The basic helix-loop-helix (bHLH) transcription factor family is one of the largest transcription factor gene families in Arabidopsis thaliana, and contains a bHLH motif that is highly conserved throughout eukaryotic organisms. Members of this family have two conserved motifs, a basic DNA binding region and a helix-loop-helix (HLH) region. These proteins containing bHLH domain usually act as homo- or heterodimers to regulate the expression of their target genes, which are involved in many physiological processes and have a broad range of functions in biosynthesis, metabolism and transduction of plant hormones. Although there are a number of articles on different aspects to provide detailed information on this family in plants, an overall summary is not available. In this review, we summarize various aspects of related studies that provide an overview of insights into the pleiotropic regulatory roles of these transcription factors in plant growth and development, stress response, biochemical functions and the web of signaling networks. We then provide an overview of the functional profile of the bHLH family and the regulatory mechanisms of other proteins. Plants frequently encounter a wide array of environmental stresses, including drought, cold, salinity, UV radiation, ozone and other abiotic stresses through their lifecycle, which severely affect plant growth, development and crop yield. To cope with those problems, plants adapt to the different harsh conditions through transcription factors that regulate the expression of a series of target genes. The basic helix-loop-helix (bHLH) protein family is one of the largest transcription factor gene families in Arabidopsis thaliana, and contains a highly conserved amino acid motif that can be found throughout eukaryotic organisms. They were originally identified in animals, and found to play important roles in diverse regulatory networks, via the functions of DNA binding and dimerization ,2. The bThe bHLH superfamily, named after its highly conserved alkaline/helix-loop-helix domain, is the second largest transcription factor family and is widely present in animals and plants ,4. The bAs a superfamily, bHLHs have been characterized in Arabidopsis over the years, and members of this family members play vital roles in plant growth, development, light signal transduction and stress responses ,18,19,20To date, many excellent reviews have covered the roles of bHLH transcription factors in plants in different contexts, but an overall summary is not available. Thus, we focused mainly on summarizing the knowledge on bHLH functions in various essential processes, such as how bHLH proteins mediate plant growth and development, including flowering time, seed germination and cell fate determination; how they are involved in maintaining iron homeostasis in plants, how they respond to light, stress, phytohormones and the crosstalk among these factors; and how they perform the functions in other processes, such as senescence and anthocyanin biosynthesis .Seed dormancy and germination are critical processes in the lifespan of plants, which are mediated by various external environmental factors such as temperature, light and humidity, and internal factors, such as phytohormones. Two type of phytohormones, ABA and gibberellin (GA), are crucial regulators of seed dormancy and germination. ABA enhances seed dormancy, whereas GA breaks dormancy and promotes germination. The transcription factor bHLH57 is involved in ABA-regulated the seed dormancy process. NCED (9-cis-epoxycarotenoid dioxygenase) is considered to catalyze the first dedicated step in ABA biosynthesis , ODR1 , a group of typical of bHLH proteins, could interact with diverse groups of factors to integrate external environmental and internal signals, and further control seed germination, shade avoidance and crosstalk of plant hormones and the clock-derived signaling pathway ,26. The CO gene; they bind to the E-box cis-elements in the promoter of CO and then positively regulate the CO-mediated flowering time [It is critical for plants to manage their flowering time, which is regulated by an intricate network of molecular signaling and controlled by various environmental factors such as photoperiod and temperature. The CONSTANS (CO) protein functions as an essential component for transforming biological clock signals into flowering signals to initiate plant flowering. Four bHLH related proteins (flowing bHLHs), namely, FBH1, FBH2, FBH3 and FBH4, are transcriptional activators of the ing time . Cryptocing time . CRYPTOCing time ,33.nfl mutants did not flower under SD conditions but were similar to wild type under long-day (LD) conditions [Recently, a bHLH transcription factor, named as NO FLOWERING IN SHORT DAY (NFL) was shown to be necessary for the promotion of flowering specifically under short-day (SD) conditions, and nditions . Additionditions . Moreovenditions . In Arabidopsis, temperature also affects the flowering time, and high temperature (29 °C) not only induces rapid hypocotyl elongation but also results in early flowering. In addition, the central integrator bHLH transcription factor phytochrome-interacting factor 4 (PIF4) can accelerate the flowering process by activating FT at high temperature conditions . In addiIn summary, the flowering time is strictly controlled by an intricate network, and bHLH family members act together with many other proteins to allow plants to flower at suitable time and under favorable environments.Plants process a cell determination mechanism for formatting specific cell types, and this system relies on the expression of different genes in a proper spatiotemporal manner. Many transcription factors participate in this critical process, including a number of bHLH transcription factors, which play essential roles in the root and shoot cell fate determination . During RSL3/4 and LRL3 (Lj-RHL1-LIKE3) also act as downstream of RHD6 and RSL1 to promote the root hair and cell differentiation [The bHLH VIIIc subfamily member, bHLH83 , is a transcription factor that has fewer root hairs and functions in the inhibition root hair formation in cortical cells ,39, and ntiation ,42,43. Mntiation . GL2, a ntiation . The bHLntiation ,118.Furthermore, ET is involved in root hair initiation and elongation, and ETHYLENE INSENSITIVE 3 (EIN3) and its homolog EIN3-like1 (EIL1) can coordinate with RHD6/RSL1 to upregulate RSL4 and then participate in root epidermis development . AnotherIn addition to their roles in the root epidermis formation, the bHLH family is also involved in other cell fate related processes, including stamen and stomatal development. The IIIe bHLH transcription factor MYC5 (bHLH28) has redundant functions with MYC2 (bHLH6), MYC3 (bHLH5) and MYC4 (bHLH4), which interact with MYB21 and MYB24 to form the bHLH-MYB complex to regulate the stamen development . In addiOverall, the establishment of this specification mechanism is complicated and also influenced by several plant growth regulators, including hormones such auxin , ET, JA ,119.Iron is an indispensable mineral micronutrient for photosynthesis and respiration in plants. Low concentration of effective iron in soil leads to the iron deficiency in plants, conversely, too much iron can have a toxic effect. To cope with this problem, plants have developed a series of sophisticated regulatory systems to control the iron uptake and maintain the Fe homeostasis. Among the regulatory mechanisms, bHLH transcription factors play important roles in this complicated process ,92.FIT promoter to regulate its expression [Four closely related clade Ib bHLH genes, namely, bHLH38, bHLH39 , bHLH100pression . In addipression .Four IVc bHLH transcription factors  form homo- and heterodimers to regulate the Fe deficiency response and the Fe homeostasis ,58,59,92In the case of FIT, its function is required to regulate Fe uptake responses; bHLH47  is another bHLH transcription factor that plays a major role in the Fe homeostasis. PYE interacts with bHLH104, bHLH105 and bHLH115 to bind to the promoters of several Fe response genes and repress their activity ,62,123. In most plants, Fe(II) is taken up by IRON REGULATED TRANSPORTER 1 (IRT1) in the root plasma membrane from soil under iron deficiency ,126,127.In addition to regulating the iron response, it was reported that bHLH104 loss-of-function mutants were sensitive to Cd stress, and the Cd tolerance was enhanced upon overexpression of bHLH104 . In otheInducer of CBF Expression  encodes an MYC-type bHLH transcription factors that directly binds the promoter of the C-Repeat Binding Factor/Dehydration-Responsive-Element-Binding protein (CBF/DREB1) protein-encoding gene and activates its transcription to improve cold tolerance through an ABA independent pathway . The regOther transcription factors, such as AIF2  and its partner RSA1 (SHORT ROOT IN SALT MEDIUM 1) regulate several gene for detoxification of reactive oxygen species (ROS), which are triggered by the salt stress .Some proteins, such as bHLH122, can directly bind to the CYP707A3 promoter to repress its expression and enhance the ABA content, but these proteins were not induced by ABA treatment, indicating that they may function in ABA-independent or ABA-dependent ways .As direct target genes of PIF4, JUNGBRUNNEEN1 (JUB1) and ORESARA1 (ORE1) have vital roles in salt stress response. PIF4 directly regulates ORE1 and JUB1, and is involved in regulating salt stress response ,69,70.Under specific conditions, multiple phytohormones and environmental factors are in constant crosstalk with each other to affect the plant growth and development. Based on previous studies, GA, IAA, BR, ET and light are usually considered to promote cell expansion in plant growth, while ABA, JA and SA are normally involved in the response to biotic and abiotic stresses. bHLH proteins that respond to plant hormones and environmental factors participate in various processes. They are able to interact with each other to cooperatively or antagonistically modulate the plant growth.Light is an important factor that influences the plant growth and development, and many bHLH transcription factors are reported to participate in this process by inducing the expression of related downstream genes and various light-mediated effects.PIFs interact with the active form (Pfr) of phytochrome to modulate growth, including in response to environmental signals such as light and stress and via other signaling pathways . The PIFpif mutant showed phenotypes of reduced hypocotyl elongation. PIFs also interact with diverse groups of transcription factors to integrate external environmental and internal signals, including in seed germination, shade avoidance and crosstalk among plant hormones and clock-related signaling pathways [In the dark, four PIFs  directly