E. coli sigma factor 70 (σ70)- and B. subtilis σB-, σF- and σW-dependent promoters to construct prediction models, capable of both predicting promoter TIF and orthogonality of the σ-specific promoters. This is achieved by training a convolutional neural network with high-throughput DNA sequencing data from fluorescence-activated cell sorted promoter libraries. This model functions as the base of the online promoter design tool (ProD), providing tailored promoters for tailored genetic systems.To engineer synthetic gene circuits, molecular building blocks are developed which can modulate gene expression without interference, mutually or with the host’s cell machinery. As the complexity of gene circuits increases, automated design tools and tailored building blocks to ensure perfect tuning of all components in the network are required. Despite the efforts to develop prediction tools that allow forward engineering of promoter transcription initiation frequency (TIF), such a tool is still lacking. Here, we use promoter libraries of  E. coli and B. subtilis promoter libraries using FACS and HTS, from which an online promoter design tool has been developed using CNN.Automated design tools and tailored subunits are beneficial in fine-tuning all components of a complex genetic circuit. Here the authors create  Therefore, enhancing the performance of microbial cell factories, by simultaneously varying genetic parts that determine the expression profile of the heterologous production pathway, has proven a successful strategy7. More recently, the ability for precise and reliable gene expression fine-tuning has become even more important with the emergence of genetic circuit engineering. Here, whole synthetic biological systems with artificial programs for controlling gene expression are engineered, for which the ability to precisely tune the expression levels of all components in the network is a requisite for functional signal transfer10.The flux through a metabolic pathway is not the result of multiple individual enzymatic reactions, with a single rate-limiting step determining the production rate. In concordance with these findings since the late 1990s, the emphasis of metabolic engineering shifted from overexpressing single genes to a more integrated approach that recognizes the importance of gene expression fine-tuning to balance all reactions in a multigene pathway9. In prokaryotes, the synthesis rate of RNA and subsequent protein can be directly regulated by altering the DNA sequence of the promoter and ribosome binding site (RBS), which determine their affinity for, respectively, the RNA polymerase and ribosome12. Also, synthesis rates can be modulated by using various (transacting) transcriptional and translational activators or repressors, such as LacI variants, STARs, dCas9/gRNAs, and sRNAs16. Other strategies include controlling the degradation rates of RNA and protein, e.g., by targeting their stability, or enhancing the pathway’s catalytic efficiency by building synthetic scaffolds19.The degree of active enzyme in a cell can be tuned on multiple levels of control, i.e., transcriptional, translational, and enzymatic levels. Numerous genetic building blocks have been developed to adjust these levels by taking advantage of different properties of the cell’s machinery22. However, a defined set of parts inherently limits the flexibility with which genetic designs can be created. The ability for exact fine-tuning, imposing user-defined part sequence constraints or building functional degenerated part libraries requires a deeper sequence—function relationship understanding and tools to predict the parts’ behavior. Various in silico models that facilitate the de novo design of different expression control elements have been developed. These include methods to achieve tailored gene expression directly, such as promoter transcription initiation frequency (TIF) engineering31 and tuning of the RBS properties36. Indirect approaches include the engineering of mRNA stability through transcriptional terminators37 and the synthetic regulation using dCas938 or various riboregulators42. Furthermore, the built models are the basis for the development of several (online) tools allowing user-specific de novo sequence design44. The synthetic biology community’s demand for readily applicable forward engineering tools is, for example, expressed by the success of the RBS sequence design tools created by the Salis Lab. Up to October 2020, their algorithms have been used to design over 620,000 genetic sequences by over 9100 users worldwide, including 24 industrial licensees45.The rapidly expanding toolbox of characterized expression control elements contributes to the continuous extension of engineering possibilities and allows the computational design of genetic networks47.To date, despite the abundance of work on promoter engineering and modeling, a standardized and readily applicable tool is not available for de novo promoter design. However, transcription being the first step in gene expression, promoter tuning is most essential. It allows e.g., the tuning of noncoding RNA abundance, which can fulfill various regulatory functions, or plays an important role in combination with RBS strength in the economy of gene expression50. Change in promoter TIF has been generated by modifying (i) the conserved −35 and −10 regions, which actuate the selective recognition and interaction by the sigma factor (σ) RNAP subunit53, (ii) the UP element, situated upstream of the −35 conserved region and interacting with the αCTD RNAP subunits54, (iii) the spacer sequences, spanning the region between −35 and −10 elements and upstream of the −10 element58, or (iv) a combination of multiple, or all, of these elements in a random60, or modular manner61.A prokaryotic promoter can generally be subdivided in several defined parts that determine the interaction with the RNA polymerase (RNAP), and thus its promoter functioning, offering multiple strategies for promoter engineering31. These factors, and a substantial lack of data to grasp the promoter’s structural complexity or support more complex models, often resulted in weak correlations or low promoter strength discrimination resolution. Conversely, some work indicates that the promoter’s −35 and −10 conserved regions are the greatest determinants of promoter TIF and could lead to predictions with high accuracy24. However, these relatively short sequences offer small sequence flexibility, resulting in large sequence repeats when using multiple promoters. More importantly, changes in these regions abolish the promoter’s ability to selectively bind specific σ RNAP subunits. As the orthogonality of gene expression in synthetic genetic systems becomes increasingly important, the −35 and −10 conserved regions are to be left unchanged to ensure this property in the design of genetic circuits56.Previous attempts to model promoter strength in function of its DNA sequence have often targeted multiple of these promoter regions simultaneously, severely underestimating the complexity of interplay between regions, and/or employed modeling methods that assume independence between mutations , practically limiting their predictability to single nucleotide variations56, to preserve orthogonality of the promoter sequence with specific σs, promoter libraries were constructed by randomizing the promoter spacer nucleotides spanning between the −35 and −10 conserved regions, resulting in a five log range of promoter TIFs. Here, we build upon this work by combining the use of fluorescence-activated cell sorting (FACS) on these libraries and targeted high-throughput DNA sequencing to obtain considerably large data sets  holding promoter sequence–function relationship information in view of predicting promoter TIFs, and designing promoter sequences with a specific TIF. A computational model was trained on these newly created data, to develop the first in vivo validated Escherichia coli (E. coli) σ70 Promoter TIF Designer tool, named ProD. Our tool is able to output the promoter spacer sequence, constituting 17 variable consecutive nucleotides. Additionally, albeit lacking in vivo validation, predictive models for promoter strength and orthogonality have been trained and evaluated to expand such a tool with three different promoter architectures with specificities toward heterologous Bacillus subtilis (B. subtilis) sigma factors B, F, and W. This is achieved by the unprecedented size of the characterized promoter libraries and the use of convolutional neural networks, a machine learning methodology achieving state-of-the-art performances on motif detection tasks62. The neural network was adapted for ordinal regression, a classification problem for values with a meaningful ordering , by applying constraints to the output nodes of the model.In previous workσs from B. subtilis, that recognize specific promoter sequences to create a functional and orthogonal expression system in E. coli. To this end, the spacer sequence between the conserved −35 and −10 σ recognition sites of E. coliσ70 and B. subtilisσB, σF, and σW-specific promoter sequences  was engineered, to introduce variability in promoter TIF while preserving the orthogonal features toward specific σs56. A vector (pLibrary) was constructed for each σ-specific promoter, consisting of a promoter library site in a red fluorescent protein (mKate263) expressing operon, and a second operon, constitutively expressing sfGFP64 as an internal reference for normalization  unique sequences. From the unique sequences, 211,772 (65.85%) have more than one read, with 117,249 (36.46%) instances having reads sequenced in multiple bins. To identify possible inconsistencies within the data, several data properties  have been derived from sequences featuring multiple reads: the total amount of reads, the number of bins with the highest amount of reads and their relative distances. A plethora of sequences have reads present in bins that provide incompatible properties, such as the presence of reads in distant bins constituting both low and high expression rates. Therefore, in order to exclude aberrations in the data, promoter sequences with outliers  on any of the data properties were removed. Furthermore, reads recovered from bin 0 (for promoter libraries sorted in presence of their cognate sigma factor) have not been considered for training. This bin covers all sequences with background levels of red fluorescence. Absence of functional mKate2 expression might be caused by a variety of factors, such as mutations outside the promoter region or other cell defects. A preliminary analysis showed the exclusion of this bin to result in better accuracy of the model on the test set. This is not surprising, as the relative small sequence count and marginal position of the bin results in a high impact on the loss function of the ordinal regression setting, as a result of weighing the loss in function of the bin size . The E. coli σ70 promoter TIF prediction model was trained on 284,421  unique sequences covering 938,863  reads. For training purposes, the label assigned to each sequence is the bin with the most reads. As bin 0 has not been included to train the model, sequences from bin 1 through 11 are adopted as classes 0 through 10. An overview of the amount of labeled sequences for each class before and after data filtering is depicted in Fig. For our 31. Prior to model building, we created sequence motifs of the promoter spacers, for every class (~promoter TIF), to detect potential single nucleotides that dominantly determine promoter TIF. The motifs are depicted in Fig. In previous studies attempting to model promoter TIF in function of its DNA sequence, one or more nucleotides at specific positions could often be identified as significant determinants of the TIFB, σF, σW) or the three-nucleotide sequence “TCG” (σ70), adjacent to either the −35 or −10 conserved regions, can be explained by the architecture of the libraries56. Given motifs are overrepresented as an effect of the blueprint used for the randomized sequences, thereby showing a substantial presence in the data sets. These specific motifs, with an increased presence in bins representing