HNF4A were identified as the cause of Maturity Onset Diabetes of the Young 1 (MODY1) two decades ago, the mechanisms by which this nuclear receptor regulates glucose homeostasis remain unclear. Here we report that loss of Drosophila HNF4 recapitulates hallmark symptoms of MODY1, including adult-onset hyperglycemia, glucose intolerance and impaired glucose-stimulated insulin secretion (GSIS). These defects are linked to a role for dHNF4 in promoting mitochondrial function as well as the expression of Hex-C, a homolog of the MODY2 gene Glucokinase. dHNF4 is required in the fat body and insulin-producing cells to maintain glucose homeostasis by supporting a developmental switch toward oxidative phosphorylation and GSIS at the transition to adulthood. These findings establish an animal model for MODY1 and define a developmental reprogramming of metabolism to support the energetic needs of the mature animal.Although mutations in DOI:http://dx.doi.org/10.7554/eLife.11183.001 HNF4 is mutated or deleted. The symptoms of MODY1 usually appear during early adulthood and include abnormally high levels of sugar in the blood, as well as the pancreas not being able to release the hormone insulin properly in response to these sugars.Diabetes is a complex disease that is caused by a combination of factors, including the person’s habits and environment, as well as their genetic make-up. However, there are some rare forms of diabetes that are caused simply by mutations in single genes and are directly inherited. For example, it has been known for twenty years that a type of diabetes called “Maturity Onset Diabetes of the Young type 1” (or MODY1 for short) occurs when a gene called Previous studies in mice have tried to understand how losing the HNF4 gene leads to MODY1. However, these mouse models did not fully recreate the symptoms of this disorder and the precise role of HNF4 in preventing diabetes remains unclear. Barry and Thummel have now used the fruit fly, because it is a model organism with simple genetics, to help shed light on this question. Furthermore, flies and mammals use many of the same pathways to control metabolism, making the fly a good model for the disease in humans.HNF4 gene in fruit flies and observed that the flies had all the symptoms that are typical in people with MODY1. These symptoms included high sugar levels and decreased production of insulin-like hormones. The experiments also showed that HNF4 normally supports the proper expression of another gene called Hex-C; this gene encodes a protein that senses how much sugar is available and helps to keep the amount of sugar circulating the body within normal levels. Barry and Thummel went on to discover that the HNF4 gene is required for the expression of some genes in structures called mitochondria, which provide most of the energy used by animal cells. Lastly, the HNF4 gene became more active as the flies matured, and appeared to help the metabolism of a developing fruit fly transition towards that of an adult.Barry and Thummel deleted the HNF4 protects against MODY1 by influencing several components of sugar metabolism in fruit flies. In the future, more studies are needed to understand how exactly HNF4 acts in mitochondria and to explore if similar results are seen in mammals.Together these findings show that DOI:http://dx.doi.org/10.7554/eLife.11183.002 Glucokinase (GCK/MODY2), and Insulin (INS/MODY10). Mechanistic insight into the anti-diabetic roles of other MODY genes, however, remains limited.The global rise in the prevalence of diabetes has prompted increased efforts to advance our understanding of metabolic systems and how they become disrupted in the diseased state. Although genetics and environment have a significant impact on diabetes susceptibility, severity, and care, the causal factors are often complex and unclear. Several cases of familial diabetes have been identified, however, that show clear patterns of heritability due to monogenic disease alleles, highlighting these genes as critical factors for glycemic control. To date, mutations in 13 genes have been shown to cause autosomal dominant inheritance of Maturity Onset Diabetes of the Young (MODY1-13), representing the most common forms of monogenic diabetes. MODY patients typically present with hyperglycemia and impaired glucose-stimulated insulin secretion (GSIS) by young adulthood, while having normal body weight and lacking β-cell autoimmunity . ConsistHepatocyte Nuclear Factor 4A (HNF4A) as responsible for MODY1  from neuroendocrine cells in the fly brain  with the goal of defining its roles in maintaining carbohydrate homeostasis. dHNF4 is a close ortholog of human HNF4A, with 89% amino acid identity in the DNA-binding domain and 61% identity in the ligand-binding domain. The spatial expression patterns of the fly and mammalian receptors are also conserved through evolution, raising the possibility that they share regulatory activities . A homolog of mammalian GCK, Hex-C, is also under-expressed in mutants. dHNF4 appears to act through these pathways to promote GSIS in the IPCs and glucose clearance by the fat body. In addition, we show that dHNF4 expression increases dramatically at the onset of adulthood, along with its downstream transcriptional programs. These studies suggest that dHNF4 triggers a developmental transition that establishes the metabolic state of the adult fly, promoting GSIS and OXPHOS to support the energetic needs of the mature animal.Here we describe our functional studies of tivities . In supp mammals . Here wedHNF4 null alleles (Δ17/dHNF4Δ33dHNF4) and genetically-matched controls that were transheterozygous for precise excisions of the EP2449 and KG08976 P-elements, as described previously , less than 30% of mutant animals survive though eclosion, and the rest die primarily during the first day of adulthood , and serine, which is produced from 3-phosphoglycerate, although the increased DHAP was only observed on the 15% sugar diet  metabolomic analysis was used to further characterize the metabolic state of gar diet . This stgar diet . Several pathway . This pa pathway . dHNF4 mhropathy  , with just over half of these genes showing reduced abundance   that contribute to oxidative phosphorylation (OXPHOS). Further analysis of these transcripts by northern blot hybridization confirmed their reduced expression in dHNF4 mutants, corresponding to mtDNA genes involved in Complex I , Complex IV  and Complex V/ATP synthase , along with reduced levels of the mitochondrial large ribosomal RNA (mt:lrRNA)  . Gene on 644 up) . In cont mutants . Interes mutants . In Drost:lrRNA) . Importa mutants . In addi animals .10.7554/dHNF4 for their maximal expression, including genes that encode the alpha and beta subunits of the electron transfer flavoprotein (ETFA and ETFB), ETF-ubiquinone oxidoreductase (ETF-QO), and the Complex II  assembly factor dSdhaf4 , CG5599 (which encodes a protein with homology to the E2 subunit of the α-ketoglutarate dehydrogenase complex (α-KGDHC) as well as the E2 subunit of the branched-chain alpha-ketoacid dehydrogenase complex), CG1544 (which encodes a homolog of α-KGDHC E1), as well as Isocitrate dehydrogenase   . These chenotype .dHNF4 mutants also have decreased expression of the GCK homolog Hexokinase-C (Hex-C) , which is involved in glycogen metabolism, and transaldolase and CG17333, which are involved in the pentose phosphate shunt. Additionally, the gluconeogenesis genes Pyruvate carboxylase (CG1514) and Phosphoenolpyruvate carboxykinase  show reduced expression in mutant animals, similar to their dependence on Hnf4A for expression in the mammalian liver  . GCK is an liver   was performed to identify direct transcriptional targets of the receptor. Through this analysis, forty-seven genes were identified as high confidence targets by fitting the criteria of showing proximal dHNF4 binding along with reduced transcript abundance in mutant animals  . These id CG5599 . We alsod CG5599 . Taken tnt cells . In contstaining . This mi and SOD . Taken tdHNF4 expression in the IPCs, fat body, and intestine to examine the contributions of dHNF4 in these tissues to systemic glucose homeostasis. This revealed a requirement in both the IPCs and fat body for glucose homeostasis, consistent with the well-established roles of these tissues in insulin signaling and the regulation of circulating sugar levels    in eithe 30 kDa) . Fat bodfunction  (Cho et function . In contrphology .10.7554/ATPsynβ RNAi) in the fat body caused lethality prior to eclosion, IPC-specific RNAi produced viable adults that appeared normal but displayed significant hyperglycemia (Cox5a RNAi) failed to produce hyperglycemia, while RNAi in the fat body caused lethality prior to adulthood, similar to ATPsynβ. This premature lethality was accompanied by severe developmental delay and more than 50% of the animals dying prior to puparium formation when raised on the 15% sugar diet. Interestingly, we discovered that these animals are sugar intolerant, similar to dHNF4 mutants, such that rearing them on the 3% sugar diet allowed for 100% survival to puparium formation while also alleviating the developmental delay  for GSIS, fat body (liver) for lipid metabolism and glucose clearance, and intestine to suppress inflammation, there are likely to be divergent roles as well. One example of this is the embryonic lethality