However, how this network regulates chlorophyll degradation at molecular level is not yet elucidated. Here we report a feed-forward regulation of chlorophyll degradation that involves EIN3, ORE1, and chlorophyll catabolic genes (CCGs). Gene expression analysis showed that the induction of three major CCGs, NYE1, NYC1 and PAO, by ethylene was largely repressed in ein3 eil1 double mutant. Dual-luciferase assay revealed that EIN3 significantly enhanced the promoter activity of NYE1, NYC1 and PAO in Arabidopsis protoplasts. Furthermore, Electrophoretic mobility shift assay (EMSA) indicated that EIN3 could directly bind to NYE1, NYC1 and PAO promoters. These results reveal that EIN3 functions as a positive regulator of CCG expression during ethylene-mediated chlorophyll degradation. Interestingly, ORE1, a senescence regulator which is a downstream target of EIN3, could also activate the expression of NYE1, NYC1 and PAO by directly binding to their promoters in EMSA and chromatin immunoprecipitation (ChIP) assays. In addition, EIN3 and ORE1 promoted NYE1 and NYC1 transcriptions in an additive manner. These results suggest that ORE1 is also involved in the direct regulation of CCG transcription. Moreover, ORE1 activated the expression of ACS2, a major ethylene biosynthesis gene, and subsequently promoted ethylene production. Collectively, our work reveals that EIN3, ORE1 and CCGs constitute a coherent feed-forward loop involving in the robust regulation of ethylene-mediated chlorophyll degradation during leaf senescence in Arabidopsis.Degreening, caused by chlorophyll degradation, is the most obvious symptom of senescing leaves. Chlorophyll degradation can be triggered by endogenous and environmental cues, and ethylene is one of the major inducers. ETHYLENE INSENSITIVE3 (EIN3) is a key transcription factor in the ethylene signaling pathway. It was previously reported that EIN3,  ACS2 during senescence, and subsequently activates a positive feedback to ethylene synthesis. Our work reveals a feed-forward loop that promotes ethylene-mediated chlorophyll degradation during leaf senescence, advancing our understanding on the molecular mechanism of leaf yellowing.Yellowing, caused by chlorophyll degradation, is the most obvious symptom of senescent leaves. Chlorophyll degradation can be triggered by a broad range of endogenous and environmental cues, and ethylene is one of the major inducers. Yet, the molecular regulation of chlorophyll degradation remains largely unknown. Here, we report a feed-forward regulation of ethylene-mediated chlorophyll degradation that involves ETHYLENE INSENSITIVE3 (EIN3), ORE1/NAC2, and major chlorophyll catabolic genes. EIN3, a master positive regulator of ethylene signaling, could directly promote chlorophyll degradation by physically binding to the promoters of three major chlorophyll catabolic genes to activate their expressions. Meanwhile, ORE1, a direct target of EIN3, also activates the expression of the similar set of chlorophyll catabolic genes directly. Moreover, ORE1 activates the expression of a major ethylene biosynthesis gene  Arabidopsis thaliana have identified dozens of senescence-related mutants and hundreds of senescence-associated genes (SAGs) involved in light signaling, hormone signaling and chl catabolism [Leaf senescence occurs at the final stage of leaf development and involves a series of changes at the molecular, cellular and phenotypic levels. Senescence is initiated by characteristic degenerative processes, e.g. chlorophyll (chl) degradation and macromolecule breakdown, and particularly recycling of nutrients to actively growing tissues or storage organs . Molecultabolism –4. The pArabidopsis via the identification of chl catabolic genes (CCGs). As the initial step, chl b is converted into chl a through two reductive reactions that are catalyzed by chl b reductase (NYC1/NOL) and 7-hydroxymethyl chl a reductase (HCAR), respectively [a is removed by an enzyme not yet identified to form pheophytin a. The phytol tail of pheophytin a is subsequently removed by pheophytin pheophorbide hydrolase (PPH) to produce pheophorbide a [a oxygenase (PAO) to generate red chlcatabolite (RCC), which is degraded further by RCC reductase (RCCR) [A biochemical pathway of chl degradation was recently elucidated in ectively –7. Then orbide a ,9. The re (RCCR) . The cone (RCCR) . SGR1/NYe (RCCR) ,12.1-Aminocyclopropane-1-carboxylic acid (ACC) synthase (ACS) and ACC oxidase (ACO), were upregulated in senescing leaves, coupled with an increased ethylene level [ACSs showed a stay-green phenotype [ETR1, etr1-1, and loss-of-function mutants ein2  and ein3 were all isolated as delayed-senescence mutants [Plant hormones have been extensively reported to regulate leaf senescence, with ethylene, abscisic acid, jasmonic acid, brassinosteroid and salicylic acid functioning as inducers and auxin, cytokinin, and gibberellic acid as inhibitors ,13–16. Ene level . An octuhenotype . In the henotype , leadinghenotype ,20. EIN2henotype –24. EIN3 mutants –27, whicmiR164 and one of miR164 target genes, ORE1/NAC2 [ORE1/NAC2 is a member of NAC transcription factor family which has been shown to play an important role in leaf senescence. In particular, ORE1 is a positive regulator of leaf senescence, promoting the expression of senescence-associated genes BFN1, SAG29, and SINA1 by directly binding to their promoters [miR164, which negatively regulates ORE1 at the post-transcriptional level [ORE1 by binding to its promoter to accelerate leaf senescence [ORE1 directly and indirectly. Although both mutants of EIN3 and ORE1 showed delayed senescence or stay-green phenotypes, the molecular mechanism of how these genes regulate chl degradation during senescence is still largely unknown.The pivotal role of ethylene in leaf senescence was further confirmed by the revelation of a feed-forward loop, whereby EIN2 affects leaf senescence in part by regulating the expression of RE1/NAC2 . ORE1/NAromoters . EIN3 waal level . Meanwhinescence . These fNYE1, NYC1 and PAO, by binding to their promoters. Meanwhile, one of the EIN3 direct targets, ORE1/NAC2 [NYE1, NYC1 and PAO as well as NOL. Moreover, EIN3 and ORE1 promote NYE1 and NYC1 transcriptions in an additive manner. Intriguingly, ORE1 can also promote the transcription of ACS2 for a positive feedback regulation of ethylene biosynthesis and signaling.In this study, we report that EIN3 promotes chl degradation via the direct up-regulation of major chl catabolic genes, RE1/NAC2 , also diORE1/NAC2, a master senescence-associated NAC transcription factor with significantly increased expression in the senescing leaves [ORE1 expression was abolished in the leaves of 4-week-old ein3 eil1 plants , ATGAACCT, located 1056~1064 bp upstream from the start codon (ATG) of the gene  caused early leaf yellowing  directly binding to the ORE1 promoter and activating its expression, and 2) indirectly inhibiting the expression of miR164 and thereby activating ORE1.We then tested whether ellowing . To chec3 mutant . The OREn3 lines . Considecleavage . The miRpromoter . So the 1ox ein3 . This reeviously . We alsoat in WT , suggestein3 eil1 showed delayed senescence and a stay-green phenotype with ACC treatment [ein3 eil1 with ethylene treatment  gene [35S:REN) with the Renilla luciferase (REN) gene under the control of a CaMV 35S promoter and functioned as an internal control to normalize the expression of each reporter gene (35S promoter driving the full-length EIN3 cDNA (35S:EIN3) was used as an effector, and the empty vector was included as a control (Arabidopsis protoplasts prepared from WT plants and luciferase activity (LUC/REN) was detected. Overexpression of EIN3 increased luciferase activity of each reporter as compared with the corresponding empty control   . Therefo and PAO . As wellbidopsis .CCGs was further confirmed by transient dual luciferase assay in Arabidopsis protoplasts, with a construct overexpressing ORE1 (35S:ORE1) as an effector and promoters of NYE1, NYC1, NOL and PAO driving LUC as reporters , which displayed an early-yellowing phenotype with ethylene treatment (ein3 mutant. ein3 exhibited a stay-green phenotype with high chl content upon ethylene treatment (NYE1 efficiently reversed the stay-green phenotype of ein3 (EIN3 line (EIN3iox) to nye1 mutant. EIN3iox line displayed an early-yellowing phenotype with low chl content upon ethylene treatment  indirectly activating the intermediate regulator ORE1, which in turn activates more CCGs and enhances their expressions. EIN3, ORE1, and CCGs constitute a coherent feed-forward loop in the regulation of ethylene-mediated chl degradation during leaf senescence  directly activating the expression of nescence . We notiO levels , indicatNYE1, NYC1 and PAO to modulate ethylene-mediated chl catabolism, ABSCISIC ACID INSENSITIVE3 (ABI3), a B3 domain transcription factor that confers desiccation tolerance during seed maturation, regulates NYE1 expression during seed degreening [NYE1 and NYC1 to directly accelerate chl degradation [NYE1 to activate chl catabolism [NYE1, during chl breakdown. This mechanism allows plants to effectively and coordinately respond to environmental changes or stress conditions by hormone-mediated chl degradation.In addition to EIN3 and ORE1 being able to bind to the promoters of greening . ABI5 anradation . A more tabolism . TherefoACS2 transcript level in the loss-of-function nac2-1 mutant than that in WT plants  background. The mutants ein3 eil1 [nye1 [EIN3iox transgenic line [NYE1iox transgenic line, the full-length NYE1 coding sequence (CDS) was PCR amplified, using WT cDNA as template, and cloned into the vector pTA7002 [nye1 mutant using the floral-dipping method [ORE1ox line [35S:ORE1-GFP line [nac2-1 (SALK_090154) was obtained from the ABRC and the homozygosity of this line was confirmed by PCR-based genotyping. NYE1iox ein3, EIN3iox nye1, NYE1iox nac2-1 and ORE1ox nye1 were generated by genetic crossing. Homozygous lines were genotyped by PCR. Primers for genotyping are listed in All plants, including the WT, mutants and transgenic lines, were in in3 eil1 , nye1 [1l1 [nye1  and the nic line  were des pTA7002 . The fing method . The ORE1ox line  and 35S:GFP line  were kin-2 s-1 under a 16-hr light/8-hr dark photoperiod.After surface sterilization, imbibed seeds were stratified for 3 days at 4°C to synchronize germination. Plants were grown in an environmentally controlled chamber at 22°C-24°C, at light intensity of approximately 120 μmol m2HPO3 buffer at the bottom of the desiccator [The third and fourth rosette leaves from 4-week-old plants were used for ethylene-induced senescence assay. Leaves were detached and placed on two layers of moist filter papers in Petri dishes to maintain moisture and were placed in a sealed glass desiccator. Ethylene was released by adding 1M ethephon stock solution into 5 mM Nasiccator . The fin645 + 8.02×D663. The chl content was converted to microgram per gram fresh weight of leaf tissue (mg/g FW).Chl content was measured as previously described . BrieflyACT2 was an internal control for normalization. Primers used for qRT-PCR are listed in Total RNA was extracted by use of TRIzol reagent (Invitrogen) according to the manufacturer's instructions. First-strand cDNA was synthesized with the PrimeScript RT Master Mix  and then used as templates for quantitative RT-PCR (qRT-PCR) with SYBR Premix Ex Taq II  and the MyiQ2 Real Time PCR Detection System . EIN3 CDS containing the DNA-binding domain and full-length CDS of ORE1/ANAC092 were cloned into pMAL-c5g (New England Biolabs). The empty vector pMAL-c5g was used for MBP expression alone as a negative control in EMSA. Plasmids were transformed into Escherichia coli strain Rosetta (DE3) pLysS (Merck). The expression of proteins was induced by 1mM isopropyl thio-β-D-galactoside (IPTG) at 20°C for 10 hr in 200 mL LB medium. Cells were then collected and sonicated. Protein was purified with Amylose resin (New England Biolabs) following the manufacturer’s instructions.For protein expression and purification, 1 to 942 bp of EMSA was carried out using the LightShift Chemiluminescent