interact with Pfr to promote skotomorphogenesis by repressing photomorphogenesis. Loss-of-function of pathways ,25. A nuPIF3 (bHLH8), the first identified member in the PIF family, acts as a regulator in the seedling de-etiolation and modulates both positive and negative response to phytochrome-mediated signaling ,71. PIF3PIF4 is a key transcription factor in the light signaling pathway; it interacts selectively with Pfr and negatively regulates phyB signaling in Arabidopsis , PhytochThe PIL  family has six members, designated as PIL1, PIL2, PIL3, PIL4, PIL5 and PIL6. PIF1/PIL5 (bHLH15) is a component that negatively regulate the chlorophyll biosynthetic pathway, seeds germination and inhibit hypocotyl elongation in the dark. The activity of PIF1 was repressed by phyA and phyB in light, and regulated ABA signaling ,80,81,82Taken together, the bHLH proteins PILs/PIFs are proposed to form heterodimers to regulate bHLH network activity and are central components that integrate multiple signals in response to light.COI1 ubiquitin E3 ligase complex. Then, JAZ proteins were degraded by the 26S protease, resulting in multiple transcription factors free from JAZ-mediated repression and further activating downstream JA-mediated responsive genes. The bHLH transcription factor MYC2 forms a signaling module COI1/JAZs/MYC2 to participate in the JA-induced signaling pathway. The homologs of MYC2, MYC3 (bHLH5) and MYC4 (bHLH4) are known to form homodimers/heterodimers, and they can also bind to the G-box involved in the JA signaling pathway but exhibit gene redundancy with MYC2 [The phytohormone jasmonate acid (JA) plays a vital role in the plant development and the response to various stresses. The presence of JA triggers the key protein jasmonate ZIM-domain (JAZ) to interact with Coronatine Insensitive 1 (COI1), part of the SCFith MYC2 ,87.The bHLH transcription factor GLABRA3  can form a WD-repeat/bHLH/MYB complex with TRANSPARENT TESTA GLABRA1 (TTG1) and the R2R3-MYB transcription factor GLABRA1 (GL1), which is repressed by JAZs and DELLAs, is responsible for trichome initiation ,89,90,91Four subgroup IVa bHLH transcription factors  can be induced by JA and inhibit the transcription of the FIT and Ib bHLH genes, which have been suggested to function redundantly in JA-mediated FIT protein degradation in the presence of JA or under iron deficient conditions via the 26S proteasome pathway .The jasmonate-activated transcription factor MYC2 has also been found to interact with the key component in the ET signaling pathway EIN3 and its close homolog EIL1 to repressed its DNA binding activity and affect hook formation , suggestThe plant hormone IAA has multiple roles in the plant growth and development, such as in cell division, cell elongation and cell differentiation, which are affected by the regulation of IAA response genes . BIGPETAPlant are constantly under extrinsic abiotic/biotic environmental stresses, including cold, drought, high salinity, pathogen and extreme temperature. In response to these diverse stresses, plants have evolved sophisticated adaptation mechanisms. To date, several bHLH transcription factors have been reported to mediate abiotic and biotic stress signaling pathways to regulate plant responses in Arabidopsis in different ways. The plant hormone ABA plays a central role in a variety of physiological processes and environmental response involved in plant growth, including responses to drought, cold, heat and salinity stresses ,137,138.A loss-of-function mutant of bHLH112, a transcriptional activator, displayed a late-flowering phenotype under long day conditions in Arabidopsis, and its transcript level was correlated with salt and drought tolerance. bHLH112 regulates gene expression by binding to E-box and GCG-box motifs in the gene promoters and then mediate multiple physiological response to improve stress tolerance ,97.ABA-inducible bHLH-type transcription factor (AIB) and ABA-inducible gene (AIG1) are ABA-induced genes, the proteins contain a bHLH type DNA binding domain and play a positive role in ABA signaling in Arabidopsis ,99. MYC2The expression level of bHLH129 is reduced upon exogenously application of ABA, and bHLH129 regulates the expression of several ABA signaling component genes  to promoPREs are involved in plant growth and development and are also involved in the regulation of ABA mediated salt responses in Arabidopsis. Some PREs are ABA responsive genes; their expression levels are decreased under ABA treatment, and this response has functions in regulating plant growth and environmental stimuli .ABA induces stomatal closure and changes the expression of numerous genes to adapt to drought stress, ABA-responsive kinase substrate (AKS1), also a bHLH transcription activator, is inhibited by ABA through phosphorylated to form monomer by SNF1-related protein kinase 2 (SnRK2) in Arabidopsis guard cells ,143.In addition, the BEE transcription factor family members (BEE1/2/3) regulate plant responses to abiotic stress. BEE genes are strongly repressed by ABA and are redundant negative regulators of physiological responses to abiotic stress, whereas the BEE2 dimerized protein IBH1 is a positive modulator that improves salt and drought tolerance . NaCl-inSome bHLH transcription factors are involved in signal transduction networks mediated by plant hormones. For example, several genes are involved in light and GA signaling pathways, such as PIL5 and SPT, which also belong to the bHLH transcription factor family ,80. MoreSeveral atypical bHLH proteins, such as Arabidopsis ILI1 binding bHLH1 (IBH1) and ATBS1 Interacting Factors (AIFs), negatively regulate cell elongation in Arabidopsis ,108. ActBEE1 (bHLH44), BEE2 (bHLH58) and BEE3 (bHLH50) are functionally redundant bHLH transcription factors for which expression is induced by BL treatment, indicating that they function in the early response to BRs and their expression is required by ABA . In brieIn Arabidopsis, bHLH members are also involved in other aspects of plant growth and development, such as senescence and the anthocyanin biosynthesis pathway. These aspects are only briefly discussed here.In plants, senescence is triggered by developmental and environmental factors. The IIId bHLH transcription repressors  can bind to the promoter of senescence-associated gene 29 (SAG29) to repress MYC2-activated leaf senescence . PIFs cabHLH transcription factors have been identified as key regulators of anthocyanin biosynthesis in various plant species . MYC likAs the second largest superfamily in Arabidopsis, most bHLH transcription factors are characterized by a signature domain, which consists of approximately 60 amino acids, with an N-terminal basic DNA binding domain and a C-terminal protein interaction domain. Although more than 160 genes have already been predicted to belong to the bHLHs family and are classified into 12 subfamilies , relativSome transcription factors play the more crucial roles in many aspects of plant development, such as MYCs, PREs and PIFs, and these bHLHs are key transcriptional regulators in the phytohormone crosstalk pathway and multiple biosynthesis pathways. As JAZ targets, MYCs are involved in JA-mediated gene expression and the ABA signaling pathway; they also mediate ET biosynthesis and regulate stamen development and flowering time. PREs respond to GA, BR, temperature and light signaling to positively regulate cell elongation. PIFs are also involved in many other signaling pathways, such as in mediating pathways responsive to light, GA, IAA, ABA, ET and abiotic/biotic stress ,149,150 Overall, in this review, we have compiled the current research on bHLH function and provided a relatively complete overview of the bHLH transcription factor family. This review enriches our understanding of this family and provides new insight into the mechanism by which bHLHs regulate various biological processes. However, there remain many aspects that have not been described because of the complicated crosstalk with other transcription factors. Our understanding of function the bHLH proteins have improved tremendously during the past several years, and the research in this area is well characterized. Future studies will further elucidate the mechanism of how bHLH proteins coordinate the multiple internal and external environments to regulate plant growth.


Nucleoli form around actively transcribed ribosomal RNA (rRNA) genes (rDNA), and the morphology and location of nucleolus-associated genomic domains (NADs) are linked to the RNA Polymerase I (Pol I) transcription status. The number of rDNA repeats (and the proportion of actively transcribed rRNA genes) is variable between cell types, individuals and disease state. Substantial changes in nucleolar morphology and size accompanied by concomitant changes in the Pol I transcription rate have long been documented during normal cell cycle progression, development and malignant transformation. This demonstrates how dynamic the nucleolar structure can be. Here, we will discuss how the structure of the rDNA loci, the nucleolus and the rate of Pol I transcription are important for dynamic regulation of global gene expression and genome stability, e.g., through the modulation of long-range genomic interactions with the suppressive NAD environment. These observations support an emerging paradigm whereby the rDNA repeats and the nucleolus play a key regulatory role in cellular homeostasis during normal development as well as disease, independent of their role in determining ribosome capacity and cellular growth rates. Although genetic information is encoded in a linear DNA sequence, the transcription of particular genes (or gene clusters) depends on the surrounding chromatin structure and higher-order chromosomal interactions. Eukaryotic chromatin is tightly packed into the nucleus with a portion compressed into subnuclear domains, one of which is the nucleolus. Nucleoli form around ribosomal RNA (rRNA) genes (rDNA) and dictate the nucleolar morphology and the positioning of nucleolar-associated chromatin domains (NADs) within the nucleus. rRNA genes were first visualized in yeast in the late 1960s by Miller and Beatty using Miller spreads, which provided structural details of actively transcribed rRNA genes, specifically showing a single rDNA repeat transcribed by a multitude of RNA Polymerase I (Pol I) complexes, which they described as the Christmas tree structure . In highIn humans, the rDNA genes are arranged in a head-to-tail orientation forming repeat arrays organized in the nucleolar organizer regions (NOR) at the short arm of the 5 acrocentric chromosomes. The precise organization and exact number of repeats is species, cell type and age dependent ,14. CanoThe upstream transcription enhancer elements (UTEEs), also known as the spacer promoter