The activation of the GATA-binding factor 4 (GATA4) transcription factor induces cardiac hypertrophy and heart failure. The multimerization of transcription factors often plays an important role in the regulation of transcriptional activity. Here, we report that the GATA4 transcription factor forms a homomultimer and that residues 308-326 of GATA4 are necessary for its multimerization. The acetylation of GATA4 by the transcriptional co-activator p300 induces the multimerization of GATA4 and activates its DNA binding activity. In addition, we found that the suppression of GATA4 multimerization did not reduce its acetylation, but repressed GATA4/p300-induced gene transcription. Furthermore, the inhibition of GATA4 multimerization suppressed phenylephrine (PE)-induced hypertrophic response in cardiomyocytes. This study demonstrates that the multimerization of GATA4 during the p300-induced acetylation of GATA4 activates the transcription of hypertrophic response genes, which leads to cardiomyocyte hypertrophy. Therefore, the inhibition of GATA4 homomultimerization could serve as a potential therapeutic strategy for the development of novel drugs against heart failure. The number of individuals with heart failure is estimated to be 26 million worldwide in 2014, making it a major contributor to global deaths GATA4 is a zinc finger transcription factor that is expressed at an early stage of embryonic development and is involved in the formation of the heart It has been reported that GATA4 interacts with various transcription factors, including T-box transcription factor 5 (TBX5), myocyte enhancer factor 2 (MEF2), serum response factor (SRF), and NK2 homeobox 5 (Nkx2.5), as well as transcriptional cofactors, including cyclin-dependent kinase-9 (CDK9), heart- and neural crest derivatives-expressed protein 2 (HAND2), receptor for activated protein kinase C1 (RACK1), and nuclear factor of activated T-cells, cytoplasmic 4 (NFATC4) In general, transcription factors, including tumor protein p53 (p53), signal transducers and activator of transcription 3 (STAT3), and cAMP responsive element binding protein (CREB), regulate transcriptional activity by forming complexes such as homodimers. Estrogen receptors and glucocorticoid receptors, which are zinc finger transcription factors like GATA4, increase transcriptional activity by forming homodimers in vitro. A glutathione S-transferase (GST) pull-down assay was performed with an 35S-labelled GATA4 protein using GST-GATA4. The results demonstrated that GST-GATA4 bound to the 35S-labeled GATA4  containing residues 308-326 of GATA4, the nuclear localization sequences of the SV40 antigen, a 3xHA tag, and a V5 tag. HEK293T cells were transfected with this construct to determine the intracellular localization of GMP. Fluorescence imaging revealed that GMP was localized in the cellular nuclei  assay and an ANF Fig. E or ET-1ANF Fig. F promoteANF Fig. G and H. In order to confirm whether GMP localizes in the nucleus of cultured neonatal rat cardiomyocytes (NRCMs), the cardiomyocytes were transduced with GMP using a lentiviral vector and subjected to immunocytochemical staining with anti-α-actin antibody  lentiviruses were introduced into NRCMs. The cells were stimulated with 30 µM PE or left unstimulated for 48 h, and subsequently stained with an anti-α-actin antibody. As shown in Fig. GATA4 is a zinc finger transcription factor that plays an important role in the development and progression of heart failure The multimerization of transcription factors plays an important role in the regulation of transcriptional activity. For instance, p53 forms homotetramers such as STAT3, and CREB forms homodimers and heterodimers that bind to DNA and regulate transcriptional activity. The post-translational modification of these transcription factors, including phosphorylation and acetylation, play important roles in their multimerization Previous studies have reported that the transcription of hypertrophic response genes increases in transgenic mice with a cardiac-specific overexpression of GATA4, leading to cardiac hypertrophy and heart failure The signaling pathways of cardiomyocyte hypertrophy include ERK/JNK/p 38 (MAPK), calcineurin-NFAT, JAK/STAT, and p300/GATA4 The members of the GATA family can be categorized into two subgroups based on their developmental and pathological functions, namely, GATA1/2/3, which partake in the hematopoietic system, and GATA4/5/6, which partake in the functions of endodermal tissues The E1A binding protein p300 partakes in transcriptional activation via its acetyltransferase activity and also by serving as a scaffold for the assembly of multiprotein complexes or by acting as a bridge allowing the binding of proteins to the transcriptional machinery Although the structure of the GATA4-DNA complex is unknown at present, the structures of GATA1 and GATA3 have been reported. The side chains of arginine, especially those of R305 and R307 of GATA1 and R364 and R366 of human GATA3 , which are located in the multimerization region, insert into the DNA double helix and interact with the DNA It has been reported that phosphorylation and acetylation increase the stability of p53, and that tetramerization is important for p53-DNA binding This study has also eliminated the relationship between the formation of GATA4 multimerization and DNA binding. We investigated the inhibition of GATA4 multimerization by GMP and the acetylation and DNA binding of GATA4. While GMP did inhibit GATA4 multimerization Fig. D-F, it hSeveral transcription factors undergo post-translational modifications that induce their multimerization and DNA binding function, thereby increasing their transcriptional activity. For instance, estrogen receptor α, which has a zinc finger domain, is phosphorylated by protein kinase A and activates transcriptional activity. This phosphorylation enhances the dimerization of estrogen receptor α and its DNA binding activity GATA6, a homolog of GATA4, has been detected in many tissues. In the heart, GATA6, like GATA4, is involved in the differentiation and induction of cardiomyocytes and in their hypertrophic response The GATA4 binding proteins, including p300, RACK1, CDK9, TBX5, Nkx2.5, MEF2, SRF, NFATc4, and HAND2, bind with the C-terminal zinc finger domain of GATA4 (residues 256-326), which includes the multimerization region It has been reported that both the expression level and the HAT activity of p300 are increased in hearts with ischemic, diluted, or unspecified end-stage cardiomyopathy compared with hearts without heart failure (67). Therefore, GATA4 multimerization may be increased in the hearts of human heart failure patients, together with increased GATA4 acetylation. Protein homomultimers have been detected by immunoprecipitation followed by Western blotting using tagged proteins, by native polyacrylamide gel electrophoresis, and by electrophoretic mobility shift assay (68-70). It has been reported that GATA4 interacts with many proteins, including MEF, NKx2.5, NFATc4, RACK1, and Cdk9 . Therefore, it is difficult to determine whether GATA4 is multimerized based on molecular weight after separating the complex in a non-native state. In this study, the multimerization of GATA4 was detected by immunoprecipitation using GATA4 tagged with HA and FLAG tags. As cardiomyocytes are non-dividing, it is difficult to establish cardiomyocyte cell lines following gene transfer, which makes it difficult to tag endogenous GATA4. Moreover, the overexpression of GATA4 in cardiomyocytes itself induces cardiomyocyte hypertrophy It has been reported that curcumin, which inhibits the acetyltransferase activity of p300, suppresses the acetylation not only of GATA4 but also of histone, and thereby suppresses heart failure In conclusion, this study demonstrates that the inhibition of GATA4 multimerization suppresses hypertrophic responses in cardiomyocytes. The results of this study suggested that the inhibition of GATA4 homomultimerization can serve as a possible therapeutic strategy and preventive measure for heart failure. The study further revealed that it may be possible to develop GATA4-specific drugs and avoid the potential side effects triggered by the inhibition of GATA1/2/3 dimerization. This can be achieved by targeting the multimerization region of GATA4, which is not highly conserved in the rest of the GATA family, instead of inhibiting the zinc finger domain, which is highly conserved among the GATA family of transcription factors. The development of drugs that specifically inhibit GATA4 multimerization is a promising novel approach to the treatment of heart failure.The expression vectors for full length pDEST15 GATA4 and residues 1-179, 180-326, 256-326, and 325-440 of pDEST15 GATA4, pGEX6P-1 GATA4, pCMV-p300, p300 AS, pcDNA3.2 FLAG-GATA4, FLAG-GATA4 m456A, pcDNA3.2 HA-GATA4, pANF-luc, and pET-1-luc have been previously described 35S-labeled protein was prepared using a TnT® Quick Coupled Transcription/Translation System , following the manufacturer's instructions. The GST fusion proteins were expressed in Escherichia coli BL21 DE3 and immobilized on Glutathione-Sepharose 4B beads . The beads were mixed with 35S-labeled protein and incubated for 2 h at 4°C. The beads were subsequently washed five times with wash buffer , resuspended in sample buffer, analyzed by SDS-PAGE, and transferred to a Poly vinylidene fluoride (PVDF) membrane . The GST fusion proteins were detected by Coomaisse brilliant blue staining. The PVDF membrane was subsequently dried and exposed to a BAS-IIIS imaging plate  for 3 h. The 35S-labeled proteins were detected using a BAS2000 bio-imaging analyzer (Fujifilm).An Escherichia coli BL21 DE3 and immobilized on Glutathione-Sepharose 4B (Cytiva). The beads were mixed with HRV3C protease. The GST-tag was removed from GST-GATA4, and the GATA4 protein was obtained. The purified GATA4 was passed through a size-exclusion column, Superdex200 Increase 10/300 GL (Cytiva), equilibrated with eluent buffer .GST-GATA4 was expressed in 5 cells/well on a 6-well plate for dual-luciferase assay or 6.0 × 103 cells/well on a 48-well plate for immunofluorescence staining in Dulbecco's Modified Eagle's Medium (DMEM) consisting of 10% (vol/vol) fetal bovine serum  at 37°C with 5% CO2. Twenty-four hours after plating, cells were washed twice with DMEM without FBS before being replaced with fresh media. The primary neonatal rat cardiomyocytes were transfected with the indicated amounts of DNA by using Lipofectamine LTX with Plus Reagent (Thermo Fisher Scientific), as previously described HEK293T cells were maintained in Dulbecco's Modified Eagle's Medium  as previously described Nuclear extracts were prepared from HEK293T cells, and immunoprecipitation studies and Western blotting were performed as previously described For Western blotting, rabbit polyclonal acetylated lysine antibody, , goat anti-GATA4 polyclonal antibody, murine anti-GATA4 monoclonal antibody, rabbit anti-p300 polyclonal antibody, murine anti-p300 monoclonal antibody, rabbit anti-V5-probe polyclonal antibody , murine monoclonal FLAG (M5) antibody (Sigma-Aldrich), murine anti-FLAG monoclonal antibody, murine anti-HA monoclonal antibody, and murine anti-Myc monoclonal antibody  were used. The levels of the bands were detected with an Amersham Imager 680 (Cytiva) and quantified using ImageJ software, version 1.52q.In this study, the ChIP assays were performed as previously described 2, 400 mM NaCl, 0.2 mM EDTA, 25% glycerol, 0.02% Tween10) and incubated for 2 h at 4°C. Streptavidin Sepharose High Performance Beads (Cytiva) were added to the protein-DNA mixtures and incubated for 2 h at 4°C. The beads were then washed four times with wash buffer, resuspended in 0.1 M glycine (pH 2.5 at 4°C for 5 min), and subsequently analyzed by Western blotting.Nuclear extracts were prepared from HEK293T cells and mixed with a biotin-labelled ET-1 probe  in DNA binding buffer , 0.1 mg/ml salmon sperm, 20 mM Hepes pH 7.9, 1.5 mM MgClHEK293T cells were co-transfected with pLp1 (gag/poly), pLp2 (rev), pLp/vesicular stomatitis virus G, and plenti6.3-GMP, and subsequently packaged into a pseudotyped lentivirus as previously described The immunofluorescence staining of cultured cardiomyocytes was performed as previously described p < 0.05.The values are presented as the mean ± standard error (S.E.) of data from at least three independent experiments. The statistical comparisons were performed using the Analysis of Variance test with the Tukey-Kramer test. Statistical significance was considered at Supplementary figure and methods.Click here for additional data file.