either higher or lower promoter TIF, resemble the observations made in our previous work, where the different libraries were characterized using flow cytometry56. With respect to the σB library, the higher presence of the “A” and “T” nucleotides near the −10 conserved region, with exception of the base pair most adjacent to this region, indicate the importance of a local low GC% in enhancing promoter TIF. In case of σF libraries, libraries were constructed allowing a “G” nucleotide besides the original “T” in the −10 conserved region most adjacent to the spacer. An increased presence of “G” in the bins representing stronger promoters is observed, confirming literature stating the G-16 strongly facilitates σF recognition67. The strong sequence motif for bin 11 of the σF library is most likely due to the relatively small number of unique sequences in the data set (486 sequences).In general, the majority of the motifs do not show any specific nucleotides with higher occurrence frequencies, indicating an equal distribution of the four nucleotides at any given sequence position. The motifs that do show up, comprising half the spacer . An additional class was created (denoted as “high”) that includes the sequences predicted as class 10 with the highest probabilities in the randomly generated set. Generated spacer sequences were selected to not be present in the original data set, and range from 2 to 5 single nucleotide mutations from the nearest sequence (hamming distance70). Supplementary Table p-value < 2.2e−16), indicating the ordinal character of the observations with respect to the predicted class. Figure R2 = 0.876), together with the 95% confidence interval (shaded area) for the class means and a 50% prediction interval (red dashed line).The model that is trained to predict TIFs of σB, σF, and σW-specific promoters, we predicted the TIF class and orthogonality of a limited set of library promoters were constructed and characterized in our previous study56. The tested promoters do show an ordinal relation between measured expression level and predicted class, especially for the sigmaB-specific promoters, though the number of observations is small and a fraction of the sequences was also present in the model training sets , or the abundance of studies on correlating sequence features to the rate of transcription, a thorough understanding of the promoter sequence is absent. Furthermore, a promoter TIF prediction tool supporting the de novo design of complete promoters remains absent from the synthetic biologist’s toolbox. The progress made on computational methods for motif detection tasks joined with the construction of promoter libraries of unprecedented size empowered us to take a large step forward in meeting this need. In this work, four models were created to enable forward engineering of E. coli σ70 and B. subtilis σB, σF, and σW-specific promoters based on their TIF and and mutual orthogonal functioning in E. coli. Moreover, the E. coli σ70 model was validated in vivo to create the first Promoter TIF Designer tool, named ProD, allowing 17 degrees of freedom, encompassing the complete spacer that spans the region between the −35 and −10 conserved promoter elements.Despite the development of protein–DNA interaction models enabling the prediction of transcription factors’ affinity for DNA , which is practically unfeasible to fully characterize, library promoter sequences displaying similar promoter TIFs were pooled using FACS for subsequent genotyping. The application of a custom built convolutional neural network for ordinal regression proved succesful in capturing the complex interactions, within the promoter spacer sequence in function of promoter TIF. The σ70 model achieved a Spearman correlation of 0.56 with a mean error of 1.6 classes on predictions. However, in vivo validation on 54 forward engineered promoters resulted in a Spearman correlation of 0.91, indicating a strong ordinal relationship between predicted an measured promoter TIFs.The promoter libraries were designed by randomizing only the spacer DNA sequence delimited by the conserved −35 and −10 regions to preserve specific σ recognition, an essential feature in orthogonal genetic circuits72. This includes the variability in the expression profile introduced by the environment, where the normalization of the constitutively expressed fluorescence protein accounts for factors such as plasmid copy number and cell size. The presence of both extrinsic and intrinsic noise negatively impact accuracy on the test set. In contrast, measured expression rates of the in vivo validation promoters have been adjusted for extrinsic noise, and performances obtained are therefore expected to better represent the capability of the model.A notable difference exists between the performance on the test and in vivo validation set. This difference can be explained by the noise present in the FACS data used to train and validate the model. Importantly, binning is performed solely in correlation to the fluorescence of the expressed mKate2 protein, given a minimal expression of sGFP  regulates the model against overfitting on noise.70 model, the σW model substantially underperforms and the distributions of the predicted classes for the sequences of each assigned class  σs to which class of sigma factors σW belongs. The model might correctly predict the true mean expression of promoters found in different bins, to be similar. An in vivo validation experiment is essential to support this hypothesis.Compared to the σass Fig.  display 56 are very promising, as the sequences with the highest probability for loss of orthogonality have been reviewed as such . Insights from reported observations presumably apply solely to the promoter (spacer) under study and cannot be extended to other base promoters. Rather than by specific nucleotides, it is believed that the spacer sequence influence on promoter TIF is determined on a structural level48. We therefore analyzed the correlation between the GC-content of the spacer and promoter TIF, previously established as an inverse correlation, and found our results do not support these observations . The geometry of base pair steps and shaping of the DNA 3D-structure of a specific sequence is further characterized by a large set of properties . The development of methodologies to study these structural properties for big data could be the key to provide fundamental understanding of the role of the promoter spacer.Determination of the features playing the most important role in promoter TIF remains unsolved. Sequence motifs for the different classes of TIF were created to detect contributing nucleotide positions for each class. The absence of pronounced occurrence frequencies of specific nucleotides in the sequence motifs clearly shows that more complex interactions between base pairs are responsible for the observed TIF. Essentially, this is demonstrated by the effectiveness of neural networks, capable of complex higher-order interactions, to evaluate and classify sequences. In contrast, PWM represent the relative frequencies of the nucleotides at every position of the genome, and are therefore incapable of capturing higher order interactions. This also indicates that caution should be exercised with models predicting the effect of single base mutations on promoter TIF 73. Therefore, it is expected that the developed tool performs equally well for the transcription of different open reading frames. Also, by insulating the promoter region from nearby transcription factor binding sites, impact from environmental context, other than general changes in the expression of the cell’s shared transcription machinery, is minimized. However, changing the genetic context outside of the modeled region, and especially in the −105 to +55 region, would still jeopardize the robustness of any promoter TIF prediction model available.Moving beyond the promoter’s spacer, the UP element, spanning the region from −40 to −60 and the further upstream promoter background sequence are important factors to take into account regarding promoter TIF. Rhodius et al.70 promoters is developed and validated, as a valuable addition to the synthetic biology toolbox, providing the ability to engineer custom promoters and defined libraries. Based on the 95% confidence interval of the in vivo validation set, promoters can be reliably constructed spanning distinct ordinal catagories. This was enabled by both the construction of promoter libraries with randomized spacer sequences in E. coli, leading to data sets of an unprecedented size for this setting, and the recent developments in deep learning methods, which have been proven successful in topics involving big data. In addition, this tool can be further developed into a complete orthogonal expression toolbox by assembling the power of multiple prediction models for the TIF and orthogonality of multiple sigma factor specific promoters, boosting the potential of orthogonal genetic circuit design. Finally, the developed methodology will be useful in similar sequence-dependent ordinal problems, and the created data sets might contribute in revealing the essential spacer features contributing to transcriptional performance.In conclusion, a highly practical tool to predict the promoter TIF of σ74. All DNA fragments were amplified using PrimeSTAR HS DNA polymerase  and purified using the innuPREP PCRpure Kit .All products were purchased from Sigma-Aldrich  unless otherwise stated. Agarose and ethidium bromide were purchased from Thermo Fisher Scientific . Standard molecular biology procedures were conducted as described by Sambrook et al.2HPO4 and 0.3 g KH2PO4 in 1 L water. Kanamycin (60 µg/mL) was added to all media for selection.Lysogeny broth (LB) was used for cloning purposes. Complex medium (853) was used for all further experiments. LB medium was composed of 10 g bacto-tryptone, 5 g yeast extract and 5 g NaCl in 1 L water. Eight hundred and fifty-three medium was composed of 10 g bacto-tryptone, 5 g yeast extract, 0.1% glucose, 5 g NaCl, 0.7 g KE. coli Top10 cells  were used for cloning purposes. E. coli K12 MG1655 was used for all further experiments requiring promoter TIF measurements.56, as well as the construction of all (heterologous) sigma factor specific promoter libraries.The construction of the promoter library expression vector (pLibrary), and its complete annotated DNA sequence, is described in detail in Bervoets et. al.70-specific promoter (library) sequences in pLibrary are derivatives of the insulated proD promoter, constructed by Davis et. al.73:The used σGGTCTATGAGTGGTTGCTGGATAACTTTACG– 17 bp spacer –TATAATATATTCAGGGAGAGCACAACGGTTTCCCTCTACAAATAATTTTGTTTAACTTT, with promoter sequence −60 to +1 in bold, and conserved −35 and −10 regions underlined. To insert forward engineered spacer sequences for the in vivo model validation, first a cloning vector was created, replacing the promoter region partially by an operon expressing the chromoprotein aeBlue75 for visual selection (and later counterselection), flanked by restriction enzyme recognition sites for Golden Gate (GG) assembly76. Oligonucleotides and their reverse complements  of 60 basepairs, containing the engineered spacer sequences and GG restriction enzyme sites matching with the cloning vector, were duplexed as described by the manufacturer. The general duplexed DNA sequence is:TTCTAGAGCACAGCTAACACCACGTCGTCCCTATCTGCTGCCCTATTACGGGTCTCGTTACG-17 bp spacer—TATAATATATTCAGTGAGACCAGCCA-3′, with restriction enzyme recognition sites underlined and the restriction sites in bold. The DNA sequences surrounding the recognition sites  are designed with a custom script using the ViennaRNA, RNAcofold package77 to minimize homodimer/monomer formation, to facilitate duplexing and the following GG assembly. All forward engineered 17 bp spacer sequences are given in Supplementary Table 5′-56. In short, a BD Influx Cell Sorter utilizing the BD FACS sortware sorter software  and calibrated with Rainbow Calibration Particles  (BD), was used for cell sorting to split the promoter libraries in presence of their cognate sigma factor into 12 separate bins, covering the entire expression range, to gather the genetic