enhancer repeat, are another regulatory element located in the IGS . This isUpstream the enhancer boundary complex is flanked by nucleosomes, while downstream various components of the Pol I basal transcription apparatus were found, including Pol I, selectively factor -1 (SL-1), UBTF, RRN3, and TTF-1. The functional significance of these components is unclear as they are not involved in transcription. This is probably an artefact caused by the spatial proximity of the enhancer boundary complex and the core promoter, which leads to cross-linking of factors associated with the core promoter and the UTEE. It has been proposed that the enhancer boundary complex forms and serves as entry points for chromatin remodelling .Traditionally, with exception of the IGS, which mainly contains repetitive sequences and transposable elements, the rRNA genes are believed to be highly conserved among species; however, increasing evidence suggest that not all rRNA genes are identical and instead exist in several variants ,27,28. TThe concept of heterogeneous rDNA repeats and copy number variation was further strengthened by two recent studies , which analysed whole genome sequencing data from the 1000 genome project  and diffAnalysis of over 700 tumours and corresponding normal tissues revealed a coupling of 5S rDNA array expansion with a loss of 45S repeats, which was most prevalent in TP53 mutant cancers. However, these variations were considered within the limits of natural variability and did not mediate an overall decrease in rDNA transcriptional output per cell. Two studies  hypothesized that loss of copies of 45S rDNA may be caused by replicative stress, as a result of rapid replication and high rDNA transcription rates affecting sister chromatid cohesion. They suggested that this loss would be beneficial for cancer cells as excessive 45S rDNA copy numbers are believed to promote genomic stability by facilitating recombinational repair ,30. The In conclusion, genome-wide sequencing analysis ,14 and gThree key “basal” Pol I transcription factors have thus far been identified; these are SL-1, Pol I associated regulatory factor RRN3  and UBTF .SL-1 is a complex of the TATA-binding protein (TBP) and 4 TATA-binding protein-associated factors (TAF), TAFI48 (TAF1A), TAFI63 (TAF1B), TAFI110 (TAF1C) and TAFI41 (TAF1D) ,32. SL-1RRN3 has a unique HEAT repeat fold and regulatory serine phosphorylation sites . RRN3 inUBTF not only acts as an archetypal transcription activator but also facilitates post-initiation events  via a vaMore globally, UBTF1 has been reported to remodel chromatin, such as converting inactive rRNA genes into active chromatin by displacing linker histone 1 histones ,49,50, aAround two decades ago, two distinct Pol I subcomplexes were identified initially in yeast and later in humans (Pol Iα and Pol Iβ) ,41. BothPol I transcription is regulated in response to extracellular  or intracellular  stimuli by a number of mutually non-exclusive mechanisms, including post-translational modification of the Pol I machinery, alterations in rDNA topology, changes in rDNA chromatin structure and through non-coding RNAs .In response to environmental stimuli  and various stresses , components of the Pol I transcription machinery are targeted by a number of signalling pathways, including PI3K-mTOR, RAF-MEK-ERK, AMPK and AKT signalling, which often converge, forming a complex signalling network ,71,72,73In general, DNA topology is affected by transcription and replication. Top are a family of enzymes that release torsional stress at transcribed and replicated DNA loci. Two types of Top, Type I and Type II, relax supercoiled DNA by catalysing either single-strand or double-strand DNA breaks, facilitating DNA rotation or the passage of one DNA strand and re-ligation.Experiments in yeast showed that Top I is involved in alleviation of the negative superhelical density formed behind elongating Pol I, whereas Top II is required for resolving positive supercoiling formed ahead of the transcription complex .More recently, Denissov et al. revealed that regulatory elements, including the promoter, upstream region and terminator of actively transcribed genes, spatially interact throughout the cell cycle, forming so-called core–helix structures and Top I plays an essential role in maintaining this topology . This rDNon-coding RNAs were first described as regulators of rDNA transcription over a decade ago , specifiInterestingly, Abraham et al. proposed recently that Pol II-driven production of anti-sense transcripts originated from the rDNA IGS facilitated the formation of DNA–RNA hybrid structures, known as R-loops, at the boundaries of the IGS and coding rDNA regions. R-loops prevented Pol I-driven transcription of the IGS and also the production of sense intergenic noncoding RNAs (sincRNAs) that can negatively affect rRNA transcription . These fDrosophila oocytes suggested that actively transcribed rRNA genes were nucleosome depleted [It is well established that chromatin undergoes extensive and dynamic remodelling in order to modulate gene transcription. While repositioning and remodelling of nucleosomes, plus modifications of histones at specific sites , are central to the control of gene transcription, earlier studies in yeast and depleted ,90. Howedepleted . Currentdepleted ,92, whildepleted ,87.Integrative genomic analysis of human and mouse embryonic stem cells (ESCs) revealed similarities in the enrichment of euchromatic and heterochromatic histone marks ~2 kb upstream of the rDNA core promoter, while the other regions within the rDNA were markedly different ,94. A reA landmark study in 2008 presented evidence that, in fact, the rDNA repeats exist in three distinct chromatin configurations: (i) transcriptionally active rDNA repeats that are hypo-CpG methylated at the promoter-specific CpG, enriched for euchromatin histone marks and bound by UBTF; (ii) pseudo-silent/poised rDNA repeats that are hypo-CpG methylated at the promoter, bear repressive histone modifications, but are not bound by UBTF, and thus exist in a closed chromatin conformation; and (iii) silent rDNA repeats that are promoter hyper-CpG methylated and associated with heterochromatic histone marks adopting a highly compact chromatin state . The silIn contrast to the promoter-associated CpG methylation, the presence of CpG methylation within the rDNA coding region and its association with active transcription is still a matter of debate and complicated by their repetitive multi-copy nature. A recent study by Wang and Lemos reported that the rDNA CpG hypermethylation strongly correlated with aging, thus serving as an evolutionarily conserved biological clock . HoweverThe transcriptional pseudo-silent/poised rDNA chromatin conformation is established by nucleosome remodelling by deacetylation complexes  complexes, such as cohesin and condensin ,106,107,Overall, regulation of rDNA chromatin structure plays a pivotal role in maintaining the balance between actively transcribed, pseudo-silenced and silenced rDNA repeats, and thus is crucial for controlled responses to, e.g., stress, development, aging and genomic instability. Despite the identification of a number of key players, our understanding of these complex mechanisms, and in particular the crosstalk between them, is still limited, and the focus of ongoing research.The overall three-dimensional (3D) organization of the genome highly depends on the formation of chromatin contacts within and/or between each chromosome and the nuclear domain. These types of interactions include: (i) chromatin loop formation that bypass long genomic distances and connect distant genomic regions, such as enhancers and promoters; (ii) the formation of topologically associated domains (TADs) that are local-interacting DNA neighbourhoods; and (iii) regions where genomic loci interaction is driven by their transcriptional activity.Several studies have demonstrated a direct role for the nucleolus in genome organization and as a global modulator of all transcription  ,110,111.However, NADs are not solely enriched on transcriptionally silenced genes; a number of highly transcribed Pol III-dependent RNA genes are also NAD associated. The dynamic regulation of the NAD interactions with genomic loci still requires intensive study. Comparative Hi-C analysis of NAD interactions in human embryonic fibroblasts revealed that surprisingly most of these interactions remained unchanged when comparing proliferating and senescent cells, with the exception of specific satellite sequence clusters that segregate from the nucleoli after cells underwent replicative senescence . To shedInterestingly, most of the developmental Hox gene clusters rarely associated with the rDNA, supporting the idea of a highly coordinated framework of spatially and temporally defined genomic interactions . A recenTherefore, the number and size of nucleoli, which depends on the rate of Pol I transcription, can drive changes in the spatial organization of the genome, which directly modulates the global transcriptome. These findings indicate another layer of 3D transcriptional regulation, potentially playing an important role during normal cellular processes such as differentiation and aging, but may also, if dysregulated, be associated with malignant transformation.The first link between Pol I transcription and differentiation dates back to the 1940s where high levels of rRNA synthesis and large nucleoli were observed in stem cells while rates attenuated as cells differentiated. These observations were further confirmed by subsequent studies, e.g., Altmann and Leblond revealed that nucleolar morphology and size changes were associated with a loss in rRNA synthesis when columnar cells matured and migrated from the crypt to the villus in rats . ConsistAnother line of evidence supporting the notion that rDNA transcription is directly involved in the regulation/maintenance of pluripotency and differentiation is the fact that canonical pluripotency factors, such as Oct3–4/POU5F1, Nanog and Klf4, bind to the regulatory and transcribed regions of rDNA in mouse ESC, and this was also confirmed for Oct3–4/POU5F1  in humanThus, for many years, the decrease in the level of rRNA synthesis was regarded as a consequence of differentiation due to reduced metabolic requirements rather than being a driver. This view is now challenged by an increasing number of studies showing that inhibition of Pol I transcription can drive cell differentiation. A study by Hein et al. revealed that pharmacological inhibition of Pol I in murine models of AML and human AML cell lines led to an increase in apoptotic cell death, a delay in cell cycle progression and the induction of myeloid differentiation in leukemic blasts . In lineDrosophila ovarian germline stem cells (GSCs). GSCs