In the human ATP2B4 gene, coding for the plasma membrane calcium pump PMCA4b, a minor haplotype results in the decreased expression of this membrane protein in erythroid cells. The presence of this haplotype and the consequently reduced PMCA4b expression have been suggested to affect red blood cell hydration and malaria susceptibility. By using dual-luciferase reporter assays, we have localized the erythroid-specific regulatory region within the haplotype of the ATP2B4 gene, containing predicted GATA1 binding sites that are affected by SNPs in the minor haplotype. Our results show that, in human erythroid cells, the regulation of ATP2B4 gene expression is significantly affected by GATA1 expression, and we document the role of specific SNPs involved in predicted GATA1 binding. Our findings provide a mechanistic explanation at the molecular level for the reduced erythroid-specific PMCA4b expression in carriers of ATP2B4 gene polymorphic variants. The PMews, see ,4,5. Genydration ,7. Moreoydration .ATP2B4 minor haplotype in modulating the expression and regulation of PMCA4b in erythroid cells. This relatively large haplotype resides in the region of intron 1 and exon 2, a predicted promoter/enhancer area of the ATP2B4 gene. Zámbó et al. [In 2017, two independent studies examined the role of an ó et al.  found thó et al.  found thATP2B4 gene, causing a major effect on PMCA4b expression. Although these experiments indicated the potential role of some transcription factors, the mode of regulation and the transcription factor(s) involved have not been identified so far. Analyzing the changes in transcription binding sites in the minor haplotype of this enhancer, a potential GATA1 binding site has been found to be altered [ATP2B4 gene regions and their potential GATA1 regulation in malaria susceptibility. The ATP2B4 gene polymorphism has been suggested to be a malaria-driven selection force in some African regions [The results of Zámbó et al.  and the  altered ,12. The  altered  reinforc regions . TherefoDifferent regions of the ATP2B4 gene see  were clo4945mut_for5′ CACCTTCAGCCCTCCGTTTTGTCACCTACACCACACC 3′4945mut_rev5′ GGTGTGGTGTAGGTGACAAAACGGAGGGCTGAAGGTG 3′51mut_for5′ GAGAGGTATCTTACCGCTCCCACTCCAG 3′51mut_rev5′ CTGGAGTGGGAGCGGTAAGATACCTCTC 3′Site-directed mutagenesis on the H1st WT-containing plasmid to 4945, 51 or 4945/51 was carried out by standard mutagenesis protocol using Platinum SuperFi polymerase  and the following primers:For GATA1 co-expression experiments, GATA1 coding cDNA was cloned into the pIRES2 expression vector that contains a CMV promoter and enhancer sequence, along with a GFP coding sequence, independently translated from GATA1, as transfection control.4 cells/well, in 80 µL Opti-MEM serum-free cell culture medium. A total of 0.2 µL Mirus TransIT 2020 transfection reagent and 100 ng total plasmid DNA/well were used for transfection. A 10:1 molar ratio of the examined vector (pGl4-Firefly) and co-reporter (pRL-TK-Renilla) vector was used. The transfection reagent and plasmid DNA were diluted in Opti-MEM. Five hours after transfection, the Opti-MEM cell culture media were supplemented with 200 µL fresh complemented appropriate medium. HEK293 cells were cultured in DMEM medium supplemented with 10% FBS, 100× GlutaMAX and 100× Pen/Strep. HEK 293 cells were transfected with Lipofectamine 2000 reagent in Opti-MEM, and the same amounts and methods were used as described above with the following differences: one day before transfection, HEK293 cells were plated on 96-well cell culture plates, and 5 h after transfection, the transfection mix diluted in Opti-MEM was replaced with fresh medium.HEL cells were cultured in T25 vented cap cell culture flasks in RPMI-1640 cell culture medium, K562 cells in IMDM cell culture medium, both supplemented with 10% FBS, 100× GlutaMAX and 100× Pen/Strep. Prior to transfection, K562 and HEL cells were seeded onto a 96-well cell culture plate at 2.5 × 10For GATA1 co-expression experiments, transfection was performed as described above. A 7:3:1 molar ratio of the (pGL4-Firefly:pIRES2-GATA1:pRL-TK-Renilla) vectors was used. In the control (no GATA1) experiments, the pIRES2 empty plasmid was transfected along with pGL4 and pRL-TK plasmids.t-tests were performed.The dual-luciferase reporter assay system was used according to the manufacturer’s guidelines for 96-well cultured cells . Results were read by a VictorX3 Multilabel Plate Reader. Reagents were added on 96-well white plates to the cell lysates manually, immediately before reading the signals one by one. Firefly luminescence was read after mixing 20 µL of cell lysate and 50 µL LARII reagent, Renilla luminescence was read after the addition of 50 µL Stop & Glo reagent. At least two technical and two biological parallel experiments were performed in all cases. The data were normalized to HEK WT  was used for reverse transcription. GATA1 specific primers were used to amplify GATA1 cDNA in a PCR reaction with Phusion HF DNA polymerase.RNA isolation was performed by the PureLink RNA Mini Kit according to the manufacturer’s protocol from 1 × 10Proteins were isolated from HEK293, HEL92 and K562 cells in TE sample buffer  for Western blot experiments. For detecting the respective proteins, the anti-GATA1 (Abcam ab181544) rabbit monoclonal and anti-β-actin  mouse monoclonal primary antibodies, goat anti-mouse IgG (H + L) HRP conjugate  and goat anti-rabbit IgG (H + L) HRP conjugate (Abcam ab6721) secondary antibodies and Pierce™ ECL Western Blotting Substrate were used.ATP2B4 haplotype region, which has been shown to have the highest regulatory potential at transcription level. This region includes several transcription binding sites and was shown to have a pronounced effect on transcription [In these experiments, we examined the promoter activities of the first part of the cription ,12. To aATP2B4 gene, previously indicated to be responsible for the regulation of PMCA4b expression. The enlarged area depicts the SNPs present in the potential erythroid-specific enhancer, the H1st region.As shown in ATP2B4  and K562 . These cells were transfected with Firefly luciferase-based reporter DNA plasmid constructs containing  the putative promoter/enhancer regions from P2B4 see b left. TP2B4 see b right. P2B4 see .In our preliminary studies, when the Firefly luciferase expression was driven by the combined sequences of the H1st plus the PR2 regions, a major activation of the luciferase expression (an F/R ratio of 200–300 see ) was obsATP2B4 regions in HEK cells. When the WT form of the H1-start cDNA was inserted into the Firefly luciferase vector, very low expression was found in the HEK cells. In contrast, in the K562 and HEL cells, higher luciferase expression was observed , while in these cells the expression driven by the minor haplotype sequence (H1-start minor H) was much lower, practically indistinguishable from that in the HEK cells (F/R ratio around 3). Interestingly, when the PR2 site was inserted in front of the luciferase gene, we saw an immense expression from this construct in HEK cells, while in K562 and HEL cells the expression was much lower. In erythroid cells, higher expressions from the haplotype-containing construct could be observed. The luciferase expression from H1.1 was somewhat higher in HEK cells from the haplotype-containing vector than from WT. In case of the H1.2 region, we did not observe any promoter activity (data not shown), which may indicate the margin of the promoter region. Therefore, this region was excluded from our further experiments.ATP2B4  in the cell lines used for the above experiments. As shown in ATP2B4 gene. In the case of the HEK cells, GATA1 overexpression only slightly increased the luciferase expression, both in the case of the WT and the variant H1 constructs. In contrast, GATA1 overexpression greatly increased luciferase expression in the K652 and HEL erythroid cells compared to the control vector lacking the GATA1 sequence. High luciferase expression by GATA1 co-expression in the erythroid cell lines was more pronounced from the plasmid containing the wild-type H1-start than that containing the minor variant of this region.In order to further establish the role of GATA1 in the enhancer activity, we transfected the HEK, K562 and HEL cells with an expression vector containing the GATA1 coding cDNA, or with an empty pIRES2 vector as a control, and performed the dual-luciferase assay in these GATA1-overexpressing cells c. In theIn further experiments, we focused on the actual role of the SNPs in the predicted GATA1 transcription factor binding sites within the H1-start region. Therefore, we selectively mutated the SNPs  in the predicted GATA1 transcription factor binding sites. We generated luciferase expression constructs containing the minor variant SNPs, rs107751449 + rs10736845 . Based on these studies, it has been established that an erythroid-specific regulatory region of the ATP2B4 gene is present in the first intron region, and SNPs located in this region significantly affect both PMCA4b expression and susceptibility to malaria. The malaria-protective SNPs in ATP2B4 also associate with increased mean corpuscular hemoglobin concentration (MCHC) in the red blood cells, and thus may cause a wider disease-connected phenotype. The mechanism through which reduced PMCA4b expression affects parasitic disease is currently unknown—the changes in cellular calcium homeostasis or pleiotropic effects of this calcium pump expression have been suggested [The role of uggested ,10,13.ATP2B4 (see ATP2B4 gene by the SNPs within the predicted (H1-start) enhancer region, and the modulation of the enhancer properties of this sequence by naturally occurring SNPs.The regulatory region in P2B4 see  has beenATP2B4 promoter/enhancer regions were inserted into a promoterless expression plasmid and luciferase expression  was examined. According to our results, the PR2 (exon 2) region is highly active in HEK293 cells, while it has much lower promoter/enhancer activity in the examined erythroid cell lines . In the erythroid cells, somewhat higher PR2 activity could be observed in the case of the minor haplotype construct. The H1.1 region also showed promoter/enhancer activity, and in this case only a minor increase in the luciferase expression was observed in the presence of the minor haplotype construct, and only in HEK cells.In this work, we have generated luciferase expression-based reporter constructs and examined the effects of SNPs in human non-erythroid and erythroid model cell lines. The proposed The H1-start region—which was indicated to have a major role in gene regulation in erythroid cells—had promoter/enhancer activity, and this activity in the non-erythroid HEK cells was very low and not altered by the presence of the minor variant SNPs. In contrast, in the erythroid cell lines, the minor variant had significantly reduced promoter/enhancer activity as compared to the wild-type sequence. In addition, the overexpression of GATA1 increased the promoter/enhancer activity of the examined regions in HEK293 cells independently of the presence or absence of SNPs, while this effect of GATA1 was significantly more pronounced in the erythroid cell lines and strongly reduced in the presence of the minor variant of the H1-start region. These results suggest that this region harbors an erythroid-specific transcription factor binding site—most probably a GATA1 binding site, which is diminished in the minor haplotype.In order to further explore the role of specific sequences, we selectively mutated the SNPs predicted to be involved in GATA1 