of Hnf4A mutant mice, which is clearly distinct from the early adult lethality reported here for dHNF4 mutants. Further studies are required to dissect the degree to which the regulatory functions of this receptor have been conserved through evolution.Interestingly, gene ontology analysis indicates that the up-regulated genes in osophila . This re disease . Disrupt mutants . Moreovevolution . Taken tHnf4A plays a role in hepatocyte differentiation and proliferation in addition to its roles in metabolism   . Fourth,studies) . Some ofl OXPHOS , and stul OXPHOS .dHNF4, dHNF4-B, encodes a predicted mitochondrial localization signal in its 5’-specific exon, providing a molecular mechanism to explain the targeting of this nuclear receptor to this organelle. Efforts are currently underway to conduct a detailed functional analysis of dHNF4-B by using the CRISPR/Cas9 system to delete its unique 5’ exon, as well as establishing transgenic lines that express a tagged version of dHNF4-B under UAS control. Future studies using these reagents, along with our dHNF4 mutants, should allow us to dissect the nuclear and mitochondrial functions of this nuclear receptor and their respective contributions to systemic physiology.Although unexpected, our proposal that dHNF4 may directly regulate mitochondrial gene expression is not unprecedented. A number of nuclear transcription factors have been localized to mitochondria, including ATFS-1, MEF2D, CREB, p53, STAT3, along with several nuclear receptors, including the estrogen receptor, glucocorticoid receptor, and the p43 isoform of the thyroid hormone receptor . The sigHnf4A by immunohistochemistry in tissue sections, including in postnatal pancreatic islets  acts in mid-embryogenesis to directly induce genes that function in biosynthetic pathways related to the Warburg effect, by which cancer cells use glucose to support rapid proliferation  and genetically-matched controls that were transheterozygous for precise excisions of the EP2449 and KG08976 P-elements, as described previously . Fasting was achieved by using 1% agar as a medium. For adult studies, 8–10 day old males were selected for all studies unless otherwise indicated.All genetic studies used a transheterozygous combination of eviously . Sugar dr4-GAL4 , RNAiUAS-Cox5a (TRiP 27548)RNAi, UAS-CIA30 (TRiP 55660), RNAiUAS-ATPsynβ (TRiP 28056), RNAiUAS-Scs-α (TRiP 51807), RNAiUAS-CG5599 (TRiP 32876), and RNAiUAS-HexC  . Animals collected for developmental RNA and glycemia measurements  for 4 day pupae, and males at mid-eclosion from the pupal case  and/or Glucose Oxidase (GO) assay kits  as previously described, with approximately six biological replicates  assayed per condition . Total pMature adult males were placed on 10% sucrose + 1% agar overnight prior to analysis. Six biological replicates per genotype  were analyzed for ATP levels by using a luminescence assay kit  as described .Animals were raised on the 3% sugar diet until five days of adulthood and transferred to a fresh vial with either the 3% or 15% sugar diet for three days prior to collection. Twenty adult males per sample were snap-frozen in liquid nitrogen and prepared for analysis by gas chromatography-mass spectrometry (GC/MS) as described . Data isTissues were dissected in cold 1xPBS, fixed in 4% paraformaldehyde for 20-30 min at room temperature, and washed once quickly followed by three washes for 20 min each in PBS, 0.2% Triton-X100. Samples were blocked using 5% normal goat serum for 1–2 hr at room temperature and incubated with primary antibodies for a minimum of 24 hr at 4˚C, washed, and incubated with secondary antibody at 4˚C for 24 hr. Images were acquired using an Olympus FV1000 confocal microscope and analyzed by Volocity software to generate Z-stack projections and overlay images. The following antibodies were used for immunofluorescence studies: rat anti-dHNF4 , rat antDissected brains stained for DILP2 peptide were mounted in SlowFade® Gold (Life Technologies) and imaged using an Olympus FV1000 confocal microscope and 60X water-immersion objective. Scan settings were fixed to be identical for all captured images, with Z-stack limits set to encompass the entire depth of DILP2 fluorescence for each brain. Maximum projection Z-stacks were analyzed using Volocity software to calculate mean pixel intensity of DILP2 fluorescence within the IPCs (selected by ROI tool) for each set of IPCs analyzed.20, 1 ml 10% SDS, 100 μl sheared herring sperm ssDNA) for two hours at 42˚C prior to the addition of radiolabeled probe. Probes were generated by Klenow-mediated random primer amplification of purified template DNA corresponding to approximately 100–500 bp of the transcript of interest, allowing incorporation of 32P radiolabeled-nucleotide . Probes were incubated with membranes overnight, and the hybridized membranes were washed and exposed to X-ray film at -80˚C using two intensifying screens.Total RNA was extracted from groups of 10–20 animals using TriPure isolation reagent (Roche). RNA was fractionated by 1% formaldehyde gel electrophoresis at a constant voltage (70V) for ~3.5 hr prior to transfer to a nylon membrane overnight. After transfer, RNA was UV cross-linked to the membrane and placed in hybridization buffer  were collected using TriPure isolation reagent (Roche). Pairs of biological replicates were pooled to obtain four biological replicates for further purification using an RNeasy kit (QIAGEN). RNA quality was subsequently analyzed using an Agilent Bioanalyzer RNA 6000. PolyA-selected RNAs from each biological replicate were then assembled into barcoded libraries and pooled into a single-flow cell lane for Illumina HighSeq2000 50-cycle single-read sequencing, which produced ≥21.9 million reads per sample. Standard replicate RNA-seq analysis was performed using USeq and DESeq analysis packages with alignment to the Drosophila melanogaster dm3 genome assembly. Transcripts meeting a cutoff of ≥1.5 fold difference in mRNA abundance and FDR ≤1% were considered as differentially expressed genes. RNA quality control, library preparation, sequencing, and data analysis were performed at the University of Utah High Throughput Genomics and Bioinformatics Core Facilities. Although mt:Cyt-b and mt:ND6 are included among the down-regulated genes in our RNA-Seq dataset  for 1.5 min using a Brinkmann Homogenizer Polytron PT 10/35. The homogenate was filtered through a layer of 100 μm-pore nylon mesh into a pre-chilled glass-Teflon homogenizer, stroked on ice 35 times using a B pestle, and filtered through two layers of 40-μm-pore nylon mesh prior to adding one volume of warm cross-linking buffer  to bring the sample to room temperature for crosslinking . 2.5 M glycine was added to a final concentration of 125 mM to stop the crosslinking after 3 min. The mixture was pelleted for resuspension into 10 ml of RIPA buffer  for sonication. The sonicated material was centrifuged at 20,000 g, and the supernatant was distributed into 500 μl aliquots that were snap frozen in liquid nitrogen. To each aliquot, 1 ml of cold RIPA buffer (without SDS) was added prior to removing 150 μl for an input control, and then 5 µl of polyclonal affinity-purified anti-dHNF4 antibody was added to each sample for immunoprecipitation overnight at 4˚C , transferred to PVDF membrane overnight at 4˚C, and blocked with 5% BSA prior to immunoblotting. Antibodies used for western blots include rabbit anti-pAKT , rabbit anti-AKT , mouse anti-SDHA (Abcam 137756), rabbit anti-SDHB , mouse anti-ATP5A (Abcam 14748), and mouse anti-βTubulin (Chemicon MAB380).UAS-RNAi line or 1118w controls  peptide were used for ELISA assays, essentially as described . The indcontrols  were cro libitum  or faste libitum . The pos40A;tub-GAL4)yw,hsFLP,UAS-GFP; tub-GAL80,FRT were crossed to ∆33/CyO twi>GFPw;HNF4 males for MARCM analysis. Flies were reared on the 3% sugar diet and heat treated at 37°C for one hour as pharate adults, and again as newly-eclosed adults. Adults were maintained on the 15% sugar diet for 8–10 days prior to analysis.Virgin female flies (Adult flies were dissected in room temperature Schneider’s medium (ThermoFisher 21720024) with microdissection scissors to separate the abdomen from the thorax. The intestine was removed and the abdominal cavity was cut open to allow maximal contact of fat body with the TMRE solution (ThermoFisher T669). Dissected abdomens were placed in freshly-prepared solution of 20 nM TMRE in Schneider’s medium and incubated in the dark for 5–7 min. Samples were then washed briefly twice in Schneider’s medium, mounted on glass slides in fresh Schneider’s medium, and immediately imaged on an Olympus FV1000 confocal microscope with a 60x water objective.DHE staining was performed as previously described . BrieflyP values were calculated using a two-tailed Student’s t-test, multiple comparison P values were calculated using one-way ANOVA with Šídák multiple test correction (except th quartiles (box), and the median (midline).GraphPad PRISM 6 software was used to plot data and perform statistical analysis. Pairwise comparison  In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.Drosophila HNF4 promotes glucose-stimulated insulin secretion and increased mitochondrial function in adults" for consideration by eLife. Your article has been favorably evaluated by K VijayRaghavan (Senior editor) and three