information of different promoter TIF levels. With a focus on the practical application, the ability to construct a promoter library with 12 levels of TIFs were deemed adequate. Additionally, further increase of the resolution becomes more obsolete as an effect of the normal distribution of the cellular fluorescence. Nonuniform bins are used to account for the variability in the distribution of the cells along the expression level. To account for the varying expression ranges of the bins, the predictive model was given an ordinal design. Also, the B. subtilis σB, σF, and σW-specific promoter libraries in presence of their noncognate sigma factors, were sorted in two bins to gather information about sequences resulting in conservation or loss of orthogonality. Constitutive sfGFP expression was taken into account for bin selection to exclude artifacts. A visual representation of the bin selection, the size of all population fractions and the number of sorted cells is given in Supplementary Figs. The preparation of cells for fluorescence-activated cell sorting (FACS) is described in Bervoets et al.Sorted cells were collected in collection tubes with 1 mL 853 medium supplemented with kanamycin. Subsequently, sorted cells were added to 5 mL fresh 853 medium supplemented with kanamycin in 50 mL tubes and incubated overnight at 30 °C while shaking. Plasmid DNA was isolated for all individual bins with a Qiagen Plasmid Mini Kit  to prepare for DNA sequencing.78. The two-step PCR workflow creates amplicons of the region of interest in a first PCR reaction and includes a primer binding site for a second PCR reaction, adding sample-specific indexes and sequencer flow cell binding sites for subsequent sequencing.The followed sample preparation workflow for sequencing of the sorted libraries, is adapted from the “16S Metagenomic Sequencing Library Preparation” protocol (Illumina Inc.)Plasmid template concentrations were determined using a Quant-iT™ PicoGreen™ dsDNA Assay Kit (ThermoFisher Scientific). 0.7 ng template (≈maximum recommended template concentration) and 0.15 µM of each primer was added to 40 µL PrimeSTAR® HS (Takara Bio Inc.) PCR reactions to produce amplicons of 270–275 bp. The promoter region-specific primers are given in Supplementary Table For index PCR reactions, a Nextera XT Index Kit (Illumina Inc.) and the KAPA HiFi HotStart ReadyMix (F. Hoffmann-La Roche Ltd) were used. Each of the 66 samples (12 bins × 4 libraries + 2 bins × 3 libraries × 3 different genetic backgrounds) was tagged with a unique pair of indexes. Subsequent DNA purification was performed using AMPure XP beads (Beckman Coulter Inc.), followed by LabChip analysis to determine amplicon concentrations. Samples were pooled together proportionally with the number of sorted cells for each bin  and a 45 s heat shock. Pre-cultures for analysis  (150 µL 853 medium with kanamycin) were grown for 24 h in sterile 96-well flat-bottomed black MTPs , enclosed by a Breath-Easy® sealing membrane (Sigma-Aldrich), at 30 °C while shaking . Cultures were then diluted 300-fold  in 150 µL fresh medium with kanamycin and cultured similarly to the precultures. Optical density at 600 nm (OD600), mKate2 fluorescence (FL)  and sfGFP FL  were measured after reaching stationary phase in a Tecan Infinite m200 Pro plate reader . Management of the hardware and processing of the data is achieved using Tecan i-control and Magellan software. FL measurements were processed by first correcting mKate2 and sfGFP FL for growth media (blank) and subsequently, calculating the ratio of mKate2 over sfGFP FL (FluorescenceC).x the transformed data and Pmin and Pmax the fluorescenceC value of the promoter displaying the lowest and highest TIF, respectively. Linear regression, Spearman’s rank correlation test and confidence and prediction intervals calculation is performed with a custom written R-script.To characterize the forward engineered promoters, plasmid DNA was introduced in the cells on microtiter plate (MTP)-scale by adding 2 µL of DNA to 10 µL chemically competent cells prepared in TSS bufferr throughout the observed bins. These are the total amount of reads present in all binsM with similar heights (M1−binM2). Sequences containing outliers (exceeding 95th percentile) on given properties were removed from the data. The target label given to each sequence is defined as the bin with the highest count of reads.Data was processed using Python . Read samples containing mutations within the nonspacer region of the sequenced 51 bp were removed from the database, as well as sequence samples present in bin 0 (for sorted promoter libraries in presence of their cognate sigma factor), covering the sequences resulting in background levels of red FL. Several properties were described in order to better identify the relationship between a unique sequence and its distribution of reads 81 was used for the purposes of building and using a shallow neural network model. Convolutions were applied in the first layers, having shown to be optimal for feature extraction (motifs) of DNA-protein interaction62. Several networks were evaluated before selecting the final model architecture. The structure and performances of several of the less complex networks are listed in Supplementary Table p = 0.3) and two fully connected layers with sizes 128 and 64.The PyTorch libraryx with a set of weights w is taken. A final sigmoid transformation returns values between 0 and 1:K = number of classes.In order to perform ordinal regression, for which a latent variable exists that is correlated to the promoter TIF represented by the eleven classes, a single linear combination of the output vector ζout. Importantly, a weight wn, having a negative correlation to the abundance of the sequence class label in the training data, is assigned to the loss of each sample, ensuring the importance of sequences from every class n in an imbalanced setting.The sum of the binary cross entropy (BCE) from the individual outputs thereby obtains the prediction loss b that serve as the delimiter of the classes. Specifically, the auxiliary training loss ζaux enforces the condition bi > bi+1 or b during training. The total loss ζ of the network equals the sum of ζout and ζaux.To enforce the strict ordering of Based on the target label and loss, the model is optimized for the output to approach The architecture of the binary classification model predicting promoter orthogonality follows the same architecture, albeit without the specialized final layer and loss function. The training, validation and test data are created through randomized stratified sampling, ensuring equal class proportions for the three sets, and exist out of 70%, 10%, and 20% of the data, respectively. The model with a minimum in loss on the validation set is used for evaluation on the test set. For a given model architecture, multiple performance metrics on are obtained by evaluating five trained models using a 5-fold cross-validation scheme.Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Acod1, Fgf21, Serpina11, Cdh16, Lrrc27, and Lrrc66, key islet genes. Collectively, our findings suggest alterations of histone modification in key transcription factors and genes that may contribute to long-term gene dysregulation and an abnormal islet phenotype in IUGR rats.Intrauterine growth retardation (IUGR), which induces epigenetic modifications and permanent changes in gene expression, has been associated with the development of type 2 diabetes. Using a rat model of IUGR, we performed ChIP-Seq to identify and map genome-wide histone modifications and gene dysregulation in islets from 2- and 10-week rats. IUGR induced significant changes in the enrichment of H3K4me3, H3K27me3, and H3K27Ac marks in both 2-wk and 10-wk islets, which were correlated with expression changes of multiple genes critical for islet function in IUGR islets. ChIP-Seq analysis showed that IUGR-induced histone mark changes were enriched at critical transcription factor binding motifs, such as C/EBPs, Ets1, Bcl6, Thrb, Ebf1, Sox9, and Mitf. These transcription factors were also identified as top upstream regulators in our previously published transcriptome study. In addition, our ChIP-seq data revealed more than 1000 potential bivalent genes as identified by enrichment of both H3K4me3 and H3K27me3. The poised state of many potential bivalent genes was altered by IUGR, particularly  Tfunction . Immune function . In the ecretion ,7,8. To eek rats . ThousanPdx1, a pancreatic and duodenal homeobox 1 transcription factor critical for β-function and development, is epigenetically silenced in IUGR rats [Pdx1 and prevents the development of diabetes in IUGR rats [β-cell dysfunction in IUGR animals.Epigenetic modifications of the genome are heritable changes affecting gene expression and allow the stable propagation of gene activity states from one generation of cells to the next ,11,12. EUGR rats . A shortUGR rats ,19. ThesThere are at least three distinct categories of epigenetic modifications: histone modifications, DNA methylation, and non-coding RNAs ,21,22. WIn the current study, we present the first genome-wide assessment of histone modifications in both 2-week and 10-week rat islets and assess IUGR-induced changes of H3K4 trimethylation (H3K4me3), H3K27 trimethylation (H3K27me3), and H3K27 acetylation (H3K27Ac). We have demonstrated that alterations of histone modifications in key transcription factor binding motifs and genes are associated with changes in expression of key genes, suggesting that these epigenetic modifications contribute to long-term gene dysregulation and an abnormal islet phenotype in IUGR rats.The animals and procedures used in this study were approved by the Animal Care Committee of the Children’s Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania. Our IUGR animal model has been previously described . Briefly3 and 1% BSA for 15 min at 37 °C. Digested tissues were then washed in cold supplemented HBSS solution without collagenase. Islets were isolated by histopaque gradient centrifugation.Pancreata were excised at 2 and 10 weeks of age, and followed by islet isolation. Following the previous phenotypic studies using pooled samples from both sexes at 2 weeks of age ,9, 4 panChromatin was extracted from freshly isolated islets and ChIP with antibodies for H3K4me3 , H3K27me3 , and H3K27Ac  and prepared as previously described . Briefly® pathway analysis (IPA®). Enrichment analysis of transcription factor binding motifs was carried out using HOMER. Bivalent domains were identified by the enrichment of both H3K4me3 and H3K27me3 marks in which enrichment peaks have at least 5 bp overlap [http://software.broadinstitute.org/software/igv/). Sequence data have been deposited in NCBI’s Gene Expression Omnibus and are accessible through GEO Series accession number GSE147992.Multiplexed ChIP-Seq libraries were created using the Illumina ChIP-seq DNA sample prep kit  following the manufacturer’s instructions and a previously published protocol . Three b overlap . Genome We performed ChIP-Seq analysis for H3K4me3, H3K27me3, and H3K27Ac histone modifications on pancreatic islets isolated from 2 and 10 weeks old control and IUGR Sprague Dawley rats. All ChIP-Seq data aligned well with the reference genome (rn6 assembly). The alignment rates ranged from 70.8% to 87.5%. Principal component analysis  is a calcium-activated non-selective cation channel. It is expressed in β-cells and regulates glucose-stimulated insulin secretion [Tfam) is a key regulator for mitochondrial genome replication and gene transcription [Mcf2l) encodes a guanine nucleotide exchange factor DBS that can interact specifically with the GTP-bound Rac1 and plays a role in the Rho/Rac signaling pathways [Slc28a2) encodes a purine-specific concentrative nucleoside transporter, CNT2 [Tnf) is an important cytokine regulating immune function and inflammation. Myelin protein zero (Mpz) is a major structural protein of the peripheral myelin sheath and is necessary for normal neuronal function [To avoid the complexity of gene overlapping, we focused on the alterations of histone marks within 5 kb of transcriptional start sites. Thousands of genes showed histone mark changes