binding within the H1-start region and expressed the luciferase-based reporter construct in the erythroid K562 cell line. These experiments indicated that the two predicted GATA1 binding sites, eliminated by the presence of minor SNPs, are both functionally important in erythroid cells. The luciferase expression constructs containing these affected minor SNPs, that is, rs107751449 + rs10736845 or rs10751451, had significantly reduced promoter/enhancer activity. Interestingly, the minor variant of rs10751451 had a more pronounced effect on this activity, either used separately or together with the other two SNPs.ATP2B4, thus the entire promoter region, including the first promoter upstream of exon 1, may have additional complex regulatory properties.The results showing a stronger effect of the selected SNPs than the whole-length H1-start region on protein expression may point to the exact molecular background of the polymorphic variants affecting malaria susceptibility or other blood-related conditions. Interestingly, a similar role of a polymorphic GATA1 binding site in the promoter region has been documented in modulating the expression of the Duffy blood group antigen, a receptor for Plasmodium in erythroid cells, thus reducing malaria infection . In our ATP2B4 expression in erythroid cells, these results also suggest that, in addition to GATA1, other transcription factors may also be involved in the erythroid-specific regulation of this enhancer region. The potential complex role of regulatory factors is indicated by the relatively small effect of GATA1 expression in the HEK cells compared to that in the erythroid cell lines, as these latter cells may also contain additional, erythroid-specific transcription factors. Additionally, in our experiments (not shown in detail here), we failed to find a direct GATA1 protein binding to the H1-start DNA sequences by electrophoretic mobility shift assay (EMSA). Therefore, additional studies are required to clarify the role of GATA1 and/or other complexing factors in the regulation of this enhancer region.While our results document the functional role of the specific haplotype region and SNPs in GATA1 regulation of ATP2B4 genes  and dempreprint  indicateATP2B4 gene in polymorphic genetic variants. These results also depict the corresponding SNPs involved in this regulation and suggest a mechanism for decreased red blood cell PMCA4b expression observed among the carriers of the minor haplotype of the ATP2B4 gene, connected to decreased malaria susceptibility.The results presented here point to the importance of a limited promoter/enhancer region and demonstrate the functional role of GATA1 in modulating the expression of the


MSX1 and SPRY2). Comparison with independent data suggest that 802 of them might be specific to craniofacial development, and genes near these peaks are enriched in processes relevant to nsCL/P. Integration with nsCL/P GWAS data, however, did not show robust evidence for co-localization of common nsCL/P risk variants with TFAP2A ChIP-seq peaks. This data set represents a new resource for the analyses of craniofacial processes, and similar approaches with additional cell lines and TFs could be applied to generate further insights into nsCL/P etiology.Non-syndromic cleft lip with/without cleft palate (nsCL/P) is a frequent congenital malformation with multifactorial etiology. While recent genome-wide association studies (GWAS) have identified several nsCL/P risk loci, the functional effects of the associated non-coding variants are largely unknown. Furthermore, additional risk loci remain undetected due to lack of power. As genetic variants might alter binding of transcription factors (TF), we here hypothesized that the integration of data from TF binding sites, expression analyses and nsCL/P GWAS might help to (i) identify functionally relevant variants at GWAS loci, and (ii) highlight novel risk variants that have been previously undetected. Analysing the craniofacial TF TFAP2A in human embryonic palatal mesenchyme (HEPM) cells, we identified 2845 TFAP2A ChIP-seq peaks, several of which were located near nsCL/P candidate genes (e.g.  In approximately one third of patients, CL/P occurs within the context of a known genetic syndrome3. However, in the majority of cases, CL/P arises as an isolated malformation, and is referred to as non-syndromic CL/P (nsCL/P)3. NsCL/P has a multifactorial etiology, which is characterized by the contribution of both genetic and environmental risk factors4. Heritability estimates from twin studies and multiplex pedigrees are high, with reported values of up to 90%6. This suggests that genetic factors make a substantial contribution to nsCL/P etiology.Cleft lip with or without cleft palate (CL/P) is a frequent form of human orofacial clefting, and ranks among the most common of all congenital malformations7. These have included several genome-wide association studies (GWAS) and meta-analyses in diverse populations. Together, these genetic studies have identified 45 nsCL/P risk loci, which explain around 30% of the heritability21. Still, identifying causal variants at these loci remains challenging, since most of the associated single nucleotide polymorphisms (SNPs) are (i) located in non-coding regions, and (ii) their biological effect is difficult to dissect due to the presence of linkage disequilibrium22.Over the past decade, multiple investigations have been performed to identify the causal variants, risk genes, and functional mechanisms that contribute to nsCL/Pcis-regulatory elements23. Differential TF binding can modify the expression pattern of direct target genes, and also trigger downstream effects at the gene network level. Since the majority of gene regulation networks are highly cell-type and cell-state-specific, identifying effects of this nature requires analyses of cellular systems that are relevant to the specific disease in question24.One of the mechanisms through which risk variants in non-coding regions can contribute to disease phenotypes is altered transcription factor (TF) binding to 27 and nsCL/P GWAS data. We first identified candidate TFs in HEPM through expression profiling. Among those, we prioritized TFAP2A for further analyses, for several reasons. First, deleterious mutations in TFAP2A cause Branchio-Oculo-Facial Syndrome28. This syndrome is characterized by dysmorphic anomalies and characteristic facial phenotypes including cleft palate28. Second, TFAP2A has been shown to bind to the nsCL/P risk variant rs642961, located within an enhancer of the nsCL/P candidate gene IRF620. Furthermore, the TFAP2A-IRF6 pathway is a well-established pathway involved in orofacial clefting29. Finally, TFAP2A is located at an nsCL/P risk locus (6p24) previously identified by GWAS8.The major goal of the present study was to develop a framework for investigation of transcription factor binding events in nsCL/P, through integration of molecular data from human embryonic palatal mesenchyme (HEPM) cells9 with two aims. First, we wanted to identify potential causal variants at known GWAS risk loci. Therefore, we looked whether TFAP2A ChIP-seq peaks co-localize with associated risk variants, and whether they exhibit allele-specific TFAP2A binding effects at heterozygous positions. Second, we hypothesized that binding of TFAP2A in HEPM might contribute to nsCL/P at loci that are not yet genome-wide significant, due to limited power of current GWAS studies. While the results of our analyses provide only limited evidence for a role of genetically mediated effect of nsCL/P risk variants at TFAP2A ChIP-seq peaks in HEPM, the map of binding sites as well as the framework described here can be used as blueprint for further integrative analyses of epigenetic and genetic data in nsCL/P.Performing chromatin immunoprecipitation followed by sequencing (ChIP-seq) in HEPM, we then identified ChIP-seq peaks indicative of TFAP2A binding and confirmed plausibility of these regions through comparisons with external data sets. This map of binding regions was next integrated with (i) genotype information from HEPM cells, and (ii) summary statistics of a previous nsCL/P GWAS meta-analysis30 (Supplementary Table TFAP2A and MSX1), additional support for an involvement in nsCL/P etiology was available through their location at previously identified nsCL/P risk loci . In the present study we prioritized TFAP2A, as the GWAS signal at this locus was mainly driven by the European population, thus matching the ethnicity of the HEPM donor .RNA-seq in HEPM revealed 14,508 expressed genes, defined by an expression with ≥ 5 aligned m-RNA-seq reads in average. This included 350 TFs that were represented by motifs in the JASPAR core vertebrate assembly 2020−333; present in 1535 summit regions Fig. 31  5–50, Supplementary Tables 34, we identified co-localization of 2678 out of 2845 hc-peaks , which is the lead variant at this locus, and of rs447476 with rs2303914, the lead SNP at 2p25.1 21 ; rs12882215 and rs7144455 ; and rs4774822  comprising the 45 nsCL/P GWAS risk lociPGWAS < 0.001 were found to be homozygous. At 18 positions we found statistical evidence for allele-specific reads . Analysis of potential downstream genes at these 18 sites revealed that 8 and 10 SNPs were associated with 1 or 2 possible target genes, respectively  outside of the known GWAS loci, for instance, at suggestive loci. For the analysis of allele-specific effects of TFAP2A binding, we first retrieved array-based genotypes for HEPM and found that 461/1,564 SNPs were heterozygous, including rs463271, rs672819 and rs447476 (see above). The other 3 SNPs at 25. Examples include a recent study by Huo et al.36, who analyzed TFBS from ChIP-seq data of 30 TFs in brain tissues. The authors identified 132 schizophrenia risk variants that exert a functional effect on gene expression by disrupting the binding sites of 21 TFs. Also, Benaglio et al.37 investigated the regulatory landscape and gene expression profiles of human induced pluripotent stem cell derived cardiomyocytes and identified differential binding of the cardiac TF NKX2-5 to risk SNPs at GWAS loci for electocardiographic traits such as atrial fibrillation.A major challenge to our understanding of the biological role of nsCL/P-associated risk variants is their predominant mapping to non-coding regions of the genome. Although in vivo and in vitro approaches exist to identify functional variants among the statistically associated passenger variants, the major prerequisite is the analysis of disease-relevant tissue. At mechanistic level, altered TF binding to variant alleles has been suggested as one biological process through which non-coding risk variants might contribute to complex traits and diseases, including nsCL/P27. TFAP2A was chosen since it is (i) encoded by an nsCL/P candidate gene with robust evidence for an involvement in craniofacial development, and (ii) is strongly expressed in HEPM. Further evidence for a role of TFAP2A has been gained in mice, where knock-down of Tfap2a leads to severe malformations including facial clefting38, and in a multi-omics study of human dental pulp stem cells39. Importantly, while the orchestrational role of TFAP2A in structures derived from neural crest or ectodermal cells is well documented, few data are available concerning its role in the palatal mesenchyme41. For instance, it has been shown that in mice, Tfap2a is expressed in the facial mesenchyme during palate development42, and knock down of Tfap2a leads to an increase in the expression of Fgf8, which is implicated in the differentiation of mesenchymal