are enriched for RiBi factors and display high levels of Pol I transcription compared to their differentiating daughter cell. Depletion of the Drosophila SL-1-like complex subunits under-developed (Udd) and TAF1B, resulted in reduced GSC proliferation and GSC loss. In contrast, overexpression of TIF-IA (RRN3) increased rRNA synthesis and impaired GSC differentiation [Prakesh et al. described the dynamic regulation of rRNA transcription during epithelial–mesenchymal transition (EMT) in breast cancer. While rRNA transcription and processing as well as RiBi-associated factors, including UBTF, RRN3 and nucleolin, are transiently increased during EMT, mesenchymal cells have reduced Pol I transcription. The elevation of rRNA transcription observed during EMT resulted from previously silenced rDNA repeats being activated by the release of TIP5 from the rDNA promoter, a decrease in rDNA promoter methylation and increase in H3Kme3 and H3K27ac. Interestingly, Snail1, a key regulator of EMT, is also recruited to the rDNA while cells undergo EMT . Pharmacntiation .Understanding how Pol I transcription and differentiation are mechanically linked is critical, as both are inherently important for normal development but are frequently  altered in cancer. The observation that Pol I transcription inhibition induces differentiation gives rise to the speculation that elevated rates of rRNA transcription may cause an opposite effect and induce (or at least contribute) the differentiation defect observed in malignancies. Further, it would explain why inhibition of Pol I restores a cancer cell’s ability to undergo differentiation. How the rate of rRNA synthesis affects cell fate requires further investigation. A possible mechanism may involve changes in long-range rDNA–NAD interactions caused by changes in the rate of Pol I transcription. As the level of transcription determines nucleolar size and morphology, and thus the sub-nucleolar organization of rRNA genes, changes in the rate of Pol I transcription will alter these and subsequently reorganize the rDNA–NAD interactome, potentially changing Pol II-dependent gene expression programs associated with pluripotency and differentiation.Collectively, these findings provide strong evidence that rRNA synthesis is critical for stem cell maintenance, and its downregulation can drive differentiation.Over the last decade, our concept of the nucleolus has emerged from being simply the site of RiBi to a multifunctional hub. Studies of the nucleolar proteome provided the first evidence by revealing that, of the total number of ~4500 proteins sequestered in the nucleolus, a large percentage was not associated with RiBi. For example, a significant number of DNA-damage response (DDR) proteins, including ~130 DNA repair proteins ,135,136,Saccharomyces cerevisiae revealed that loss of rDNA copies leads to a disequilibrium between active and inactive rRNA genes. Consistent with the findings in Saccharomyces cerevisiae, loss of mammalian Sir2-homolog SIRT7 induces excision and loss of rDNA copies, promoting rDNA instability and subsequent cellular senescence in primary human cells [+-dependent protein deacetylase SIRT7, a chromatin-silencing factor, is required for the stabilization of components of the NoRC to the rDNA and therefore is crucial for heterochromatin formation [rDNA genes are considered genomic hotspots of recombination; their repetitive nature and high transcription rate make these repeats highly susceptible to replicative stress and replication fork stalling, causing DNA DSBs . As mentan cells . The NADormation . AlternaNot only do rDNA copy number variations impact genome stability, a number of rDNA-associated factors have been reported to play a role in the maintenance of rDNA/genome integrity. Recent findings revealed that UBTF depletion leads to DNA damage, abnormal mitotic progression and formation of micronuclei. However, these effects on genome stability are not simply mediated by a reduction in rDNA synthesis since knockdown of RRN3 equally reduced Pol I transcription but failed to induce micronuclei formation . AnotherAnother structure thought to threaten genome stability is the R-loop. R-loops are RNA:DNA hybrids that form naturally when genes are actively transcribed, such as the ribosomal genes that have high rates of transcription and are GC-rich regions, both of which favour their formation . R-loopsOverall, it is conceivable that relocalization of rDNA to nucleolar caps as a result of DNA damage and/or Pol I inhibition, or alteration in rDNA copy numbers as a result of loss/mutation of some proteins, may affect the number and distribution of NADs. Such alterations of the NADs can lead to changes in the cellular transcriptome, which provides an explicit link between the role of rDNA loci in maintaining genomic integrity and controlling cell fate.The discovery of the plurifunctional nature of the nucleolus about two decades ago was rightly regarded by the scientific community as a paradigm shift, and since then our knowledge of the functions of the nucleolus and our understanding of the underlying molecular mechanisms have expanded significantly. It has become clear that the nucleolus plays a key role in various cellular processes, such as carcinogenesis, development, differentiation and aging. Recent studies indicate that the rDNA loci and Pol I transcription are important for the dynamic regulation of global gene expression via modulating long-range genomic interactions with the suppressive NAD environment. Research also demonstrates a role for the rDNA chromatin structure in the spatial organization of the genome and genome stability. However, there are many gaps in our understanding of the functions and structure of the nucleolus. Questions about how heterogeneous the rDNA is, whether rDNA heterogeneity manifests in heterogeneous ribosomes, what is the mechanism for selecting the rDNA copy number, and how is the ratio between active and inactive repeats selected and maintained, are just a few still to be satisfactory answered. Moreover, despite our new understanding of a range of functions, to which the nucleolus is pivotal; a picture as to how these functions are interrelated is still unclear. It is evident that further intensification of research aimed at a comprehensive understanding of the role of rDNA and the nucleolus, including its impact on cell fate is required. In more practical terms, it is tempting to speculate that, given the plurifunctionality of the nucleolus and its dependence on ongoing rDNA transcription, the efficiency of the recently described Pol I inhibitors to treat cancer may be mediated in part through their effect to disrupt the non-ribosomal functions of the nucleolus.


FST gene were significantly associated with wool quality traits in Chinese Merino sheep (Junken type), indicating that FST is involved in the regulation of hair follicle development and hair trait formation. The transcription regulation of human and mouse FST genes has been widely investigated, and many transcription factors have been identified to regulate FST gene. However, to date, the transcriptional regulation of sheep FST is largely unknown. In the present study, genome walking was used to close the genomic gap upstream of the sheep genomic FST gene and to obtain the FST gene promoter sequence. Transcription factor binding site analysis showed sheep FST promoter region contained a conserved putative binding site for signal transducer and activator of transcription 3 (STAT3), located at nucleotides −423 to −416 relative to the first nucleotide  of the initiation codon (ATG) of sheep FST gene. The dual-luciferase reporter assay demonstrated that STAT3 inhibited the FST promoter activity and that the mutation of the putative STAT3 binding site attenuated the inhibitory effect of STAT3 on the FST promoter activity. Additionally, chromatin immunoprecipitation assay (ChIP) exhibited that STAT3 is directly bound to the FST promoter. Cell proliferation assay displayed that FST and STAT3 played opposite roles in cell proliferation. Overexpression of sheep FST significantly promoted the proliferation of sheep fetal fibroblasts (SFFs) and human keratinocyte (HaCaT) cells, and overexpression of sheep STAT3 displayed opposite results, which was accompanied by a significantly reduced expression of FST gene (P < 0.05). Taken together, STAT3 directly negatively regulates sheep FST gene and depresses cell proliferation. Our findings may contribute to understanding molecular mechanisms that underlie hair follicle development and morphogenesis.Follistatin (FST) is a secretory glycoprotein and belongs to the TGF-β superfamily. Previously, we found that two single nucleotide polymorphisms (SNPs) of sheep  FST transgenic mice exhibited shinier and more irregular hair  , inner root sheaths (IRS), and the hair matrix . Hair folar hair . FST knowhiskers . Our preen Type) . CollectFST genes has been widely investigated, and many transcription factors have been identified to regulate FST gene. For example, erythroid 2 related factor (Nrf2) directly regulates FST gene and inhibits the apoptosis of human lung epithelial cells and A549 cells (FST gene is directly regulated by β-catenin/transcription factor 4 (TCF4) transcription factor complex to promote the murid myogenic differentiation and myoblast fusion in vitro and in vivo  in human keratinocytes , and our results demonstrated that FST gene is a target of STAT3 and that STAT3 inhibits cell proliferation at least partly via direct negative regulation FST gene expression.In this study, we investigated the transcription regulation of sheep All animal experiments were conducted according to the guidance for the care and use of experimental animals established by the Ministry of Science and Technology of the People’s Republic of China  and approved by the Laboratory Animal Management Committee of Northeast Agricultural University.2.HEK293T and HaCaT cells, purchased from the China Center for Type Culture Collection, were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) . Sheep fetal fibroblasts (SFFs), gifted from Dr. Tiezhu An, Northeast Forestry University, Harbin, were cultured in DMEM nutrient mixture F12 . All cells were cultured in the medium supplemented with 10% fetal bovine serum (FBS)  plus 1% penicillin/streptomycin  at 37°C in 5% COFST gene according to Ovis aries reference genome (ISGC Oar_v3.1/oviAri3). To close the genomic gap upstream of the sheep FST gene, genome walking was performed as previously described , 1 μL Kx Pfu DNA Polymerase (1 U/μL), 7.5 μL ZFP2primers (10 pmol/μL), and 1.5 μL FST-SP1 (10 pmol/μL). The first PCR conditions were as follows: initial denaturation at 94°C for 2 min, followed by 2 cycles , 98°C for 10 s, 25°C for 2 min, 25 to 68°C for 0.2°C/s, 68°C for 2 