EMSA Kit (Thermo Scientific). Briefly, 400 ng purified protein was incubated with 12.5 fmol 5’-biotin-labeled probe DNA and 1 μg poly (dI-dC) in binding buffer for 15 min. Binding reactions were resolved on a polyacrylamide gel and electrophoretically transferred to nylon membrane. The transferred DNA was cross-linked to membrane by use of CL-1000 Ultraviolet Crosslinker . Biotin-labeled DNA was detected by chemiluminescence and exposed with a ChemiScope 3500 Mini Imaging System .ORE1 (1694 bp), NYE1 (2012 bp), NYC1 (493 bp), NOL (309 bp), PAO (365 bp), and ACS2 (1019 bp) were amplified from Col-0 genomic DNA and cloned into the transient expression vector pGreenII 0800-Luc, with the expression of two cassettes—the target promoters driving a firefly luciferase (LUC) reporter gene and a CaMV 35S promoter driving an Renilla luciferase (REN) gene as an internal control [35S:EIN3 effector construct, the full-length EIN3 coding sequence (CDS) was PCR amplified, using WT cDNA as template, and cloned into pDONR221 , then into the destination vector pEarleyGate203 [35S:ORE1 effector construct pHB-ANAC092 was described previously [To generate luciferase reporter constructs, the promoters of bp), PAO 5 bp, andyGate203  to get peviously . Empty vArabidopsis mesophyll cell protoplast isolation and transformation were as described [Renilla luciferase activity was quantified using Dual-Luciferase Reporter Assay System  and detected with a Synergy 2 multi-mode microplate (Bio-Tek) according to the manufacturer’s instructions.escribed . Rosette35S:ORE1-GFP plants were harvested and cross-linked with 1% formaldehyde. ChIP was carried out using the EpiQuik Plant ChIP Kit  with the antibody against GFP . Input samples and immunoprecipitated samples were analyzed by qPCR. Primers flanking the ORE1 binding sites in NYE1, NYC1, NOL, PAO and ACS2 promoters were used to detect ORE1 enrichment. Primers amplifying a fragment in the heterochromatic region (At4g03770) were used for a negative control. The primer sequences are listed in 35S:ORE1-GFP plants among all tested regions compared with using IgG (no antibody was conjugated). ChIP-qPCR results were first normalized with input sample as follows: cycle threshold (Ct) = CtChIP − CtInput. Relative enrichment was then calculated by the ratio of normalized results from 35S:ORE1-GFP plants and WT control.The third and fourth leaves of 5-week-old WT and nac2-1 were used for quantification of ethylene production. The detached leaves were weighed and incubated in 2 mL Agilent vial (clear glass) at 22°C to 24°C under a normal 16-hr/8-hr photoperiod. Ethylene produced within 72 hr period after detachment was measured with a sensitive laser-based ethylene detector  following the manufacturer’s instructions.The third and fourth rosette leaves of 4-week-old plants of WT and t-test or one-way ANOVA. p < 0.05 was considered statistically significant.Data are given as mean ± SEM and were analyzed by two-tailed Student’s Arabidopsis Genome Initiative or GenBank/EMBL are as follows: EIN3 (AT3G20770), EIL1 (AT2G27050), ORE1/NAC2/ANAC092 (AT5G39610), NAP (AT1G69490), miR164A (AT2G47585), NYE1/SGR (AT4G22920), NYC1 (AT4G13250), NOL (AT5G04900), PAO (AT3G44880), PPH (AT5G13800), HCAR (AT1G04620), RCCR (AT4G37000), ACS2 (AT1G01480), ACT2 (AT3G18780).Genes and their associated accession numbers in the S1 Figein3 eil1 mutant showed a stay-green phenotype compared to the wild type (WT) with 100 μL/L ethylene treatment for 4 d. (B) Detached third and fourth rosette leaves from 4-week-old WT and ein3 eil1 plants treated with 100 μL/L ethylene for 4 d. (C) Quantitative analysis of total chl content in leaves of each genotype shown in (B). Data are mean ± SEM (n>4). *** p < 0.001 (t-test).(A) Whole plants of 4-week-old (TIF)Click here for additional data file.S2 FigThe expression level of each corresponding gene in the WT at 0 hr was set to 1. The scales of y-axes are consistent with that in (TIF)Click here for additional data file.S3 Fignac2-1 mutant showed a stay-green phenotype compared to the WT with 100 μL/L ethylene treatment for 4 d. (B) Detached third and fourth rosette leaves from 4-week-old WT and nac2-1 plants treated with 100 μL/L ethylene for 4 d. (C) Quantitative analysis of total chl content in leaves of each genotype shown in (B). Data are mean ± SEM (n>4). *** p < 0.001 (t-test).(A) Whole plants of 4-week-old (TIF)Click here for additional data file.S4 FigACT2 was used as an internal control to normalize different samples. The mRNA levels of each corresponding gene in WT at 0 hr were arbitrarily set to 1. Data are mean ± SEM from 3 biological replicates with technical duplicates for each.Detached third and fourth Leaves from 4-week-old plants were treated with 100 μL/L ethylene for various times. RT-qPCR was performed to quantify the mRNA levels of each gene. (TIF)Click here for additional data file.S5 FigNYE1iox transgenic line was sprayed with 15 μM DEX or 0.05% Methanol (mock) and incubated for two days. The transcript level of NYE1 in the third and fourth leaves was examined by RT-qPCR. ACT2 was used as an internal control for normalization. The transcript level of NYE1 with mock treatment was arbitrarily set to 1. Data are mean ± SEM of 3 biological replicates. ** p < 0.01 (t-test).Four-week-old (TIF)Click here for additional data file.S6 FigACS2 transcript levels in third and fourth leaves of 4-week-old WT, nac2-1, and ORE1ox with 100 μL/L ethylene treatment for 4 d. The ACS2 transcript level in WT was arbitrarily set to 1. Data are mean ± SEM from 2 biological replicates (one-way ANOVA). Levels not connected by same letter are significantly different. p < 0.01.qRT-PCR analysis of the (TIF)Click here for additional data file.S7 Fignyc1, and pao plants treated with 100 μL/L ethylene for 3 d. (B) Quantitative analysis of total chl content in leaves of each genotype shown in (A). Data are mean ± SEM (n = 3). * p < 0.05 (t-test).(A) Detached third and fourth rosette leaves from 4-week-old WT, (TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.


While the importance of gene enhancers in transcriptional regulation is well established, the mechanisms and the protein factors that determine enhancers activity have only recently begun to be unravelled. Recent studies have shown that progesterone receptor (PR) binds regions that display typical features of gene enhancers. Here, we show by ChIP-seq experiments that the chromatin remodeler CHD8 mostly binds promoters under proliferation conditions. However, upon progestin stimulation, CHD8 re-localizes to PR enhancers also enriched in p300 and H3K4me1. Consistently, CHD8 depletion severely impairs progestin-dependent gene regulation. CHD8 binding is PR-dependent but independent of the pioneering factor FOXA1. The SWI/SNF chromatin-remodelling complex is required for PR-dependent gene activation. Interestingly, we show that CHD8 interacts with the SWI/SNF complex and that depletion of BRG1 and BRM, the ATPases of SWI/SNF complex, impairs CHD8 recruitment. We also show that CHD8 is not required for H3K27 acetylation, but contributes to increase accessibility of the enhancer to DNaseI. Furthermore, CHD8 was required for RNAPII recruiting to the enhancers and for transcription of enhancer-derived RNAs (eRNAs). Taken together our data demonstrate that CHD8 is involved in late stages of PR enhancers activation. A lot of research has been devoted during the last decades to understand the mechanisms that control gene promoters activity, however, much less is known about enhancers. Only recently, the use of genome-wide chromatin immunoprecipitation techniques has revealed the existence of more than 400,000 enhancers in the human genome. We are starting to understand the importance of these regulatory elements and how they are activated or repressed. In this work we discover that the chromatin remodeler CHD8 is recruited to Progesteron Receptor-dependent enhancers upon hormone treatment. CHD8 is required for late steps in the activation of these enhancers, including transcription of the enhancers and synthesis of eRNA (long noncoding RNAs derived form the enhancers). During the last decade it has become clear that regulation of gene transcription is accompanied by extensive changes in the chromatin organization of promoters . More rein vitro in an ATP-dependent reaction [in vivo functions are unclear. Inactivation of CHD8 by homologous recombination in mice provokes a strong growth retardation from embryonic day 5.5 and developmental arrest accompanied by massive apoptosis [et al. reported that CHD8 interacts with CTCF and plays a role in insulation activity [TMPRSS2 gene [Chromatin changes are normally performed by two types of enzymes: enzymes that chemically modify histones or ATP-dependent chromatin remodelers. ATP-dependent remodelling is performed by enzymes of the SNF2 family that use the energy of ATP hydrolysis to destabilize the interaction between DNA and histones ,7. In hureaction ; howeverpoptosis . Ishiharactivity . It has activity ,12,13,14activity . In contactivity ,17. Addiactivity , and forSS2 gene . These tIn this work, we have investigated the role of CHD8 in progesterone-dependent transcriptional regulation. Progesterone controls transcription through a complex mechanism . On the –10, 10–15 and 10–20). In all cases, false discovery rates (FDR) were lower than 0.03  using a different anti-CHD8 antibody (–135), ELK-1 , AP-2 , and SP1  transcription factors binding sites  is shown in CHD8 has been suggested to be a nuclear receptor co-activator ,19; howe–75) for the sequence CTGTNC, which is very similar to the consensus sequence of the progesterone receptor binding site TGTYCY [De novo analysis of sequence motifs in progestin-dependent CHD8 bound regions identified a highly significant enrichment –75) for e TGTYCY . Interese TGTYCY . NRI is e TGTYCY . Distal e TGTYCY . In the e TGTYCY . CHD8 wa–130, hypergeometric distribution) of the CHD8 containing regions were also enriched in CTCF (It has been reported that CHD8 interacts and cooperates with the insulator factor CTCF (CCCTC-binding factor) . Therefo in CTCF . However in CTCF . Upon pr in CTCF , suggest–103)  .HSD11B2, DUSP1, FKBP5, NFE2L3 and IL6ST genes. Thus, depletion of CHD8 severely impaired accumulation of mRNA, both 45 min and 6 h after progestin treatment  we decided to study the role of FOXA1 in CHD8 and PR recruiting. First, we investigated using ChIP whether FOXA1 binds to the analyzed regulatory regions of HSD11B2, FKBP5, NFE2L3 and IL6ST genes. As shown in HSD11B2e, NFE2L3e and IL6STe enhancers was similar in T47D-MTVL and T47D-YV cells, suggesting that PR is not involved in FOXA1 recruitment at these regions . ChIP-DNA was purified and subjected to deep sequencing using the Solexa Genome Analyzer (Illumina). The sequence reads were aligned to the human genome reference (assembly hg19). ChIP-seq peak calling, genomic annotation of peaks and comparison between ChIP-seq and ENCODE datasets were performed using ChIPseeqer (v.2.1) . An empiAll siRNAs were transfected using Oligofectamine (Invitrogen) according to the manufacturer’s instructions, with following siRNA sequences: for siCHD8, 5′-GAGCAAGCUCAACACCAUC-3′; siFOXA1, 5′-GAGAGAAAAAAUCAACAGC-3′; siCt, 5′-CGUACGCGGAAUACUUCGA-3′; siBRG1, 5′-GCGACUCACUGACGGAGAA-3′; and siBRM, 5′-GAAAGGAGGUGCUAAGACA-3′. After transfection, medium was replaced by serum-free fresh medium without phenol red. After 48 h in serum-free conditions, cells were treated with 10 nM R5020 or vehicle (EtOH) for the indicated times. The down-regulation of CHD8, FOXA1, BRG1 and BRM was confirmed by RT-PCR and Western blotting, respectively.T47D-MTVL cells were grown in serum-free conditions, as explained previously, during 48 h and treated with 10 nM R5020 or vehicle (EtOH) during 6 h. Total RNA was isolated in triplicate from cells using RNeasy Mini Kit (Qiagen). Purity and quality of isolated RNA were assessed by RNA 6000 Nano assay on a 2100 Bioanalyzer . RNA (100 ng) was used for production of end-labelled biotinylated ssDNA. Labelled ssDNA was hybridized to the GeneChip human Gene 1.0 ST array oligonucleotide