cells into cartilage in the anterior plate44. While this suggests a regulatory connection of Tfap2a and Fgf8, in our study, we did not observe any TFAP2A ChIP-seq peak in the proximity of FGF8. However, we observed TFAP2A binding sites near other nsCL/P candidate genes, such as MSX1 on chr4p168, and SPRY2 on chr13q3111. At the MSX1 locus, the TFAP2A ChIP-seq peak is located ~ 200 bp upstream of the MSX1 transcription start site (TSS). In concordance with prior evidence of Msx1 being expressed in the palatal mesenchyme at various stages of development, we also observed strong expression of MSX1 in HEPM. Additionally, Msx1 has been suggested to be required for normal outgrowth of palatal shelves and mesenchymal proliferation46, and research has shown that Tfap2a regulates Msx1 expression in murine neural crest cells47. At the SPRY2-locus, several TFAP2A ChIP-seq peaks have been identified, the closest of which is located ~ 1.9 kb upstream of the TSS of SPRY211. Spry2 is expressed in mouse palatal mesenchyme, and both knock out and overexpression of the gene lead to cleft palate49. Spry2 knock out mice display an increased proliferation of palatal mesenchyme and a higher expression of other clefting genes, such as Msx1, Etf,5 and Ptx148. We also observed strong expression of SPRY2 in HEPM. Together, these lines of evidence suggest that these three nsCL/P risk genes  might form an nsCL/P regulatory network in HEPM cells. In addition, TFAP2A binding sites have been observed near other nsCL/P candidate genes from GWAS, i.e., ARHGAP29, FILIP1L, TP63, GREM1, TPM1, ARID3B, ADCY9, and NOG. With the exception of TP63, all of these were also expressed in HEPM. We also observed TFAP2A ChIP-seq peaks downstream of CD58 (~ 16 kb), and PTGS2 , both of which have been implicated in the TFAP2A-gene regulatory network described by Razaghi-Moghadam et al.39. Together, these genes represent interesting candidates for further studies of nsCL/P in HEPM cells. Based on the well-established interaction between TFAP2A and IRF6, we specifically looked at TFAP2A binding sites near IRF6. We could not detect any TFAP2A ChIP-seq peaks within 1 Mb of the TSS of IRF6, and also IRF6 expression was only merely detected above background in HEPM. Thus, while there is robust interaction of TFAP2A and IRF6 in epithelial cells29, our data indicate that such effects might not be present in palatal mesenchymal cells. Importantly, in the present study, the genes were assigned to the hc-peaks on the basis of proximity. Therefore, long-distance regulatory effects of TFAP2A binding sites would have been missed by design.In the present study we examined binding of TFAP2A in human embryonal palatal mesenchyme cells which serve as in vitro model of human palate development, since they have been retrieved from the palatal shelves of an embryo at a gestational age when elevation and fusion processes take place51.In the comparison of TFAP2A ChIP-seq peaks in HEPM cells and HeLa S3 cells, almost half of the ChIP-seq peaks in HEPM cells were found to overlap between both cell lines. Besides indicating that these peaks are true positives, this finding also suggests that some TFBS are specific to HEPM cells . In support of this we observed a strong overlap of TFAP2A sites within DNase1 hypersensitivity sites (94.1% overlap), and H3K27ac signals (57.8% overlap) from human embryonic craniofacial tissue. This indicates that these TFAP2A ChIP-seq peaks reside at chromatin sites that are accessible to TF binding during human facial development. The output of our GO analysis provides further support for a role of TFAP2A binding sites in facial development, as craniofacial-specific terms such as “abnormality of facial soft tissue”, “abnormal palatine bone morphology”, or “abnormal palatal shelf elevation” were significantly enriched. We also found evidence for a contribution of the transforming growth factor beta pathway in HEPM, which is implicated in the epithelial-mesenchymal-transition processes that occur during secondary palate formationFinally, our data set was used to analyze whether common nsCL/P risk alleles located at the TFAP2A ChIP-seq peaks in HEPM might contribute to disease pathomechanism. We did not observe any risk SNP at test-wide significance within the TFAP2A ChIP-seq peaks. Four SNPs were detected at suggestive significance, which does not exceed the number expected by chance. In addition, no allele-specific effect was observed for the one variant of those four that was heterozygous. Further analyses outside of established GWAS risk loci identified 18 SNPs with allele-specific TFAP2A binding, but again, none of them showed a nominally significant association with nsCL/P. Thus, our data do not provide evidence that the biological effect at any of the common risk variants is genetically mediated through differential TFAP2A binding in mesenchymal cells.52. This could be overcome by future investigations of three-dimensional organoid systems, such as recently established by Wolf et al.53 and Hughes et al.54. Second, the integration of TFAP2A binding peaks and genetic risk variants from GWAS meta-analyses only informs about common risk variants, but does not provide information on potential effects of rare variants on TFAP2A binding. Herefore, the integration of whole genome sequencing data would be required, e.g. those recently described by Bishop et al.55. Also, the analyses of allele-specific effects were limited by the fact that only one HEPM-donor was available, resulting in a limited number of heterozygous sites usable for the analysis. Finally, our approach does not cover effects of (i) TFAP2A in other cell types , (ii) other TFs in HEPM , or (iii) other types of gene regulation (e.g. miRNA57). While potential TFs can be identified as presented in this study, alternative approaches also exist—for instance, integrating GWAS risk SNPs and TF databases such as JASPAR30. This, however, would then require subsequent identification of the relevant cell type for in vitro investigation, which is still a challenge for embryonic human phenotypes.Our study is influenced by some limitations. First, we investigated a two-dimensional in vitro model, which lacks the complexity of cell-to-cell interactions. Particularly, we might have missed effects that are driven by the interaction between epithelial and mesenchymal cells, and/or environmental clues, such as those present in three-dimensional embryonic palateTaken together, the present data suggest that TFAP2A binding in HEPM might play a role in normal craniofacial development, and indicate a set of presumably craniofacial-specific TFAP2A ChIP-seq peaks near nsCL/P candidate genes, which might be functionally followed up. No strong evidence was obtained for the hypothesis that genetic variability at these sites contributes to nsCL/P etiology. Despite this, similar analyses in other cell types of relevance to craniofacial development might provide novel insights into our understanding of genetically-mediated nsCL/P risk.2), with a change of medium every two days. After five days of cultivation, the cells were split using 0.25% Trypsin/EDTA. DNA and RNA were extracted from the cells using the DNeasy® Blood &Tissue kit and the RNaeasy® kit , respectively, in accordance with the manufacturer’s protocols.A human embryonic palatal mesenchyme cell line was commercially available at ATCC (ATCC Cat# CRL-1486). Upon purchase these cells were cultured in DMEM-Dulbecco's Modified Eagle Medium (high Glucose) with 10% heat inactivated fetal bovine serum (FBS) and Penicillin/Streptomycin at a final concentration of 1%. Cells were stored in an incubator  was used, in accordance with the manufacturer’s instructions. Sequencing was performed at 1 × 50 bp on an Illumina HiSeq2500, with a minimum depth of ~ 20 mio reads per sample. Reads were quality checked using FastQC (v0.11.7), adapters were trimmed using bbduk (BBMap v37.44), and reads were aligned to the GRCh37/hg19 reference genome using STAR Aligner (v2.5.2b). Gene expression was quantified using featureCounts (v1.5.1), and the Ensembl Human GRCh37.p13 annotation as a reference. Quality control was carried out using MultiQC (v1.2). Genes were classified as “expressed” if the average number of aligned mRNA reads was ≥ 5, and “strongly expressed” if the average number of aligned mRNA reads was within the upper quartile of all genes expressed with ≥ 5 mRNA-seq reads in HEPM . The JASPAR CORE vertebrate assembly (2020)To identify TFs with an involvement in craniofacial development and/or orofacial clefting, a systematic search was performed in the Pubmed database. A TF was considered to be a candidate TF if the respective gene had been reported previously: (i) as a candidate gene at a nsCL/P risk locus; (ii) in a mutated state in patients with craniofacial malformations; (iii) to result in disturbed craniofacial development when modified in animal models; or (iv) to be part of a gene regulatory network involved in facial development. To identify TFs whose potential role in nsCL/P etiology involved a change of TF binding in HEPM, this list of candidate TFs was cross-referenced with the HEPM expression data.To determine genotypes for common variants in HEPM, DNA was extracted from HEPM cells. The DNA was then genotyped on an Illumina Infinium GSAv2.0 array , comprising ~ 700.000 SNPs with a major allele frequency > 0.1%. After stringent quality control, genotypes of SNPs that were not represented on the array were imputed using IMPUTE2 (v2.3.2), the 1000 genomes phase 3 GRCh37/hg19 variants as a reference panel, and an info metric threshold of 0.5. For imputed variants with mono-allelic binding in the subsequent ChIP-seq analysis, genotypes were validated by Sanger sequencing in order to exclude imputation artifacts.6 HEPM cells were crosslinked for 10 min at room temperature using 37% formaldehyde at a final concentration of 1%. The reaction was stopped with 0.125 mM Glycine. Cells were washed twice with ice-cold PBS and scraped into a tube. Cells lysis was performed by sequential cold incubation  with two buffers provided in the reagent kit. Chromatin was digested by 0.5 µl micrococcal nuclease per IP for 15 min at 37 °C on a constantly shaking heating block. After stopping digestion by the addition of 0.5 M EDTA, nuclei were suspended in ChIP buffer and sonicated with a Diagenode Bioruptor . A fraction of the sample was used for measuring DNA-concentration using Nano Drop and to check fragmentation size via electrophoresis. A total of 0.5 µg DNA was used as the input control. A total of 0.005 µg of polyclonal ChIP Grade TFAP2A antibody (Abcam Cat# ab52222) was added to 25 µg of DNA and incubated overnight with rotation at 4 °C. Fragments were pulled down using Protein G magnetic beads, and then removed from the beads via incubation with ChIP elution buffer on a shaking thermomixer at 65 °C for 30 min. The supernatant was treated overnight with NaCl and Proteinase K in order to reverse DNA-crosslinking, and then purified using spin column tubes, as provided in the reagent kit.The SimpleChIP®Enzymatic Chromatin IP Kit  was applied with minor modifications and using two replicates. Briefly, for each immunoprecipitation (IP), around 4 × 1058.Library preparation for sequencing was performed using the NEBNext® Ultra™ II DNA Library Prep Kit for Illumina® , in accordance with the manufacturer’s protocol. AmPure XP beads  were used for the cleanup steps. Since the amount of input DNA was < 50 ng, no size selection was performed. Equimolar pooling of the samples was then performed, and the quality of the library