybridization, DamID and most recently HiC. As our knowledge about genome organization grows, it becomes apparent that the mechanisms are conserved in evolution, even if the individual players may vary. These mechanisms involve DNA binding proteins such as histones, and a number of architectural proteins, some of which are very much conserved, with some others having diversified and multiplied, acquiring specific regulatory functions. In this review we will look at the principles of genome organization in a hierarchical manner, from DNA packaging to higher order genome associations such as TADs, and the significance of radial positioning of genomic loci. We will then elaborate on the dynamics of genome organization during development, and how genome architecture plays an important role in cell fate determination. Finally, we will discuss how misregulation can be a factor in human disease.Every living organism, from bacteria to humans, contains DNA encoding anything from a few hundred genes in intracellular parasites such as  Escherichia coli bacterium and three billion bp in a human nucleus   . Interacs (TADs) . A subses (TADs) .Genome organization and packaging into higher-order structures poses challenges with respect to protein accessibility to tightly packed regions. Local decondensation and chromatin looping is therefore required to allow gene expression. A popular model to explain looping suggests that CTCF functions with two subunits of a possible motor in a complex. The two subunits of the motor protein then slide along the genome in opposite directions, either actively  or throuTopologically Associated Domains can further be part of long-range interactions resulting in chromosome compartments. The genome seems to be divided between A and B compartments. Based on epigenetic marks, the A compartment is enriched in actively transcribed chromatin and the B compartment in inactive chromatin. Dynamic changes in compartment organization and transcription support physiological state of the cell and organismal development .Hydra, suggesting that specific radial positioning mechanism evolved at least 600 million years ago , identified from DamID maps as stretches of the genome interacting with the periphery , are typSeveral recent studies have attempted to approach the idea of genome organization from a more facile standpoint, using only the most basic components of the environment in which genetic material is contained to build models, rather than dealing with complexities that arose through evolution. Toward this end, a nucleus or a prokaryotic cell can be thought of as an environment with DNA (a polymer), DNA binding proteins and non-DNA binding proteins, all confined within a boundary.Monte Carlo simulations yielding probability distributions for the range of possible outcomes to a problem are a useful computational tool to model genome organization. For simplicity, simulations were first performed to study only DNA-DNA interactions, considering two kinds of polymers in a confined space – flexible ones representing euchromatin and stiff ones representing heterochromatin. Remarkably, simulations showed that spontaneous movement of euchromatin to the interior and heterochromatin to the periphery had the greatest likelihood, recapitulating what is seen in cells. Additionally, stiff polymers exhibited greater contact frequencies, resulting in separation between rigid and flexible polymers . With thFurther, an additional layer of complexity was added to the system in the form of chromatin binding proteins, the system now involving DNA-DNA and DNA-protein interactions. This showed spontaneous aggregation of binding sites as a result of DNA-protein interactions. This promoted further binding of proteins from the soluble pool, in turn increasing local chromatin concentration. It is not hard to imagine then, that if the bound factors have bi- or multi-valency they can effectively bridge out forming chromatin loops that will remain stable for as long as the factors are bound. Such bound clusters and the resultant looping are stabilized again by a non-specific force called depletion attraction, which is in play in crowded environments like cells .In cells, there are many different transcription factors, each binding to DNA in a sequence specific manner. In such a situation, there would be specialized clusters, effectively separated in 3D space. Specificity can also be conferred by epigenetic marks separating euchromatin from heterochromatin. Thus, each individual transcriptional event would contribute its part in affecting global genome organization. This model of self-assembly and clustering is popularly referred to as the “transcriptional factor model” of genome organization .In silico models collectively demonstrate how a certain degree of order is achieved in the system merely through entropic forces and stabilized by genome-wide transcriptional events.Development is a complex process, involving extremely tight spatio-temporal regulation of gene expression. Dynamic physiological state-dependent changes in chromatin folding allow for this stringent regulation. With the understanding of hierarchical genome organization, we now explore its plasticity through organismal development.Multicellular life begins with fusion of haploid gametes to form a totipotent zygote which, through divisions, gives rise to a population of pluripotent cells which then differentiate into the many different lineages. 3D organization of the haploid genome within gametes was studied only recently. Hi-C data on mouse spermatozoa shows a remarkable conservation of TADs and loops, with those observed in somatic cells. There is a distinct enrichment of intrachromosomal contacts and contacts with DNA that is more than 10 Mb away . HoweverThe genome of the zygote is transcriptionally inactive and utilizes gene products from the oocyte until a widespread recruitment of RNA polymerase II along with concurrent epigenetic changes leads to zygotic genome activation (ZGA) . Microscin vitro cultures of embryonic stem cells (ESCs) derived from the inner cell mass (ICM) of the blastocyst. These cells are maintained in their pluripotent state through the function of core transcription factors like Oct3/4, Sox2, and Nanog, which orchestrate self-renewal by repressing expression of genes required for lineage commitment and/or sustaining expression of one another , plays a major role in determining genome interactions with NE, along with several other nuclear envelope transmembrane proteins (NETs). Immunofluorescence studies show the absence of Lamin A/C until tissue specification begins at embryonic day 12 during mouse embryogenesis  and acco studies . The pro studies . However studies . Further studies . These rMouse ESCs depleted of A- and B-type lamins, and subjected to Emerin-DamID, yielded LAD profiles similar to LaminB1-DamID, suggesting that lamins are not necessary in establishing genome-NE interactions during pluripotency . One cavDifferentiation of pluripotent cells is coupled with a dramatic