in both 2-wk and 10-wk IUGR islets . Integraecretion ,36. Mitocription . It is acription ,39. Thiscription . MCF.2 cpathways . These spathways ,42,43. Ser, CNT2 , and is er, CNT2 . Adenosier, CNT2 ,46. Tumofunction . Pancreafunction ,49. The function .Dram1, Foxa3, Gpt2, Ppard, Pycr1, Sel1l, Tst, and Ulk1 (Dram1) and unc-51 like autophagy activating kinase 1 (Ulk1) are two genes regulating autophagy. Autophagy is important for normal islet function [Dram1 and Ulk1 regulate autophagy via modulating mTOR signaling [Gpt2), Pyrroline-5-carboxylate reductase 1 (Pycr1), and thiosulfate sulfurtransferase (Tst) are three enzymes important for mitochondrial function. Gpt2 catalyzes the reversible transamination between alanine and 2-oxoglutarate to generate pyruvate and glutamate, and is pivotal to metabolic adaptation [Pycr1 catalyzes the conversion of pyrroline-5-carboxylate to proline, and is important for amino acid metabolism, oxidative stress regulation, and mitochondrial integrity [Tst is essential for the import of 5S ribosomal RNA to mitochondria [Sel1l, a component of the endoplasmic reticulum-associated degradation (ERAD) pathway, regulates glucose-stimulated insulin secretion and insulin trafficking via modulating integrin and extracellular matrix [Foxa3, a.k.a. hepatocyte nuclear factor 3-γ) regulates the expression of glucose transporter 2 (Glut2), plays a role in the maintenance of glucose homeostasis, and also modulates innate immunity [Ppard) is critical in regulating insulin sensitivity, glucose metabolism, and fatty acid β-oxidation [We also identified multiple differentially expressed genes with decreased H3K27Ac modifications in 2-wk IUGR islets, and the changes persisted until 10 weeks of age. These genes included and Ulk1 . The decfunction . Both Drignaling . Glutamiaptation . Pycr1 cntegrity . Tst is chondria . It is achondria . Sel1l, r matrix . Forkheaimmunity ,59. Peroxidation .β-catenin signaling, and mitochondrial function. There was also enrichment for pathways that regulate T-cell, B-cell, and macrophage function, and pathways modulating innervation and neuronal function, including axonal guidance signaling and c-AMP signaling. The pathways regulating angiogenesis and vascular remodeling were also altered in 10-wk IUGR islets, including PDGF signaling and phospholipase C signaling. Of note, these findings overlapped with key pathways identified by our RNA-Seq data and were also highly correlated with IUGR phenotypes [To identify molecular pathways potentially regulated by histone modifications that were disrupted in 10-wk IUGR islets, Ingenuity Pathway Analysis (IPA) was used to map histone mark alterations at identified gene loci into functional networks. IPA analysis of genes predicted to be regulated by histone modifications revealed enrichment for pathways critical for islet function , such asenotypes .To further investigate whether changes in histone modification in IUGR islets were located near transcription factor binding sites that may facilitate or block transcription factor binding and result in gene dysregulation in IUGR, we performed HOMER binding motif analysis for all 3 histone marks. The top binding motifs for each histone modification are listed in Additional binding motifs that were enriched with H3K4me3 in IUGR islets include FoxL2, ETS like 1 (Elk1), ETS proto-oncogene 1 (Ets1), ETS variant 1 (Etv1), neurofibromin 1 (Nf1), and hepatocyte nuclear factor 1homeobox B (Hnf1b) a, which The top binding motifs associated with H3K27Ac enrichment for both 2-wk control and IUGR islets included androgen receptor (AR), Foxo1, thyroid hormone receptor-β (Thrb), ETS-related gene (Erg), and ETS variant 2 (Etv2) . Friend Finally, the top three binding motifs associated with H3K27me3 in 2-wk IUGR islets were insulin gene enhancer protein ISL-1, Nkx6.1, and zinc finger protein ZBTB7A . Other tAt 10 weeks of age, the top binding motifs enriched with H3K4me3 in both control and IUGR islets were IRFs, Foxa1, LIM/homeobox protein 3 (Lhx3), and Nkx6.1 . Other bNeurogenic differentiation 1 (NeuroD1), neurogenin-2 (NeuroG2), Foxa1, Foxo1, protein atonal homolog 1 (Atoh1), and oligodendrocyte transcription factor 2 (Olig2) were among the top binding motifs associated with H3K27Ac , and theIn 10-wk IUGR islets, several transcription factors in the SRY-related HMG-box (Sox) family were among the top binding motifs enriched with H3K27me3, including Sox3, 6, 10, and 17 , which pGlp1R) [Interestingly, Lhx1, 2, and 3 were among the top binding motifs associated with H3K27me3 in both control and IUGR islets at both ages. Lhx1, 2, and 3 are LIM-HD transcription factors related to Isl1, and are critical for regulating organogenesis and development of neuronal and hematopoietic systems , which aGlp1R) . Indeed,Glp1R) . In addiWe identified several binding motifs with altered H3K4me3 marks in 2-wk IUGR islets, which persisted until 10 weeks of age, including ELF3, ELF5, ERG, ETS1, ETV1, ETV2, EWS:ERG, GABPA, and SMAD4 . All of MEIS1, PR, and Olig2 were the binding motifs with altered H3K27me3 enrichment in both 2-wk and 10-wk IUGR islets . All of Consistent with the HOMER binding motif analysis, many transcription factors discussed above were also identified as critical upstream regulators modulating gene expression changes observed in IUGR islets in our transcriptome datasets .Grpr) and proprotein convertase subtilisin/kexin type 9 (Pcsk9) were the only two genes that gained bivalency in 2-wk IUGR islets. Grpr gained the bivalency in 2-wk IUGR islets and maintained a poised state at 10-wks. Grpr is important for normal islet function and mediates the effect of gastrin-releasing peptide (Grp), an islet neuropeptide, and neutrally stimulated insulin and glucagon secretion [Myo1a) lost its bivalency in 2-wk IUGR islets, and this change was sustained until 10-wks of age. It is an unconventional myosin and functions as actin-based molecular motors in immune cells [Bivalent genes, identified by enrichment of both H3K4me3 and H3K27me3 marks in promoter regions, play critical roles in regulating pluripotency of embryonic stem cells, maintaining gene imprinting, and fine-tuning gene expression during development ,100,101.ecretion . Mice wiecretion . Pcsk9 iecretion ,108. Defecretion . Myosin ne cells .Ang2, Grm7, and Nr0b2. Angiogenin, ribonuclease A family, member 2 (Ang2) is a potent mediator for new blood vessel formation [Several genes known to be critical in pathways modulating islet function gained de novo bivalency in 10-wk IUGR islets, such as ormation . Metabotormation . Glutamaormation . Small hormation . Overexpormation .Acod1, Fgf21, and Serpina11, which were poised in 2-wk control islets, lost their poised state in 10-wk control islets but gained bivalency in 10-wk IUGR islets which was associated with a marked loss of expression of all three genes. In contrast, Cdh16, Lrrc27, and Lrrc66, which were not poised in control 2-wk islets, gained de novo bivalency in 10-wk control islets, but lost their poised state in 10-wk IUGR islets and expression was increased. Aconitate decarboxylase 1 (Acod1) is an enzyme that catalyzes the decarboxylation of cis-aconitate to produce itaconate, and is involved in the inhibition of inflammatory responses [Fgf21 induces insulin resistance and islet dysfunction in mice [Serpina11) is an uncharacterized antitrypsin-like serine proteinase inhibitor [Cdh16) is an atypical cadherin. It functions as the principal mediator for homotypic cell-cell adhesion and plays a role in morphogenesis during tissue development [Interestingly, we identified six potential bivalent genes critical for islet maturation and long-term IUGR phenotype . Three gesponses . It actsesponses ,118. Fibesponses . It stimesponses . Fgf21 pesponses . It alsoesponses . Loss of in mice . Serpin nhibitor . Cadherielopment . Leucineelopment ,127. TheMany studies have demonstrated that intrauterine growth restriction is associated with epigenetic changes in different tissues of the offspring ,135,136,Histone modifications are an important epigenetic mechanism regulating gene expression. Different modifications, as well as which amino acid residue is modified, have different influences on gene transcriptional activity. In the present study, approximately 80% of H3K27me3 and H3K27Ac marks were enriched in the loci >5 kb from the nearest genes. Less than 10% of differentially enriched loci were located in promoters and TSS. This is consistent with previous findings showing that both H3K27me3 and H3K27Ac also mark enhancer/regulatory regions ,33,34. WOur ChIP-seq analysis of the IUGR islets identified marked changes at pertinent genes and signaling pathways that could underlie β-cell and islet abnormalities associated with uteroplacental insufficiency. Histone modifications at genes that regulate tight junction, Wnt/β-catenin signaling, mitochondrial function, immune responses, neuronal function/innervation, and angiogenesis were significantly altered in 10-wk IUGR islets, which was consistent with observed IUGR phenotypes and reinforced our findings in our previous transcriptome studies ,6,7,9,40StAR) gene, which mediates the transport of cholesterol across the mitochondrial membrane and controls steroidogenesis [Fgf16), a growth factor for embryonic brown adipocytes [Interestingly, IUGR induced alteration of H3K4me3 and H3K27me3 modifications at many transcription factor binding motifs. These transcription factors were also identified as critical upstream regulators in our transcriptome study , and areogenesis . Nkx2.5 ogenesis . It alsoipocytes ,154. Paxipocytes . Pax7 alipocytes . The funTrpm5, Tfam, Mcf2l, Slc28a2, Tnf, and Mpz that had differential expression in IUGR versus control islets had changes in all three histone modifications. The low number of genes with altered expression that correlated with changes in the enrichment of all three marks was unexpected and suggested that perhaps there is not a histone code in differentiated β-cells in vivo.Interestingly, only six genes, Grpr, Pcsk9, Ang2, Grm7, and Nr0b2. Interestingly, we identified six potential bivalent genes, Acod1, Fgf21, Serpina11, Cdh16, Lrrc27, and Lrrc66, whose alterations in bivalency and expression levels may contribute to IUGR phenotypes observed in adult islets. Although the roles of Serpina11, Cdh16, Lrrc27, and Lrrc66 in regulating islet function remain unclear, Acod1 is known to be important in modulating the immune system and mitochondrial function [Fgf21 can protect against type 2 diabetes in mice by increasing insulin expression and secretion [Bivalent genes play critical roles in embryonic stem cells and during development ,99. Lu efunction ,117,118,ecretion ,122. HowAlthough animal studies cannot completely translate to human research, animal models have a normal genetic background upon which environmental effects during gestation or early postnatal life can be tested in vivo for their role in inducing diabetes. However, our current study using a rat model to investigate IUGR-induced histone modification changes and their association with β-cell dysfunction has certain limitations. First, rat genome is not as well-annotated as human or mouse genomes, thus the genomic and epigenetic changes observed in rats may be difficult to apply to the human genome. Second, due to tissue or species specificity, some IUGR-induced epigenetic changes in rat islets may not be the same as changes in other tissues or in humans. For example, in a human study of IUGR placenta, H3K27Ac modifications are altered in genes comprising HIF-1-alpha pathway and transcription factor binding motifs for SP1, ARNT2, HEY2, and VDR . These cHistone modifications are an important epigenetic mechanism modulating gene expression changes and the development of T2D. This study is the first genome-wide study of histone modification of the marks H3K4me3, H3K27me3, and H3K27Ac in rat islets. While serving as a valuable resource for elucidating chromatin landscapes in rat islets, we have demonstrated alterations of histone modifications in key transcription factor binding motifs and genes as a potential epigenetic mechanism contributing to long-term gene dysregulation and abnormal islet phenotypes in IUGR rats.