was controlled on an Agilent High Sensitivity D1000 system. The samples were diluted to a final concentration of 2 nM. To achieve sufficient coverage, each replicate was sequenced twice on an Illumina MiSeq v2. This yielded ~ 20 million 2 × 250 bp paired end reads for each sample (ChIP and input control), in accordance with the ChIP-seq guidelines of the ENCODE consortium59 using BEDtools (v2.27.0). Peaks were then visually inspected in the Integrative Genomics Viewer . To extract a high-confidence set of peaks (termed “hc-peaks”), only those regions included in both replicates were included in the analysis.Quality control of the fastq-files was performed using FastQC (v0.11.7). Adapter sequences were cut-off using Cutadapt (v1.15), and reads were trimmed to a maximum length of 200 bp. For each sample and replicate, fastq files of both sequencing runs were merged and aligned to the GRCh37/hg19 reference genome using Bowtie2 (v2.3.4). Peak calling was performed using MACS2 (v2.1.1). Quality control included the retention of peaks with a fold enrichment (FE) of 5–50, and a false discovery rate (FDR) < 0.05. Peaks mapping to irregular chromosomes and ENCODE blacklist regions were removed31 and the most significant motif from ChIP-seq was further quantified and displayed by presenting the optimal alignments with the Tomtom motif comparison tool (v.5.1.0).Motif discovery was performed using the genomic sequence around the summit of each hc-peak (± 50 bp) and MEME ChIP (v.5.1.0). The similarity between TFAP2A motifs from the JASPAR Core 2018 assembly32. Here, concordant regions were defined as those for which HEPM TFAP2A ChIP-seq peaks showed a ≥ 50% overlap with the base pairs of HeLa S3 TFAP2A sites. Second, HEPM TFAP2A ChIP-seq peaks were compared with H3K27ac histone marks and DNase1 hypersensitivity sites derived from craniofacial tissues  at Carnegie stage 15 (CS15)34, indicating active regulatory elements in a human developmental stage that equated with the time point of the HEPM cells during craniofacial development. Since the ChIP-seq peak distribution for TFs and histone modifications differs, overlaps were defined using separate cut-offs . For both data sets, enrichment of the identified hc-peaks was determined using Chi2-test (1df).First, hc-peak positions were compared to TFBS in another TFAP2A ChIP-seq data set that had been obtained in HeLa S3 cells by ENCODEP binomial < 0.05). The subset of hc-peaks that contained SNPs with allele-specific TF binding was compared to TFAP2A ChIP-seq peaks in HeLa S3 cells32 and chromatin marks in CS15 craniofacial tissue34.NsCL/P associated SNPs that were located within the hc-peaks and predicted to be in a heterozygous state in the HEPM cells were extracted, and corresponding allele counts from ChIP-seq were analyzed using ABC (v.1.3). SNPs were considered allele-specific variants if one of the two alleles was overrepresented at a statistically significant level (Gene Ontology (GO) enrichment analysis was performed using the Genomic Regions Enrichment of Annotations Tool  with default parameters . GO biological processes, human phenotypes, and mouse single knockout phenotypes were considered. For these analyses, three subsets were defined: (i) all hc-peaks; (ii) hc-peaks that contained SNPs with allele-specific effects; and (iii) hc-peaks that overlapped with H3K27ac markers and DNase1 hypersensitivity regions in CS15 craniofacial tissue but not with the TFAP2A ChIP-seq peaks in HeLa S3.9. This imputed dataset contains nsCL/P association data for ~ 8.01 million variants . Briefly, this study included individuals of European  and of Asian ancestry . The association P-values of the GWAS meta-analysis were not corrected for multiple testing. Only SNPs with an info score > 0.8 in the GWAS meta-analysis were retrieved, and pairs of SNPs in high linkage disequilibrium were identified using LD link . This selection of SNPs was intersected with topological associated domains in embryonal stem cells, as identified by Dixon et al.35, and information on the 45 nsCL/P risk loci as described in Welzenbach et al.21.Positional data of the hc-peaks were integrated with results from our recent nsCL/P GWAS meta-analysisSupplementary Information.


Iridoviridae. Ranaviruses infect cold-blood vertebrates including amphibians, fish and reptiles, and contribute to catastrophic amphibian declines. FV3 has a genome at ~105 kb that contains nearly 100 coding genes and 50 intergenic regions as annotated in its reference genome. Previous studies have mainly focused on coding genes and rarely addressed potential non-coding regulatory role of intergenic regions.Frog Virus 3 (FV3) is a large dsDNA virus belonging to Ranaviruses of family cis-regulatory elements (CREs) in intergenic regions neighboring highly transcribed coding genes. These CREs include not only a virus TATA-Box present in FV3 core promoters as in eukaryotic genes, but also viral mimics of CREs interacting with several transcription factors including CEBPs, CREBs, IRFs, NF-κB, and STATs, which are critical for regulation of cellular immunity and cytokine responses. Our study suggests that intergenic regions immediately upstream of highly expressed FV3 genes have evolved to bind IRFs, NF-κB, and STATs more efficiently. Moreover, we found an enrichment of putative microRNA (miRNA) sequences in more than five intergenic regions of the FV3 genome. Our sequence analysis indicates that a fraction of these viral miRNAs is targeting the 3’-UTR regions of Xenopus genes involved in interferon (IFN)-dependent responses, including particularly those encoding IFN receptor subunits and IFN-regulatory factors (IRFs).Using a whole transcriptomic analysis of total RNA samples containing both the viral and cellular transcripts from FV3-infected frog tissues, we detected virus-specific reads mapping in non-coding intergenic regions, in addition to reads from coding genes. Further analyses identified multiple Using the FV3 model, this study provides a first genome-wide analysis of non-coding regulatory mechanisms adopted by ranaviruses to epigenetically regulate both viral and host gene expressions, which have co-evolved to interact especially with the host IFN response. Iridoviridae, which consists of a group of emerging viruses infecting fish, amphibians, and reptiles (Frog virus 3 (FV3) is a large ~105 kb), double-stranded DNA (dsDNA) virus belonging to Ranaviruses of the family 05 kb, doreptiles . FV3 infreptiles . Increasreptiles . So far,reptiles . Vilaça reptiles  detectedreptiles , 9. In treptiles , 9. Owinin vitro mostly using a model of fathead minnow (FHM) fish cells , it is reasonable to hypothesize that these intergenic regions in the FV3 genome exert a regulatory role underlying viral gene expression and virus-host interaction, especially at the epigenetic level  for interacting with host transcription machinery and orchestrating viral and host gene expression , was shown to interact with a FV3 protein  critical for transcription of ICP-18 gene  and one late (major capsid protein [MCP]) identified conservative CRE motifs located 127 to 281 bp upstream of the transcription start site (TSS), and other ones located within 30 bp proximity to the TSS . The TATA-Box is recognized by the TATA-binding protein (TBP) in a complex of several other transcription factors (TF), which recruits the RNA polymerase II (pol II) to initiate transcription process . Virusespression . For exanfection . Variousoviridae . Studies-18 gene . Additioene  species . miRNAs Along with recent virome studies and the identification of novel ranavirus isolates , 9, we pCREs in these intergenic regions corresponding to transcriptomic profiles of the coding genes. These CREs include those similar to TATA-Box marking the core promoters of typical eukaryotic genes  or baby hamster kidney (BHK) cells (ATCC® CCL-10) or a kidney A6 cell line (ATCC® CCL-102) were maintained and used for propagation and titration of FV3 virus stocks. Virus stocks were purified and the virus load was assessed by plaque assays in the BHK or A6 cells. Outbred specific-pathogen-free adult (1-2 years old) frogs were obtained from the X. laevis research resource for immunology at the University of Rochester (http://www.urmc.rochester.edu/mbi/resources/xenopus-laevis/).Two Frog virus 3 (FV3) strains, a wild type (FV3-WT) and an ORF64R-deprived strain (FV3-Δ64R), were used. The virus preparation and animal infection were conducted as previously described , 27, 32.6 PFU/each) or FV3-Δ64R (at 1 × 106 PFU/each) virus in 100-μl amphibian phosphate-buffered saline solution (APBS) or only APBS for mock controls. At 0, 1, 3, and 6 days postinfection (dpi), animals were euthanized and indicated tissues were sampled and pairwise allotted for classical viral titration and gene expression analyses, and the samples of 3 dpi were cryopreserved for further transcriptomic analysis as described  regulations . Adult frogs with the comparable Age/body-weight were randomly allotted into mock controls and infected groups (n = 5/group). Animal infections were conducted by intraperitoneal (i.p.) injection with FV3-WT  for PCR-based assays or a column-based RNA/DNA/protein purification kit  for transcriptomic analysis. RNA concentration and integrity were examined with a NanoDrop 8000 spectrometer  and an Agilent 2100 Bioanalyzer  to ensure RNA samples with A260/A280>1.8 and RNA integrity number (RIN) >7.0 qualified for construction of sequencing libraries , 32, 33.Quantitative PCR (qPCR) or qRT-PCR assays were conducted as described , 33. In X. laevis or FV3 virus through Xenbase (http://ftp.xenbase.org/) or NCBI genome ports , respectively. Data of virus-targeted transcriptome was reported here. The workflow of RNA-Seq analysis, bioinformatics software used, and some exemplary data to show general quality and comparability of the transcriptome data was schematically shown and previously reported  as previously described . For RNAreported . Differereported . The trahttps://www.ebi.ac.uk/). Other sequence management was conducted using programs at the Sequence Manipulation Suite (http://www.bioinformatics.org). Sequence alignments were visualized using Jalview  and MEGAx (https://www.megasoftware.net). Two programs/databases were used to confirm each other for the major CRE detection. The CREs (and corresponding binding TFs) in intergenic regions were examined against both human/animal TFD Database using a program Nsite . The mean position weight matrix (PWM) of key cis-elements in intergenic regions were examined and calculated using PWM tools through https://ccg.epfl.ch/cgi-bin/pwmtools, and the binding motif matrices of examined TFs were extracted from MEME-derived JASPAR CORE 2020 vertebrates or JASPAR CORE 2018 vertebrates clustering affiliated with the PWM tools  were extracted from FV3’s reference genome (GenBank accession number: NC_005946.1). The sequences were aligned using the multiple sequence alignment tools of ClustalW or Muscle through an EMBL-EBI port , delayed early (DE), and late (L) viral transcripts as previously designated. The expression levels of individual FV3 ORF coding genes were determined as averages across all samples to demonstrate the differential expression using the transcriptomic data. The relative expression order across and within each temporal gene classes was sorted. The intergenic regions immediately upstream of top-ten highly expressed FV3’s coding genes in each temporal class were extracted to perform PWM analyses as described above, and were compared to overall scores of all intergenic regions. The comparative analyses