reviewers, one of whom is a member of our Board of Reviewing Editors.Thank you for submitting your work entitled "The reviewers have discussed the reviews with one another and the Reviewing editor has drafted this decision to help you prepare a revised submission.SummaryDrosophila glucose homeostasis. In humans, mutations in HNF4A cause an early onset form of diabetes. The authors make the insightful observation that mutations in HNF4 result in early adult death just after eclosion. This phenotype is rescued if the adults are fed on 3% sugar diet instead of the regular diet, which contains about 15% sugars in it. Thus, reduced carbohydrate intake increases viability of HNF4 mutants suggesting that it might function in the regulation of sugar homeostasis. Further analysis suggests indeed that HNF4 mutants have increased levels of free glucose and trehalose in adults and have impaired glucose tolerance and reduced levels of ATP . The authors then use MS to determine the levels of different intermediates in glycolysis and mitochondrial metabolism and find that many of the intermediates of glycolysis and the associated pathways that function in the biosynthesis of other metabolites show a significant increase when HNF4 mutants are fed on 15% sugar diet but not when they are reared on 3% sugar diet. Consistent with these observations the authors show that loss of HNF4 causes mitochondrial fragmentation. Based on these observations that authors conclude that HNF4 functions in the metabolic reprogramming from the larval to the adult mode during development consistent with the lethality of HNF4 mutants.In this manuscript the authors study the role of HNF in Interestingly, mutant flies survive longer on a low sugar diet. Using global analyses such as metabolomics, RNA-seq and ChIP-seq the authors find that glycolysis and mitochondrial function are altered in mutant flies. Surprisingly, the RNA-seq and ChIP-seq data point to the possibility that HNF acts in the mitochondria to increase mtDNA transcription. The authors then use tissue specific knock-downs to show that glucose homeostasis is most perturbed when HNF is knocked down in the IPCs and fat body. Indeed, knock-down of HNF in the IPCs reduces DILP2 in circulation. The authors then explore the possibility that HNF triggers a developmentally regulated metabolic switch towards GSIS and OXPHOS at the onset of adulthood.The authors use a range of technologies to establish links between development, metabolic regulation and glucose homeostasis. A number of novel findings are reported. The most notable  is the finding that HNF might regulate mtDNA transcription. If so, this would alter our understanding of how mitochondrial transcription is regulated, and offer insights into how mtDNA transcription might be altered in diseases, such as diabetes. Unfortunately, the experiments that this novel claim is based on are not conclusive.The following is a list of major concerns that the reviewers have expressed and would like addressed.Essential revisions:1) A major, most exciting, finding of the paper is that dHNF4 might directly regulate mtDNA transcription. If so, this will change much about how we think mtDNA transcription is regulated. While the authors provide some evidence for this (for example ChIP-seq data), further experiments should be conducted to solidify this finding. In particular, it would be nice if the authors provide further evidence that dHNF4 is indeed targeted to mitochondria and present within the mitochondrial matrix where mtDNA resides. This could be achieved by subcellular fractionation of tissues or cells to show that dHNF4 first associates with the mitochondrial fraction and then further sub-fractionation to determine where within mitochondria it is. Along the same lines, are there any sequences in dHNF4 specifically required to target it to mitochondria? Does it possess a canonical N-terminal mitochondrial targeting sequence? If so, what are the phenotypic consequences of preventing mitochondrial targeting?The key evidence that dHNF binds to mtDNA is the ChIP-seq data. It is unclear how to interpret this mtDNA Chiq-seq data for a couple of reasons:A) The presumably high copy number of mtDNA in the sample (perhaps 1000X in excess of nuclear).B) The low signal to noise ratio in the nuclear binding sites. Presumably, most ChIP-seq experiments will detect mtDNA as a background signal. This will usually be discarded, because of the excess signal at specific nuclear DNA binding sites. In this study, in which the signal to noise ratio in nuclear genes is quite low, any background signal caused by the mtDNA might seem more important. A nice control would have been to perform the ChIP-seq in the mutant flies. The mtDNA signal should be much reduced in the mutants (assuming the mtDNA copy number is the same in mutant flies).2) The second piece of evidence supportive of HNF4 being present in the mitochondria is an IF experiment, which uses the same antibody as the ChIP-seq study. Given the novelty of the finding, it would have been useful to see independent validation of mitochondrial localization using an alternative antibody or a genetic construct. In summary, whilst it is plausible that HNF is directly binding to mtDNA and regulating mtDNA transcription, further evidence, using a method that doesn't require the antibody used in this study, would make the claim more compelling. Given the interest in such a finding, further independent evidence of direct mtDNA binding would be necessary.3) As a related issue, the argument that loss of dHNF4 specifically impairs mitochondrial metabolism needs further clarification. Loss of dHNF4 could also or instead, cause a reduction in mitochondrial number and mass. To what degree can the consequences of dHNF4 depletion be attributed to a reduction of mitochondrial number or mass as opposed to specific TCA cycle and OXPHOS impairment? Does loss of dHNF4 reduce mitochondrial number, mass or mtDNA copy number?HNF4 tissue and does scavenging of ROS suppress the phenotype?Similarly, the mitochondrial organization is significantly impaired upon loss of HNF4 functions. Do the authors also see an increase in the expression of enzymes such as Drp1 in the RNA-seq? And does the knockdown of DRP1 function result in the rescue of the phenotype? Do ROS levels increase in mutant Related to this issue, the authors should determine if the integrity of the cells that normally express it is compromised in any way such as an incorrect specification/physiology in the absence of HNF4, and please provide a more complete justification for why they think that the cells show a "mitochondrial fragmentation" phenotype.For the RNA-seq data, a systematic enrichment analysis (GO term/KEGG pathway) needs to be carried out on all differentially expressed genes in order to support claims regarding specificity of pathways regulated by dHNF4. In the current version of the manuscript, the authors seem to have cherry-picked genes  One potential caveat with the RNA-seq and ChIP-seq experiments is that they have been carried out in whole flies. dHNF4 is expressed in multiple tissues, and both its functions and targets may be tissue-specific. This is something that will not be captured by whole-fly approaches, and may in fact prevent identification of some targets. For example, the contribution of the IPCs to total fly chromatin or RNA is likely to be negligible.While it is understandable that whole adult flies are used for technical reasons, presumably, each of the tissues in question will respond differently to the loss of HNF function, with different metabolic consequences, so it is unclear how to relate these global analyses of a heterogeneous tissue extract to pathology in a particular tissue (e.g. the IPCs). For example, the metabolomics data shows that HNF deletion increases glucose-derived metabolites, but the RNA-seq data suggests that glycolytic genes are down-regulated. These data are not incorrect, since the experiments and analysis were done with care and competence, but such analyses are easier to interpret if using a homogeneous extract. The ambiguities introduced by a mixture of tissues with mixed metabolic profiles make it difficult to appreciate the importance of the genomic analyses.The Reviewing Editor does not feel that this issue can be fully solved in a reasonable period of time. So perhaps some initial experiments that address aspects of this issue, and attending to this issue in the Discussion, as a caveat will suffice.5) All the mutants characterized in this study involve constitutive dHNF4 loss or downregulation throughout development – either from all tissues or a subset thereof. Consequently, the adult phenotypes described in this manuscript could be adaptive and result from the metabolic alterations caused by dHNF4 loss during larval life . The abundance of genes involved in stress and immunity in the RNA-seq dataset is consistent with this idea. The authors should knockdown dHNF4 specifically in the adult  and test whether some of the key phenotypes  are still apparent. Related to this, the specificity of the Ilp2-Gal4 used in this study  has not been investigated/described in larvae. Why did the authors not use the Ilp2-3-Gal4 generated in the Partridge lab, which is confined to late larva/adult IPCS? This would avoid targeting non-IPC dHNF4 expression