min, 6 cycles , with a final extension at 68°C for 5 min. The second and third PCRs were also conducted in a 50 μL reaction volume including 1 μL template, 10 μL dNTPs (2.5 mM), 25 μL 2 × Kx PCR Buffer (with Mg2+), 1 μL Kx Pfu DNA Polymerase (1U/μL), and 1.5 μL primers , and run with a thermal protocol of 94°C for 2 min, followed by 30 cycles , with a final extension at 68°C for 5 min. The third PCR product was resolved on a 1.2% agarose gel, recovered, and cloned into pEASY-T1 Simple Cloning Vector  for sequencing in both directions.There is a genomic gap immediately upstream of the sheep escribed . Brieflyescribed , using tescribed . Three FFST was assigned position + 1. The FST promoter sequences of different animal species were obtained from the UCSC website1. The conserved transcription factor binding sites were predicted by using the Mulan website tool2 with the option “optimized for function” in matrix similarity and “vertebrates” in biological species  of the initiation codon (ATG) of  species .FST and STAT3 expression vectors, based on FST (NM_001257093.1) and STAT3 (XM_015098787) sequences, two pairs of primers  from the pooled total RNA of sheep skin (n = 3) using the primer pairs FST-V and STAT3-V, respectively. The FST and STAT3 PCR products were individually ligated into the pCMV-Myc , and the resulting plasmids were named pCMV-Myc-FST and pCMV-Myc-STAT3, respectively.For the construction of FST promoter luciferase reporter vectors, the highly conserved region (−980/−340) of sheep FST promoter, which harbored the conserved putative STAT3 binding site (from −423 to −416), was PCR amplified with two primer pairs FST-P(+) and FST-P(−)  to yield two FST promoter reporters. The reporter with the FST promoter fragment in the right direction was named pGL3-FST(−980/−340) and the other one with the FST promoter fragment in opposite direction was named pGL3-FST(−340/−980).To construct FST-P(−)  using shFST promoter  using the Fast Mutagenesis System  and the primer pairs FST-M according to the manufacturer’s recommendation. The resulting reporter construct was named pGL3-FST(−980/−340)-mutSTAT3. All primers were synthesized by Invitrogen  and all constructs were confirmed by Sanger sequencing .There was only one putative STAT3 binding site “CGATTCCCC” in sheep FST promoter (locating from −423 to −416). The mutation of this putative STAT3 binding site was expected to prevent STAT3 from binding to the promoter . This si5 cells/well) and cultured in the DMEM medium supplemented with 10% FBS and 1% penicillin/streptomycin. After the HEK293T cell reached 70–80% confluence, HEK293T cells were co-transfected with either pGL3-basic, pGL3-FST(980/−340), pGL3-FST(−340/−980) or pGL3-FST(−980/−340)-mutSTAT3 and either pCMV-Myc or pCMV-Myc-STAT3 using Lipofectamine 2000  according to the manufacturer’s instructions. Dual-luciferase reporter assays were performed 48 h post-transfection using the dual-luciferase reporter assay system  according to the manufacturer’s instructions. The firefly luciferase (Fluc) signal was normalized to that of Renilla luciferase (Rluc).Briefly, the HEK293T cells were seeded in a 24-well plate (2 × 10Western blotting was performed to identify the two expression vectors (pCMV-Myc-FST and pCMV-Myc-STAT3). Briefly, HEK293T cells were transfected with pCMV-Myc-FST or pCMV-Myc-STAT3, 48 h after transfection, the cells were harvested in RIPA lysis buffer  containing 1% phenyl methane sulfonyl fluoride . After incubation on ice for 30 min, the supernatant was collected by centrifugation at 10, 000 × g for 5 min at 4°C. Equal amounts of protein from the cell lysates were separated by 12% sulfate dodecyl sodium-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to nitrocellulose membranes . After blocking with 5% (w/v) dry milk and 0.1% Tween 20 for 2 h, the membranes were incubated with Myc-tag mouse monoclonal antibody  at room temperature for 2 h. Subsequently, the membranes were incubated with horseradish peroxidase-conjugated secondary rabbit anti-mouse IgG (H&L) antibody  at room temperature for 1 h, followed by visualization using an ECL Plus detection kit .–ΔCt, ΔCt = CtIPsample][ − CtInputsample][  as previously described . Brieflytsample] . The amp4 cells/well) and cultured in the DMEM-F12 and DMEM medium, respectively, supplemented with 10% FBS and 1% penicillin/streptomycin. The cells were individually transfected with pCMV-Myc, pCMV-Myc-FST or pCMV-Myc-STAT3 for 24, 48, and 72 h, every well was added with 10 μL CCK-8 solution  and incubated at 37°C for 2 h, following the absorbance was measured at 450 nm using a Model 680 Microplate Reader . The cells transfected with pCMV-Myc were used as the negative control.The Cell Counting Kit-8 (CCK-8) assay was used to assay cell proliferation. Briefly, the SFFs and HaCaT cells were seeded in a 96-well plate  according to the standard procedures, and RNA quality was assessed by denaturing formaldehyde agarose gel electrophoresis. Reverse transcription was performed with ImProm-II Reverse Transcriptase  according to the manufacturer’s protocols.Ki67 and proliferating cell nuclear antigen (PCNA), were detected by quantitative real-time PCR (qPCR). The qPCR reaction volume was 20 μL containing 1 μL of cDNA, 10 μL of 2 × SYBR Green PCR MasterMix , 0.5 μL each of the forward and reverse primers (10 μM), and 8 μL double-distilled water. Thermal cycling consisted of an initial step at 95°C for 10 min followed by 40 cycles at 95°C for 30 s and 60°C for 30 s. The primers used for qPCR are listed in GAPDH) gene using the 2–ΔCt method, where ΔCt = Cttargetgene][-CtGAPDH][. The negative control was the cells transfected with pCMV-Myc.The expression of proliferation marker genes, t-test using SAS 9.1.3 . Statistical significance was indicated by ∗P < 0.05, ∗∗P < 0.01, or different letters above error bars indicating a statistical significance (P < 0.05).Results were expressed as the mean ± standard error of the mean (SEM), and all experiments were performed in triplicate. The equity of variance was tested using the Hartley F test and the result showed that the variance was homogeneous. In our present study, every group had three samples, which was not enough for normality testing. Because of the continuity and regularity of gene expression, we considered that the data were normally distributed. The statistical significance of differences was evaluated with the student’s FST gene according to Ovis aries reference genome (ISGC Oar_v3.1/oviAri3). To obtain the promoter sequence of the sheep FST gene, we first closed the genomic gap by genome walking. The results showed that the gap sequence was 775 bp in length and we submitted the sequence to GenBank (Accession No. MT917184). The complete genomic sequence immediately upstream of the initiation codon (ATG) of the sheep FST gene was obtained by sequence assembly using the acquired genomic gap sequence and the genomic sequence from the UCSC Genome Browser database (see text footnote 1). Then we performed sequence alignment of FST promoters (3-kb genomic sequences immediately upstream of the initiation codon (ATG) of FST genes) from various animal species, which were obtained from the UCSC Genome Browser database (see text footnote 1), including sheep, cow, pig, human, mouse, and rat. The result showed that there was a conserved region, which was located at the −1,900/−1 region of sheep FST gene promoter. Using Mulan website tool (see text footnote 2), several putative binding sites for transcription factors, such as homeobox A4 (HOXA4), E2F transcription factor 2 (E2F2), hepatocyte nuclear factor 4 (HNF4), and STAT3, were predicted within the conserved region of the sheep FST gene promoter. As shown in FST is not clear.There is a genomic gap immediately upstream of the sheep FST gene expression, firstly, we constructed and verified the STAT3 expression vector, pCMV-Myc-STAT3 by western blotting  was significantly reduced by 22.83% in the cells co-transfected with pCMV-Myc-STAT3, as compared with the cells co-transfected with pCMV-Myc  and either pCMV-Myc-STAT3 or pCMV-Myc were co-transfected into HEK293T cells, and chromatin immunoprecipitation (ChIP) assay was employed with anti-Myc antibody or mouse IgG (negative control). The ChIP-qPCR results exhibited that the FST promoter fragment (−547/−356) was significantly enriched  in the DNA immunoprecipitated by the anti-Myc antibody related to negative controls   were obtained from the DNA fragments immunoprecipitated by the anti-Myc antibody  by western blotting  Bioinformatics analysis showed that FST promoter harbored a conserved putative STAT3 binding site (FST promoter activity and that STAT3 inhibited the FST promoter activity (FST promoter (FST and STAT3 overexpression had opposite effects on the proliferation of SFFs and HaCaT cells (STAT3 overexpression inhibited the endogenous FST expression in SFFs and HaCaT cells (FOXL2) (IL-17A) (F-4), and B cell lymphoma 6 (Bcl-6)  Theactivity . (3) Thepromoter . (4) FuraT cells , 3 and taT cells . Moreove (FOXL2) , interle(IL-17A) , interfe (Bcl-6) . To our FST gene promoter, such as HOXA4, E2F2, and HNF4. Previous studies have demonstrated that HOXA4 and E2F2 were involved in the development of epidermis and dermis, as well as hair follicles -mutSTAT3 in the future.In the present study, we found that the STAT3 negatively regulated feration –3. ConsiFST overexpression promoted SFFs and HaCaT cell proliferation  and demonstrated that STAT3 inhibits the proliferation of SFFs and HaCaT cells at least in part via direct negative regulation of FST gene expression. Our findings will contribute to an understanding of the FST transcriptional regulation and the molecular mechanisms underlying hair follicle development. To gain a better understanding of the mechanisms underlying sheep hair follicle development and morphogenesis, in vivo studies will be needed to validate the regulatory relationship between STAT3 and FST in sheep hair follicle development.In summary, in the present study, we closed the genomic gap upstream of sheep genomic The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The animal study was reviewed and approved by all animal works were conducted according to the guidance for the care and use of experimental animals established by the Ministry of Science and Technology of the People’s Republic of China  and approved by the Laboratory Animal Management Committee of Northeast Agricultural University.NW designed the study and provided funding support. HX and GM carried out the experiments, analyzed data, and wrote the first draft of the manuscript. FM and BN contributed to the subject discussion. HL and NW critically revised the manuscript. All authors reviewed and approved the final version of the manuscript.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.