were broadly performed against various  factors , 34.http://www.softberry.com. The miRNA target prediction on the 3’-UTR of various Xenopus genes were performed using three RNA analysis programs through an online BiBiServ Service (https://bibiserv.cebitec.uni-bielefeld.de/). The sequences of 3’-UTR regions and information about alternative transcripts of X. laevis genes/transcripts were extracted from the gene annotations at Reference genome/transcripts of X. laevis or FV3 virus through Xenbase (http://ftp.xenbase.org/) and NCBI genome ports . The locations and sequences of all predicted v-miR are listed in The miRNA prediction and RNA structure prediction were analyzed using a findMiRNA and FoldRNA programs, respectively, through an online bioinformatic suite at Xenopus IRF and IFN receptor genes, transcriptomic analyses of X. laevis mRNA encoding various IRF and IFN receptor gene families to show the differential expression of these genes was compared between FV3-Δ64R- and FV3-WT-infected tissues. Wherein, some intergenic regions containing putatively responsible v-miR were demonstrated to transcribe differentially between these two FV3 strains. Particularly, several representative v-miR were synthesized and transformed into X. laevis A6 kidney cells to evaluate RNA interference effect against Xenopus IRF and IFN receptor genes. The small interfering RNA (siRNA) identical to representative v-miR sequences were synthesized and transformed as previously described ?. One-way analysis of variance (ANOVA) and Tukey’s nificant , 32, 33.The FV3 genome regions are functionally classified into exons, or intergenic regions based on annotation of the reference genome (NC_005946.1). All FV3’s coding ORFs span about 80% of the genome sequence, and lack introns, i.e., intronless . In contcis-regulatory role of intergenic regions on expression of coding genes, we first searched for putative viral TATA-box equivalent. In eukaryotic genes, the TATA-box is a cis-regulatory element (CRE) marking the core promoters. To identify a putative viral TATA-like box we used a software based on an evaluating score system of position weight matrix (PWM) used for vertebrate CREs  ahead of the TSS of downstream associated coding genes  with most scores higher than 5.0, which is close to the median value across PWM scores of multiple CREs executed in this study. The line chart in CRE in intergenic regions may function to recruit vPol II through binding of the transcription factor TBP and signifies the core-promoter regions, it is not the only determinant  in FV3 genome intergenic regions. We focused our interest on CRE families that are critical in regulation of amphibian antiviral immunity. These v-CREs include those predicted to interact with transcription factors (TFs), such as the IRF and STAT families that critically mediate cytokine- and IFN-dependent signaling. Among these factors, NF-κB-like and PU.1 (a.k.a. SPI1) regulate inflammation, whereas other like the CEBP and CREB families control immune cell proliferation and activation  for other IRFs. Similarly, v-CREs with significant prediction for binding members of the STAT family were detected in almost all intergenic regions and for all vertebrate STAT members with average PWM scores between 2.0-6.0 log2Unit in an increasing order of STAT1(2.0)<STAT4≈STAT6(4.0)<STAT3(5.0)<STAT2≈STAT5a/b(6.0)  define a class of small 21-25 nt), non-coding regulatory RNA species discovered widely across biological kingdoms from bacteria to humans , 44. Mic nt, non-Xenopus genomes may contain two or more gene loci especially for the beta subunits of IFN receptors, and the increased complexity of relevant gene composition is observed particularly in X. laevis species that has an allotetraploid genome , II (ifngr1/2), and III (ifnlr1/il10rb) IFNs. The basal expression of these IFN receptor genes, as estimated by FPKM values (Fragments Per Kilobase of transcript per Million mapped reads) in the control kidney, shows a differential expression order: ifnar1.S≈il10rb.L>il10rb.S>ifngr2.L≈ifngr1.S≈ifnar2.2.S>>others. This observation raises several points about the intricated expression of IFN receptor genes in X. laevis: (1) In X. laevis’s allotetraploid chromosomes, both short (S) and long (L) subgenomes harbor actively expressed isoforms of IFN receptor genes (il10rb.S and il10rb.L), perhaps because il10rb is shared by IL-10 cytokine family  Dese family , 50; andifnar1.S and upregulation of ifnar2.S seemed not correlated to the v-miR-target prediction as shown in ifnar2.S v-miRs and a v-miR-independent suppression of ifnar1.S that warrants further investigation  are a family of transcription factors that comprise about 10 homologous members (IRF1-9) in tetrapods . As studresponse . Collectresponse , 57. Taphibians , 51–56. phibians , 46. The. Indeed, the threshold of Mfe for the v-miR prediction was set as -28.0 kcal/mol to reflect Mfe of typical miRNA (like let7) hybridization to its mRNA target. ifnxr2 gene targets at one site of each gene; and irf genes. Noted that some v-miR has multiple target sites on the targeted genes, such as both C-20 and AT-20 have six targeting sites on the 3-UTR of ifnar2.2S, and have three or four target sites on il10rb.S, respectively  in these intergenic regions corresponding to transcriptomic profiles of highly expressed coding genes. These CREs include not only the TATA-Box-like similar to bona fide TATA-Box marking the core promoters of typical eukaryotic genes, but also viral mimics of CREs interacting with various transcription factors including CREBs, CEBPs, IRFs, NF-κB, and STATs, which are all critical for regulation of cytokine responses and cellular immunity , a representative Ranaviruses that causes prevalent infection in anurans and is implicated in catastrophic amphibian declines –7. We foimmunity , 37–42.  factors , 40, 57.N system , 33, 57.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The animal study was reviewed and approved by University of Rochester Committee on Animal Resources (UCAR) regulations .YT, CNK, JL, and FJ contributed to conduct experiments, student training, and proof reading. JR contributed to conceptualization, funding acquisition, advisory direction, and resource sharing. YS performed overall conceptualization, experimental coordination, data analysis, draft writing, and funding acquisition. All authors contributed to the article and approved the submitted version.This work was primarily supported by NSF-IOS-1831988, and in part through reagent sharing of USDA NIFA Evans-Allen-1013186, NIFA AFRI 2018-67016-28313, and NIFA AFRI 2020-67016-31347 to YS, and NSF-IOS-1456213 to JR. The Xenopus laevis research resource for immunobiology is supported by NIH R24AI059830.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.


Gsk3β, a critical regulator of Wnt signaling, in the developing mouse neocortex. Gsk3β expression was higher in ventricular neural progenitors, while it gradually declined in differentiated neurons. We identified active cis-regulatory module (CRM) of Gsk3β that responded to cell type-specific transcription factors, such as Sox2, Sox9, and Neurogenin2. Furthermore, we found extensive conservation of the CRM among mammals but not in non-mammalian amniotes. Our data suggest that a mammalian-specific CRM drives the cell type-specific activity of Gsk3β to fine tune Wnt signaling, which contributes to the tight control of neurogenesis during neocortical development.Temporal control of neurogenesis is central for the development and evolution of species-specific brain architectures. The balance between progenitor expansion and neuronal differentiation is tightly coordinated by cell-intrinsic and cell-extrinsic cues. Wnt signaling plays pivotal roles in the proliferation and differentiation of neural progenitors in a temporal manner. However, regulatory mechanisms that adjust intracellular signaling amplitudes according to cell fate progression remain to be elucidated. Here, we report the transcriptional controls of  The mammalian neocortex is a remarkable architecture in terms of its enormous tangential expansion of surface areas and a six-layered laminar organization . These cThe anatomical features of the neocortex are unique in extant mammalian species. Several comparative studies have identified neocortical homolog in non-mammalian vertebrates, despite extraordinary divergence in their size and morphology . For exavia the regulation of the FGF-, Notch-, and Shh-dependent signaling pathways  for murine Gsk3β that responds to cell type-specific transcription factors (TFs), such as Sox2, Sox9 and Neurogenin2. Furthermore, we found extensive conservation of the CRM among mammals but not in non-mammalian amniotes. These data suggest that the mammalian-specific CRM drives cell the type-specific activity of Gsk3β to fine tune Wnt signaling, which contributes to the tight control of neurogenesis during neocortical development.Here, we report the transcriptional controls of Gsk3β is higher in ventricular progenitors but gradually declines according to neuronal differentiation  and examined transcriptional activities by luciferase assay , a transcription factor responsible for neuronal specification, decreased Gsk3β promoter-dependent transcriptional activity  were obtained from Japan SLC, Inc., The day on which vaginal plugs were found at midday was considered embryonic day 0.5 (E0.5). All experimental procedures in this study were approved by the experimental animal committee of Kyoto Prefectural University of Medicine and Institutional Animal Care and Use Committee of RIKEN Kobe Branch and were performed in accordance with the relevant guidelines .Pregnant mice  based on H3K4me3 and H3K27ac ChIP-seq data of Mus musculus C57BL/6 E14.5 forebrain tissue . Searching TF binding sites in Gsk3β promoter sequences was performed by using JASPAR CORE.2 Comparative analysis of Gsk3β genomic loci was performed using VISTA-point3 and the UCSC genome browser based on mouse assembly . Multiple sequence alignment between green anole , painted turtle , and chicken  was performed by using mVISTA.4 Five primes UTR sequences of mouse Gsk3β and predicted TF binding sites are deposited to Mendelay Data (doi: 10.17632/8d3t3frxb9.2).ENCODE Encyclopedia version 5Gsk3β promoter and 1st exon were chemically synthetized (BEX) and subcloned into the pGL3-promoter vector (Promega). Mouse Sox9 (NM_011448) cDNAs were obtained by PCR amplification and subcloned into the pCAGGS vector (Expression vectors used in this study were constructed by using the In-Fusion HD cloning system (Clontech). Genomic fragments corresponding to the mouse S vector . pCAG-SoS vector ], pCAG-NS vector ]. pCAG-NGsk3β promoter and exon1 to TFs, we introduced luciferase reporter vectors together with pCAG-Sox9, pCAG-Sox2-IRES-Neo, pCAG-Ngn2, or pCAG-NeuroD1iresGFP. As a control condition, pCAGGS empty vector was co-transfected with reporter vectors. Twenty-four hours after transfection, luciferase activity was examined with a single-tube luminometer . Firefly and Renilla luciferase activities were measured with a Dual-Luciferase Reporter Assay System (Promega). To examine transcriptional activities of reporter vectors in the developing mouse brain, we isolated E13.5 mouse forebrains and injected DNA solution containing luciferase reporter vectors into the lateral ventricle. Square pulses  were applied to brains by using an electrode  and a pulse generator . After electroporation, the brains were transferred to glass bottles filled with Dulbecco Modified Eagle Medium (DMEM) containing 10% fetal bovine serum and