throughout development.Also, a related important but minor issue is that often a single RNAi construct is used, the authors are well aware of the possible pitfalls, and they need to be avoided. Additionally, all UAS and Gal4 lines need to be fully defined.6) The authors argue that dHNF4 is required in the fat body and insulin-producing cells of adults to maintain glucose homeostasis by supporting a developmental switch toward OXPHOS and GSIS at the transition to adulthood. Since all experiments in this paper were performed by removing dHNF4 early in development far before the onset of adulthood, it remains a possibility that the phenotypes observed are a consequence of an earlier requirement for dHNF4 during development. To show that dHNF4 is really required in adulthood we would like the authors to remove dHNF4 at the onset of adulthood in the whole organism, fat body and IPCs to assess whether the flies become diabetic and whether survival is affected. As the muscle is also a major contributor to glucose clearance the requirement of dHNF4 in muscles should be assessed as well.Cox5a knock-down does not increase glucose, but CIA30 knock-down does. It is more likely that each complex has differential control of flux in specific tissues or flux through the ETC has differential sensitivity to knock-down of specific complexes, rather than suggesting that there is a greater requirement for CI or CV than CIV per se.7) Based on RNAi to knock-down of specific OXPHOS complexes in the IPC and fat body the authors conclude that there are differential requirements for different ETC complexes in glucose homeostasis. This requires functional validation e.g. on the rate of oxygen consumption. The authors demonstrate that 8) The authors' previous study was consistent with dHNF4 as a nutrient sensor, whereas this manuscript suggests it functions as a developmental switch that converts a cell to a fate that supports responsiveness to glucose. Are dHNF4 expression, activity and/or subcellular localization nutritionally regulated in adult flies? The very low number of ChIP-seq could be explained low dHNF4 activity if a 3% sugar diet was used. RNA-seq experiments used 15% sugar. The diets used for every experiment also need to be clearly stated, and the data analyzed accordingly. Essential revisions:1) A major, most exciting, finding of the paper is that dHNF4 might directly regulate mtDNA transcription. If so, this will change much about how we think mtDNA transcription is regulated. While the authors provide some evidence for this (for example ChIP-seq data), further experiments should be conducted to solidify this finding. In particular, it would be nice if the authors provide further evidence that dHNF4 is indeed targeted to mitochondria and present within the mitochondrial matrix where mtDNA resides. This could be achieved by subcellular fractionation of tissues or cells to show that dHNF4 first associates with the mitochondrial fraction and then further sub-fractionation to determine where within mitochondria it is. Along the same lines, are there any sequences in dHNF4 specifically required to target it to mitochondria? Does it possess a canonical N-terminal mitochondrial targeting sequence? If so, what are the phenotypic consequences of preventing mitochondrial targeting?dHNF4 mutants.  predicted by both MITOPROT and TargetP protein localization programs. Importantly, one of these is dHNF4-B, one of the five protein isoforms encoded by the dHNF4 locus  but not in isolated nuclei. We have conducted these studies with a variety of different antibodies including affinity-purified guinea pig anti-dHNF4 (unpublished from our lab), affinity-purified rat anti-dHNF4 , chicken anti-GFP (Abcam 13970), and mouse anti-FLAG monoclonal (Sigma F3165). We also attempted pre-absorbing the antibodies using purified mitochondria, but this was not sufficient to fully eliminate interference from non-specific bands. Our need for additional approaches to detect dHNF4 protein has been a major motivating factor for developing the new reagents described above that tag all dHNF4 protein isoforms as well as the dHNF4-B isoform. We now include in our paper a discussion of the importance of conducting mitochondrial fractionation studies in the future .We fully agree with the reviewers that mitochondrial fractionation is important to both confirm our model and determine the location of dHNF4 within mitochondria. Indeed, we were doing these experiments while the paper was out for review and have continued our efforts over the past few months. So far, we have conducted six attempts using control animals compared to dHNF4 mutant phenotypes. We now include this information in a new section of our Discussion that is focused on mitochondria, along with our conclusion that, although our data strongly support the model that dHNF4 directly regulates mitochondrial gene expression, they do not prove it. We now present this as a working model. We have revised all parts of the text that previously referred to “direct regulation of mitochondrial gene expression” to be clear that we cannot make this conclusion based on the evidence presented. We also now state that substantial future studies will be needed to provide conclusive evidence in support of our model. We invite the reviewers to read this modified section of the Discussion .The focus of the reviewers on requesting additional evidence for the mitochondrial functions of dHNF4 is our fault, due to a vague discussion of this topic throughout the paper. At no point in our paper did we enumerate the evidence for and against a direct role for dHNF4 in mitochondria, as well as the key experiments that are needed to conclusively prove this model. These include a full functional analysis of the dHNF4-B isoform and its contributions to dHNF4 in adults. We agree that many experiments can and should be done – particularly regarding its roles in mitochondria – and it is our intention to conduct these experiments over the coming years. We have rewritten major portions of the manuscript to be sure that these points are made clear to the reader. We have also added 7 new figures to the revised manuscript, significantly expanding the scope of our study.Finally, we want to point out that, although the reviewers are focused on the mitochondrial functions for dHNF4, this is only one of three major findings in our paper. Importantly, this study provides the first accurate animal model for MODY1 and thus the first insights into the molecular mechanisms that underlie this disorder. In addition, we show that the induction of dHNF4 in early adults provides a regulatory mechanism to explain the classic “U-shaped curve” of mitochondrial oxygen consumption in holometabolous insects – consisting of high respiration rates in larvae, low levels during metamorphosis, and a dramatic increase at the onset of adulthood. Our data supports the model that dHNF4 contributes to establishing the metabolic state of the adult fly by supporting both GSIS and mitochondrial activity. This coupling of developmental progression with metabolic state is a critical regulatory connection that is poorly understood in all animals. In addition, our paper defines a developmental shift in systemic glucose homeostasis and provides new evidence to explain why adult IPCs secrete DILP2 in response to glucose, unlike those of larvae. Finally, it is important to note that this is the first paper to report functional studies of The key evidence that dHNF binds to mtDNA is the ChIP-seq data. It is unclear how to interpret this mtDNA Chiq-seq data for a couple of reasons:A) The presumably high copy number of mtDNA in the sample (perhaps 1000X in excess of nuclear).B) The low signal to noise ratio in the nuclear binding sites. Presumably, most ChIP-seq experiments will detect mtDNA as a background signal. This will usually be discarded, because of the excess signal at specific nuclear DNA binding sites. In this study, in which the signal to noise ratio in nuclear genes is quite low, any background signal caused by the mtDNA might seem more important. A nice control would have been to perform the ChIP-seq in the mutant flies. The mtDNA signal should be much reduced in the mutants (assuming the mtDNA copy number is the same in mutant flies). The reviewers are correct that the abundance of mtDNA can complicate ChIP-seq peak calling for the mitochondrial genome. Indeed, we were aware of this and thus our analysis of the ChIP-seq data was performed using the MACS2 platform, which addresses this potential artifact by accounting for local differences in read depth across the genome (including the increased abundance of mtDNA relative to nuclear DNA). This program performs peak calling by calculating dynamic Poisson distribution parameters  and thus adjusts for biases due to local differences in abundance compared to the rest of the genome. In effect, this results in peak calling relative to protein binding levels within adjacent flanking sequences of DNA. As a result, we detect specific dHNF4 enrichment that is restricted to a portion of the mtDNA control region and, importantly, this enrichment is not observed in the input control. Although the triple-stranded structure of the D-loop in the control region of mammalian mtDNA has been proposed to contribute to possible false-positive ChIP-seq peaks in mammalian