Vibrio cholerae, c-di-GMP can exert its effects via the transcription factors VpsT and VpsR. Together, these proteins activate genes needed for V. cholerae to form biofilms. In this work, we have mapped the genome-wide distribution of VpsT in a search for further regulatory roles. We show that VpsT binds 23 loci and recognises a degenerate DNA palindrome having the consensus 5′-W−5R−4[CG]−3Y−2W−1W+1R+2[GC]+3Y+4W+5-3′. Most genes targeted by VpsT encode functions related to motility, biofilm formation, or c-di-GMP metabolism. Most notably, VpsT activates expression of the vpvABC operon that encodes a diguanylate cyclase. This creates a positive feedback loop needed to maintain intracellular levels of c-di-GMP. Mutation of the key VpsT binding site, upstream of vpvABC, severs the loop and c-di-GMP levels fall accordingly. Hence, as well as relaying the c-di-GMP signal, VpsT impacts c-di-GMP homeostasis.Many bacteria use cyclic dimeric guanosine monophosphate (c-di-GMP) to control changes in lifestyle. The molecule, synthesized by proteins having diguanylate cyclase activity, is often a signal to transition from motile to sedentary behaviour. In  Vibrio cholerae  and three proteins: RbmA, RbmC and Bap-1  . Within clusters . In rugoclusters ,25. The vpsA, vpsL and rbm promoters, VpsT displaces the histone-like nucleoid structuring (H-NS) protein that otherwise silences transcription (rpoS transcription start sites (TSSs)  . Similar04 genes . The DNA04 genes . Effortsromoters ,32. Howeromoters ,29,32. IV. cholerae strains are derivatives of E7946  according to the protocol of Ali et al.  with Bowtie 2 using the QuasR package. MACS2 (v2.1.2) was used to identify ChIP-seq peaks where aligned reads were significantly enriched  compared to a control (without anti-FLAG antibody). Briefly, MACS2 exploits the characteristic bimodal distribution of sequencing reads at sites enriched by immunoprecipitation of transcription factors. This distribution, in single-end short read Illumina sequencing experiments, arises because only the 5′ ends of precipitated DNA fragments, on each strand either side of the transcription factor binding site, are sequenced. Hence, the actual position of DNA binding is in the centre of the offset peak maxima for each DNA strand  as previously described  in our ChIP-seq analysis . Co. CoV. chsT Table . The funsT Table . Binding control .et al. showed binding of VpsT to a DNA palindrome at the vpsL regulatory region   . To aid (bottom) . Whilst et al. used DNAse I footprinting to locate VpsT binding upstream of vpsL . Conversely, in the presence of c-di-GMP, VpsT could elicit a substantial footprint (lane 3). Mutations −216C (lanes 4 and 5) −213T (lanes 6 and 7) and −200G (lanes 12 and 13) target positions in the Zamorano-Sánchez et al. logo but beyond the boundaries of the ChIP-seq derived motif. None of these mutations altered VpsT binding. Mutations −208T and −203T target positions conserved in both motifs. Whilst the −208T mutation had no impact (lanes 8 and 9) the −203T mutation abolished VpsT binding (lanes 10 and 11).Recall that Zamorano-Sánchez  of vpsL . Figure mary TSS . The cenmary TSS . To furtvpsL, by DNAse I footprinting  a motif was found but the most highly conserved positions, usually −3C and +3G, were inverted  operon that contains three genes: vpvA, vpvB and vpvC. Importantly, whilst VpvA and VpvB are hypothetical proteins of unknown function, VpvC is a diguanylate cyclase contributing to the corrugated morphology of rugose phase variants . Hence, activation of vpvAP1 by VpsT does not require T-box II. To confirm the importance of T-box I we altered the sequence of this DNA element in the context of the truncated DNA fragment. The mutations are indicated by red text in Figure vpvAP2Mut. Mutation of T-box I abolished activation of vpvAP1by VpsT . In a final experiment, we deleted T-box I completely and activation by VpsT was similarly ablated .To further understand interplay between the promoter and T-box sequences we made derivatives of the d Figure , ΔvpvAP2vpvABC, which encodes a diguanylate cyclase. We reasoned that this should constitute a positive feedback loop dependent on T-box I. To test this, we made alterations to the chromosomal vpvABC regulatory region. Specifically, we deleted a 60 bp section of chromosomal DNA, containing vpvAP2 and T-box II, before making a derivative of this strain with point mutations in T-box I. The chromosomal changes are equivalent to the ΔvpvAP2 and ΔvpvAP2Mut constructs described above for lacZ fusion assays. We also examined the effect of deleting vpsT or vpvABC. To assess the consequences, we used a plasmid encoded intracellular c-di-GMP biosensor ..−5R−4[CGs Figure  and 3B. s Figure  and 4B. ed genes . The unued genes . Hence, pression ,32. Thisind H-NS . Hence, vpvAP1 and vpvAP2 promoters have different roles. The latter is constitutively active whilst vpvAP1 is activated by VpsT . Th. ThvpvAP2 Figure  47,48).,48.vpvAPy Figure . Hence, P Figure . Deletioy Figure . Howevers Figure . The stas common ,51. If sOriginal DNA sequencing data are available from ArrayExpress using the accession numbers provided above. Original gel mages are provided as supplementary material. All other data are available from the authors upon request.gkab1194_Supplemental_FilesClick here for additional data file.


Drosophila embryos. Quantitative live imaging analysis revealed that the timing and the continuity of burst induction are common regulatory steps on which core promoter elements impact. We further show that the upstream TATA also affects the burst amplitude. On the other hand, Inr, MTE and DPE mainly contribute to the regulation of the burst frequency. Genome editing analysis of the pair-rule gene fushi tarazu revealed that the endogenous TATA and DPE are both essential for its correct expression and function during the establishment of body segments in early embryos. We suggest that core promoter elements serve as a key regulatory module in converting enhancer activity into transcription dynamics during animal development.Regulatory interactions between enhancers and core promoters are fundamental for the temporal and spatial specificity of gene expression in development. The central role of core promoters is to initiate productive transcription in response to enhancer's activation cues. However, it has not been systematically assessed how individual core promoter elements affect the induction of transcriptional bursting by enhancers. Here, we provide evidence that each core promoter element differentially modulates functional parameters of transcriptional bursting in developing  Communication between enhancers and core promoters is critical for the temporal and spatial specificity of gene expression. Enhancers are distal regulatory elements that contain a cluster of binding sites for sequence-specific transcription factors and co-activators, which usually span several hundreds to thousands base pairs (bp) in length. Recent quantitative imaging studies reported that enhancers are responsible for driving transcriptional bursting from their target genes e.g. . HoweverDrosophila   is typicosophila . The preosophila , which iosophila . We prevosophila . HoweverDrosophila MS2 strains that contain a variety of core promoter modifications at different positions. Quantitative image analysis revealed that each core promoter element differentially modulates the functional parameters of transcriptional bursting in developing embryos. Our data suggest that the timing and the continuity of burst induction are common regulatory steps on which core promoter elements impact. We also show that core promoters use the upstream TATA to increase the amplitude of transcriptional bursting upon activation by distal enhancers. On the other hand, Inr, MTE and DPE mainly contribute to the regulation of the bursting frequency. In addition, promoter-proximal Zelda sites were found to facilitate burst induction at the beginning of new cell cycle, adding another layer of complexity to this process. To further dissect the function of core promoter elements in the context of endogenous genome, we combined genome editing and site-directed transgenesis. Using the pair-rule gene fushi tarazu (ftz), we show that both TATA and DPE mutations dramatically change transcription dynamics throughout its expression domains, resulting in disrupted spatial patterning of gene expression and misregulation of the downstream segment polarity gene engrailed (en). We therefore suggest that core promoter elements serve as a key regulatory module in converting enhancer activity into transcription dynamics during animal development.Importantly, quantitative measurement of enhancer responsiveness has been technically challenging with traditional bulk approaches because transcriptional output is controlled not only by core promoter sequences, but also by combinatory effects of surrounding regulatory landscapes such as enhancer strength and chromosome topology , mInr-MS2-yellow-sna shadow enhancerDSCP (this study), mMTE-MS2-yellow-sna shadow enhancerDSCP (this study), mDPE-MS2-yellow-sna shadow enhancerDSCP (this study), mGAGA-MS2-yellow-sna shadow enhancerDSCP (this study), 3xZelda-MS2-yellow-sna shadow enhancerDSCP (this study), WT-MS2-yellow-rhoNEEDSCP (this study), mTATA-MS2-yellow-rhoNEEDSCP (this study), mInr-MS2-yellow-rhoNEEDSCP (this study), mMTE-MS2-yellow-rhoNEEDSCP (this study), mDPE-MS2-yellow-rhoNEEDSCP (this study), WT-MS2-yellow-sna shadow enhancerlabPr (this study), TATA-MS2-yellow-sna shadow enhancerlabPr (this study), WT-MS2-yellow-gypsy-sna shadow enhancerDSCP (this study), WT-MS2-yellow No enhancerDSCP (this study), WT-MS2-yellow-IAB5 enhancerDSCP (this study), mTATA-MS2-yellow-IAB5 enhancerDSCP (this study), mDPE-MS2-yellow-IAB5 enhancerDSCP (this study), WT-MS2-yellow-sna shadow enhancersnaPr (this study), mTATA-MS2-yellow-sna shadow enhancersnaPr (this study), 3xZelda/mTATA-MS2-yellow-sna shadow enhancerDSCP (this study), WT-MS2-yellowrhoNEE-rhoPr (this study), mTATA-MS2-yellowrhoNEE-rhoPr (this study), mDPE-MS2-yellowrhoNEE-rhoPr (this study), Δftz-attP/TM6 (this study), ftz WT core promoter-ftz-HA-24xMS2 (this study), ftz mTATA core promoter-ftz-HA-24xMS2/TM6 (this study) and ftz mDPE core promoter-ftz-HA-24xMS2/TM6 (this study).In all live-imaging experiments, we studied mRFP/CyO , DSCPWT-enhancer , DSCPmTAPlasmid construction is detailed in the supplementary materials.vas-phiC31 strain  were co-injected. Injection mixture contains 500 ng/μl MS2 plasmid, 500 ng/μl phiC31 expression plasmid, 5 mM KCl, 0.1 mM phosphate