cultured in the rotating culture system (IKEMOTO RIKA) at 37 C° for 24 h supplied with 40% oxygen.HEK293T cells were transfected with the pGL3, pGL3-Gsk3β promoter or pGL3-Gsk3β exon 1 by using Lipofectamine 2000 (Thermo Fisher Scientific). To monitor the transfection efficiency, the pRL-SV40 vector expressing Renilla luciferase was transfected under all experimental conditions. To examine the response of In situ hybridization was performed according to previous studies (Gsk3β (NM_019827) were obtained from Origene and subcloned into pBluescriptSK vector. cDNA corresponding to Gecko Gsk3β  was chemically synthesized. The in situ hybridization data were obtained from samples examined in our previous study  and Prism9 . Raw data obtained in this study is available as a Souse Data File at Mendelay Data .For statistical analysis of the luciferase assay, three or four independent biological samples from each experimental group were compared. Normality of each data set was confirmed by Shapiro-Wilk test, and statistical significance was examined by unpaired The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.The animal study was reviewed and approved by the Satoshi Ohtshuka (Kyoto Pref Univ Med), Yasuhide Furuta (RIKEN).TN contributed to the experimental design, data collection, interpretation, and manuscript preparation. HK contributed to the establishment and maintenance of the Madagascar ground gecko colony. HG and KO contributed to the acquisition of the reagents and interpretation. All authors discussed the data and interpretation and confirmed the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Omics studies are crucial to improve our understanding of myotonic dystrophy type 1 (DM1), the most common muscular dystrophy in adults. Employing tissue samples and cell lines derived from patients and animal models, omics approaches have revealed the myriad alterations in gene and microRNA expression, alternative splicing, 3′ polyadenylation, CpG methylation, and proteins levels, among others, that contribute to this complex multisystem disease. In addition, omics characterization of drug candidate treatment experiments provides crucial insight into the degree of therapeutic rescue and off-target effects that can be achieved. Finally, several innovative technologies such as single-cell sequencing and artificial intelligence will have a significant impact on future DM1 research. DMPK) gene. Disease severity varies with the number of CTG repeats: unaffected individuals carry 5 to 37 triplets, mildly affected persons between 50 and 150, patients with classic DM1 from 100 to 1000, and those with onset at birth can have more than 2000 repeats [DMPK transcripts, which alters the function of various downstream effectors, triggering gene deregulations through alterations in transcription [DMPK transcript toxicity are the CUGBP-ETR-3-like (CELF) and Muscleblind-like (MBNL) factors, both controlling the inclusion of alternative exons in several transcripts according to tissue and developmental state cues [Myotonic dystrophy type 1 (DM1), an inherited neuromuscular disease, is the most common type of muscular dystrophy in adults, with a reported prevalence of up to one in every 2100 births . The dis repeats . The pricription , gene sicription , and polcription . In DM1,ate cues . New andate cues .MBNL1 and 2 are broadly expressed, but MBNL1 is the paralog that serves a primary role in most tissues, except for the brain, where MBNL2 is predominantly detected, whereas MBNL3 expression is more restricted and has been related to muscle-cell differentiation inhibition, aging, and regeneration [The MBNL family comprises the MBNL1, MBNL2, and MBNL3 RNA metabolism regulators, whose expression levels are tightly regulated by the developmental stage in each tissue. neration ,14,15,16neration ,18.Alternative splicing (AS) is an RNA-processing mechanism that removes sequences (introns) between splicing sites in pre-mRNAs to process mRNAs . It is mLR mouse model, a transgenic mouse carrying a genomic fragment of the human skeletal actin (ACTA1) gene with ~250 CTG repeats in the 3′-UTR, which is expressed in the skeletal muscle only. This model recapitulates RNA toxicity alterations by displaying myopathy, centrally located nuclei in muscle fibers, and AS defects [ATP2A1, BIN1, INSR, LDB3, MBNL1, and TNNT2 [Various disease models have been developed to investigate the pathogenic mechanisms associated with DM1. Some of the most commonly used in omics studies are: (1) the HSA defects . (2) The defects ,25,26. Fnd TNNT2 . Other lIn recent years, new advances in and the widespread application of omics technologies have enabled cost-efficient, high-throughput, in-depth analyses of transcripts, proteins, and other molecules, creating an unprecedented body of knowledge  and enabTranscriptomics is the study of the full range of transcripts at the RNA level of a biological system . Tools sThe broad DM1 symptomatology impinges particularly on three critical body systems: skeletal and cardiac muscles and the brain. Together, these tissues comprise the focus of most omics studies done in DM1 so far, addressed specifically below .LR mice quadriceps were reproduced in the same muscle of mice lacking functional MBNL1 proteins  and C2C12 cells helped map the MBNL binding sites precisely. This study revealed that skeletal muscle had the most MBNL1 CLIP sites, and that these sites showed a defined pattern around alternative exons across all samples and tissues, suggesting that splicing activation or repression depends on where MBNL1 binds. Specifically, two repression peaks were found, one located right on the cassette exon and another upstream of the 3′-splice site, consistent with the blocking of exon enhancer elements or intronic elements , respectively [One of the most supported hypotheses in DM1 is that MBNL proteins are responsible for a large fraction of the aberrant AS patterns observed in muscle. Initial work with splicing sensitive microarray analysis found that 80% of approximately 200 alternative isoform changes observed in HSA1ΔE3/ΔE3 ), leavin1ΔE3/ΔE3 ,37. A la1ΔE3/ΔE3 . A complectively . Howeverectively .ΔE3/ΔE3; MBNL2+/− mouse  showed a high correlation of splicing alterations between MBNL3/4KO, MBNL1ΔE3/ΔE3, and HSALR, indicating a major role for MBNL sequestration in murine models of this disorder [LR and MBNL3/4KO mice. Clear developmental transitions for most events across embryonic and adult samples were observed, suggesting that mis-splicing in DM1 reflects a reversion to fetal or neonatal AS patterns in muscle, as has been extensively reported in previous studies [A different RNA-Seq study analyzing muscle samples of a compound loss of MBNL1disorder . MBNL bidisorder  in which studies ,38,40. I studies . No corewww.dmseq.org (accessed date 20 December 2021) was created as part of a major RNA-Seq work that sequenced various human samples from biopsies and autopsies, including tibialis anterior samples of 44 DM1 patients and 11 unaffected controls [CLCN1 and CLASP1 and various alternative last exon inclusions. Furthermore, AS alterations found in biopsies correlated significantly with known DM1 splicing biomarkers [tibialis biopsies. In the case of autopsies, a lower degree of altered AS pattern was also observed in the quadriceps when compared with other distal muscles, such as the deltoids, gastrocnemius, or soleus, providing a molecular explanation for the distal to proximal pattern of muscle weakness and wasting found in DM1 patients  [CLCN1) transcripts, both triggering nonsense-mediated decay resulting in a severe reduction in functional CLCN1 [Despite major advances from in vitro and in vivo models, the DM1 field lacked a transcriptome dataset that would serve as a benchmark to compare to subsequent experimental analyses. To this end, controls . While mcontrols . Using tmuscles) . The AS al CLCN1 .To evaluate the full extent of AS deregulation in DM1, another study used whole human exome microarrays to compare skeletal muscle samples of DM1 with those of other neuromuscular disorders: dystrophy type 2 (DM2), Duchenne muscular dystrophy, Becker muscular dystrophy, and Tibial muscular disease . CompareΔE3/ΔE3 and MBNL2ΔE2/ΔE2 double KO (DKO) and in MBNL null MEF (DKO/3KD) conditions, the last obtained by siRNA-induced MBNL3 silencing in the DKO background [LR mice [Calm3 transcript presents overlapping binding sites for all three MBNL proteins in two different polyadenylation sites. To clarify the biological effects of APA in DM1, HSALR quadriceps muscle was analyzed using polyA-Seq. The findings suggest that MBNL sequestration by CUG repeats often leads to reversion to the fetal APA pattern observed in MEFs. To validate these observations, human DM1 and control vastus lateralis were analyzed by both polyA-Seq and microarray. Similar to findings in DKO/3KD MEFs, the results showed that DM1 patients have a majority (59%) of polyadenylation sites shifted upstream. Key genes related to muscle atrophy  showed altered APA, suggesting that pathways known to inhibit protein synthesis and activate protein catabolism were altered [Hundreds of genes presenting APA have been reported in DM1 muscle as part of previous RNA-Seq work . A laterckground . Microar[LR mice , an overajority 5% of polyProteomics studies provide critical data about protein post-translational modifications, activity, and stability, which are crucial to elucidate the cellular pathways affected in DM1. Since these effects cannot be reliably predicted from RNA-Seq data, a combination of both transcriptomics and proteomics is desirable. In this regard, André et al. used myoblasts derived from DM1 patients (carrying a (CTG)2600 repeat expansion) with isogenic controls obtained after removal of the repeat tract by CRISPR/Cas9 gene editing . Fifty-tCentral nervous system (CNS) impairments are also prominent in DM1, particularly in congenital cases, which present with intellectual disability, attention-deficit hyperactivity, and autism spectrum disorders . The broDMPK RNA foci with MBNL1 and MBNL2 in brain samples [An important question addressed in the past was whether MBNL proteins are functionally affected by expanded CUG-repeats in the diseased brain, as suggested by the colocalization of  samples ,53. Inde samples .DMPK gene constructs with 0 and 648 CTG repeats in an inducible doxycycline-dependent manner. Control and DM1 cell lines were analyzed using microarray technology to quantify gene expression, finding alterations in the inflammatory response. Furthermore, MBNL1- and MBNL2-dependent AS were dysregulated, and both splicing factors colocalized with CUG RNA foci, demonstrating that in MIO-M1 cells, lacking the natural DMPK genomic context, CTG expansions are sufficient to recapitulate critical molecular aspects of the disease [In a complementary approach, a glial cell model of DM1 was generated using the MIO-M1 (human Muller glia) cell line expressing human  disease .DMPK transcripts [DMPK overexpression rather than expanded CUG RNA. SYN1 aberrant activation by phosphorylation affects synaptic vesicle transport, which was confirmed in transfected cells and post-mortem brains of DM1 patients. In another study analyzing cerebellum samples of the same mouse model, a global proteomics approach identified strongly downregulated GLT1 (a glutamate transporter) in DM1 mice and human patients [A few recent studies have combined multiple omics approaches, including proteomics analysis, to elucidate DM1 pathological mechanisms in the brain using the DMSXL mouse model, with characteristic disease alterations in the CNS ,25. In anscripts . Using Dpatients . GLT1 dopatients . Moreovetibialis anterior and heart muscles [MBNL1 exon 5, MBNL2 exon 5, and MAPT exon 3, suggesting a similar mechanism for splicing dysregulation across all tissues [A study in the frontal cortex comparing the transcriptome from 21 DM1 and 8 unaffected post-mortem, age- and sex-matched individuals found 130 exons differentially included between DM1 and controls . These a muscles , finding tissues .