datasets , the D-loop structure is not present in Drosophila mtDNA . Furthermore, the peak for dHNF4 on mtDNA represents the 5th strongest enrichment peak in our ChIP-seq dataset out of 68 total. This suggests that its significance is not overemphasized due to low signal, as the high-confidence direct targets for dHNF4 identified from this analysis show robust enrichment for proximal dHNF4 binding. In addition, only select mtDNA genes are underexpressed in dHNF4 mutants while mtDNA copy number is unaffected, suggesting a specific regulatory defect in mitochondrial gene expression. Finally, in two other ChIP-seq studies performed in our lab for other nuclear receptors in adult flies using the same protocol, we have not observed such localized enrichment to this predicted mtDNA promoter region. As a result, we feel that specific binding of dHNF4 to mtDNA is a reasonable conclusion from our studies. We have added the information cited above to our Discussion in an effort to address this important concern for readers .dHNF4 mutant flies as the reviewers request, this is an expensive experiment to conduct as a control for the specificity of dHNF4 binding to mtDNA. Indeed, we know of no comparable control studies in the literature. In addition, the low viability of dHNF4 mutants makes it difficult to get the large quantities of fresh material we need for this experiment (gram quantities of flies). We have attempted to design PCR primers to perform focused ChIP on mtDNA, followed by qPCR, but the sequences within and proximal to the region of dHNF4 binding lack suitable annealing sites due to AT-rich content.Although we agree that it would be ideal to perform a ChIP-seq study in 2) The second piece of evidence supportive of HNF4 being present in the mitochondria is an IF experiment, which uses the same antibody as the ChIP-seq study. Given the novelty of the finding, it would have been useful to see independent validation of mitochondrial localization using an alternative antibody or a genetic construct. In summary, whilst it is plausible that HNF is directly binding to mtDNA and regulating mtDNA transcription, further evidence, using a method that doesn't require the antibody used in this study, would make the claim more compelling. Given the interest in such a finding, further independent evidence of direct mtDNA binding would be necessary. We fully agree with the reviewers that additional evidence is needed to support our detection of dHNF4 in mitochondria by IF. Accordingly, we now include antibody stains of adult fat body from both controls and dHNF4 mutants, conducted in parallel and imaged under identical conditions. This data, included as In addition, we agree that our IF studies would benefit from using a second independent antibody to detect dHNF4. Unfortunately, however, no such reagent exists. In our original work, we raised antibodies against a 317 amino acid region shared by all dHNF4 protein isoforms, using both rats and guinea pigs. Both rodent antibodies were affinity-purified, and both detect similar patterns of cytoplasmic dHNF4 protein. The rat antibody, however, has a significantly higher signal to noise ratio as determined by stains of mutant tissue. We use this antibody for all our published work. In an effort to address the reviewers concerns, we obtained the GFP+FLAG-tagged dHNF4 BAC transgenic line from Bloomington (stock 38649). However, efforts to detect either GFP or FLAG tags using several antibodies  resulted in significant background signal in the cytoplasm from cells lacking this transgene. As stated above, we are currently developing multiple tagged lines with the express purpose of addressing this important issue raised by the reviewers as part of our future studies.3) As a related issue, the argument that loss of dHNF4 specifically impairs mitochondrial metabolism needs further clarification. Loss of dHNF4 could also or instead, cause a reduction in mitochondrial number and mass. To what degree can the consequences of dHNF4 depletion be attributed to a reduction of mitochondrial number or mass as opposed to specific TCA cycle and OXPHOS impairment? Does loss of dHNF4 reduce mitochondrial number, mass or mtDNA copy number? This is an important question. We agree that this is a critical experiment, which is now included as dHNF4 mutants. This new data is presented as dHNF4 mutants display defects in glycolysis and mitochondrial metabolism”. We also show reduced levels of Complex II by western blot, consistent with the reduced expression of the critical Complex II assembly factor gene dSdhaf4 in dHNF4 mutants , in the fat body results in mitochondrial fragmentation and hyperglycemia, similar to loss of dHNF4. This data is now included in dHNF4 mutant cells adjacent to wild-type cells – indicative of reduced mitochondrial membrane potential. This result is consistent with the reduced ATP levels that we detect in dHNF4 mutants and provides a mechanism that can explain the mitochondrial fragmentation, as we now include in the Discussion (in the aforementioned subsection). We have also assayed for changes in ROS as requested by the reviewers. This is shown in dHNF4 mutant phenotypes by feeding the animals N-acetyl-cysteine, which provides effective antioxidant activity in Drosophila. One possible explanation for this is that the ETC complexes that produce ROS are expressed at reduced levels in dHNF4 mutants, while the ROS-scavenging enzymes, such as catalase and SOD, remain unaffected in these animals. We now comment on this in the paper .ed genes  for Drp1Related to this issue, the authors should determine if the integrity of the cells that normally express it is compromised in any way such as an incorrect specification/physiology in the absence of HNF4, and please provide a more complete justification for why they think that the cells show a "mitochondrial fragmentation" phenotype. We see no changes in the size or morphology of any cells or tissues we have examined in dHNF4 mutants, with a particular focus on the IPCs . The mitochondrial fragmentation that we see in dHNF4 mutants or upon dHNF4 RNAi, depicted in CG5599, which encodes a protein with homology to α-ketoglutarate dehydrogenase, or disruption of the ETC by RNAi against CIA30, results in mitochondrial fragmentation that resembles that seen in dHNF4 mutant tissue .t tissue . In addiFor the RNA-seq data, a systematic enrichment analysis (GO term/KEGG pathway) needs to be carried out on all differentially expressed genes in order to support claims regarding specificity of pathways regulated by dHNF4. In the current version of the manuscript, the authors seem to have cherry-picked genes . The next most significant categories primarily represent genes involved in metabolism, with “electron carrier activity” as number 4. For the up-regulated genes, all of the top categories are involved in antibacterial and innate immune responses. We now comment on this analysis in the subsections “dHNF4 regulates nuclear and mitochondrial gene expression“, first paragraph, and “dHNF4 acts through multiple pathways to regulate glucose homeostasis”, fourth paragraph.Many of the above questions are arising, and are important to address, because the central issue has not been convincingly addressed: How does HNF4 regulate mitochondrial gene expression? As outlined in our response to comment #1, we fully agree that significant further studies are needed to definitively demonstrate that dHNF4 directly regulates mitochondrial gene expression and function. We wish to emphasize, however, that our current paper is not intended to focus on this topic. Rather, it represents the first phenotypic study of dHNF4 mutant adults and a functional analysis of the roles for dHNF4 in maintaining carbohydrate homeostasis. In addition to providing compelling evidence for a direct mitochondrial function for dHNF4, our paper provides the first animal model for MODY1, 20 years after the discovery of this genetic association in humans. Our paper also establishes an important role for dHNF4 in contributing to a developmental switch in metabolic state and provides a molecular basis to understand the U-shaped curve of mitochondrial activity. We hope that the reviewers will agree that this work, taken together, is worthy of publication in eLife.4) One potential caveat with the RNA-seq and ChIP-seq experiments is that they have been carried out in whole flies. dHNF4 is expressed in multiple tissues, and both its functions and targets may be tissue-specific. This is something that will not be captured by whole-fly approaches, and may in fact prevent identification of some targets. For example, the contribution of the IPCs to total fly chromatin or RNA is likely to be negligible.While it is understandable that whole adult flies are used for technical reasons, presumably, each of the tissues in question will respond differently to the loss of HNF function, with different metabolic consequences, so it is unclear how to relate these global analyses of a heterogeneous tissue extract to pathology in a particular tissue (e.g. the IPCs). For example, the metabolomics data shows that HNF deletion increases glucose-derived metabolites, but the RNA-seq data suggests that glycolytic genes are down-regulated. These data are not incorrect, since the experiments and analysis were done with care and competence, but such analyses