microarray  according to manufacturer’s recommendations. The arrays were scanned using the GeneChip Scanner 3000 7G (Affymetrix), and raw data were extracted from the scanned images and analyzed with the Affymetrix GeneChip Command Console Software (Affymetrix). The raw array data were pre-processed and normalized using the Robust Multichip Average (RMA) method . Data weDNase I assay was performed as previously described . BrieflyFKBP5e and HSD11B2e eRNA determination, strand-specific oligonucleotides were used for RT, in order to avoid expression form close promoters. cDNA (2 μl) was used as a template for qPCR. Gene products were quantified by real-time PCR with the Applied Biosystems 7500 FAST real-time PCR system, using Applied Biosystems Power SYBR green master mix. Sequences of all oligonucleotides are available upon request. Values were normalized to the expression of the 28S housekeeping gene. Each experiment was performed at least in duplicate, and qPCR quantifications were performed in triplicate.Total RNA was prepared by using the RNeasy Kit (Qiagen), as described in the manufacturer’s instructions; note that the step of DNase I digestion was included to avoid potential DNA contamination. cDNA was generated from 800 ng of total RNA  using Superscript First Strand Synthesis System (Invitrogen). For progesterone-dependent eRNA induction analysis 2 μg of total RNA was used. In the case of Co-immunoprecipitations were performed as described in  using thS1 FigCCND1, HDS11B2 and CCNE2 promoters using a home-made anti-CHD8 antibody [(A) ChIP-qPCR analysis of CHD8 binding to antibody . Pre-imm(PDF)Click here for additional data file.S2 Fig and the bars represent the percentage of CHD8 target genes within a functional category. (B) The top transcription factor binding motifs of CHD8 bound promoters in proliferating T47D-MTVL cells, analyzed using Weeder PScan [P-value) are also shown.(A) Gene ontology functional categories of CHD8 target genes in proliferating T47D-MTVL cells, analyzed by DAVID . The numer PScan  and TRANer PScan . The ass(PDF)Click here for additional data file.S3 FigCHD8 occupancy after 5 (red) or 45 (green) min of R5020 treatment, plotted as the normalized tag density around TSS.(PDF)Click here for additional data file.S4 FigCHD8 occupancy after 5 (red) or 45 (green) min of R5020 treatment, plotted as the normalized tag density around the centre of H3K4me1 enriched regions.(PDF)Click here for additional data file.S5 Fig(A) Venn-diagram showing overlap between CHD8 and CTCF peaks in proliferating T47D-MTVL cells. (B) Distribution of CHD8-CTCF co-occupied sites, relative to known RefSeq genes. Promoters: ± 2 kb around transcription start site (TSS); Downstream extremities: ± 2 kb around transcription end site; Exons: exonic regions; Introns: intronic regions; Intergenic > 2 kb away from RefSeq TSS. (C) Venn-diagram showing overlap between CHD8 and CTCF peaks in T47D-MTVL cells upon hormone induction with R5020.(PDF)Click here for additional data file.S6 FigHSD11B2, MMTV-Luc, DUSP1, FKBP5, NFE2L3 and IL6ST was monitored by RT-qPCR. Level of CHD8 expression was determined as control of silencing.T47D-MTVL cells were transfected with a control siRNA or siCHD8-2 specifically targeting CHD8. Forty-eight hours after transfection cells were stimulated with progestin (R5020) or vehicle (EtOH) for 45 min. Expression of the following genes: (PDF)Click here for additional data file.S7 FigBRG1 and BRM expression upon transfection of T47D-MTVL cells with control siRNA (siCt) or a pool of siRNAs against BRM and BRG1 (siBRG1+siBRM). After 48 hours, cells were stimulated during 45 min with progestin (R5020) or vehicle (EtOH). (C) Western blot analysis of BRG1 and BRM expression upon transfection of T47D-MTVL cells with control siRNA (siCt) or siRNAs against BRG1 and BRM (siBRG1 siBRM).(A) SWI/SNF subunits co-immunoprecipitate with CHD8 both in the presence and in the absence of progestin. Extract from T47D-MTVL cells treated with R5020 (+) or vehicle (-) for 45 min were subjected to immunoprecipitation using anti-CHD8 antibody. Precipitated proteins were then revealed by western blotting using the indicated antibodies. (B) RT-qPCR analysis of (PDF)Click here for additional data file.


Transcriptional dysregulation in Huntington’s disease (HD) is an early event that shapes the brain transcriptome by both the depletion and ectopic activation of gene products that eventually affect survival and neuronal functions. Disruption in the activity of gene expression regulators, such as transcription factors, chromatin-remodeling proteins, and noncoding RNAs, accounts for the expression changes observed in multiple animal and cellular models of HD and in samples from patients. Here, I review the recent advances in the study of HD transcriptional dysregulation and its causes to finally discuss the possible implications in ameliorative strategies from a genome-wide perspective. To date, the use of genome-wide approaches, predominantly based on microarray platforms, has been successful in providing an extensive catalog of differentially regulated genes, including biomarkers aimed at monitoring the progress of the pathology. Although still incipient, the introduction of combined next-generation sequencing techniques is enhancing our comprehension of the mechanisms underlying altered transcriptional dysregulation in HD by providing the first genomic landscapes associated with epigenetics and the occupancy of transcription factors. In addition, the use of genome-wide approaches is becoming more and more necessary to evaluate the efficacy and safety of ameliorative strategies and to identify novel mechanisms of amelioration that may help in the improvement of current preclinical therapeutics. Finally, the major conclusions obtained from HD transcriptomics studies have the potential to be extrapolated to other neurodegenerative disorders. Huntington’s disease (HD) is the most common polyglutamine (polyQ) disorder, with a prevalence of 5–10 cases per 100,000 persons worldwide. In the classical variant, pathology onset occurs in mid adulthood (approximately 30–40 years old) and ends with the patient’s death, normally after 10–15 years. HD is characterized by personality changes and psychiatric symptoms , cognitive deficits , motor impairment , sleep disturbance, and weight loss [Conversely to more common neurodegenerative disorders, such as Alzheimer’s (AD) and Parkinson’s (PD) diseases, the cause of HD for all the patients is known: an aberrant expansion of the polymorphic trinucleotide sequence CAG (in the range of 37–121 repeats) at the N-terminus of the huntingtin (Htt) protein. Whereas the number of repeats is strongly correlated with the age of disease onset, additional genetic variants may contribute to the differential manifestation of the cognitive and motor symptomatology among patients [Initial reports during the 1980s and 1990s demonstrated selective altered expression of highly identifiable neuronal genes, such as neurotransmitter receptors and neuropeptides, first in patients’ brains and later in animal models –7. The iA long list of gene expression datasets have been generated in less than 15 years of research on multiple HD animal and cellular models and, importantly, on postmortem material from patients , neurotransmitter receptor and ion channel functions , neuropeptides , synaptic transmission (anchoring and vesicle components), and calcium binding and homeostasis, whereas upregulation is generally associated with genes related with RNA metabolism, protein folding, and stress markers. Expression of transcription and chromatin remodeling factors can be altered in either direction. A more exhaustive discussion of the biological implications of deregulated genes in the context of HD can be found in the excellent reviews by Cha  and SereHD mouse models in which the mHtt transgene was designed to reproduce the ubiquitous expression pattern of the endogenous Htt  show altTo date, the best attempt to meta-analyze striatal profiles from different animal models (including knock-in and transgenic mice for different mHtt lengths) within the same study  revealedIntrinsic properties of the tissues, such as sensitivity to degeneration and tissular-specific transcription. The striatum exhibits a special sensitivity to neurodegeneration, as demonstrated by general insults that severely affect striatal cells, such as hypoxia, hypoglycemia, and ischemia , systemiIntrinsic properties of the models. For example, the promoter sequences driving transgene expression  determine which cell types will be more affected, and the length of the mHtt determines the progression rate of the disease because N-terminal transgenes lack the required signals present in full-length mHtt (either transgenic or knock-in) to promote degradation in response to misfolding . Gene prAnalytical procedures. The intrinsic properties discussed above make performing a reliable meta-analysis of distinct gene profiles difficult; this limitation is more evident if based on the results of conventional pair-wise comparisons between the control and the aberrant Htt expansion situations using arbitrary thresholds. Exploring alternative approaches has led to interesting insights that otherwise would have remained undetected: for example, the aforementioned accumulative dysregulation associated with CAG repeats, the detection of subthreshold HD signatures in a less affected brain area , and theThe presence of specific changes is the result of several factors as discussed below:2+ homeostasis, the impairment of mitochondrial respiration and trafficking in mHtt-expressing cells, and the reduced activity of peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α), which is relevant for the expression of genes related to mitochondrial biogenesis and oxidative phosphorylation [Mitochondrial dysfunction is supported by several pieces of evidence: the mitochondrial localization of mHtt, the defective Carylation . 3-Nitrorylation ; thus, 3rylation , 55 and rylation . This isvator-1α , which iAmong the gene expression regulators, we can find transcription factors and associated cofactors, including chromatin-remodeling proteins and noncoding RNAs (ncRNA). Chromatin-remodeling proteins are gaining increasing interest in neuropathology as they are responsible for the epigenetic deficits observed in mental and neurological disorders , 74. ResBy a loss of interaction with wild-type Htt. The best-known example is the RE1-silencing transcription factor/neuron-restrictive silencer factor (REST/NRSF) that is physiologically retained by wild-type Htt in the cytoplasm. Thus, loss of a single allele promotes the nuclear translocation of this factor and alters the expression of neuronal genes , as discBy aberrant interactions with mHtt. This is the best-characterized action and was originally proposed because several transcription regulators, such as the acetyltransferase CREB-binding protein (CBP), the histone deacetylase complex subunit mSin3a, the tumor suppressor p53, the transcription elongation regulator 1 Tcerg1/CA150), and the TATA-binding protein (TBP), among many others –88, were0, and thBy the disruption of upstream gene expression regulators. Apart from miRNAs, transcription factors and associated cofactors can also be prominently deregulated at the transcript level, as retrieved by functional enrichment analyses of pathological gene profiles. Nonetheless, such dysregulation does not always contribute to the progression of the disease by affecting downstream target genes, but it can also be a part of the homeostatic response in an attempt to restore lost activities. An example is the CCAAT-binding protein nuclear factor Y (NF-Y) that is present in mHtt aggregates with a concomitant reduction in protein levels but upregulated at the mRNA level .By abnormal protein degradation, by either promoting or preventing the removal of regulators such as CBP  or the WThe activity of gene expression regulators can be affected in several ways, as defined in single-gene studies:To gain further insight on the regulatory mechanisms responsible