ΔE3/ΔE3 mice [Another highly studied tissue in DM1 is the heart. Alterations specific to this organ were described in a transcriptome analysis using AS profiling microarrays performed in embryonic and adult MBNL1ΔE3 mice . This woΔE3 mice .Gallus gallus to identify transcripts regulated by CELF1 in the embryonic myocardium. RNA-Seq and CLIP-Seq analyses were performed for this purpose, finding that 75% of the CELF1 CLIP tags within genes mapped to intronic regions, consistent with the localization of CELF1 in the nucleus in embryonic heart muscle cells, and with its known role as a regulator of pre-mRNA AS in the heart [A similar study was performed in the hearts of he heart . Upon ovhe heart . Of the he heart .DMPK exon 15 containing 960 CUG repeats. A coordinated adult to embryonic shift was observed in the hearts of these mice upon CUG repeat RNA expression, as analyzed by microarray technology. Functional annotation of the altered genes revealed downregulation in the cardiac transcription factors MEF2a and MEF2c, correlating with the mRNA and miRNA alterations described in this tissue [RBFOX2) was up-regulated in this DM1 tissue. Next, a doxycycline-dependent CELF1 overexpression mouse was developed to understand the relationship between this RBP and CELF1. This model showed a significant change in RBFOX2 isoforms and pro-arrhythmic phenotypes, demonstrating a link between elevated CELF1 activity and DM1-related cardiac conduction delay and arrhythmogenesis [Failure of a developmental switch was also found in the heart-specific EpA960 mouse model that inducibly expresses human ogenesis .tibialis tissues from the autopsies of 10 DM1 patients with three unaffected individuals [PDLIM3 were altered in all DM1 samples, suggesting a possible biomarker for disease progression in this tissue. A high correlation was found in the percentage of cassette exon inclusion between the heart and tibialis, suggesting that the molecular mechanisms of DM pathogenesis are conserved across both tissues. Many of these exons have been validated as MBNL-dependent targets, including MAPT, NUMA1, MBNL2, NCOR2, and LDB3. Nevertheless, several exons were tissue-specific for heart or tibialis [To evaluate the extent of the gene expression alterations present in DM1 hearts, an RNA-Seq approach compared AS events in heart and ividuals . The fintibialis .DMPK exons 11–15 carrying 960 interrupted CTG repeats in cardiomyocytes [Recently, a new mouse model has been reported, with inducible expression of human myocytes . RNA-Seqmyocytes .DMPK mRNA is highly expressed in the lens epithelia, which indicates that significant RNA toxicity may be occurring in the eyes. Gene expression alterations were also highly similar in DM1 and DM2 samples, identifying 317 significantly altered common genes and no significant alterations in DMPK transcript levels between control and DM1 or DM2 samples. A pathway analysis of the altered common genes in DM1 and DM2 identified type 1 interferon signaling pathways as a potential contributor to the advent of cataracts [Misregulated AS and alterations in RBP expression explain key phenotypes in the muscles, brain, and heart, but DM1 clinical manifestations in other tissues remain poorly understood. One example where omics approaches are providing insight is in explaining cataracts. Recent studies using microarray technology with epithelial cell lines established from the cataracts of affected DM1 and DM2 patients suggest that ataracts ,64.MBNL1 to be highly expressed while DMPK had little expression during embryogenesis, suggesting that MBNL proteins play a vital role in thymic organogenesis and thymocyte development. To further evaluate this hypothesis, publicly available RNA-Seq data from 9-week-old MBNL1ΔE3/ΔE3 mice were compared to littermate controls, finding over 1000 genes with altered expression in pathways related to the apoptotic process and cell differentiation. At the AS level, 866 alterations were found, including known MBNL1 targets CLASP1, NCOR2 exon 46, DNM2 exon 10 and 11, and transcription factor Lef1 exon 6, which has been extensively described as an important factor in thymocyte development [Lef1 are related to MBNL1 depletion. Results indicate that MBNL1 proteins play a role in pre-mRNA processing by regulating the AS of these critical transcription factors required for normal T-cell development [Although traditionally neglected in the DM1 field, the immune system is also known to be affected in DM1 . In one elopment ,68. TheyGiven their previously known significance in human disease, DNA methylation (DNAme) and regulatory microRNA (miRNA) profiles are suitable for characterization in DM1 by means of whole-genome epigenomics experimental strategies. To date, DNAme omics studies in DM1 have focused only on CpG islands surrounding the CTG repeat , mainly MiRNAs are ncRNA molecules that play crucial roles as epigenetic modulators, inducing post-transcriptional changes in gene expression by mRNA destabilization and/or translation repression . The expDM1 is also defined as a metabolic syndrome due to features such as dyslipidemia, insulin resistance, hypertension, and pro-inflammatory state, among other alterations consistently present in DM1 patients . RecentlGiven the well-defined transcriptome alterations associated with DM1, evaluating the degree of rescue and off-target effects of candidate drugs during preclinical testing by AS quantification has become customary in the field. Among the therapeutic strategies currently being explored ,78, the LR mouse model without signs of toxicity. One of the most relevant rescue mechanisms was the increase of Muscleblind protein levels in Drosophila, HSALR mice, and PDIM disease models, which prevented protein degradation [In a recent study, autophagy was found to be up-regulated in DM1 patient muscle biopsies  and PDIMradation .LR mice versus controls, a synergistic effect was found when erythromycin was combined with furamidine. RNA-Seq analysis detected recovery of around 73% of the AS defects observed in HSALR mice, a percentage nearly double the amount of that detected for furamidine or erythromycin alone, independently of dosage. Off-target effects of each treatment were evaluated by quantifying the alterations not present in control vs. HSALR mice but present in the HSALR vs. HSALR-treated comparison. Off-targets were increased in the combined treatment compared to each treatment alone, but not nearly as much as when higher doses of each drug were tested alone [An alternative approach, used by Nakamori et al., was to interrupt the interaction between toxic RNA and MBNL proteins. A drug screening searching for small molecules with these characteristics found erythromycin as a promising candidate . Using Hed alone .INSR exon 11, TNNT2 exon 5, ATP2A1 exon 22, DMD exon 71, DMD exon 78, and KIF13A exon 32, among others [A type 2 diabetes mellitus drug known as metformin is well ahead in the race to develop a treatment for DM1. It was tested in mesodermal precursor cells differentiated from control and patient embryonic stem cell lines at 10 and 25 mmol/L, following which 63 and 1171 genes showed recovery of expression levels, respectively. Regarding AS correction, 95 and 416 exons presented a reversal above 10% at each dose. Gene enrichment analysis of the 416 transcripts identified gene sets involved in the cytoskeleton, nuclear lumen, and RNA binding. A subset of recovered AS events were validated by RT-qPCR, including DM1-related mis-splicing of g others .DMPK transcripts via activation of the RNase-H machinery in the nucleus using antisense oligonucleotides (ASOs). Microarray technology was employed to evaluate alterations in genes related to apoptosis, cytotoxicity, and inflammation processes at tenfold the optimal dosage, finding no significant alterations in these processes. Promising results were also found rescuing the expression of 41 and 14 genes affected in human cell culture and DMSXL mice, respectively, advancing progress towards a clinical trial [Since DM1 is a genetic disease, RNA-based therapies are potentially an effective strategy. An approach tested in one study aimed to degrade toxic al trial .GSK3B  and DMPNUMA1, MBNL2, and LDB3. Interestingly, disease-causing DMPK transcripts also presented AS.CRISPR/Cas9 is a promising platform to potentially correct dominant genetic diseases by gene editing, showing unprecedented precision. In the DM1 field, this technology was applied to patient-derived iPSC to delete the expanded CTG repeats, after which these cells were compared to non-corrected ones by RNA-Seq ,91. The This review has provided an overview of the most relevant key studies to date using omics data to elucidate DM1 molecular pathogenesis , puttingDMPK gene, together with the toxicity of expanded CUG repeats over both RBPs, may partly explain the multisystemic nature of DM1. In addition, the key role in splicing regulation of these proteins most probably accounts for the high quantity of AS alterations found across DM1 tissues.As known major players in DM1 pathology, MBNL and CELF proteins are a primary focus of analysis in multiple omics studies. Mounting omics evidence suggests critical roles for these RBPs as competitors or co-regulating factors in key AS and APA events. The ubiquitous nature of the Future perspectives in DM1 research advocate implementing current state-of-the-art technologies such as single-cell and third-generation sequencing. Single-cell analysis is currently used as a potent tool to explore omics changes in tissues composed of a complex mixture of cell types. This could be particularly important in the DM1 field since the most affected tissues are composed of a variety of cells with very specialized functions. Furthermore, expanded CTG microsatellites show somatic instability , presentThe unprecedented accuracy in evaluating the RNA composition of DM1 samples has provided strong support for the toxic RNA hypothesis, by pinpointing all AS and APA changes in the disease and the regulatory factors involved. Moreover, omics approaches now provide global metrics to compare the efficacy of candidate therapies. Nevertheless, current sequencing technologies suffer from limitations: repeat expansions or structural variants have proven very challenging to sequence, and, despite certain progress, there is still room for improvement. Third-generation sequencing, such as Oxford Nanopore Technologies (ONT) or Pacific Bioscience single-molecule, real-time technologies (SMRT), can bypass these limitations by generating long reads covering an average of 20 Kbp and 30 Kbp, respectively, with the current record being 2.3 Mbp of a single continuous read from ONT ,94,95,96tibialis anterior tissue and ankle dorsiflexion force was found, suggesting a relationship between circRNA and disease severity [Another field with great potential is data mining of already available datasets. For example, taking advantage of the extreme depths of RNA-Seq data in dmseq.org , one stuseverity .Finally, breakthrough advances in artificial intelligence (AI) are enabling accurate protein structure predictions , which i