are easier to interpret if using a homogeneous extract. The ambiguities introduced by a mixture of tissues with mixed metabolic profiles make it difficult to appreciate the importance of the genomic analyses. The Reviewing Editor does not feel that this issue can be fully solved in a reasonable period of time. So perhaps some initial experiments that address aspects of this issue, and attending to this issue in the Discussion, as a caveat will suffice. The reviewers make the important point that different tissues can respond in different ways to a loss-of-function mutation. Tissue-specific RNA-seq, ChIP-seq, and GC/MS metabolomic analysis would address this issue, but they require significant technical effort and financial resources. Rather, we have chosen to address this topic through tissue-specific functional studies of select target genes for dHNF4, as depicted in 5) All the mutants characterized in this study involve constitutive dHNF4 loss or downregulation throughout development – either from all tissues or a subset thereof. Consequently, the adult phenotypes described in this manuscript could be adaptive and result from the metabolic alterations caused by dHNF4 loss during larval life . The abundance of genes involved in stress and immunity in the RNA-seq dataset is consistent with this idea. The authors should knockdown dHNF4 specifically in the adult  and test whether some of the key phenotypes  are still apparent.tubGal80ts>dHNF4-RNAi stock and tested this extensively in adults. Unfortunately, however, we could not obtain a sufficient reduction in dHNF4 expression to result in reproducible phenotypes. As an alternative approach, we have used CRISPR/Cas9 to engineer two FRT sites into introns in the endogenous dHNF4 locus in an effort to generate a conditional allele that lacks all dHNF4 functions. We believe that this is a better way to conduct this experiment, allowing us to selectively eliminate dHNF4 function in a temporally and spatially regulated manner. We have successfully used this approach to conduct adult-specific functional studies of another nuclear receptor, dERR, in our lab. We thus feel confident that this approach will allow us to perform a comprehensive adult-specific functional analysis in the future. To address this concern of the reviewers, we now discuss this topic in the Discussion (fifth paragraph of the subsection “dHNF4 acts through multiple pathways to regulate glucose homeostasis”), pointing out that developmental functions for dHNF4 could contribute to the phenotypes we observe.We agree that it is important to selectively remove dHNF4 function from adults and then conduct a complete phenotypic analysis to determine how the resulting phenotypes compare to those of the germline mutant used in our paper. Accordingly, we established the recommended Related to this, the specificity of the Ilp2-Gal4 used in this study  has not been investigated/described in larvae. Why did the authors not use the Ilp2-3-Gal4 generated in the Partridge lab, which is confined to late larva/adult IPCS? This would avoid targeting non-IPC dHNF4 expression throughout development. We agree with the reviewers that restricting RNAi against dHNF4 to the adult IPCs would be ideal to avoid non-specific effects from such constructs being expressed during larval development. The dilp2-GAL4 line we use is recombined into a complex genetic background developed by Seung Kim’s lab to allow for picomolar detection of circulating DILP2 peptide (DILP2HF) upon targeted RNAi in these cells. For details, see our Materials and methods and the paper from the Kim lab . We wanted to ensure that all of our functional studies could be related to the critical phenotype of glucose-stimulated DILP secretion, given that this is a hallmark for MODY1. We thus used this same dilp2-GAL4 driver for all functional studies in our paper. Importantly, this line has been validated to drive expression specifically in adult IPCs . In addition, this line includes a UAS-Dcr transgene in the background, which we have found is critical for efficient knockdown in IPCs. Finally, it is important to note that dHNF4 is not detectable in the IPCs during larval stages   , and we The reviewers ask about a Ilp2-3-GAL4 line generated by the Partridge lab. To our knowledge, however, this line does not exist. Perhaps the reviewers are referring to the Ilp2-GAL4 line generated by the Hafen lab (Ilp215-3-GAL4), which has been misattributed to the Partridge lab in at least one previous publication. The Ilp215-3-GAL4 driver, however, has been reported to initiate expression during the late L3 and thus would not provide the desired adult-specific expression . In addition, there is no data to support this temporal induction since, to our knowledge, a systematic time course study of Ilp215-3-GAL4 expression has not been published.Also, a related important but minor issue is that often a single RNAi construct is used, the authors are well aware of the possible pitfalls, and they need to be avoided. Additionally, all UAS and Gal4 lines need to be fully defined. We thank the reviewers for this suggestion and fully acknowledge the limitations of RNAi, especially when only a single RNAi line is available. We have used multiple RNAi lines whenever possible, in particular for our most critical results, focusing on hyperglycemia and the defects in GSIS. We use two separate lines for dHNF4 RNAi and examine the effects on glucose levels and DILP2 secretion  and within the relevant figure legends.ecretion . We alsox-C RNAi . These d6) The authors argue that dHNF4 is required in the fat body and insulin-producing cells of adults to maintain glucose homeostasis by supporting a developmental switch toward OXPHOS and GSIS at the transition to adulthood. Since all experiments in this paper were performed by removing dHNF4 early in development far before the onset of adulthood, it remains a possibility that the phenotypes observed are a consequence of an earlier requirement for dHNF4 during development. To show that dHNF4 is really required in adulthood we would like the authors to remove dHNF4 at the onset of adulthood in the whole organism, fat body and IPCs to assess whether the flies become diabetic and whether survival is affected. As the muscle is also a major contributor to glucose clearance the requirement of dHNF4 in muscles should be assessed as well. Please see the first section of #5 above for our response to this request to perform adult-specific loss-of-function studies to complement our studies using germline dHNF4 null mutants.7) Based on RNAi to knock-down of specific OXPHOS complexes in the IPC and fat body the authors conclude that there are differential requirements for different ETC complexes in glucose homeostasis. This requires functional validation e.g. on the rate of oxygen consumption. The authors demonstrate that Cox5a knock-down does not increase glucose, but CIA30 knock-down does. It is more likely that each complex has differential control of flux in specific tissues or flux through the ETC has differential sensitivity to knock-down of specific complexes, rather than suggesting that there is a greater requirement for CI or CV than CIV per se. We thank the reviewers for raising this point. We have removed this speculation from the text since we cannot be sure of the effect of each RNAi knockdown on ETC activity, as the reviewers point out.8) The authors' previous study was consistent with dHNF4 as a nutrient sensor, whereas this manuscript suggests it functions as a developmental switch that converts a cell to a fate that supports responsiveness to glucose. Are dHNF4 expression, activity and/or subcellular localization nutritionally regulated in adult flies? The very low number of ChIP-seq could be explained low dHNF4 activity if a 3% sugar diet was used. RNA-seq experiments used 15% sugar. The diets used for every experiment also need to be clearly stated, and the data analyzed accordingly.Drosophila. Needless to say, we wondered the same thing and have conducted a number of nutritional studies, with a particular focus on changes in the subcellular localization of dHNF4. We could not, however, detect any reproducible differences. The levels of dHNF4 mRNA are also unaffected by fasting and starvation, as demonstrated by both larval and adult microarray studies done in our lab, and several studies done by other labs. With regard to the diet used for the ChIP-seq study, we used a normal sugar diet since this experiment was conducted using wild-type  Drosophila adults. We now clearly state the diets for each experiment in the legends and within the Materials and methods section.The reviewers raise the interesting and important possibility that dHNF4 expression, activity and/or subcellular localization might be regulated by nutrition in