for HD signatures, gene expression datasets can be analyzed for the enrichment of transcription factor binding sites (TFBS) to infer the most promising factors involved in the transcriptional deficits. Along the same lines, the 3′UTRs of deregulated genes can be scanned for the putative binding of miRNAs. Early attempts, although limited by the scarce knowledge of genomic sequences at the time, were able to identify a small subset of deregulated genes with DNA motifs at their promoters for Sp1  and CREBThere are, however, obvious limitations to the prediction strategy. First, regulatory proteins are able to bind through noncanonical consensus sequences or indirectly through the recruitment of other associated factors; second, the use of predicted DNA motifs may depend on the tissue-specific context, i.e., on the presence of specific cofactors and interacting partners; and third, this strategy is not valid for chromatin-remodeling proteins, as they do not recognize any primary sequence in the DNA. Finally, predictions are highly dependent on the assumptions made by the algorithms, which can be especially problematic in the case of miRNA-binding sequences. Two different approaches circumvent these issues: (i) meta-analysis of gene profiles to determine the degree of similarity between the HD signature and the transcriptional changes caused by genetic manipulation of particular regulators , 104 andNext, studies designed to link transcriptomics with the activity of particular expression regulators are discussed in detail.REST is a Kruppel-type zinc finger protein that was originally described as a repressor of neuronal genes in nonneuronal cells for maintaining the phenotypic identity of these cells, according to its high expression level in embryonic and nonneuronal cells, opposed to the lower level observed in neurons (reviewed in Adachi and Monteggia ). As prebona fide target genes, including some associated with inflammatory and immunological disorders in other systems [Foxp1 and other members of the subfamily play important roles in cell-type-specific gene expression in the heart, lung, thymus, immune cells, and developing brain. Haploinsufficiency in humans may be the cause of an intellectual disability that severely affects the onset of speech and language and is also commonly associated with distinctive facial features, autistic traits, and congenital malformations . Foxp1 s systems . In agre systems . AlthougHdhQ111/Q111 [HdhQ7/Q7 cells. However, under heat shock conditions, HSF1 showed increased genomic binding in the control cell line that was impaired under the expression of the expanded polyQ version and affected more than one third of HSF1-dependent genes. Whereas proteostatic genes were enriched in the HSF1-associated signature in the two cell lines, genes showing deficits in both gene expression and HSF1 binding in the mutant condition were represented by other unrelated functions, suggesting that the response to HSF1-induced stress is largely preserved in this HD model. However, this situation is more complex in vivo [HSF1 is a leucine zipper transcription factor and a key regulator of the heat shock proteins (HSPs), including chaperones involved in protein homeostasis , the expression of which is induced in response to different types of stress. In fact, some reports demonstrated an altered gene expression pattern for some of these proteins , 118, an111/Q111 . In the  in vivo , as we w in vivo .PGC-1α is a transcriptional coactivator that regulates the expression of mitochondrial genes among other targets. Its potential relevance in HD has been suggested by a specific decrease in PGC-1α in the postmortem caudate nucleus of HD patients, a similar motor phenotype in PGC-1α knockout and HD mice that is worsened when combining both mutations and by the fact that overexpression experiments restoring PGC-1α levels ameliorated neurodegeneration and mHtt aggregation , 120. InHdhQ111/Q111 and control STHdhQ7/Q7 cells). However, in the latter case, 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC) were in principle not distinguishable. 5-mhC is highly enriched in neurons and may constitute an intermediate step in demethylation, leading to gene derepression [Epigenetic marks that are linked to physiological processes, such as memory formation, and to intellectual disabilities and aging –123 havepression . The genpression . InteresSurprisingly, the genome-wide correlation between differential histone acetylation and gene expression is poor, despite observance of a net hypoacetylation , 111. MeTo complement these results, a genome-wide landscape of chromatin-remodeling proteins is missing. At the moment, a reduction of the hypomethylation of the H3K4 mark in HD has been ascribed to the upregulation of the specific histone demethylase lysine (K)-specific demethylase 5C (KDM5C/SMCX/Jarid1c). This is supported by knockdown experiments that reported an increase in the expression levels of selected genes .In the absence of nucleosome resolution, meta-analysis of transcriptome data from different studies may provide key insight. Histone deacetylation as a result of decreased acetyltransferase and increased deacetylase activities is present in several polyQ models, although this latter finding needs further clarification . Anyway,Interestingly, Htt can bind directly to DNA, as shown in immortalized striatal cell lines and in brain tissue from R6/2 mice and patients, not only at the promoter level but also to intronic and intergenic regions, including repetitive sequences . BecauseA review of the vast literature together with a systematic analysis of transcription factor activities as performed by Cha and colleagues  leads toHdhQ111/Q111 and STHdhQ7/7 cell lines identified differential patterns of cytosine methylation that were more evident at CpG-poor regions. The primary focus was on low methylated CpG-poor regions, as they could be potentially created by transcription factor binding, as reported in embryonic stem cells [Integrating different regulatory mechanisms may provide a more complete picture, as changes in expression levels may be the result of disruption of convergent regulators Fig. . Transcrem cells . While sem cells .Fig. 2CoAnother aspect to consider for integration is the fact that histones and transcription factors can be posttranslationally modified by the same enzymes. For example, mitogen- and stress-activated kinase 1 (MSK-1) phosphorylates both histone H3 and CREB , and CBPIn addition to elucidating the cause and consequences of transcriptional dysregulation in HD, transcriptomics analysis has been used to test the efficacy of ameliorative strategies that directly or indirectly restore the altered activity of gene expression regulators. In this section, the genome-wide studies aimed at analyzing the transcriptional changes associated with amelioration by genetic and pharmacological means are summarized.Transcriptional profiles can be considered to be intermediate outcomes between the origin of the pathology  and the phenotypical manifestation at the level of behavior. Brain transcriptomes have the potential to record experiences, plasticity events, perturbation episodes, and medical interventions either in a transient or, as often occurs with neuropathologies, in a permanent manner. In the case of HD, the accumulation of gene expression rearrangements involves direct regulatory mechanisms, cytosolic processes that affect the fine-tuned activation of downstream signaling pathways converging in the nucleus, and the transcriptional homeostatic responses to minimize damage, which together constitute the “disease signature.” In the same way, it is possible to define the “ameliorative signature” as the fraction of genes which expression is restored by a particular treatment , 149. ThLong-term silencing of mHtt by RNA interference  represents a promising strategy to alleviate the gain-of-function effects in patients . To reacOne of the main advantages of proliferative cellular-based models is the ability to conduct large systematic and unbiased screenings. Regarding mHtt-expressing cells, this approach allows the identification of both tractable intracellular pathways and novel compounds by investigating the reversal of polyQ-induced cell death. This information would be useful for the posterior design of therapeutics in animal models. Target candidates for amelioration can be determined within the HD signature. Thus, overexpression may potentially restore cellular deficits   and poteCocktail preparations may have synergic actions in improving cognitive and motor symptoms. This is the basis for the triple treatment used in the fast progressive R6/2 transgenic model. This treatment aims to increase neurotransmitter levels and mitigate mitochondrial dysfunction simultaneously, using the acetylcholine esterase inhibitor tacrine, the monoamine oxidase A inhibitor moclobemide, and creatine . InteresSeveral reports indicated that the housing conditions of HD mice have an impact on disease progression and opened the possibility for occupational-related therapies. Thus, animals maintained under environmental enrichment  exhibited phenotypical amelioration and an extended survival rate –163. AltBdnf locus but also interferes with the trafficking of BDNF-containing vesicles. Overall, cortical supply of this neurotrophic factor to the striatum becomes impaired in HD [The meta-analysis of datasets from diverse sources, as discussed in the “ed in HD . Cross-ced in HD , 171, alDrosophila model of HD [Because transcriptional dysregulation is an early event in HD, directly targeting expression regulators may have an influence on the disruption of other processes in the neuron. This idea is supported by numerous experiments that rescued altered transcriptional activities by either overexpressing activators or knocking down repressors, thus restoring the expression levels of selected target genes and improving the well-being of sick animals and unhealthy cells. Interestingly, augmentation of the expression levels of wild-type Htt at the transcriptional regulatory level has been proposed to restore its physiological roles, as exemplified by homeodomain transcription factor Engrailed, which prevents mHtt aggregation and neurodegeneration by activation of endogenous Htt in a el of HD . The nexThe drugs belonging to different chemical families that are capable of inhibiting deacetylase activity are generally referred to as HDACi. Therefore, these drugs counterbalance possible deficits in acetyltransferase activity and restore the acetylation levels of histones and other nuclear proteins. This is the main proposed mechanism underlying the transcriptional-dependent amelioration of pathophenotypical traits observed in HD models , spinobulbar muscular atrophy (SBMA) or Kennedy disease, and spinocerebellar ataxia types 1 and 7 , share altered transcriptional genes with HD signatures , 182.Similarities can be extended to other neurodegenerative disorders that exhibit common characteristic hallmarks, such as channel-mediated cytotoxicity, mitochondrial dysfunction, intracellular trafficking, and deposition of misfolded proteins may influence and be influenced by shared transcriptional and epigenetic regulatory mechanisms. Therefore, it is not surprising that similar ameliorative strategies in HD are also applicable in other neuropathologies. For example, HDACi have been tested in cognitive pathologies, including neurodegenerative disorders and intellectual disabilities: HD, AD, Parkinson’s disease (PD), stroke, traumatic brain injury, amyotrophic lateral sclerosis (ALS), Friedrich ataxia, SBMA, DRLA, and Rubinstein-Taybi syndrome , 184. An