Almost half of the human genome is made up of transposable elements (TEs), and about 8% consists of endogenous retroviruses (ERVs). ERVs are remnants of ancient exogenous retrovirus infections of the germ line. Most TEs are inactive and not detrimental to the host. They are tightly regulated to ensure genomic stability of the host and avoid deregulation of nearby gene loci. Histone-based posttranslational modifications such as H3K9 trimethylation are one of the main silencing mechanisms. Trim28 is one of the identified master regulators of silencing, which recruits most prominently the H3K9 methyltransferase Setdb1, among other factors. Sumoylation and ATP-dependent chromatin remodeling factors seem to contribute to proper localization of Trim28 to ERV sequences and promote Trim28 interaction with Setdb1. Additionally, DNA methylation as well as RNA-mediated targeting of TEs such as piRNA-based silencing play important roles in ERV regulation. Despite the involvement of ERV overexpression in several cancer types, autoimmune diseases, and viral pathologies, ERVs are now also appreciated for their potential positive role in evolution. ERVs can provide new regulatory gene elements or novel binding sites for transcription factors, and ERV gene products can even be repurposed for the benefit of the host. Transposable elements (TEs) are a large component of all eukaryote genomes, comprising a major fraction of all their repetitive sequences. As much as 40–60% of the mammalian genome consists of TEs ,2,3. ImpTEs can be categorized into two classes: DNA transposons and retrotransposons. The retrotransposons are further subdivided by the absence or presence of long terminal repeats (LTRs) flanking a central coding region. Prominent non-LTR retrotransposons are the long interspersed nuclear elements (LINEs), or the short interspersed nuclear elements (SINEs)gag, which encodes structural matrix and capsid proteins; pro, encoding the viral protease; pol, which encodes the retroviral enzymes reverse transcriptase as well as integrase; and env, encoding glycoproteins that determine host cell tropism , which are the remnants of ancient virus infections A 6]. Th. Th6]. T tropism B. Due toIt has been known since the mid-1950s that TEs are highly regulated, with the discovery of “controlling elements” in maize ,11 and aIn this review, we will summarize recent findings concerning the silencing and transcriptional regulation of ERVs. Furthermore, we will give an overview of how ERVs fulfill physiological functions and can be utilized as targets for cancer therapies. This review particularly focuses on the silencing and transcriptional regulation of ERVs. However, some regulatory mechanisms have been described solely or additionally for non-LTR retrotransposons and are therefore included briefly in this article, since they might also impact the transcriptional regulation of ERVs. Due to the considerable differences between mouse and human ERVs, we discuss the elements in the two species in this review separately. Importantly, the majority of findings regarding ERV silencing has been studied in the murine system, mostly during embryonic development and in germ cells. Many mechanisms and concepts of mouse ERV regulation might be applicable to human ERVs, but there may be considerable differences.pol regions with reverse transcriptase sequences of exogenous retroviruses: class I resembles gamma- and epsilonretroviruses, class II resemble alpha-, beta- and deltaretroviruses, and class III resemble the spumaviruses . R. Rpol rede novo methylation . He. He84]. Many regulators of chromatin structure may regulate ERV expression, for example through the interactions of chromatin remodelers with Trim28. Recently, it has been shown that the SWI/SNF-like adenosine triphosphate (ATP)-dependent chromatin remodeler Smarcad1 plays a role in ERV regulation in mouse ESC . DepletiIn addition to chromatin modifiers and repressor proteins, histone chaperones were found in a systematic genome-wide siRNA screen to induce proviral silencing in mouse ESCs . BrieflyDistinct sets of histone chaperones may be involved in loading distinct histone variants onto ERV DNAs. One study reported that the H3 histone variant H3.3 was enriched at class I and class II ERVs including IAPs and the histone chaperones Daxx and Atrx were found to perform H3.3 deposition onto ERV sequences . In thisde novo DNA methylation within the first days in mammalian embryogenesis [de novo DNA methylation seems to require KRAB-Zfp as well as both Trim28 and Setdb1 binding [de novo DNA methylation. Dnmt3a and Dnmt3b expression in ESCs is very high, in contrast to very low expression levels in somatic cells [de novo DNA methylation through Dnmt3a and Dnmt3b and preexisting H3K9 methylation has been noted [In addition to histone-based silencing, ERVs exhibit distinctive DNA methylation patterns. ERVs undergo ogenesis . Interes binding . The autic cells . Interesen noted . Dnmt3l en noted ,100. In en noted . Dnmt1 wen noted ,102,103,en noted . ESCs laen noted . Howeveren noted . Knock-oen noted ,40. The en noted ,72,106. en noted . CpG-ricen noted .In addition to the broad and diverse silencing mechanisms operating through DNA-specific binding by co-repressors and chromatin remodeling factors summarized here, another field is emerging: the RNA-mediated targeting of TEs. Mechanisms such as siRNA- or antisense transcripts-based silencing pathways have been reported to suppress IAPs as well as non-LTR retrotransposons such as LINE-1 ,109. ProAbout 8% of the human genome is comprised of TEs containing LTRs. The majority of these elements have lost various regions of similarity to retroviral coding gene sequences due to massive accumulation of mutations over the course of evolution. In contrast to mouse, all ERVs extant in the human genome are replication-defective, with HERV-K (HML-2) most likely the element that is closest to being replication competent . Many ERA comprehensive microarray study determined the transcription profiles of HERVs in healthy human tissues . ImportaIt became clear that our “viral fossils” have undergone a long history of co-evolution with our genome. Notably, 25% of regulatory regions in the human promoter database harbor TE-derived sequences . Of courAlthough most HERVs have lost the ability to carry out retrotransposition and create new insertional mutations, they still influence host cell signaling and gene regulation either through their viral mRNA or viral protein products, or their remaining LTR-derived gene regulatory regions, which can affect genes even at a considerable distance ,131. AddAside from neurological disorders, deregulated expression of HERVs in various cancer cell types has been reported. HERV-K expression is an example that has been linked to many cancers such as breast cancer, lung cancer, prostate cancer, melanoma, germ cell tumor, lymphoma ,138,143.HERV transactivation has been reported to be triggered by infections of a number of human exogenous viruses such as HIV-1, hepatitis B and C, human T-lymphotropic tumor virus-1 (HTLV-1), influenza A or herpes virus ,144. In Interestingly, envelope proteins from the HERV-H and HERV-K family were shown to have immunosuppressive functions in vivo. This observation reveals that HERVs possess the potential to regulate the host immune system ,148. ThiThere is an increasing number of examples in which TEs were domesticated for the benefit of the host. This process, in which the host makes use of TE-derived functions, are often called exaptation, co-option, or simply repurposing. Either regulatory elements or even encoded proteins, can be beneficial to the host. TE sequences can serve as alternative promoters, enhancer elements, alternative splice sites, or polyadenylation signals ,152,153.Another regulatory network that likely functioned as a driving force in ERV silencing in humans, as in mice, is the arms race between KRAB-ZFPs and TEs . ZFPs arERV proteins, encoded by viral open reading frames, have also been exapted for the benefit of the host. A prominent and powerful example of exaptation of ERV envelope glycoproteins are the ERV-encoded syncytins. These proteins, used by viruses to mediate virus–cell membrane fusion, were co-opted for cell–cell fusion, and now function in placenta formation in mammals. The syncytins induce formation of the multinuclear syncytiotrophoblast through receptor-mediated membrane fusion ,170. NotFriend virus susceptibility 4 (Fv4) gene, an incomplete remnant of an MLV provirus, acts as a restriction factor to prevent exogenous infection by ecotropic MLV at the cellular entry step of the retroviral life cycle [Gag gene with similarities to the ORFs in HERV-L or MERV-L in mouse [Another fascinating example of co-option of HERV envelopes is called superinfection interference. Previously endogenized exogenous retroviruses confer resistance to further viral infections . The murfe cycle ,172,173.in mouse ,175. Fv1in mouse .Gag, and its functions of self-assembly and encapsidation of nucleic acids have been repurposed for the benefit of the host [More recently, the co-option of an ERV Gag protein has been explored. Activity-regulated cytoskeleton-associated (ARC) proteins generate virus-like particles, perform intercellular mRNA transfer in neurons and fulfill important functions in neuronal development ,178,179.the host .Many efforts are underway to make use of the induction of ERV expression for cancer treatment. Drug-dependent derepression of HERVs induces a state of cell activation by a process sometimes called viral mimicry. Reactivated HERVs generate double-stranded RNA products, which activate type I or type III interferon responses, resembling the antiviral response upon viral infection . HERV-enWhy do ERVs persist in our genome over millions of years? How do humans function with almost half of the genome derived from transposable sequences? There are still more questions than definite answers with regard to our ancient “roommates”. Perhaps they first entered our genomes selfishly as successful parasites. They were then silenced by our defense systems, and then domesticated for the benefit of the host in response to both negative and positive evolutionary forces to avoid severe genomic instability and to employ the potential for transcriptional gene regulation, new binding sources for transcription factors, and even exaptation of viral genes. While many of the players in ERV silencing have been identified, more are yet to be found, and the detailed mechanisms for ERV silencing are still not fully understood. It is not clear why some species or even individuals show higher endogenous ERV activity than others. To fully understand transcriptional silencing of ERVs we will need to understand the mechanisms for the establishment of certain DNA- or histone-based posttranslational modifications as well as the maintenance and re-establishment of these silencing marks during replication and DNA damage repair. TRIM28 is unquestionably a master regulator for transcriptional silencing of many retroviruses, both exogenous and endogenous. Nevertheless, the full story of ERV expression and regulation is still not complete and other regulators and contributing factors remain to be identified. Finally, there are specific settings of enormous research interest in which ERVs were found to be deregulated, for example, in aging processes and memory impairment ,185,186.