Fusion transcripts are found in many tissues and have the potential to create novel functional products. Here, we investigate the genomic sequences around fusion junctions to better understand the transcriptional mechanisms mediating fusion transcription/splicing. We analyzed data from prostate (cancer) cells as previous studies have shown extensively that these cells readily undergo fusion transcription.N = 8) and other (N = 14) clinical prostate tumors with adjacent non-cancer cells, and from the LNCaP prostate cancer cell line that were mock-, androgen- (DHT), and anti-androgen-  treated. In total, 185 fusion transcripts were identified from all RNAseq datasets. The majority (76 %) of these fusion transcripts were ‘read-through chimeras’ derived from adjacent genes in the genome. Characterization of sequences at fusion loci were carried out using a combination of the FusionMap program, custom Perl scripts, and the RNAfold program. Our computational analysis indicated that most fusion junctions (76 %) use the consensus GT-AG intron donor-acceptor splice site, and most fusion transcripts (85 %) maintained the open reading frame. We assessed whether parental genes of fusion transcripts have the potential to form complementary base pairing between parental genes which might bring them into physical proximity. Our computational analysis of sequences flanking fusion junctions at parental loci indicate that these loci have a similar propensity as non-fusion loci to hybridize. The abundance of repetitive sequences at fusion and non-fusion loci was also investigated given that SINE repeats are involved in aberrant gene transcription. We found few instances of repetitive sequences at both fusion and non-fusion junctions. Finally, RT-qPCR was performed on RNA from both clinical prostate tumors and adjacent non-cancer cells (N = 7), and LNCaP cells treated as above to validate the expression of seven fusion transcripts and their respective parental genes. We reveal that fusion transcript expression is similar to the expression of parental genes.We used the FusionMap program to identify high-confidence fusion transcripts from RNAseq data. The RNAseq datasets were from our  contains supplementary material, which is available to authorized users. The latest estimates indicate that the human genome comprises only 20,687 protein coding genes . This nuTMPRSS2 and ERG genes, resulting in ERG transcription being driven by the androgen-responsive TMPRSS2 promoter [TMPRSS2-ERG study by using RNAseq to identify 11 other fusion transcripts that are not produced by chromosomal alterations (hereafter termed transcription-induced transcripts) [SLC45A3-ELK4 are more highly expressed in metastatic prostate cancers compared to benign cells [SLC45A3-ELK4 expression with an unfavorable prostate cancer prognosis, resulting in a growing interest in fusion transcription in the prostate cancer biomarker field [Here, we use prostate (cancer) cells as a model to study fusion transcription given extensive studies that indicate that the prostate readily expresses fusion transcripts. For example, the most studied fusion in prostate cancer is formed between the promoter –8. This promoter , 10. Intpromoter . The Chiscripts) , 13. Latscripts) . Importagn cells . Other sgn cells , 16 haveer field , 18.A recent study of 974 diverse cancer cases has identified 198 fusion transcripts, some of which comprise kinase genes that have great potential to be targeted therapeutically .In this study we characterized the genomic sequences flanking fusion transcripts to better understand the mechanisms that mediate fusion transcription, using prostate (cancer) as a model given the aforementioned extensive studies in this tissue. Indeed, a study in prostate (cancer) cells reveals that the CTCF transcription factor mediates changes in chromosomal conformation that results in the possible formation of at least 56 fusion transcripts {Qin, 2015 #33}. Here, we reveal that the sequences flanking fusion loci are similar to non-fusion loci, indicating that the mechanisms adopted by fusion transcription are likely to be similar to non-fusion transcription and intron splicing.A recent study indicates that the number of protein coding genes in the human genome is similar to lower vertebrates . Thus, tThis resulted in the detection of a total of 185 high-confidence fusion transcripts from Ren and colleagues (14 patients) and our (eight patients) dataset of clinical prostate cancers and their adjacent non-cancer prostate cells, and from our dataset of cultured LNCaP cells treated with androgens (DHT) and anti-androgens   detected in our FusionMap analysis are formed at the exon borders of either one or both parental genes Fig. , and tha, 87 % deIt has been proposed that fusion transcripts might be the result of ‘chromosomal looping’ that brings distal loci together . Thus, aAlu repeats mediate aberrant gene transcription through exonization [We also assessed whether there was a selection of repetitive sequences at fusion loci as it has been found that nization . Sequencnization  to ensurCTBS-GNG5 (2→0), DHRS1-RABGGTA (0→), SIDT2-TAGLN (2→), HARS2-ZMAT2 (→0), NOS1AP-C1orf226 (0→1), and C17orf106-CDK3 (→). Three of these fusion transcripts comprise of genes that are adjacent to each other in the genome , with the other three derived from non-adjacent genes . RT-qPCR was also carried out on the C1QTNF3-AMACR (1→1) as a representative transcript with an interrupted reading frame. Our analysis indicates that all candidate fusion transcripts are either two-fold higher-  or lower-  expressed after androgen or anti-androgen treatment in LNCaP cells  could be readily detected in clinical prostate tumors and/or adjacent non-cancer cells  were found in both our clinical RNAseq dataset comprised of Caucasian men, and in Ren and colleagues dataset which comprised of Han Chinese men [Of the seven candidate fusion transcripts, only four  cells in order to accurately analyze the sequences around fusion junctions in order to better understand fusion transcription and/or splicing. We reveal that fusion splices sites generally use the same nucleotide sequences as non-fusion transcripts, thereby indicating that fusion transcription likely co-opts the same transcriptional processes. However, this hypothesis may only apply to “read-through” chimeras which comprise the majority (76 %) of fusions that were detected in this study. Regardless of the mechanism, the recombination of exons from biologically distinct genes provides an interesting source of genetic variation that warrants further study which will further our understanding of the transcriptional nuances of more evolutionary complex species such as humans.All men have given written informed consent to the Australian Prostate Cancer BioResource to use their tissue and associated medical records for this study, as well as for publication of de-identified patient data. This study is also approved by the Queensland University of Technology Ethics committee (1000001165).FFPE blocks from prostate tumors and their adjacent non-cancer cells were obtained from the Australian Prostate Cancer Bio-Resource tumor bank. Cells were extracted from formalin-fixed and paraffin-embedded sections of micro-dissected benign and malignant prostate tissues. Tissue blocks containing the tumor cells were serially sectioned (20 μm sections), transferred to glass slides, stained with methyl green, and tumor areas were marked and Gleason grades scored by a pathologist . Briefly, ribosome-depleted RNA was paired-end sequenced on the Illumina HiSeq 2500 platform using 100 nt read lengths, and using the Illumina TruSeq strand-specific protocol . On average, 23.3 million reads were sequenced from each sample .Custom Perl scripts matching exon-exon junction co-ordinates from assembled bed and GTF files from a recent large-scale RNAseq study  against 20--upstream gene 2, upstream gene 1--N20--downstream gene 2, downstream gene 1-N20--upstream gene 2, downstream gene 1--N20-- downstream gene 2  were chosen for analysis. A subset (168 of 185) of the 100 nucleotide sequences flanking random exons of random genes from above were also assessed to determine the baseline distribution of repetitive sequences at non-fusion loci. Repetitive sequences were defined by the RepeatMasker library . The prevalence of repetitive DNA near fusion and non-fusion splice sites where determined if the start and end coordinates of repetitive DNA overlapped with the start and end coordinates of the 100 nucleotide flanking sequences.The 100 nucleotide sequences both up- and down-stream of fusion loci from above was also subjected to in The androgen receptor positive, LNCaP prostate cancer cell line was treated with androgen (10 nM DHT) , or therapeutic anti-androgens   for 48 h as described previously . RNA was