TERT) promoter, rs2853669 influences patient survival rates and the risk of developing cancer. Recently, several lines of evidence suggest that the rs2853669 suppresses TERT promoter mutation-mediated TERT expression levels and cancer mortality as well as recurrence rates. However, no reports are available on the impact of rs2853669 on TERT expression in hepatocellular carcinoma (HCC) and its association with patient survival. Here, we found that HCC-related overall and recurrence-free survival rates were not associated with TERT promoter mutation individually, but rs2853669 and the TERT promoter mutation in combination were associated with poor survival rates. TERT mRNA expression and telomere fluorescence levels were greater in patients with HCC who had both the combination. The combination caused TERT promoter methylation through regulating the binding of DNA methyltransferase 1 and histone deacetylase 1 to the TERT promoter in HCC cell lines. The TERT expression level was significantly higher in HCC tumor with a methylated promoter than in that with an unmethylated promoter. In conclusion, we demonstrate a substantial role for the rs2853669 in HCC with TERT promoter mutation, which suggests that the combination of the rs2853669 and the mutation indicate poor prognoses in liver cancer.A common single-nucleotide polymorphism in the telomerase reverse transcriptase ( TERT expression levels are highly associated with cancer risk in various human cancers [TERT gene variant, rs2853669 (−245T > C) [Telomerase reverse transcriptase (TERT) is the catalytic subunit of telomerase , which i cancers –3. Cance853669 −25T > C [4TERT expression, which is necessary for telomerase activity, is greater in various human tumors than in normal organs [TERT promoter were discovered in melanoma; a reporter assay showed that these mutations increased TERT transcription activity by creating a binding motif for transcription factor ETS2 in multiple cell lines [TERT promoter mutations are responsible for elevated TERT expression or low patient survival rate in a variety of cancers, including, but not limited to, cutaneous melanoma [TERT expression is greater in cirrhotic preneoplastic lesions (a HCC precursor) with the TERT promoter mutations compared with that of lesions that do not include the mutations [TERT promoter affect the TERT expression levels or patient survival rates in HCC [Telomerase activation is responsible for circumventing cellular senescence or cell death caused by telomere shortening in cells –9. TERT l organs . Recentlll lines –12. Thesmelanoma , 14, thymelanoma , bladdermelanoma –18, and melanoma , 20. Altutations , it is ys in HCC , 20.TERT promoter mutation-mediated TERT expression regulation and mortality or recurrence rates for bladder cancer [TERT transcription is regulated remains unknown. So far, no studies have considered effect of rs2853669 combined with somatic mutations at the TERT promoter on liver cancer. Here, we aim to discover a novel role for the rs2853669 variant and a mechanism for regulating rs2853669 variant-dependent TERT promoter activity in liver cancer.Several lines of research suggest that rs2853669 suppresses the r cancer , gliomasr cancer , 22, andr cancer ; howeverTERT promoter mutation (−124C > T or −146C > T) on liver cancer survival rates, we first analyzed the overall survival rates of a Korean HCC patient cohort  and 9 Figure . Moreoven Figure , which iTERT promoter mutation combination influenced the risk of HCC recurrence in two independent Korean HCC patient cohorts . The data show that rs2853669 is associated with poor recurrence-free survival rates and a significant risk of HCC recurrence in patients with the TERT promoter mutation  was increased in all four HCC cell lines examined  the binding site of E2F transcription factor 1 (E2F1)  Figure . Therefo variant . As a res Figure . In conty Figure , suggestTERT promoter activity was associated with the function of E2F1 as a transcriptional repressor. A previous study showed that the two E2F1 binding sites at −247 bp and −171 bp relative to ATG can regulate TERT promoter activity [TERT-mut1-luc) compared to the E2F1-binding site mutation at −171 bp relative to ATG (TERT-mut2-luc) had a greater impact on the TERT promoter activity ; however, TERT-mut1-luc luciferase activity was not affected by E2F1 overexpression , similar to that demonstrated for the TERT promoter with a mutation at the E2F1-binding site (TERT-mut1-luc)  on activity . As demoy Figure . In addin Figure . Moreove) Figure . These rTERT transcription level repression.E2F1 represses gene transcription levels by recruiting DNA methyltransferase 1 (DNMT1) . BecauseTERT promoter in Huh7 cells  decreases both DNMT1 and HDAC1 binding to the s Figure . On the 1 Figure . Taken tTERT promoter, we analyzed the interaction between E2F1 and the rs2853669 variant in HepG2 cells, which is a HCC cell line with the rs2853669 variant  affects E2F1-mediated DNMT1 and HDAC1-binding to the  variant . The TERm of ATG ; Supplems Figure . The difs Figure . This red Figure . As expen Figure , which iTERT transcription repressor was dependent on DNMT1 activity. We found that 5-aza-2-deoxycytidine (5-aza-dC)-treated Huh7 cells had lower TERT promoter methylation levels and increased TERT transcription levels, despite an increase in the binding of E2F1 to the TERT promoter . The level of binding between ETS2 and the TERT promoter decreased in E2F1 overexpressed–Huh7 cells, whereas the level remained unchanged in E2F1-overexpressed HepG2 cells  was not only located near the E2F1 binding site, but also overlapped with an ETS2 binding site at the promoter  . In Huh7 cells, blocking both E2F1 and ETS2 also decreased both DNMT1 and HDAC1 binding to the TERT promoter and decreased TERT promoter methylation TERT promoter and further increased the TERT expression in HCC cells.Both HepG2 cells and Huh7 cells exhibited a −124C > T mutation , which cs Figure . Blockins Figure , which iTERT promoter region spanning from −270 bp to −31 bp upstream of the ATG start site correlates with high TERT expression levels and poor recurrence-free survival rates in HCC patients [TERT expression, which is involved in TERT promoter methylation as described in our previous report [TERT expression is increased by TERT promoter methylation in HCC tumors with the rs2853669 variant and −124C > T mutation combination. The data show that the TERT promoter methylation is positively associated with TERT mRNA expression and TERT protein expression in HCC tumors , the HCC tumors the with rs2853669 variant alone (P = 0.0003), and the HCC tumors with the −124C > T mutation alone (P < 0.0001)  and the TERT mRNA expression level was also confirmed by linear regression analysis  Figure . A positn Figure .TERT promoter has been observed in various tumor tissues and transformed cell lines [TERT expression levels and poor survival rates in patients with childhood brain tumors [TERT promoter methylation contributes to HCC progression by increasing TERT expression [TERT promoter methylation was induced by decreasing E2F1 binding (in the presence of rs2853669 (−245T > C)) combined with increasing ETS2 binding at the TERT promoter (in the presence of the −124C > T mutation). Notably, we found that the rs2853669 variant and −124C > T mutation combination is markedly associated with high TERT expression levels, poor overall survival rates, and poor recurrence-free survival rates in HCC patients. HCC patients with the combination also show greater TERT promoter methylation levels compared with HCC patients with the variant alone or mutation alone and HCC patients without both the variant and mutation, indicating that the variant combined with the mutation contributes to TERT promoter methylation, which leads to increased TERT expression, HCC mortality, and HCC recurrence.Methylation at the ll lines . Furthern tumors . Our prepression . Here, oTERT expression is increased by the inhibition of E2F1 as a transcriptional repressor through the rs2853669 variant (−245T > C); however, the concurrent stimulation of ETS2 as a transcriptional activator through the −124C > T mutation is also required for increased TERT expression  cooperate with native ETS sites to form high-order structures such as G-quadruplexes; as a result, these structures contribute to the recruitment of the multimeric GA-binding protein (GABP) transcription factor and to the up-regulation of TERT expression [TERT promoter to improve its activity.The level of n Figure . The ETSgulation , 33. Howpromoter . As the pression . The −24pression . This suTERT gene, the SNP rs13167280 (IVS3–24 C > T), located on the third intron of the TERT gene, is associated with a decreased risk of HCC progression, whereas no significant association is reported between rs2853669 (−245T > C) and HCC risk [TERT promoter increases TERT expression, telomere length, and HCC mortality and recurrence rates. Thus, in order to better predict the prognosis of HCC patients, we suggest that studies of SNPs expand to incorporate the relationships and the clinical implications of SNPs when coupled with other SNPs or genetic alterations.Several SNPs in the telomere maintenance genes are highly associated with the survival rates in HCC patients . AccordiTERT reporter vector with the −146C > T mutation  [TERT promoter activity in a cell type-specific manner. Different cancer types have various TERT promoter mutation frequencies [TERT promoter mutations and ETS binding sites [TERT promoter activity in four HCC cell lines, which indicates that rs2853669 is involved in regulating TERT promoter activity in cell types that are originated from HCC.We show that rs2853669 (−245T > C) does not affect the luciferase promoter activity of the n Figure  which isn Figure . Therefoll line) , therebyquencies , 19, 20.quencies , HCC shong sites  can reguTERT promoter mutations are major genomic alterations in the step-by-step hepatocarcinogenic process, which is involved in HCC developed from chronic liver disease as well as from hepatocellular adenomas (HCA) [TERT promoter mutations are key determinants for HCC, as they are observed in low- or high- grade dysplastic nodules , while other mutations in ten cancer genes  have not been observed in cirrhotic livers, LGDNs, and or HGDNs [TERT promoter mutations may be a determinant for HCC, HCC tumors displaying increased TERT expression independent of the TERT mutation status also exist [TERT promoter mutations increased TERT expression compared to TERT promoter mutations only  , 37. A ror HGDNs . AlthougTERT gene, rs2853669, is significantly associated with a high risk of death and cancer recurrence in patients with liver cancer, and that the rs2853669 variant (−245T > C), combined with the −124C > T mutation, mediates TERT transcriptional activity by modulating the binding of both E2F1 and ETS2, which is responsible for the high risk of HCC. Our study suggests that the rs2853669 variant combined with the −124C > T mutation in the TERT promoter is a novel risk factor for poor prognosis in liver cancer.In conclusion, we report for the first time that a common variant of the The Seoul National University Institutional Review Board (SNUIRB No. E1308/001-035) approved this study .® TriPrep Kit , respectively, in accordance with the instructions of each manufacturer  and NucleoSpinfacturer .An immunoFISH protocol , 40 was ® TriPrep Kit , and cDNA was synthesized using TOPscript™ RT Drymix (dT18)   .The HCC cell lines  were obtained from the Korean Cell Line Bank  .5 HCC cells were seeded onto 6-well plates and transfected using Fugene® 6  and 1 μg of the wild-type TERT promoter-luciferase construct with or without the variant rs2853669 (−245T > C) or TERT promoter mutation (−124C > T or −146C > T). The wild-type (WT) TERT promoter was subcloned into the pGL3 luciferase empty vector   .The cells were fixed using 4% paraformaldehyde, permeabilized using 0.5% Triton X-100 in PBS, blocked with 20% NGS  and treated with a mouse monoclonal anti-DNMT1 antibody  as well as a rabbit polyclonal anti-E2F1 antibody  overnight at 4°C. After washing and incubating in a secondary antibody for 1 hour, the slides were mounted using a medium containing DAPI (Vector Laboratories). The images were collected using a confocal microscope . The image analyses were performed using Image-Pro plus 6.0 software .5 cells were boiled for 5 minutes in 2× SDS sample buffer  and subjected to SDS–PAGE as well as western blotting  experiments were performed as previously described  with cerTwo micrograms of genomic DNA was treated with sodium bisulfite, and the bisulfite-converted DNA was purified using an EpiTect Bisulfite Kit (Qiagen) in accordance with the manufacturer's instructions .www.r-project.org) and GraphPad Software version 4.0 . The survival data were estimated using the Kaplan–Meier method, and the differences in the survival rates were compared using the log-rank test. The mRNA expression levels and telomere lengths were analyzed using the Mann–Whitney rank sum test, and the promoter activity and ChIP assay were analyzed using a two-tailed t test. The experiments were independently repeated at least three times. The significance values were *P < 0.05, **P < 0.01, and ***P < 0.001.The data were analyzed using R software (