buffer, pH 6.8. mini-white marker was used for screening. Resulting ftz complementation alleles were balanced over TM6. After phiC31-mediated integration, extra sequences derived from plasmid backbone, ampicillin resistant gene and mini-white marker gene were also incorporated into the ftz locus.First, endogenous O strain . InjectiTotal RNA was extracted from 40 adults of Oregon-R using TRIzol reagent (Thermo Fisher) followed by chloroform purification and isopropanol precipitation. Three μg of total RNA was subjected to reverse transcription using PrimeScript 1st strand cDNA Synthesis Kit (Takara).in vitro Transcription T7 Kit (Takara). Template DNA for ftz probe was PCR amplified from genomic DNA using primers (5′-CGT AAT ACG ACT CAC TAT AGG GTG GGG AAG AGA GTA ACT GAG CAT CGC-3′) and (5′-ATT CGC AAA CTC ACC AGC GT-3′). Template DNA for en probe was PCR amplified from cDNA using primers (5′-CGT AAT ACG ACT CAC TAT AGG GCA TGA ACT TGC TTT AGC ACA AAC ATT TCG-3′) and (5′-CAA CTA ATT CAG TCG TTG CGC TCG-3′). Template DNA for sna probe was PCR amplified from genomic DNA using primers (5′-CGT AAT ACG ACT CAC TAT AGG GCA GTT GGC TTA ACA GTA CTG-3′) and (5′-ACC TGT CAC AGC CAC CTC AGC-3′). Antisense MS2 probe was in vitro transcribed using T3 RNA polymerase (NEB). Templated DNA was prepared by linearizing pBlueScript-MS2 plasmid  or biotin  were transcribed using  plasmid  with Ecohttps://fiji.sc).Embryos were dechorionated and fixed in fixation buffer  for ∼25 min at room temperature. Vitelline membrane was then removed by shaking embryos in a biphasic mixture of heptane and methanol for ∼1 min. Antisense RNA probes labeled with digoxigenin and biotin were used. Hybridization was performed at 55°C for overnight in hybridization buffer . Subsequently, embryos were washed with hybridization buffer at 55°C and incubated with Western Blocking Reagent (Roche) at room temperature for 1 h. Then, embryos were incubated with sheep anti-digoxigenin (Roche) and mouse anti-biotin primary antibodies (Invitrogen) at 4°C for overnight, followed by incubation with Alexa Fluor 555 donkey anti-sheep (Invitrogen) and Alexa Flour 488 goat anti-mouse (Invitrogen) fluorescent secondary antibodies at room temperature for 1 h. DNA was stained with DAPI, and embryos were mounted in ProLong Gold Antifade Mountant (Thermo Fisher). Imaging was performed on a Zeiss LSM 900 confocal microscope. Plan-Apochromat 20×/0.8 N.A. objective was used. Images were captured in 16-bit. Maximum projections were obtained for all z-sections, and resulting images were shown. Brightness of images was linearly adjusted using Fiji  equipped with Moticam 10+ (Motic).nanos >MCP-GFP, His2Av-mRFP/CyO .rhoNEE reporters (https://fiji.sc). In the second method, His2Av images were first blurred with Gaussian filter to generate smooth images. Pixels expressing intensity higher than 5% of the global maxima in the histogram of His2Av channel were removed. Processed images were converted into binary images using a custom threshold-adaptative segmentation algorithm. Threshold values were determined at each time frame by taking account of (i) the histogram distribution of His2Av channel and (ii) the number and the size of resulting connected components. Boundaries of components were then modified to locate MS2 transcription dots inside of nearest nuclei. In brief, pixels with intensity twice larger than mean intensity of MS2 channel were considered as transcription dots, and new binary images were created for each time frame. The Euclidean distances between the centroid of binarized transcription dot and all boundaries of segmented nuclei were calculated. Boundary of the nucleus with the smallest Euclidean distance was modified in order to capture transcription dot within a nucleus. Centroids of connected components in nuclei segmentation channel were used to compute the Voronoi cells of the image. Resulting binary images were manually corrected by using Fiji (https://fiji.sc).For each time point, maximum projection was obtained for all z-sections per image. His2Av-mRFP was used to segment nuclei. 512 × 512 maximum projection images were initially cropped into 430 × 430 Figures  or 300 ×eporters , 512 × 5Nuclei tracking was done by finding the object with minimal movement across the frames of interest. For each nucleus in a given frame, the Euclidean distances between the centroids of the nucleus in the current time frame and the nuclei in the next or previous time frame were determined. The nucleus with the minimum Euclidean distance was considered as the same lineage.α is the local background intensity, I0 is the amplitude of the peak fluorescence intensity, x0 and y0 are the center of the peak, xσ and yσ are the spreads of the fluorescent dot. When the size of estimated fluorescent dot was larger than a fitted region of 11 × 11 pixels due to a low-quality fitting, whole time-point data of corresponding nucleus was excluded from further analysis. (iii) The intensity of MS2 transcription dot was calculated as 3D raw images with all z-sections of MCP-GFP channel were used to record MS2 fluorescence signals. Using segmented regions from max projected images of His2Av-mRFP channel, fluorescence intensities within each nucleus were extracted. 3D fluorescence values were assigned to the nearest segmented regions of projected images. Signals of MS2 transcription dots were determined by calculating an integral of fluorescence intensities around the brightest pixel within each nucleus using a 2D Gaussian fitting method as described below. (i) The xyz position of transcription site was determined as a brightest pixel in each nucleus. (ii) A 2D Gaussian fitting was performed in a 11 × 11 pixels region with a single z-plane centering the transcription site to estimate a fluorescent dot intensity and local background. Fitting was performed with the following formulackground . SubsequA transcriptional burst was defined as a local change in fluorescence intensity. First, signal trajectories were smoothed by averaging within a window of 5 timeframes. When a nucleus had above-threshold transcription activity, burst was considered to be started. Burst was considered to be ended when the intensity dropped below 55% of the local peak value of each burst. Location of defined burst was then moved 2 timeframes afterwards to better capture the center of individual bursting event. When the burst duration is less than 5 timeframes, it was considered as a false-positive derived from detection noise. It was confirmed that this filtering method does not affect quantification of the burst duration . When siFrom each trajectory, number of bursts, amplitude and duration of each burst, and total integrated signal (output) produced by each nucleus were measured. To determine amplitude, the peak value during the burst was measured using trajectories after smoothing by averaging within a window of 5 timeframes. The duration was determined by measuring the length of each burst. Total output was measured by taking the area under the raw trajectory. The amplitude and duration for each nucleus were determined by taking average of all analyzed bursts in a single nucleus. The rate of burst induction was determined as a frequency divided by a length of time after the initial burst for each active nucleus.For each time frame, nuclei with MS2 intensity above the threshold were considered as active. Threshold was determined for each group of nuclei by calculating the 10% of the maximum MS2 intensity across all trajectories.MS2 intensities in instantaneously active nuclei at each time point were averaged.Autocorrelation values were used to estimate a periodicity of each MS2 trajectory. First, MS2 trajectories were smoothed as described in the previous section. To extract periodicity, the first derivative of smoothed MS2 signal was calculated to exclude general trends of signal changes during nc14. The autocorrelation value was calculated with 16.8 s timestep lags according to the time resolution of live-imaging data (16.8 s/frame). All autocorrelation values were normalized to 1 at the smallest lag time. Random data was generated from time-shuffled MS2 trajectories of the WT reporter by using MATLAB rand function.ftz mRNAs were considered to be linearly degraded with a half-life of 7 min according to previous measurements in early embryos  (even-skipped (eve) core promoter containing TATA, Inr, MTE and DPE at optimal positions relative to the TSS  shadow enhancer . Transgenes were integrated into a specific genomic landing site via phiC31-mediated transgenesis  , a modifS Figure . The user Figure , which dr Figure  36,37).,37.Drososgenesis ,38. Imposgenesis , indicatsna shadow enhancer induces fewer number of transcriptional bursts from the MTE mutant (mMTE) than the WT    (Supplem(rhoNEE) . Furtherus locus . Overallus locus . We founsna shadow enhancer could only induce bursts with substantially lower amplitude from the TATA mutant (mTATA) . ,21. 7,21) Figure , suggest) Figure ,42–48. B) Figure , indicat) Figure . As seen) Figure  and I, r) Figure . Strong e rhoNEE  or the mnhancers . We therDrosophila homeotic (Hox) genes are typically depleted of TATA  lacks an optimal TATA motif  was linked to the mTATA DSCP , bu, buDrosopromoter . We founpromoter –D. On thpromoter  and an opromoter . Especiapromoter , suggestpromoter . Intrigupromoter . To exampromoter . At thishairy and paired lack TATA but contain promoter-proximal Zelda sites in Drosophila  (ftz is expressed in seven transverse stripes spanning across the anterior-posterior (AP) axis and is regulated by multiple enhancers located 5′ and 3′ of the transcription unit  was specifically lost from even-numbered stripes in mTATA and mDPE embryos  . ftz is ion unit . The ftzs Figure  49). Re. Refushinhancers . To test editing . Subsequs Figure . Fluoresn Figure , indicatn Figure . As a cos Figure . Cuticles Figure  and F. Wftz-MS2 complementation alleles. We focused on anterior stripe 1/2 and posterior stripe 5/6  .,68.ftz-Ms Figure  and F, ts Figure  and C, ws Figure  and C. As Figure . We thens Figure , individs Figure , suggests Figure  and the s Figure . We founs Figure  and alsos Figure . Importas Figure , suggestic locus . We ther: 7 min) . Althoug: 7 min) –F, both : 7 min) . Thus, wDrosophila embryos. Our data suggest that Inr, MTE and DPE mainly affect the frequency of transcriptional bursting by changing the timing of first burst and the continuity of subsequent bursts .Original live imaging data have been deposited to Zenodo database (gkab1177_Supplemental_FilesClick here for additional data file.