Although the epigenetic state of hTERT gene promoter is important, we still lack a clear understanding of the mechanisms by which epigenetic changes affect hTERT expression. Retinoids are well‐known inducers of granulocytic maturation in acute promyelocytic leukemia (APL). We have previously shown that retinoids repressed hTERT expression in the absence of maturation leading to growth arrest and cell death. Exploring the mechanisms of this repression, we showed that transcription factor binding was dependent on the epigenetic status of hTERT promoter. In the present study, we used APL cells lines and publicly available datasets from APL patients to further investigate the integrated epigenetic events that promote hTERT promoter transition from its silent to its active state, and inversely. We showed, in APL patients, that the methylation of the distal domain of hTERT core promoter was altered and correlated with the outcome of the disease. Further studies combining complementary approaches carried out on APL cell lines highlighted the significance of a domain outside the minimal promoter, localized around 5 kb upstream from the transcription start site, in activating hTERT. This domain is characterized by DNA hypomethylation and H3K4Me3 deposition. Our findings suggest a cooperative interplay between hTERT promoter methylation, chromatin accessibility, and histone modifications that force the revisiting of previously proposed concepts regarding hTERT epigenetic regulation. They represent, therefore, a major advance in predicting sensitivity to retinoid‐induced hTERT repression and, more generally, in the potential development of therapies targeting hTERT expression in cancers.Telomerase (hTERT) reactivation and sustained expression is a key event in the process of cellular transformation. Therefore, the identification of the mechanisms regulating  hTERT gene promoter. Our findings suggest a cooperative interplay between hTERT promoter methylation, chromatin accessibility, and histone modifications that force the revisiting of previously proposed concepts regarding hTERT regulation.Telomerase (hTERT) reactivation is a key event in oncogenesis. Although the epigenetic‐based regulation of hTERT is important, we still lack a clear understanding of the mechanisms by which epigenetic changes affect  APLacute promyelocytic leukemiaATOarsenic trioxideATRAtrans retinoic acidall‐BACbacterial artificial chromosomeFISHin situ hybridizationfluorescence GAPDHglyceraldehyde‐3‐phosphate dehydrogenasehTERThuman telomerase reverse transcriptasehTRhuman telomerase RNANOMe‐seqnucleosome occupancy and methylome sequencingqRT‐PCRquantitative reverse transcriptase polymerase chain reactionRRBSreduced representation bisulfite sequencingSAMS‐adenosylmethionineSNPsingle nucleotide polymorphismSSCsaline sodium citrateTPE‐OLDtelomere position effect over long distancesTSStranscription start site1Telomere maintenance is a primary and universal characteristic of cellular transformation, leading to unlimited replicative capacity. Without telomere maintenance, the other hallmarks of cancer described by Hanahan and Weinberg  could neTERT gene located on chromosome 5 (5p15.33)  encoded by TERC gene located on chromosome 3 (3q26.2)  encoded by hTERT expression is the primary determinant and the limiting factor for telomerase activity. The regulation of hTERT expression in human cancers is consequently of major importance. hTERT expression is tightly regulated at the transcriptional level  or activators  are important in the tight control of hTERT expression  at 1 295 228 (C288T), and 1 295 250 (C250T). These mutations generate novel binding sites for the ETS (E26 transformation‐specific or E‐twenty‐six) transcription factors and thereby, alter positively the transcriptional regulation of hTERT  is widely used as first‐line therapy in acute promyelocytic leukemia (APL) as an inducer of granulocytic maturation of APL blasts. Besides, we have previously reported that long‐term ATRA treatment could induce telomere‐dependent cell death in some ATRA‐maturation‐resistant cells. Indeed, in the maturation‐resistant NB4‐LR1 cells, pharmacological concentrations of ATRA induced strong repression of hTERT leading to telomere shortening and cell death  with histone ChIP analysis and 3D‐FISH to generate an integrated view of chromatin organization and gene expression at the level of hTERT.All‐22.1ex vivo with ATRA for 48 h, CD34+ cells from eight healthy donors, and promyelocytes generated in vitro from these CD34 cells, were downloaded from the GEO website (https://www.ncbi.nlm.nih.gov/gds/?term=GSE42119%5BAccession%5D)  and visualized in UCSC genome browser (https://genome.ucsc.edu/).DNA methylation data from bone marrow samples of 18 APL patients at diagnosis, eight matched patient at remission, one sample from an APL patient, treated or not 2.2‐trans retinoic acid (ATRA), arsenic trioxide (ATO), and protease inhibitor cocktail (P8340) were purchased from Sigma . The maturation‐resistant human APL cell lines, NB4‐LR1 and NB4‐LR1SFD, were cultured as previously described . For treatments, cells were seeded in medium containing 1 µm of ATRA, 0.2 µm of ATO alone or in combination.All2.3hTERT levels were normalized to the expression of glyceraldehyde‐3‐phosphate dehydrogenase (GAPDH) used as the internal control gene. Primer sequences and their localization on the hTERT gene are shown in Table Total cellular RNA was extracted using TRIzol reagent  according to the manufacturer's instructions and subjected to reverse transcriptase reaction with oligo(dT) using Transcriptor First Strand cDNA Synthesis kit  as described in the manufacturer's instructions. The cDNAs were subsequently submitted to quantitative real‐time PCR using the LightCycler technology and the Light Cycler FastStart DNA MasterPLUS SYBR Green Kit (Roche Diagnostics). 2.4hTERT promoter/enhancer mutations was evaluated by conventional Sanger sequencing. Genomic DNA was extracted from cells as previously reported  and a distal regulatory upstream region (region II: from the position −5500 to −4900 bp relative to the TSS) were amplified using specific primers whose sequences and localizations are reported in Table The presence of 2.5et al., m sucrose, 160 µmS‐adenosylmethionine (SAM)], and split into two aliquots. One aliquot was treated with 75 U of GpC methyltransferase M.CviPI, the other was incubated with the same amount of water. The tubes were incubated for 15 min at 37 °C before adding a boost of 75 U of M.CviPI, and 160 µm SAM in the treated nuclei for an additional 15 min at 37 °C. The reaction was terminated by the addition of one volume of stop solution  and the samples were incubated for 2 h at 55 °C. DNA was then purified by phenol/chloroform extraction and ethanol precipitation. Bisulfite conversion was performed on 1 µg of purified DNA using the EZ DNA Methylation Kit . Bisulfite‐converted DNA was used for PCR amplification of the regions of interest with the primers reported in Table et al., Nucleosome occupancy and methylome sequencing was performed as previously described . An aliquot  of the sonicated chromatin was used as input fraction to quantify the total amount of DNA. For immunoprecipitation, 4 µg of antibodies were prebound to 20 µL protein A/G magnetic beads and incubated with chromatin overnight at 4 °C. As a negative control, IgG of the same species as the antibody of interest was included. The following antibodies were used for the immunoprecipitation: H3K27Me3 ; H3K4Me3 ; H3Ac , H3K9Me3 ; IgG . Three biological replicates were produced independently at a different time of cell culture. Immunoprecipitated chromatin samples were un‐cross‐linked and purified. Immunoprecipitated and input DNA were then analyzed by quantitative polymerase chain reaction  with the appropriate primers targeting regions upstream and downstream hTERT TSS , following the manufacturer's instructions. Briefly, 10TSS Fig. . The pri2.7in situ hybridization assay was performed as previously described  before permeabilization with 0.5% Triton in PBS. Slides were dehydrated with a gradual concentration of ethanol  and then treated with RNase A (100 µg·mL−1) for 1 h at 37 °C . A second permeabilization step with 0.7% Triton in 0.1 m HCl was performed before denaturation with 50% formamide in 2× SSC  solution at 80 °C for 30 min. Probes were denatured at 75 °C for 5 min and added to the sample for hybridization overnight at 37 °C. After 3 washes in 2× SSC/50% formamide, three washes in 2× SSC, one wash in 0.5× SSC and one wash in PBS, slides were incubated with Hoechst 33342 (1 µg·mL−1 in PBS) for 15 min at room temperature and mounted with Mowiol. Probes were prepared using nick translation kit  following the manufacturer's instructions. Bacterial artificial chromosome (BAC) plasmids were purchased from Source BioScience , RP11‐44H14 for subtelomeric region 5p staining , and RP11‐846K3 for staining ‘intermediary’ region, containing TPPP and CEP72 genes . The positions of the FISH probes are indicated in Fig. m sodium acetate  and 3 volumes of 100% ethanol. Probes were then centrifuged at 12 000 g for 45 min at 4 °C. After washing with 70% ethanol, probes were then dried at 37 °C for 10 min and resuspended in 50 µL of hybridization buffer (2× SSC/50% formamide/10% dextran sulfate). Images were acquired using LSM 710 confocal microscope . A 63× Plan‐Apochromat oil immersion objective was used to capture optical sections at intervals of 0.37 µm. LSM‐type images were generated and processed with imagej (https://imagej.nih.gov/ij/) and JACoP plugin. The 3D distance between each center of the deconvolved fluorescent spot of hTERT locus, and either the subtelomeric 5p region or the intermediate locus were collected and analyzed with graphpad prism .Fluorescence 2.8graphpad prism 6.01 software. The difference between groups was analyzed using unpaired or paired Student's t‐test when there were only two groups or assessed by one‐way ANOVA followed by Tukey's multiple comparison tests when there were more than two groups. All tests carried out were two‐tailed. Differences were considered as significant when P < 0.05.Statistical analysis was conducted using 33.1hTERT promoter led us to identify two distinct functional domains differentially methylated, a proximal one fully unmethylated and a distal one whose methylation modifications could account for the capacity of ATRA to repress hTERT gene . Bone marrow samples of eight matched patients in remission were also analyzed. CD34+ cells from healthy donors and promyelocytes generated in vitro from these CD34+ cells were included in the analysis as controls. Raw methylation levels from CpG sites covered by RRBS across all samples were used to perform unsupervised hierarchical clustering  and −146 bp (C250T) upstream of the start codon  extended from −650 to +150 bp relative to TSS; the second region (region II) located far upstream from the TSS (−5500 to −4900 bp)  was significantly more methylated , suggesting that the methylation status of the proximal promoter may contribute to hTERT gene silencing. Associated with this decrease of DNA methylation, we observed a striking loss of chromatin accessibility particularly in the region between −200 and +1 bp. The size of this region is large enough to accommodate at least one nucleosome. This observation was supported by the enrichment of histone H3 observed in this region in the ChIP‐qPCR assay  and a global reduction in chromatin accessibility. Of note, ATRA treatment alone did not affect either CpG methylation or chromatin accessibility in those cells. In NB4‐LR1SFD cells, ATO treatment alone induced a decrease of DNA methylation only in the distal part of hTERT core promoter without major modifications in chromatin accessibility.To investigate the relationship between DNA methylation and nucleosome occupancy in ATRA‐treated and untreated NB4‐LR1 and NB4‐LR1SFD cells, this region displayed strikingly a variable but globally lower methylation levels (33.5%) compared to that in NB4‐LR1 cells. An increase of the DNA methylation associated with a partial increase in chromatin accessibility is observed after ATRA treatment of NB4‐LR1SFD cells. However, neither DNA methylation nor chromatin accessibility was modified after treatment with ATRA and ATO alone or in combination.In region II, NB4‐LR1 cells displayed a marked global hypermethylation (89.1%). Despite no significant change in the DNA methylation profile of this region was observed in ATRA‐treated NB4‐LR1 cells, a decrease of chromatin accessibility was noticed. In NB4‐LR1hTERT promoter are probably a necessary but not a sufficient condition for an efficient transcriptional repression of this gene; they need to be associated with a decrease in chromatin accessibility.Altogether, these results indicate that changes in the methylation status of 3.4hTERT , two active  marks, and the total histone H3 were used for ChIP assay , indicating a permissive transcriptional status of the chromatin. In NB4‐LR1 untreated cells, the active H3K4Me3 mark , H3K4Me3 and to a lesser extent H3Ac, were significantly enriched in NB4‐LR1SFD cells as compared to NB4‐LR1 cells  as well as in the region mapped by the primer set a.After a 7‐day ATRA treatment, the levels of these active marks decreased dramatically only in NB4‐LR1 cells and remained unchanged in NB4‐LR1hTERT core promoter regions  from those in trans . The spots in a pair present on the same chromosome 5 were then categorized into adjacent, intermediate, and separated. As previously reported, we analyzed the distributions of spots in the two extreme categories, that is, adjacent and separated  were ~ 37% and ~ 43%, respectively. After 7 days of ATRA treatment, this percentage was significantly increased to ~ 55% in the nucleus of NB4‐LR1 cells, while the separated pairs decreased from ~ 63% to ~ 45%. In contrast, the distances between probes corresponding to these loci remained unchanged in the nucleus of ATRA‐treated NB4‐LR1SFD cells as compared to untreated cells  and cells that maintained hTERT expression . Despite the constant low level of methylation in the proximal part of hTERT promoter, modifications in chromatin accessibility were observed correlated with a reduction of active histone marks and hTERT transcriptional activity. Interestingly, our study shows that some sites of differential accessibility did not show the expected differential DNA methylation pattern indicating that, as already reported  assay for the first time to measure simultaneously endogenous DNA methylation and nucleosome occupancy at 4.2hTERT promoter has the features of a bivalent promoter, that is, the simultaneous presence of the repressive mark H3K27Me3 and the activation mark H3K4Me3 around the TSS. These marks are commonly seen on bivalent genes ‘poised’ for activation upon stem cell commitment and differentiation. In embryonic stem cells, bivalent promoters may achieve the possibility to respond rapidly to incoming signals by suppressing the formation of active RNA polymerase II complexes on the one hand, and, on the other hand, not allow other less reversible suppressive regulatory mechanisms, like DNA methylation, to silence genes. This feature demonstrates the plasticity of the hTERT gene in NB4‐LR1 cell variants contributing to its reactivation during cellular transformation and tumorigenesis in a permissive environment. Indeed, ATRA treatment induced a strong decrease of the active histone marks, whereas enrichment of repressive marks was observed. By contrast, in NB4‐LR1SFD cells, the levels of H3K27Me3 were significantly lower. In this cell line, only the ATRA and ATO combined treatment induced a slight enrichment of this repressive mark associated with a decrease of the active histone marks more important for H3Ac than H3K4Me3.We showed in NB4‐LR1 cells that hTERT. This region is localized outside the minimal promoter approximately 5 kb upstream of the TSS and has been previously described as an enhancer  is mostly performed by the CxxC finger protein 1 (Cfp1), a subunit of the human Set1 complex, which influence chromatin structure through its binding to unmethylated CpGs and links H3K4Me3 with CpG islands  leading to the ectopic deposition of H3K4Me3 and to an aberrantly elevated level of transcription both from the enhancer and from the nearby promoter. This feature can explain the higher constitutive expression of hTERT in NB4‐LR1SFD cells than in NB4‐LR1 cells. In contrast in NB4‐LR1 cells, densely methylated CpGs in the hTERT enhancer region are likely to attract methyl‐CpG‐binding proteins that recruit enzymes reinforcing repressive histone modifications .Importantly, this study points to a role of a new region in activating SFD cells, only a combination of ATRA and ATO treatments induced hTERT repression associated with a drastic drop of the levels of H3K4Me3 and H3Ac marks at hTERT enhancer and promoter. In NB4‐LR1 cells, the hTERT enhancer is not active and consequently ATRA alone was able to induce hTERT repression provided both the enhancer and promoter region of hTERT have been enriched with the H3K27Me3 repressive mark and hTERT promoter depleted of the and H3K4Me3/H3Ac active marks  are known for organizing global chromosomal architecture, changing accessibility, but also possible interactions far away in distance. Thus, it can be proposed that a potential cross‐talk exists between the enhancer and the core promoter of hTERT gene to orchestrate its expression. As transcription factors could interact with some epigenetic modifiers, a better understanding of the cooperation between transcription factors and the epigenetic landscape will offer hope to develop new drug opportunities. The epigenetic modifications reported above could partially participate in regulation of hTERT gene expression via telomere looping in a context not related to telomere length modifications as suggested in the present study and also recently reported  and one primary (pz‐302) APL patient samples ChIP‐seq results at the hTERT locus before and after ex vivo ATRA treatment for 24 h.Click here for additional data file.Table S1. Primers sequences (5′ to 3′) and amplification conditions used for NOMe‐seq, ChIP, and hTERT expression and promoter gene analysis.Table S2. List of single nucleotide polymorphisms (SNPs) identified by genetic sequencing of the hTERT promoter.Click here for additional data file. Click here for additional data file.