BICC1) gene, which encodes an RNA binding protein, has been identified by genome wide association studies (GWAS) as a candidate gene associated with major depressive disorder (MDD). We explored the hypothesis that MDD associated single-nucleotide polymorphisms (SNPs) affected the ability of cis-regulatory elements within intron 3 of the BICC1 gene to modulate the activity of the BICC1 promoter region. We initially established that the BICC1 promoter drove BICC1 mRNA expression in amygdala, hippocampus and hypothalamus. Intriguingly, we provide evidence that MDD associated polymorphisms alter the ability of the BICC1 promoter to respond to PKA signalling within amygdala neurones. Considering the known role of amygdala PKA pathways in fear learning and mood these observations suggest a possible mechanism through which allelic changes in the regulation of the BICC1 gene in amygdala neurones may contribute to mood disorders. Our findings also suggest a novel direction for the identification of novel drug targets and the design of future personalised therapeutics.The Bicaudal C Homolog 1 ( However, both these loci occupied intron 3 of the Bicaudal C Homolog 1 gene (BICC1). BICC1 was originally identified as mouse mutations which truncated the BICC1 protein were shown to result in polycystic kidney disease in mice.8 Subsequent analyses showed that inactivation of BICC1 resulted in Wnt9 and PKA10 pathway hyperactivation. Biochemical analysis demonstrated that the BICC1 protein contained three K homology domains that are involved in RNA binding and that BICC1 protein is implicated in post-transcriptional regulation of gene expression by antagonising miRNAs.11 More recent studies have also implicated the involvement of BICC1 protein in modulating bone density.12 Two mRNA isoforms have been reported for BICC1; termed the long and the short isoform. Using microarray analysis we detected the expression of the long isoform of BICC1 in neuronal tissues but were unable to detect significant levels of expression of the short isoform.7 Interestingly, the long isoform also displayed significant evidence of differential expression between different brain areas.7 Furthermore, MRI brain scan studies of MDD patient's demonstrated that the T allele of rs999845, which was protective against MDD, was associated with greater hippocampal volumes.13 Intriguingly, this effect was lost if the patient had been exposed to stressful events during childhood suggesting an epigenetic influence.13Major depressive disorder (MDD) will affect up to 25% of the adult population at some point in their livesBICC1 gene is consistent with the vast majority of other GWA studies where 93% of disease associated SNPs fall within regions of the genome that do not encode protein.14 The discovery that such a high proportion of associated SNPs occur in non-coding regions has hampered efforts to explore the functional consequences of SNPs within the non-coding genome that still remains poorly understood. Clues as to the functional consequences of many disease associated SNPs come from whole genome functional analyses as typified by the ENCODE consortium.15 Thus, 73% of disease associated SNPs were detected in regions of the genome that had characteristics of cis-regulatory regions determined using techniques such as FAIRE-seq, DNAseI-seq and ChIP-seq that identify regions of the genome that are less condensed or, which bind transcription factors or specifically modified histones in vivo.14 These cis-regulatory sequences include promoters, enhancers and silencer elements whose integrity is essential to maintaining appropriate levels of the expression of specific genes, in specific cells and in response to the correct stimuli.16 Indeed, the burden of proof now suggests that polymorphic variation within these cis-regulatory elements represents the main reservoir of heritable disease including MDD.14The finding of disease associated SNPs within the intron 3 of the 21 Furthermore, we have demonstrated that the activity and tissue specific characteristics of cis-regulatory elements are dependent on the specific promoter used and are best explored using endogenous promoter regions.21 We have also found that the functional consequences of allelic variation only become significant following the activation of specific signalling pathways in specific cell types.22To determine the effects of non-coding SNPs on the tissue specific activity of cis-regulatory elements we have previously used a combination of comparative genomics, reporter assay analysis in transgenic mice and magnetofected primary neurones. In this way we have shown that cis-regulatory regions with strong cell specificity can be identified by virtue of their high degrees of evolutionary conservation.BICC1 gene on the cell specific and inducible activity of the BICC1 promoter. We used a combination of LD studies, comparative genomics, in situ hybridisation, transgenic analysis and primary cell culture analysis to demonstrate the presence of a novel polymorphic cis-regulatory element in LD with rs9416742 that demonstrated significant allele specific effects on BICC1 promoter activity in primary amygdala neurones. The significance of these finding in health and in the complex underpinnings of MDD are discussed.On the basis of these previous studies we explored the hypothesis that SNPs in LD with rs9416742 contributed to susceptibility to MDD by altering the activity of highly conserved cis-regulatory elements in intron 3 of the BICC1 locus was performed using the UCSC genome browser (http://genome.ucsc.edu/). Allele frequency of SNPs was determined using the NCBI SNP database (http://www.ncbi.nlm.nih.gov/SNP/). Bioinformatic analysis of the effects of allelic variants on transcription factor binding sites were determined using the RegSNP website (http://viis.abdn.ac.uk/regsnp/Home.aspx).Genomic analysis of the BICC1_Long_Prom_F and R oligonucleotide primers (Because of its high GC content BICCprom was amplified using  primers  from hum primers  from hum primers  oligonucpBICCprom-LacZ. BICCprom was digested from pGEM-T easy using NcoI and EcoICRI and ligated into the NcoI and SmaI sites of the SB LacZ reporter plasmid (A kind gift from Sanbing Shen) to form pBICCprom-LacZ. pBICCprom-Luc. BICCprom was digested from pGEMT-easy using NcoI and SalI and ligated into the NcoI and XhoI sites of pGL4-23 (Promega). pBICC77prom-Luc(CG and AA). BICC77 (CG or AA) was digested out of pGEMT-easy using ZraI and SacI and placed in a ligation containing the pGL4.23 vector linearised with NcoI and Sac1 and BICCprom digested from pGEMT-easy using NcoI and EcoICRI.−1 as previously described.23 Surviving embryos were oviduct transferred into pseudopregnant CD1 host mothers. Transgenic mice from each line were humanely sacrificed by lethal injection of euthatol according to UK Home Office guidelines. These mice were then dissected to recover the brain which underwent submersion fixation in 4% PFA  for 4 h. All tissues were then stained using 5-bromo-4-chloro-3-indolyl-beta-D-galactopyranoside  solution for 4–12 h as previously described.23 X-gal stained tissues were then prepared for vibratome sectioning by allowing tissue to equilibrate with increasing concentrations of sucrose (to 30%) in phosphate buffered saline at 4 °C. Tissues were equilibrated with bovine serum albumen/Gelatin solution  overnight at 4 °C. Bovine serum albumen/gelatin embedded tissue was then hardened by addition of one-tenth of a volume of 25% gluteraldehyde. Fifty micron sections were then cut on a Vibratome series 1000 . Sections were mounted on glass slides and photographed under light field or phase contrast illumination.Following linearization and removal of the plasmid backbone, BICCprom-lacZ construct DNA was microinjected into one cell C57/BL6xCBA F1 mouse embryos at a concentration of 2–4 ng μlin situ hybridisation was carried out as previously described.24 Mouse cDNA for use as a template for the production of antisense BICC1 probe for radioactive in situ hybridisation was purchased from Source Bioscience (Genbank accession no. AK076154.1).Radioactive 22 Cells were transfected with plasmid DNA using Neuromag according to the manufacturer's instructions . Briefly, Neuromag reagent was added to a plasmid-media preparation and incubated at room temperature for 15 min allowing 250 ng of plasmid DNA in the media per 150,000 cells to be transfected. The DNA-Media-Neuromag solution was then added to previously prepared single cell cultures in 24-well plates and incubated on a magnetic plate for 15 min in a cell culture incubator at 37 °C and 5% CO2. Luciferase activity of plasmid constructs were measured using dual luciferase assay kits (Promega) using lysates from cell cultures transfected with the GAL5.1 luciferase constructs. Cell cultures were lysed and the proteins stabilized using the passive lysis buffer as per the manufacturer's instructions (Promega). The dual-luciferase assay analysis was carried out on a Glomax 96-microplate luminometer (Promega) using 20 μl of cell lysate per well of a white 96-well plate.Primary Amygdala cultures were prepared from P1-3 rat neonates as described earlier.n⩾3) were based on pooled amygdala neurones recovered from at least three individual rat neonates. Statistical significance of data sets were analysed using either two way analysis of variance (ANOVA) analysis with Bonferoni post hoc tests or using two tailed unpaired parametric Student t-test as indicated using GraphPad PRISM version 5.02 .Sample sizes , that includes the first seven exons , although detectible in kidney and bone tissue, demonstrated consistently low expression in all brain tissues.7 These observations argue against a role for the short isoform in brain function and, for this reason, we concentrated our analysis on the long isoform. Although our microarray analyses were highly informative they lacked the resolution to determine the specific regions of the brain that expressed BICC1. For this reason we used in situ hybridisation using probes derived from the full length BICC1 complementary DNA that reflects the long isoform, on sections of adult male mouse brain to determine whether BICC1 mRNA was expressed throughout the brain or displayed discrete regions of expression. These in situ analyses demonstrated that, although full length BICC1 transcript expression was present in the majority of tissues at low levels, areas of higher expression were evident within discrete components of the limbic system including the hippocampus, the hypothalamus and the amygdala  as well as FAIRE and DNAse1 hypersensitivity patterns characteristic of promoter regions in a number of different human cell lines  we recovered data consistent with higher levels of promoter activity around the transcriptional start site of the long splice-form in comparison to the short isoform which demonstrated fewer active promoter characteristics in all cell lines used  and the region most conserved in vertebrates . Brain tissues were recovered from these lines and subjected to X-Gal staining. Two of the transgenic mouse lines demonstrated robust and consistent staining for the expression of the LacZ gene in areas of the cingulate cortex, hippocampus, thalamus and in specific nuclei of the amygdala including the basolateral, basomedial, central and lateral amygdaloid nuclei (To isolate and characterise the long isoform promoter (henceforth referred to as BICC1prom) we designed PCR primers see  to isolatebrates . This seacZ gene . Using pd nuclei . BecauseBICC1 mRNA in limbic regions of the brain  pathway are activated in the amygdala during fear conditioning27 where they may also have a role in fear learning.29 Due to the known involvement of PKA and PKC pathways in fear memory and learning we explored the effects of activation of these pathways on the activity of the BICC1 promoter in primary amygdala neurones. We found little evidence that the PKC pathway could influence BICC1prom activity in primary amygdala neurones (It is well established that modulation of the activity of protein kinase A (PKA) pathways in the amygdala play a critical role in the consolidation of fear memories.neurones . We founneurones .BICC1 mRNA in the limbic system. These studies provide a useful platform for further exploring the possible effects of mood disorder associated allelic variants in BICC1 intron 3 on the tissue specific activity of BICC1prom. Using genome wide association studies we previously demonstrated that a significant association existed between the rs9416742 and rs999845 polymorphisms  and susceptibility to MDD.7 As previously mentioned neither of these SNPs occur within any coding regions of the BICC1 gene nor were they in LD with coding SNPs. Because evolutionary conservation has been shown to be highly suggestive of functionality we explored the hypothesis that rs9416742 and rs999845 occurred within conserved cis-regulatory regions. Unfortunately, comparative genomics demonstrated that neither SNP occurred within a region of the BICC1 locus which was highly conserved or displayed markers indicative of cis-regulatory regions. However, both SNPs were found to be in strong linkage disequilibrium with a SNP (rs2393477) that occurred in a 200 base pair region of human BICC1 intron 3 that had been highly conserved in mammalian species as divergent from humans as marsupials (opossum) and monotremes (platypus)  . This hirs999845 .BICC1 intron 3 affected the activity of BICC1prom in amygdala neurones we designed PCR primers  that contained rs2393477 and its close neighbour rs10740761, which was in high LD (r2>0.95). BICC77 was then subjected to two rounds of site-directed mutagenesis  with forskolin or PMA. PMA had no significant effect on the activity of either allelic variant and forskolin did not significantly alter the ability of BICC77GC to repress BICC1prom activity  with much higher affinity . This is intriguing as overexpression of GATA factors has been associated with depressive behaviour32 and a highly conserved C/EBP binding site exists just next to this locus. This arrangement of transcription factor binding has been associated with PKA activation on the past.33We asked whether it was possible to use a bioinformatics approach to identify candidate transcription factors whose binding to BICC77 was allele dependent. We used the RegSNP website to determine whether the AA haplotype altered the predicted binding efficiency of known transcription factors compared with the protective GC haplotype. Examination of rs10740761 using RegSNP shows that the C allele potentially binds the transcription factor Deaf1 which is suspected in causing memory deficits and anxiety like behaviour if deleted from the mouse genome.BICC1 gene with significant association. We observed that the T allele of the most strongly associated SNP; rs9416742, that has a frequency of 0.235 in healthy individuals, was found to have a protective affect against depression. Although neither of these SNPs were found within the coding region of BICC1, or within an area of intron 3 that could be identified as a cis-regulatory region, they were found to be in strong linkage disequilibrium with a SNP within a region of intron 3 that had been conserved for 210 million years thus representing the majority of the extent of mammalian evolution. We isolated this conserved region, that we called BICC77, and reproduced both of the allelic forms present in the human population (referred to as AA and GC). Because these SNPs lay within the BICC1 gene and because subsequent analysis had demonstrated that the allelic variants of BICC1 in question were associated with greater hippocampal volumes13 we tested the hypothesis that allelic variants of BICC77 differentially regulating the transcription of the BICC1 gene in the brain.To locate the presence of a human genomic locus that could contribute to susceptibility to major depressive disorder we carried out a GWA analysis of a large patient cohort and succeeded in identifying two SNPs within intron 3 of the BICC1 was expressed in any areas of the brain known to control mood. We used in situ hybridisation to demonstrate that BICC1 mRNA was more strongly expressed in specific areas of the limbic system including the hippocampus, amygdala and hypothalamus. Subsequent analysis of existing genomic databases succeeded in identifying the active BICC1 promoter by virtue of its extent of conservation, its accessibility to FAIRE and DNAseI analysis and its interaction with known promoter histone marks. Using magnetofection of primary amygdala cells with luciferase markers and dual-luciferase assays we were able to show that this promoter region was highly active in primary amygdala neurones compared with a generic TATA box promoter. Furthermore, by generating two different lines of transgenic mice with the BICC1 promoter linked to the LacZ gene we also demonstrated pronounced tissue specificity in the activity of the BICC1 promoter in hippocampus, amygdala and hypothalamus. These analyses established the expression of BICC1 and the activity of its promoter in regions of the limbic system that have critical roles roles in mood modulation and depressive behaviour. In addition, identifying the tissue specific activity of the BICC1 promoter provided us with a useful platform for studying the effects of allelic variants of BICC77 on its activity and hence the activity of the BICC1 gene.To test this hypothesis it was necessary to first determine whether BICC1 promoter in primary amygdala neurones and we were able to demonstrate that BICC77 acted as a strong repressor of BICC1 promoter activity within these cells. We have previously observed this model in the regulation of BDNF promoter 4 whereby a highly conserved region of the BDNF locus, containing a SNP associated with depression (BE5.2), caused significant repression of BDNF promoter 4 within 3 different primary cell types .22 These analyses of the BDNF locus suggested an important role for selective negative regulation in the modulation of inducible gene expression in the brain. In combination with this previous study, the current study highlights the complexities of understanding the specific mechanisms by which depression associated allelic variants may alter pathological susceptibility. Thus, by subtly changing the delicate homoeostatic balance of negative and positive regulatory mechanisms required to maintain levels of gene expression essential for mental health differences in the activity or regulatory elements over a life time, or following trauma, may be sufficient to contribute to mental illness. There is every reason to believe that identifying the effects of allelic variation on negative regulation will be critical for understanding the causes of psychiatric pathologies including depression.We next asked what effect BICC77 would have on the activity of the BICC1 promoter in amygdala cells. We recreated the different genotypes of BICC77 present in the human population (AA and CG) and found that the minor haplotype of BICC77(GC), that is in LD with the protective T allele of rs9416742, was not as potent a repressor as the major allele (AA). Whilst there is currently no evidence to suggest that levels of BICC1 expression within individuals with the CG haplotype of BICC77 are higher than those with the AA haplotype, the observation of a significant difference in the influence of these haplotypes on the activity of the BICC1 promoter in primary amygdala neurones provides us with a possible insight into a mechanism contributing to mood disorders. These observations reflect the results of a previous study, which demonstrated that the CA haplotype of the GAL5.1 enhancer, that supports expression of the galanin neuropeptide in areas of the brain including the paraventricular nucleus and amygdala, was significantly weaker than the GG haplotype in primary hypothalamic neurones.19 Subsequent analysis of these haplotypes in human cohorts suggested that the CA haplotype was protective against alcohol and cannabis abuse in certain populations35With this concept in mind we then asked whether allelic variants of BICC77 differed in their ability to negatively regulate the activity of the 36 One of the best studied is the PKA signal transduction pathway that is activated in amygdala neurones by binding of stress released epinephrine to B1 adrenergic receptors.36 Because of the known contribution of chronic stress in the exacerbation of mood disorders we sought to determine the effects of agonists of signal transduction pathways such as PKA and PKC known to have a role in amygdala function. Treatment of transfected cultures to activate the PKC pathway had no effect on BICC77 and no allelic differences were observed. Activation of PKA pathways in transfected cells also had little or no effect on the ability of the BICC77GC haplotype to repress the BICC1 promoter. Intriguingly, however, forskolin treatment resulted in further repression of the BICC1 promoter by BICC77AA. Further bioinformatic analysis suggested that the AA haplotype had an increased affinity with a combination of transcription factors (GATA and C/EBP) that have previously been associated with PKA response.33 Because the AA haplotype of BICC77 is the major haplotype within the human population and also represents the ancestral haplotype present in all other mammals, it can be hypothesised that the CG allele of BICC77, which is in LD with the protective T allele of rs9416742, is not only less repressive of BICC1 promoter activity but has also lost its ability to respond to activation by PKA modulated signalling inputs. Indeed, it could be hypothesised that the reduction in its ability to repress the BICC1 promoter or to respond to PKA signalling may be mechanistically related to the protective effects observed for the T allele of rs9416742.It is accepted that one of the main roles of gene regulatory regions is to interpret signal transduction information within the surrounding cell cytoplasm for the transcriptional machinery (RNA polymerase TFIID and mediator) bound at the promoter region of genes. In the specific case of the amygdala, a number of signal transduction pathways have been implicated in modulating the cellular systems that control mood.38 However, the overwhelming conclusion that has been drawn from the results of these studies is that the genetic and epigenetic influences in susceptibility to mood disorders are unlikely to be solely due to changes in gene coding regions but will instead affect the mechanisms that control the spatial, tissue specific and inducibility of these genes. The current manuscript describes the use of novel combinations of different techniques to determine the mechanisms through which alleles associated with MDD might contribute to susceptibility. Thus, in addition to suggesting a novel contributory mechanism towards MDD susceptibility the current manuscript describes innovative approaches to exploring the mechanisms through which non-coding disease associated SNPs may contribute to disease.Major depressive disorder has been shown to be a highly complex disease state to diagnose and this may reflect the large numbers of unreplicated genome wide association studies hits associated with this condition . There is also increasing evidence of the possibility of masking or exacerbation of depression phenotypes through epigenetic influences that are altered following early life traumatic events that may have a role in reducing the efficacy of genetic association analysis.