reorganization of the genome. Typically, movement of a genomic locus toward the periphery or its direct tethering to the NE leads to its repression while movement toward the nuclear interior often results in its activation. At the chromosome territory level, ESCs have no special organization compared to differentiated cells. However, a comparison between pluripotent human ESCs (hESCs) and differentiated lymphoblastoid cells revealed a more internal position for the locus encoding NANOG in the nuclei of ESCs where it is expressed highly. Similarly, OCT4 shifted in localization from the interior of its chromosome territory in hESCs to the surface of the territory in lymphoblastoid cells . Such obPcdh9 is concomitant with its transcriptional activation in the neural lineages and the tethering of Zfp42, a pluripotency marker, with its repression as lineage specification progresses  and terminally differentiated astrocytes shows the relocation of several developmentally important genes. The release of neuron specific ogresses . Within ogresses . Analogotivation . These ontiation . These sNid1, Ptn, Cxcl1, etc. Additionally, these NETs were also important for myotube formation  seen in the nuclear interior with the corresponding loss of LADs from the periphery. SAHF are ordered structures with a core enriched in constitutive heterochromatin, surrounded by facultative heterochromatin and the outermost layer being euchromatin, a complete reversal of organization seen in healthy replicating cells. SAHF are devoid of active transcription sites with many cell-cycle genes sequestered within them to prevent these cells from cycling . The chaDisease-linked single nucleotide polymorphisms (SNPs) in protein coding regions can alter protein structure and function, thus it is easy to explain how they can cause diseases. However, over 90% disease-associated SNPs are found outside protein coding transcripts, highlighting the importance of non-coding RNAs and other regulatory elements such as promoters and enhancers in maintaining homeostasis .TP53 deletion, leading to an overall decrease in TAD sizes, affecting 3D organization at a global level  in the genome thereby disrupting higher order chromatin structures like TADs along with effects on gene expression and dosage . Oncogenal level .Shh), an important morphogen specifying the number of digits and digit identity during limb morphogenesis is controlled by Zrs, its enhancer. Gain-of-function mutations in Zrs lead to SHH expression at ectopic sites causing preaxial polydactyly, whereas an inversion leading to its loss-of-function causes holoprosencephaly along with upper limb syndactyly and lower limb polydactyly (Germline SVs with microdeletions and microduplications are implicated in congenital diseases . Accuratydactyly .Epha4, a gene important normal innervation of the limb, lead to ectopic promoter interactions and cause different kind of syn- and polydactyly (Pitx1, a gene important for hindlimb identity, is regulated by its enhancer Pen which is active in both forelimb and hindlimb. However, it is the difference in 3D chromatin conformation between forelimb and hindlimb that preferentially allows Pen-Pitx1 interaction in the hindlimb, while constraining it in forelimb. A perturbation of the 3D genome, achieved by inversion of the enhancer element led to conversion of the inactive 3D conformation of the forelimb into an hindlimb-like active conformation, PITX1 expression and an arm-to-leg transformation with an ectopic patella formation in the arm, as seen in Liebenberg syndrome in humans (Structural variations including inversion, duplication and deletion in the TAD containing ydactyly . Pitx1, n humans .Lamins and several NETs with functions in genome organization are also linked to a wide range of diseases generally termed laminopathies or nuclear envelopathies. Lamin mutations have been implicated in premature aging phenotypes like The Hutchinson Gilford Progeria Syndrome as well as muscular dystrophies, lipodystrophies, dermopathies, neuropathies and cardiomyopathy . The effComplexity of the genome increased concurrently with evolution toward multicellularity. Along with this complexity the number of potential molecular players involved in orchestrating genome organization also increased. While the “loop extrusion model” elaborating the importance of CTCF and cohesin in maintaining architecture and “transcription factor model” emphasizing spontaneous formation of specialized clusters due to transcriptional events seem like two schools of thought, we believe that the two are not exclusive.in silico modeling data. Transcription is a common denominator in all kinds of organisms containing DNA as their genetic material. That transcription itself should drive overall chromatin architecture is almost first principle and a simplistic explanation for the seemingly elaborate problem that is genome organization. However, architectural proteins like CTCF and cohesin confer stability to this order and might facilitate genome reorganization, aiding in accurate spatio-temporal gene-expression during development. In fact, deletion of CTCF binding sites has been shown to alter cell fate decisions (A first-degree organization can be achieved merely by specific DNA-protein and protein-protein affinities and driven by entropy, as shown by ecisions . It was ecisions . This stTopologically Associated Domain boundaries are defined by CTCF. Loop extrusion requires cohesin loading onto CTCF sites to facilitate its motor function. The distribution of cohesin in the mouse genome is governed by WAPL, a cohesin unloading factor. Interestingly, WAPL also controls the length of loops extruded by CTCF, suggesting that the longer cohesin is bound to the DNA, the longer the loops are . While CDrosophila have CTCF and also other insulator proteins, suggesting that at least some invertebrate branches will have CTCF too (S. cerevisiae (Interestingly, cohesin complex is evolutionarily conserved among eukaryotes, with varying degrees of similarity for different subunits, however, CTCF is not as well conserved . AlthougCTCF too . While arevisiae , indicatrevisiae , furtherrevisiae  reaffirmWe propose that genome organization is perhaps as old as DNA itself, firstly forming specialized clusters driven by entropic forces, and secondly stabilizing those structures with architectural proteins that facilitate higher order interactions. While the basic mechanism has remained conserved through evolution, individual proteins involved may have diversified and only recently we have started identifying the players.Evolution, however, is an on-going process and the idea of different mechanisms and molecular players orchestrating and maintaining genome organization is not eccentric. Dinoflagellates have a radically different genome architecture from other eukaryotes in that they have permanently condensed chromosomes that lack nucleosomes . In mammAS and JIH wrote the manuscript and made figures with help from ECS.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.