The neural crest (NC) is a transient multipotent cell population that originates in the dorsal neural tube. Cells of the NC are highly migratory, as they travel considerable distances through the body to reach their final sites. Derivatives of the NC are neurons and glia of the peripheral nervous system (PNS) and the enteric nervous system as well as non-neural cells. Different signaling pathways triggered by Bone Morphogenetic Proteins (BMPs), Fibroblast Growth Factors (FGFs), Wnt proteins, Notch ligands, retinoic acid (RA), and Receptor Tyrosine Kinases (RTKs) participate in the processes of induction, specification, cell migration and neural differentiation of the NC. A specific set of signaling pathways and transcription factors are initially expressed in the neural plate border and then in the NC cell precursors to the formation of cranial nerves. The molecular mechanisms of control during embryonic development have been gradually elucidated, pointing to an important role of transcriptional regulators when neural differentiation occurs. However, some of these proteins have an important participation in malformations of the cranial portion and their mutation results in aberrant neurogenesis. This review aims to give an overview of the role of cell signaling and of the function of transcription factors involved in the specification of ganglia precursors and neurogenesis to form the NC-derived cranial nerves during organogenesis. During the embryonic development of vertebrates, one of the main events after the gastrulation process is neurulation, which allows the formation of the neural tube (NT). The neural ectoderm generates not only the central nervous system (CNS) but also another set of cells between the NT and the non-neural ectoderm located in the most dorsal part of the NT, called the neural crest (NC) . This veNC cells (NCCs) are multipotent and give rise to several cell types, depending on the site of origin along the anteroposterior axis of the embryo. NCCs are divided into cranial, trunk (including cardiac), vagal and sacral  Minoux . CranialNCCs, which are multipotent, delaminate from their origin and migrate throughout the body to differentiate into several cell types including cells of the peripheral nervous system (PNS), melanocytes, cranial cartilage and bone, neuroendocrine cells, and several other phenotypes . In humaPax7 expression is restricted to cells located in a region in the medial epiblast, which are NC-fated and contribute to the neural folds and later to migrating NCCs (Snai2 (OMIM 602150), Sox9 , Sox10 (OMIM 602229), and HNK1  , Wnts (Wingless and Int-1), Fibroblast Growth Factor (FGF), and retinoic acid (RA). These signals reveal the tissue interactions into the ectodermal cell populations, the neural plate, the non-neural ectoderm, and the underlying mesoderm in a highly coordinated manner . It has ing NCCs . The inh 151290) . This evForkhead Box D3, OMIM 611539), Snai2 and Sox9 , SP5 (OMIM 609391), Zic3 (OMIM 300265) and Zeb2 (OMIM 605802) had their induction and peak of expression before the classical neural plate border specifier genes such Msx1/2 , Pax3/7 (OMIM 606597/167410) and Zic1 (OMIM 600470). Such specifier genes, together with signaling molecules, direct the expression of NC-specific genes like AP-2 (OMIM 107580), FoxD3, Snai2, Sox9, and Sox10. Specifiers regulate NC effector genes involved in migration  and differentiation  in human NC development   Mizusek.Xenopus have shown that there is an activity gradient of BMPs controlled by their antagonists and that an intermediate level is needed to induce the formation of the NC , HES5 (OMIM 607348), and SOX2 (OMIM 184429)  showed that if BMPs are blocked with Noggin for 24 h on days 0, 1, or 2 of the differentiation protocol, there is a dramatic decrease in the induction of human NCCs. However, if the inhibition is made on day 3, the inhibition is partial, so the participation of BMPs at the beginning of the induction of the NC is very important, while the inhibition of this pathway promoted the expression of neural genes such as  184429) . This pr 184429) . The gen mammals .BMP4 (OMIM 112262) and Smad proteins have been involved in an interesting mechanism called retrograde signaling in trigeminal ganglia from rats . This meGenetic studies have demonstrated that Hippo signaling is crucial in organ size regulation, controlling cell number by modulating cell proliferation and apoptosis processes . Hippo iA relationship between this signaling pathway and the classical NC genes, such as interaction with Pax3 is through TAZ and the phosphoprotein YAP65. These proteins participate as co-activators of Pax3. It has been suggested, using transgenic mice, that Tead2  is an endogenous activator of Pax3 in NCCs . ThroughNeurofibromatosis 2  is a tumor suppressor that inhibits YAP during dorsal root ganglia (DRG) development. Merlin, encoded by the NF2 tumor-suppressive gene, was identified through genetic studies in mouse embryos and proved to be an important upstream regulator of the Hippo-Yap pathway. Neurofibromatosis is an inherited disease characterized by the development of bilateral Schwann cell tumors originated from CN VIII. Mouse with specific Schwann cell-inactivated Nf2 alleles developed schwannomas and SC hyperplasia , Delta-3 (OMIM 602768), Delta-4 (OMIM 605185), Jagged-1 (OMIM 601920), and Jagged-2 (OMIM 602570), through interaction with four possible receptors (Notch1-4) . Once thJAGGED-1, the genes specifying NC  are down-regulated. However, the ectopic expression of NICD1 increased its expression, demonstrating that Notch also participates significantly in NC induction , Indian , and Desert Hedgehog . Shh regulation during NC differentiation is crucial during head and face morphogenesis. Mutant mice and humans lacking Shh present holoprosencephaly and cyclopia due to the lack of separation of the forebrain lobes  overexpression was shown to be sufficient to induce cranial NCCs proliferation (Sonic Hedgehog (Shh) signaling is involved in the correct development of NC and therefore in the generation of its cellular derivatives . Shh is in lobes . It is sferation .Wig/WigPtch1) of the Shh receptor Patched1 , suppressed canonical Wnt signaling in the CN region. This critically affected the survival and migration of cranial NCCs and the development of placodes, as well as the integration between NC and placodes  and facial nerves (CNVII) that did not develop properly and failed to project to their appropriate target tissues  gene produced hypoplasia and aberrant fusion of cranial ganglia  and affected NC and placode gene markers expression, suggesting that a regionalized action of the Hedgehog signaling is required for proper cranial ganglia and nerve development and patterning  receptors comprise an increasingly well studied family of signaling molecules. Ephrins bind to two families of transmembrane tyrosine kinase receptors, EphA and EphB. While A-type Ephrins preferentially bind to EphA receptors, B-type Ephrins do so to EphB receptors. In  pouches . Eph rec pouches , migrati pouches  as well  pouches .EphA5–/– (OMIM 600004) had only <15% of the normal complement of Gonadotropin-releasing hormone neurons in the brain   and parthe brain . This alhe brain .EphA5 promoter, which could account for the activation or repression of this promoter and might influence the graded EphA5 expression in the mesencephalic tectum (A key step in epigenetic control of expression is gene silencing by hypermethylation of CpG islands present at promoter regions . Both spc tectum . During c tectum . TherefoErbB2–/– (OMIM 164870) mice die around midgestation due to cardiac defects. Cranial ganglia are also morphologically aberrant and these embryos show an altered pattern of ErbB3 (OMIM 190151) staining  and the related ErbB  proteins transduce after EGF (OMIM 131530) binding. staining . ErbB3 m neurons . Chick N neurons . A chemiock-outs .ErbB4 (OMIM 190151) null mouse die at mid-gestation, at E11, due to cardiac defects  and facial (VII) ganglia (Neuregulin 1 (OMIM 142445), is expressed in r2 and r4  interactions (FGF1–10 and 16–23). There are seven signaling receptors, encoded by four FGFR genes, FGFR1–4 . FGFs exIn mice, FGF signaling is necessary for cell survival during the development of tissues, including the embryonic telencephalon and the mid-hindbrain junction . In zebrFGFR-2(IIIb) knock-in mouse shows severe dysgenesis of the cochleovestibular membranous labyrinth and sensory patches of the vestibulocochlear ganglion (CN VIII) remain small and poorly developed (Fibroblast growth factor activating FGFR-2(IIIb) (OMIM 176943) at placodal sites , and RA,eveloped .FGF2. In agreement, MBD1 loss-of-function induces the FGF2 promoter hypomethylation, thus increasing its expression in mouse adult neural stem cells, which prevents differentiation  could induce demethylation in promoters of several genes that participate in mouse neurogenesis, including Bdnf (region IX) and FGF1  -null neural stem cells display impaired neurogenesis and increased genomic stability. A possible mechanism is the direct binding of MBD1 to the hypermethylated promoter region of the important neural growth factor ntiation . Ma et a 131220) . Interesogenesis . WhetherPTK7 null mice die perinatally , also named Colon Carcinoma Kinase 4 (CCK4) and Kinase-Like Gene (KLG) in chicken, is the only member of this RTK family . PTK7 nuinatally . Interes defects . PTK7 re defects . The hum islands , but epiTrks (tropomyosin-related kinases) receptors are a subfamily of TRKs activated by neurotrophins . Three tNTR (OMIM 162010) serve as co-receptors of Ephrin-A  are important in the formation of the vascular system during embryonic development. The mammalian VEGFR are three related type III RTKs known as VEGFR1, VEGFR2, and VEGFR3. These receptors, which bind to VEGF ligands, consist of five glycoproteins referred to as VEGFA, VEGFB, VEGFC, VEGFD and placenta growth factor (PlGF) . The tra2+ pathway in vertebrates. The latter involves at least two branches: Ror1/2 activation of Phospholipase C, associated with Wnt binding to Frizzled receptors, produces IP3 and DAG, which increases cytoplasmic Ca2+ concentrations; the second