Orthodenticle Homeobox 2 (OTX2). Through these studies we have revealed that OTX2 is differentially regulated in medulloblastoma at the level of chromatin accessibility, which is in part mediated by DNA methylation. In cell lines exhibiting chromatin accessibility of OTX2 regulatory regions, we found that autoregulation maintains OTX2 expression. Comparison of medulloblastoma regulatory elements with those of the developing brain reveals that these tumors engage a developmental regulatory program to drive OTX2 transcription. Finally, we have identified a transcriptional regulatory element mediating retinoid-induced OTX2 repression in these tumors. This work characterizes for the first time the mechanisms of OTX2 overexpression in medulloblastoma. Furthermore, this study establishes proof of principle for applying ENCODE datasets towards the characterization of upstream trans-acting factors mediating expression of individual genes.Despite an emerging understanding of the genetic alterations giving rise to various tumors, the mechanisms whereby most oncogenes are overexpressed remain unclear. Here we have utilized an integrated approach of genomewide regulatory element mapping via DNase-seq followed by conventional reporter assays and transcription factor binding site discovery to characterize the transcriptional regulation of the medulloblastoma oncogene  MYC oncogene OTX2 with the goal of identifying strategies of pharmacologically inhibiting its expression.Medulloblastoma is the most common pediatric brain malignancy. The substantial comorbidities associated with the standard medulloblastoma treatment of resection, radiation, and chemotherapy necessitate the development of selective therapeutics. While Sonic Hedgehog (Shh) pathway inhibitors have shown promise in treating medulloblastomas exhibiting Shh pathway hyperactivity trans-acting regulators de novo in most brain tissues as indicated by lineage tracing of Otx2-expressing cells Otx2 (the mouse homolog of human OTX2) exhibits a dynamic expression pattern during embryonic development OTX2 genomic copy number gain OTX2 genomic copy number. While OTX2 is expressed in some tissues giving rise to midbrain and hindbrain OTX2 in medulloblastoma may thus reflect the regulatory landscape sustained from a particular developmental timepoint or rather an unrelated regulatory mechanism unique to this tumor type.Little is known about the mechanisms of OTX2 overexpression in medulloblastoma. Although a subset of medulloblastomas (∼21%) exhibit OTX2in vitro or to an inability to repress OTX2 in this tissue context. Understanding the mechanism of OTX2 repression by retinoids could reveal strategies of reinforcing this therapeutic effect. To this end, we have also investigated transcriptional regulatory elements mediating retinoid-induced OTX2 repression in medulloblastoma cells.Taking a cue from its developmental regulation OTX2The identification of transcriptional regulatory elements for individual genes is notoriously difficult OTX2 in medulloblastoma, we have utilized an integrated approach based upon an emerging technology, DNase-seq, that permits genomewide mapping of active regulatory elements such as promoters, enhancers, repressors, insulators, and locus control regions OTX2 locus, which were then characterized for activity and specificity with reporter assays. Minimally-required regions of DHS sites of interest were then interrogated for the presence of transcription factor binding motifs to identify trans-acting factors regulating OTX2 expression, which were then experimentally validated. Finally, we investigated datasets characterizing the epigenome of various relevant central nervous system (CNS) tissues to draw parallels between OTX2 regulation in medulloblastoma and in the developing brain. In addition to characterizing OTX2 regulation in this particular context, this study also establishes a framework for hypothesis-driven experiments derived from ENCODE data as this endeavor continues to map chromatin modifications and other informative characteristics of transcriptional regulatory domains.In consideration of the experimental limitations to characterizing the transcriptional regulatory regions of Brain tumor cell lines and frozen primary tumor samples were obtained from the Duke University Brain Tumor Center Tissue Bank.5 cells were plated into each well of a 24 well plate, and cells were transfected with 1.3 µg of reporter plasmid and 67 ng of internal control plasmid pRL-CMV using Lipofectamine 2000, and 24 hours later cells were harvested and tested for luciferase reporter activity using the Promega Dual-Luciferase Reporter Assay System. All luciferase assays were carried out using transient transfection of circular plasmids. For siRNA experiments, cells were transfected with siRNA's at a final concentration of 100 nM. siRNA's were obtained from Ambion. siRNA sequences are as follows: Scramble: GAGUCAACCUUAUGAUACUtt, OTX2 #1 GGAGGUGGCACUGAAAAUCtt, OTX2 #2 GGACACUAAUUCAUCUGUAtt. OTX2-targeted siRNA's were previously validated to repress OTX2 protein expression using the same transfection conditions and cell lines trans retinoic acid and cycloheximide was purchased from Sigma. 5-aza-2′deoxycytidine was purchased from MP Biomedicals.Medulloblastoma and glioblastoma cells were obtained from Darell Bigner and were maintained as previously described 7 cells using NP40 concentrations optimized for each cell line. Nuclei were treated with increasing concentrations of DNase and then prepped for either DNase-seq or DNase-PCR as previously described Medulloblastoma and glioblastoma cell nuclei were prepared with 1–5×10TGTCTCCGGGATTAATTATGGGCAC) for subsequent motif discovery. TRANSFAC TFblast The critical 13 bp fragment of DHS 4 was extended by 6 bp in either direction to yield a 25 bp fragment  or IgG control antibodies using the ChIP Assay Kit . Enriched DNA was quantified using qPCR as described above, and ΔCt was calculated relative to Line 1 primers.500 ng of DNA from each sample was bisulfite-treated using the EZ DNA Methylation Gold Kit (Zymo Research) following the manufacturer's protocol, and approximately 50 ng of bisulfite-treated or untreated DNA was amplified by PCR using Faststar Taq. Each CpG site was scored using DNAstar Seqman Software. Methylation-specific PCR was performed on 20 ng bisulfite-treated DNA using Platinum Taq. Primer sequences and genomic coordinates are listed in OTX2 gene, we performed DNase-seq on two medulloblastoma cell lines, D341 and D721, which overexpress OTX2 independent of genomic copy number gain MYC copy number) OTX2 locus, with many shared and prominent DHS sites present from 10 kb upstream to 80 kb downstream of the OTX2 long isoform transcriptional start site , in agreement with SAGE data indicating that OTX2 is expressed in a restricted subset of normal tissues and tumor types (e.g. medulloblastoma and retinoblastoma) OTX2 locus relative to retinoblastoma, and retinoblastoma exhibiting only four unique DHS sites  to determine the DNase sensitivity of the seven most prominent DHS sites in a panel of medulloblastoma cell lines. To determine the specificity of DHS sites to OTX2-expressing cell lines, we included two cell lines that did not express OTX2 (UW228 and D324). With the exception of DHS 2, all DHS sites identified in the ll lines  and S2. trans-acting factors in medulloblastoma cells, we assessed transcriptional regulatory function of the six validated DHS sites. ∼500 bp fragments encompassing each DHS site (see OTX2 status) in affecting proximal regulatory element utilization in this tumor. However, testing activities of distal DHS sites revealed that the enhancer activity of DHS 4 closely associated with OTX2 expression status  that exh, see −4), stronglMYC promoter, Del-3 We then sought to determine the requirement of OTX2 for DHS 4 enhancer activity. Knockdown of OTX2 with distinct siRNA's completely abolished enhancer activity of DHS 4 in OTX2-expressing medulloblastoma cells . As a coOTX2 locus, we then overexpressed EGFP-tagged OTX2, which migrates more slowly during SDS-PAGE electrophoresis, to determine the effect of ectopic OTX2 upon expression of the endogenous OTX2 gene. In OTX2-expressing medulloblastoma cells, we found that ectopic OTX2 indeed enhanced the expression of endogenous OTX2  to permit OTX2 expression. Thus, OTX2 expression in medulloblastoma requires both positively-acting transcriptional regulators as well as a lack of OTX2 promoter methylation.Independent of distal chromatin accessibility and the activity of form TSS . This Cpn status , with 30n status . There wOTX2 in medulloblastoma with that of related CNS tissues. To this end, we mapped medulloblastoma DHS sites onto the mouse genome and investigated relevant chromatin characteristics of these elements in publically-available genome browser tracks OTX2 regulatory landscape similar to medulloblastoma.Given the accumulation of chromatin structure data for a variety of tissue contexts, we then sought to compare the regulatory landscape of Retinoids are known to repress Otx2 during anterior-posterior embryonic patterning OTX2 transcription in medulloblastoma, thus contributing to the understanding of critical events in both medulloblastoma tumorigenesis and its response to differentiation therapy.In this study, we have implemented a genomewide approach to describe for the first time the mechanisms of basal and retinoid-repressed OTX2 genomic copy number gain is known to drive aberrant OTX2 expression in a subset (∼21%) of medulloblastomas OTX2 genomic alterations. First, OTX2 expression associates with accessible chromatin regions and unmethylated promoter DNA at the OTX2 locus, indicating that DNA accessibility limits OTX2 expression to a restricted set of normal and transformed tissues. Additionally, OTX2 protein directly activates the only OTX2 regulatory element that is specifically active in OTX2-expressing medulloblastomas. Finally, OTX2 enhancers in medulloblastoma are marked by activating histone modifications in the embryonic brain. These observations suggest that an OTX2 autoregulatory loop engages developmental enhancers to drive aberrant OTX2 expression in medulloblastoma.While OTX2 transcriptional activation through trans-acting factors. Thus, failure to repress OTX2 during development could be the critical determinant of OTX2 expression status in medulloblastoma. Notably, this prediction does not rule out the involvement of mediators that cooperate with OTX2 to modulate DHS 4 activity. The role of such factors, including chromatin modifiers and OTX2-interacting proteins, remains to be determined.Could OTX2 expression be inherited from the medulloblastoma cell of origin? OTX2 is expressed in the presumptive hindbrain OTX2 during neural development. The mechanisms of developmental OTX2 repression that may fail during medulloblastoma tumorigenesis are currently unclear. The existence of medulloblastomas that lack both OTX2 expression and promoter methylation indicates that DNA methylation is unlikely the initiator of OTX2 repression during development, but rather serves as reinforcement of a repressive chromatin state, as previously demonstrated for other loci The identification of a positive feedback loop maintaining OTX2 expression in medulloblastoma suggests that disruption of this loop is a requisite step in the repression of trans-acting factors responsible for stage- and domain-specific Otx2 expression have also been identified, and for the midbrain/hindbrain boundary, a definitive model of Otx2 regulation has been constructed trans-acting Otx2 developmental regulators cannot in any case explain the expression pattern of OTX2 in medulloblastoma  DNase hypersensitivity landscape in OTX2-expressing and -nonexpressing cell lines, wide viewing window. From top to bottom, tracks are as follows: known mouse enhancers (as summarized in (PDF)Click here for additional data file.Figure S2Validation of medulloblastoma DHS sites in a cohort of OTX2-expressing and -nonexpressing cells. Refers to (PDF)Click here for additional data file.Figure S3Identification of transcription factor binding sites in DHS 4. (A) Summary of database search results for transcription factor binding motifs in the critical 13 bp and 12 bp flanking sequence Click here for additional data file.Figure S4Cross-species comparison of the OTX2 transcriptional landscape in medulloblastoma and CNS tissues. Chromatin structure of the mouse Otx2 locus. From top to bottom, tracks are as follows: known Otx2 developmental enhancers as determined by transgenic mouse reporter assays, regions of homology to medulloblastoma DHS sites, Refseq genes, CRX ChIP-seq of mouse eye (PDF)Click here for additional data file.Figure S5Assessment of gene expression data for OTX2 regulators proposed in the literature. (A) Characteristics of each proposed regulator, direction (activator or repressor) of regulation, the proposed tissue domain of OTX2 regulation, cis-element regulated  and OTX2-negative (n = 8) medulloblastomas as determined by SAGE, Spearman's rho correlation R value and p-value (as indicated in parentheses) with OTX2 in medulloblastomas as determined by SAGE p = 0.009, Spearman's rho).(PDF)Click here for additional data file.Table S1Summary of DHS characteristics.(PDF)Click here for additional data file.Table S2Bisulfite sequencing and methylation-specific PCR results for 33 medulloblastomas.(XLS)Click here for additional data file.Table S3Genomic coordinates of known OTX2 developmental regulators.(XLSX)Click here for additional data file.