Genome Organization and Dynamics section of Frontiers in Molecular Biosciences is to provide a central forum for discussing and distributing high-quality scientific observations, concepts, and philosophies to all areas related to genome function and preservation.In encoding the fundamental information to create a cognate cell, genomes are often referred to as the blueprints of life. Yet, a perfunctory consideration of a common blueprint only envisions a flat almost lifeless paper. In reality, blueprints are lively conduits of work with the paper being rolled, folded, and even crumpled while the contents are continuously read, revised, and expanded to guide the construction of structures with balance and beauty. Comparatively, genomes are continuously read, modified, and reworked to mediate cell fate decisions and support cell health throughout all life stages and physiological conditions. Given the central importance of genomes, it is imperative to carefully shield chromosomes to ensure self- and species-preservation, yet the DNA must also be readily accessible to allow on-demand use of the information. To balance these two critical features cells have developed highly efficient systems to read, replicate, repair, and store genomic information. Intriguingly, despite decades of effort, we have only scratched the surface of our comprehension on how each system works as well as understanding how the various pathways intercommunicate to function in harmony and ensure homeostasis. The objective of the Genome Organization and Dynamics has interests in highlighting all nuclear processes/pathways including chromatin, transcription, DNA repair, telomeres, DNA replication, 3D chromosome organization, and the nucleoskeleton under both normal and disease conditions. We also welcome articles exploring the cutting-edge tools that are providing unprecedented insights into the various genome-associated pathways including physical and computational tactics based on molecular, biochemical, or cell biological assays focusing on single or bulk cell populations. In addition, we are open to serving as a platform to debate emerging concepts within the various fields of study. For further guidance, a few vignettes of exemplary topics are provided below.Transcription is the process of converting the information encoded in a strand of DNA into RNA. While it was popularized by the central dogma of molecular biology describing the flow of genetic information as “DNA makes RNA and RNA makes protein” , it is nA deceivingly simple question that remains unresolved is determining how each transcription factor finds its cognate DNA element in a physiologically timely and useful manner. It has long been appreciated that activated transcription factors, even ones residing in the cytoplasm when quiescent, only require a few minutes to engage the appropriate response elements to drive a productive gene program . Yet, hoOnce a transcription factor engages an appropriate DNA element there are several potential outcomes including controlling gene promoter activity through proximal (upstream activating sequences) or distal (enhancer) sites, opening heterochromatic areas (pioneering factors), or mobilizing chromosome regions (genome reorganization) . IntriguGenome Organization and Dynamics is interested in exploring all facets of the transcription process—from the cellular roles of non-coding RNAs to the mechanisms of RNA polymerase movements  to the involvement of nuclear bodies . Beyond transcription, we will also feature articles exploring how transcription intersects with other pathways working in the nucleus under normal and disease conditions.In addition to the described topics, The genomes of most, if not all, organisms across the kingdoms of life are compacted and organized into chromatin through the actions of select factors including histones/histone-like proteins and non-coding RNAs . InitialGenome Organization and Dynamics is eager to highlight work on chromatin features of all organisms from bacteria to archaea to plants and animals. It is well-known that eukaryotes use nucleosomes as the basic structural units to package DNA into chromatin , or physiological status ], the histone proteins are biochemically modified to mark nucleosomes thereby triggering the recruitment/retention of select proteins to perform requisite work. Basically, the sequential modification of a nucleosome serves as a breadcrumb trail guiding the nucleation of specific proteins in a set order at a precise location. The most frequently considered variations to nucleosomes are post-translational modifications  of the histone tails commonly referred to as the histone code , and is essential in most eukaryotes (budding yeast is an exception) . H2A.Z iGenome Organization and Dynamics. We are pleased to consider all areas of chromatin biology including how histone-like proteins influence bacterial biofilms, the impact of chromosome inactivation on sex determination, or the role of heterochromatin in the aging process just to name a few.Epigenetic features from the histone code to histone variants are just a few of the chromatin-related topics that interest How genetic material within a cell is organized has long been studied . While eAlthough the phenomenon of precise 3D genome packaging is now well established , how suc


Transcription factors (TFs) bind specifically to TF binding sites (TFBSs) at cis-regulatory regions to control transcription. It is critical to locate these TF-DNA interactions to understand transcriptional regulation. Efforts to predict bona fide TFBSs benefit from the availability of experimental data mapping DNA binding regions of TFs (chromatin immunoprecipitation followed by sequencing - ChIP-seq).https://unibind.uio.no/), a dedicated RESTful API, and as genomic tracks. Finally, we provide an enrichment tool, available as a web-service and an R package, for users to find TFs with enriched TFBSs in a set of provided genomic regions.In this study, we processed ~ 10,000 public ChIP-seq datasets from nine species to provide high-quality TFBS predictions. After quality control, it culminated with the prediction of ~ 56 million TFBSs with experimental and computational support for direct TF-DNA interactions for 644 TFs in > 1000 cell lines and tissues. These TFBSs were used to predict > 197,000 cis-regulatory modules representing clusters of binding events in the corresponding genomes. The high-quality of the TFBSs was reinforced by their evolutionary conservation, enrichment at active cis-regulatory regions, and capacity to predict combinatorial binding of TFs. Further, we confirmed that the cell type and tissue specificity of enhancer activity was correlated with the number of TFs with binding sites predicted in these regions. All the data is provided to the community through the UniBind database that can be accessed through its web-interface (UniBind is the first resource of its kind, providing the largest collection of high-confidence direct TF-DNA interactions in nine species.The online version contains supplementary material available at 10.1186/s12864-021-07760-6. The regulation of gene expression is a complex process involving several biological mechanisms. The first step of the regulatory process controls where, when, and at which intensity RNAs are transcribed from their DNA template. This level of transcriptional regulation is mainly coordinated by transcription factors (TFs), which are DNA-binding proteins that recognize and bind short DNA sequences - their TF binding sites (TFBSs) . TFs areThe most popular experimental assay to detect TF-DNA interactions in vivo is chromatin immunoprecipitation followed by sequencing (ChIP-seq) . After mThe TFBSs recognized by a TF are short ~ 10 bp-long) and degenerate sequences that can be modeled computationally for further predictions. The most widely used computational representations of TFBSs for a given TF are position weight matrices (PWMs), which summarize the probability of observing each nucleotide at each position within a set of observed TFBSs. Such computational models have recurrently been used to predict TFBSs in DNA sequences. For instance, one can apply PWMs to predict TFBSs in open chromatin regions (e.g. derived from DNase-seq or ATAC-seq  bp-long ) or TF CPrevious efforts used PWMs to predict TFBSs within ChIP-seq peaks and made the predictions freely available –17. ThesArabidopsis thaliana, Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Homo sapiens, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae, and Schizosaccharomyces pombe. After quality control, we provide the community with a robust collection of ~ 56 million TFBSs for 644 TFs in 1096 cell lines and tissues and > 197,000 cis-regulatory modules. A functional inspection of these TFBSs and CRMs highlighted that they are evolutionarily conserved and enriched at active cis-regulatory regions. Furthermore, we showed that this unique collection of TFBSs can predict TF binding combinatorics at cis-regulatory regions. Finally, we confirmed that a lower number of TFs binding at enhancers was associated with higher cell type and tissue specificity for these enhancers and vice-versa. The UniBind database is freely available online (https://unibind.uio.no/), through a programmatic RESTful API (https://unibind.uio.no/api/), and via genomic tracks (https://unibind.uio.no/genome-tracks/). Finally, it is accompanied with an enrichment tool to predict TFs with an enrichment of TFBSs in user-provided genomic regions (https://unibind.uio.no/enrichment/).In this report, we describe the update of the UniBind database, which now stores > 72 million direct TF-DNA interactions predicted using an updated ChIP-eat pipeline on ~ 10,000 ChIP-seq peak datasets from nine species: We aimed at providing a collection of direct TF-DNA interactions by combining experimental and computational approaches in several species. We applied an updated version of the ChIP-eat pipeline  to ChIP-Arabidopsis thaliana, Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Homo sapiens, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae, and Schizosaccharomyces pombe. For 10,264 datasets, we were able to associate a TF binding profile in JASPAR with the ChIP’ed TF. The ChIP-eat pipeline was applied to each ChIP-seq peak dataset - JASPAR PWM pair independently to predict TFBSs. ChIP-eat identified enrichment zones to predict direct TF-DNA interactions in 9654 datasets. Altogether, this analysis culminated with the prediction of ~ 72 million TFBSs in ChIP-seq peaks for 841 TFs in 1316 cell lines and tissues . In the database, the datasets are annotated with information about the ChIP’ed TF (UniProt ID  range with 0 representing ubiquitous enhancer activity and 1 exclusive expression activity.


Transcriptional regulation is essential for the correct functioning of cells during development and in postnatal life. The basic Helix-loop-Helix (bHLH) superfamily of transcription factors is well conserved throughout evolution and plays critical roles in tissue development and tissue maintenance. A subgroup of this family, called neural lineage bHLH factors, is critical in the development and function of the central nervous system. In this review, we will focus on the function of one subgroup of neural lineage bHLH factors, the Neurod family. The Neurod family has four members: Neurod1, Neurod2, Neurod4, and Neurod6. Available evidence shows that these four factors are key during the development of the cerebral cortex but also in other regions of the central nervous system, such as the cerebellum, the brainstem, and the spinal cord. We will also discuss recent reports that link the dysfunction of these transcription factors to neurological disorders in humans. The interest to understand the molecular mechanisms that generate our central nervous system has never been greater, as the intensive work of clinicians, neurologists, and developmental biologists demonstrate that several naturally occurring neurological disorders originate from deficits impairing brain development in humans  transcription factors are master regulators of cell proliferation and key in neuronal differentiation and specification , as well as on the function of these factors in the development of other areas of the central nervous system. In addition, we will discuss The bHLH superfamily of transcription factors contains numerous genes crucial for the regulation of gene expression in most eukaryotic organisms. These factors are classified according to the similarities in their protein structure and the characteristic presence of a basic domain that directly binds to chromatin as well as a Helix-loop-Helix (HLH) domain that comprises of a non-conserved loop region connecting to alpha-helices  and a class B  proneural or determination factors  and (ii) differentiation factors [predominantly expressed in postmitotic neurons  Differentiation factors. These genes encompass most of the neural lineage bHLH transcription factors and are predominantly expressed by differentiated neurons, in which they regulate fate specification and neuronal identity maintenance. Members of this group include Neurod1, Neurod2, Neurod6, Bhlhe22.(ii) Neurod1 can be first detected around embryonic day 12 in the dorsal ventricular zone (VZ) of mice , which contains transit-amplifying progenitors that contribute to the generation of most of the excitatory neurons that form the mature cortex. In the postnatal life, Neurod1 expression is retained in the cerebral cortex, particularly in most excitatory pyramidal neurons that form the upper-most layers of the cortex  are generated from progenitor cells located in the ventricular and subventricular zone of the dorsal telencephalon see . Soon afbHLH genes cooperate to control transcriptional programs that select different aspects of neural progenitor cell biology and effectively determine neuron subtype identity. Proneural bHLH genes in the telencephalon, such as Neurog1 and Neurog2, activate transcriptional cascades of gene expression in progenitor cells that eventually lead to their terminal neuronal differentiation  showed that environmental enrichment upregulates Neurod1 expression in their forebrain, which greatly improves their learning abilities  neurons , which directly receives instructive signals from the roof plate . More recently, Sega and colleagues found de novo mutations in NEUROD2 in two unrelated children diagnosed with early infantile epileptic encephalopathy and developmental delay  have been shown to be able to remodel chromatin and induce neuronal differentiation in progenitor cells, but they are also capable of reprogramming differentiated non-neuronal cells into neurons (Castro et al., ST, VT, and LH-M wrote the original draft and reviewed the literature. ST, VT, and LH-M revised the original draft. LH-M edited the final draft. All authors contributed to the article and approved the submitted final version.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.