mechanism is the direct activation of Ror1/2 by Wnts, resulting in increases in cytoplasmic Ca2+, which activates Calpain , which otherwise is phosphorylated by GSK3β (OMIM 605004) and undergoes constant degradation by the proteasome. Stabilized β-catenin interacts with TCF to activate the expression of target genes . Non-can Calpain . The int Calpain . An effiatory NC . Within atory NC . WhetherDkk1 (OMIM 605189). Loss of expression of Dkk1 promotes an ectopic activation of Wnt/β-catenin signaling during gastrulation. Using in vivo assays, it was demonstrated that Dkk1 and Wnt3a (OMIM 606359) are regulated in a negative feedback loop. In agreement with this, 51% of double heterozygous mice for Dkk1 and Wnt3a showed reduced forebrain while 30% were normal. A small percentage of mice had malformations of eyes and pharyngeal arches as well as defects in the trunk. Therefore, regulation of Wnt signaling participates in the formation of the head but also in several mouse NC derivatives, although there are other pathways and transcription factors involved in the morphogenesis of the head   . In addi pathway . The parThe basic helix-loop-helix (bHLH) DNA binding protein Hand2  is expressed in a subset of NC-derived cells where it participates in various aspects of cell specification, lineage segregation, and cell type-specific gene expression , 2008. LHes genes are homologs of the Drosophila hairy and Enhancer of Split gene. The Hes family is composed of seven members, Hes4 being absent in the mouse genome. Hes genes encode nuclear proteins that repress transcription, either actively or passively  and Math. Mice deficient for Hes1 show a severe neural hypoplasia due to accelerated neural differentiation and the consequent depletion of neural precursor cells , was upregulated in an Id1-dependent manner  located on different chromosomes in higher vertebrates  mouse null mutants die at birth from anoxia and exhibit marked reductions in the sizes of r4 and r5, hypoplasia of the inner ear and specifically in CNIII. The embryonic phenotype is characterized by the absence of facial nerve and abducens motor nerve  loss-of-function mouse mutants exhibit alterations in the molecular markers associated with r4 identity, although no overt changes in the anatomy of the developing hindbrain are present  and contralateral vestibular acoustic efferent (CNVIII), which are specific to r4, are incorrectly specified  is the only member of the Hox family expressed in r2; this fact explains why Hoxa2 null mutations in mouse result in homeotic changes transforming second arch elements of NC origin into first arch derivatives, which was correlated with perinatal lethality. Patterning of the hindbrain rostral region also depends on Hoxa2 activity for the establishment of r2 identity and influencing the migration of trigeminal motor axons (CN V) originated from r2/3. In mutant embryos, this CN V, normally derived from r2/3, migrates caudally to exit the hindbrain from r4, the normal site for facial nerve (CN VII), rather than from r2. Hoxa2 is required for the maintenance of EphA4 (OMIM 602188) as its expression results selectively abolished in Hoxa2 mutants (Hoxb2 (OMIM 142967) in mouse embryos results in impaired development of the facial nerve, CN VII, affecting its somatic motor component ( mutants . The losomponent .Hoxa3 (OMIM 142954) null mutant mice show mesenchymal NCCs defects in the formation of CN IX and also fusions between CN IX and X. In addition, Hoxa3–/– mouse are athymic, aparathyroid, and have malformations in cartilage of the throat (Hoxb3–/– (OMIM 142966) embryos revealed similar cranial ganglia defects, but at a lower penetrance than in the Hoxa3 mutants (Hoxb3/Hoxd3 (OMIM 142980) double mutants have a clear increase in the presence of aberrant ganglionic phenotypes in CN IX compared to those reported in the Hoxb3 single mutant, even though the Hoxd3–/– does not show defects in these structures  are lost, and Hoxa3 is not upregulated  participate in controlling RA concentration locally, and hence facilitate its function. CRBPs might sequester RA and thus limit its availability to bind nuclear RA receptors (RARs and RXRs) that recognize a particular element on target genes, the RARE sequence , Hoxb4 (OMIM 142965), Hoxd4 (OMIM 142981), and Hoxb5 (OMIM 142960) (RA is a morphogen derived from Vitamin A (retinol) that reaches the cell nucleus after diffusing through cell membranes to act on histone acetylation and mediates transcriptional activation of target genes. RA is another important regulator of NC development. As mentioned earlier, Hox gene expression patterns specify AP identity in the hindbrain and this is transferred to NC migration . The “cosequence . Members 142960) .Neuron navigator 2 (Nav2) was first identified as an RA-responsive gene required for RA-mediated neurite outgrowth or survival of CN IX and X   regulates the expression of nocytes) . Since YMsx) genes belong to the homeodomain family. These genes code for transcriptional factors with repressor activity. Proteins with homeodomains have various functions during embryonic development, from the formation of expression patterns to more specific functions such as differentiation toward a specific cell type , which have been characterized in mammals. There is a great diversity of studies on Pax genes in the early specification of cell fate and in the morphogenesis of various tissues and organs. The important participation of Pax genes in NC induction is discussed next. Pax3 participates in the early ontogenesis of the NT and NC; it is expressed in pre-migratory NCCs. The loss of Pax3 generates severe defects in embryonic development, leading to embryonic death  additionally exhibit malformations of ganglia of the PNS. The importance of Pax3 in the development of NC-derived structures has been shown, especially with respect to cranial ganglia and nerves. In the homozygous state, Sp and Spd alleles impair the development of the trigeminal (CN V), superior (CN IX), and jugular (CN X) ganglia, suggesting that the function of Pax3 is crucial for NC migration and proliferation, as well as for its differentiation into neurons capable of sending out axons  in the 5′ region of tor Sox2 . This shut axons . In Xenon of NCC .Pax gene in NC formation is Pax7, which has been described as necessary for NC development in birds. Pax7 is required for the expression of NC markers such as Sox9, Snai2, HNK1 and Sox10  and Phox2b are co-expressed at multiple sites, suggesting a broader role for Phox2 genes in the specification of autonomic neurons and cranial motor nuclei. The co-expression of these Phox proteins at various sites suggested positive crosstalk (Mash1 has been demonstrated to control the expression of Phox2a (but not of Phox2b) in autonomic ganglionic precursors and NC-stem cells  is a transcription factor known to play a key role in the development of the autonomic nervous system. rosstalk . Mash1 hem cells , while Ppression . Epistatf Phox2a . The mut anlages . The eff cascade . Many cr cascade . In humaensivity .Otx1 and Otx2 genes are the mouse cognates of the Drosophila head gap genes. Orthologs have also been identified in human, chick, Xenopus and zebrafish. Otx2 may act as a key head organizer during the primitive streak stage. At subsequent neurula to pharyngula stages, those genes participate in the patterning of the forebrain and midbrain. The haplo-insufficiency mutation of Otx2 in the mouse affects the mandible and pre-mandibular skull elements, as well as the ophthalmic branch of the trigeminal nerve, and the differentiation of mesencephalic trigeminal neurons, all of which correspond to derivatives originated from mesencephalic NC (A/T)CAA(A/T)G. They have a DNA binding domain of 80 amino acids. Based on phylogenetic analyses of their domains, Sox genes are divided into subgroups A-H in mouse  has a prominent participation in NC differentiation. In mouse, Sox9 and Sox10 are among the first expressed genes in the NC progenitors overlapping with FoxD3   . Sox10 iand Sox2 . Sox10 cand Sox2 .Zic genes are transcription factors with zinc fingers that contribute to different processes during embryonic development  is expressed in the cells of the inner mass of the blastocyst and is required for the synchronization of neurulation. Zic2 mutants showed delayed production and decreased numbers of NCCs. Zic2 is also necessary for the formation of r3 and r5 and participates in the normal pattern of the mouse rhombencephalon  is expressed in the dorsal part of the NT and its mutation in humans produces holoprosencephalia, a severe brain malformation. A decrease in Zic5 promotes insufficient NT closure in the rostral-most part, which was also observed with Zic2 (Zic2 mutant embryos showed affected CN V, VII and VII (Mouse homozygous mutants of ior lobe . In Zic pression . Zic5 (Oith Zic2 . Zic2 mu and VII .Zic5 mice show malformations of the facial bones derived from the NC, mainly the mandible, due to decreased generation of NCCs. During embryonic stages, there were also delays in the development of the first branchial arch and extension of the trigeminal and facial nerves. On the other hand, deletion of Zic2 promotes congenital malformation of the brain and digits in humans (Deficient n humans . Cranialn humans .Some of the most relevant pathways and genes involved in CN formation are represented in All authors listed have made substantial, direct and intellectual contribution to the work and approved it for publication. KM-M did molecular neuroscience data, conception and design, compiling and summarizing articles, manuscript writing, and final approval of the manuscript. GV-L did cell and developmental biology data, conception and design, compiling and summarizing articles, figures elaboration, manuscript writing, and final approval of the manuscript. MA involved in financial support, cell and developmental biology data, conception and design, compiling and summarizing articles, manuscript writing, and final approval of manuscript. IV involved in financial support, molecular neuroscience data, conception design, correction of style, manuscript writing, and final approval 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.