Epigenetic adjustments of the chromatin architecture through histone modifications are reactive to the environment and can establish chromatin states which are permissive or repressive to gene expression. Epigenetic regulation of gene expression is cell specific and therefore, it is important to understand its contribution to individual cellular responses in tissues like the airway epithelium which forms the mucosal barrier to the inhaled environment within the lung. The airway epithelium of asthmatics is abnormal with dysregulation of genes such as epidermal growth factor receptor (EGFR), the ΔN isoform of the transcription factor p63 (ΔNp63), and signal transducer and activator of transcription 6 (STAT6), integral to differentiation, proliferation, and inflammation. It is important to establish in diseases like asthma how histone modifications affect tissue responses such as proliferation and differentiation.To characterize the global histone acetylation and methylation status in the epithelium of asthmatic compared to healthy subjects and to identify the impact of these variations on genes involved in epithelial functions.Whole lungs were obtained from healthy and asthmatic subjects (n = 6) from which airway epithelial cells (AECs) were isolated and airway sections were taken for analysis of histone lysine acetylation and methylation by immunohistochemistry. AECs were subjected to chromatin immunoprecipitation (ChIP) using anti-H3K18ac and anti-H3K4me2 antibodies followed by RT-PCR targeting ΔNp63, EGFR, and STAT6. AECs were also treated with TSA and changes in ΔNp63, EGFR, and STAT6 expression were determined.We identified an increase in the acetylation of lysine 18 on histone 3 (H3K18ac) and trimethylation of lysine 9 on histone 3 (H3K9me3) in the airway epithelium of asthmatic compared to healthy subjects. We found increased association of H3K18ac around the transcription start site of ΔNp63, EGFR, and STAT6 in AECs of asthmatics. However, we were unable to modify the expression of these genes with the use of the HDAC inhibitor TSA in healthy subjects.The airway epithelium from asthmatic subjects displays increased acetylation of H3K18 and association of this mark around the transcription start site of ΔNp63, EGFR, and STAT6. These findings suggest a complex interaction between histone modifications and gene regulation in asthma.The online version of this article (doi:10.1186/s12931-015-0254-y) contains supplementary material, which is available to authorized users. The sequence of the human genome is essentially the same in all cells of the body within a specific individual, yet the epigenome differs from tissue to tissue . The DNAThe role of epigenetics in the pathogenesis of asthma remains unclear with evidence of both altered HAT and HDAC activity and expression in the airways of asthmatics –9. In brAbnormal expression of genes involved in repair and inflammation has been reported in the epithelium of asthmatic patients. The expression of epidermal growth factor receptor (EGFR), important for migration, proliferation, and differentiation, all integral components of the repair process, is elevated in the epithelium of childhood-onset and adult asthmatics –18. FurtFurther, as the airway epithelium is the first point of contact with inhaled environmental agents, it is well positioned for environmental factors to influence gene expression and ultimately susceptibility to disease through epigenetic modifications. The impact of altered histone modifications on the regulation of genes associated with repair and inflammation in the epithelium of asthmatic subjects is unclear. We therefore hypothesized that epigenetic changes including histone acetylation and methylation contribute to the abnormal expression of EGFR, ΔNp63, and STAT6 in the epithelium of asthmatic subjects and thus influence the disease pathogenesis. In this study we observed epigenetic differences in the epithelium of asthmatic as compared to healthy subjects. Specifically, we identified an increase in global H3K18ac and H3K9me3 in the airway epithelium of asthmatic subjects. We then found gene-specific alterations to the histone acetylation status of of ΔNp63, EGFR, and STAT6 in asthmatic airway epithelial cells, however, attempting to modulate the expression of these genes through exposure to the HDAC inhibitor TSA was unsuccessful.2 and used at passage 2 for all experiments. Donor demographics for samples used for immunohistochemistry, chromatin immunoprecipitation, and immunoblot are listed in Tables Airway sections and AECs were obtained from non-transplantable human donor lungs from the International Institute for the Advancement of Medicine . The study was approved by the Providence Research Ethics committee, University of British Columbia. AECs from asthmatic and healthy subjects were isolated by protease digestion as previously described , 29. Bri2) and used at passage 4.The human bronchial epithelial 16HBE14o- cell line was kindly provided by the Gruenert laboratory  and mainFormalin fixed, paraffin embedded airway tissue sections were used for immunohistochemical staining of histone modifications. Briefly, 5 μm sections of airway tissue were deparaffinized in xylene and then rehydrated with graded ethanol and processed for antigen retrieval. Primary antibodies listed in Additional file Five images were obtained from each donor airway using the Nikon Eclipse 700 , a 60x objective, and SPOT Advanced software . To quantify staining, color segmentation and point counting of nuclei were performed with ImagePro Plus software . For color segmentation, the same unit area was taken then the epithelium was traced manually for each image. Colors indicating positive staining were set at a threshold and a measurement of this area was obtained followed by a measurement of the total traced area of epithelium. These values were used to calculate % positive area of airway epithelium  as previously described , 32. ForAECs were grown in culture to 80 % confluence before extraction of samples for chromatin immunoprecipitation (ChIP) experiments. ChIP was performed using the EpiTect ChIP Kit (Qiagen) according to the manufacturer’s protocol. Chromatin was sheared using a Sonic Dismembrator Model 100 (Fisher Scientific) cycled at 30 s on, and 30 s off, for a total of 25 min. Sheared chromatin was immunoprecipitated with 2 μg of either H3K18ac , H3K4me2  or IgG (Qiagen) antibody. DNA, including input fraction, was purified using spin columns before undergoing PCR.Purified ChIP DNA was analyzed by quantitative real time PCR for enrichment of target genes. RT2 SYBR Green qPCR Master Mix , 10 μM primers, and ddH20 were mixed with immunoprecipitated or input DNA and analyzed in triplicate by the ViiA7 (Life Technologies). Primers used are listed in Additional file As per manufacturer’s protocol, confirmation of immunoprecipitation specificity was demonstrated by analyzing % Input at genes known to be expressed (positive locus) and repressed (negative locus). Both H3K18ac and H3K4me2 had high % Input at the glyceraldehyde-3-phosphate dehydrogenase locus , and low % Input at the spermidine/spermine N1-acetyltransferase family member 2  and myogenic differentiation 1 loci  indicating antibody specificity  at the following concentrations: 10, 100, 500, and 1000 ng/μl whereas AECs were treated with control media or TSA at 100 ng/μl.Depending on the molecular weight of each protein of interest, a 10-18 % SDS-polyacrylamine gel was used to ensure proper separation of proteins during electrophoresis. Following incubation with the specific primary antibody  of ΔNp63, EGFR, and STAT6 as it has been shown that the acetylation of H3K18 is augmented predominantly around the TSS of active genes and not transcribed regions of genes . As dysrAs shown in Fig. Next, in Fig. Lastly in Fig. As the limited HAT inhibitors available exhibit low cell permeability and potency, we chose to investigate the functionality of acetylated H3K18ac in healthy AECs using the histone deacetylase inhibitor Trichostatin A (TSA). To ensure optimization, we first used the epithelial cell line 16HBE14o- and found that treatment of cells with 100 ng/μl TSA for 24 h resulted in significantly more H3K18 acetylation compared to baseline untreated cells Fig. . We nextThe goal of our study was to identify specific histone modifications that may affect the expression of ΔNp63, EGFR, and STAT6 which are known to be altered in the epithelium of asthmatic subjects. From a panel of 11 histone modifications, we identified an increase in H3K18ac and H3K9me3 within the airway epithelium of asthmatic compared to healthy subjects. As acetylation of histone lysine residues is generally associated with a permissive chromatin structure and gene expression, we directed our focus to H3K18 and found increased association of acetylated H3K18 around the transcription start site of ΔNp63, EGFR, and STAT6 in AECs derived from asthmatics when compared to healthy subjects. These data indicate that global changes in acetylated H3K18 may have important implications for defective epithelial repair in asthma.Recently, Qian et al. identified the necessity of HDAC2 in the regulation of ΔNp63 expression . This meFor epigenetic regulation of EGFR expression, Chou et al. discovered a complex interaction between the histone deacetylase HDAC3, the histone acetyltransferase CBP, and the transcription factor SP1 . SpecifiSTAT6 may interact with histone acetyltransferases and demethylases to facilitate transcriptional activation of STAT6 target genes –44 but tAlthough differential levels of histone modifications may vary depending on specific disease pathology, there is growing evidence to support a mechanistic role for H3K18ac and H3K4me2 in cellular processes including differentiation. Specifically, low global cellular levels of these histone modifications have been identified in studies of prostate , pancreaDue to the challenges with available HAT inhibitors and their use in cell culture, including low cell-permeability, low potency, and a lack of specificity , we focuNumerous epigenetic mechanisms are now being proposed as pharmaceutical targets for various disease pathologies . Such thAlthough we show significant alterations in epithelial gene specific acetylation of H3K18 in asthma, our study does have limitations. Firstly, there is evidence that histone acetylation of inflammatory genes is responsive to corticosteroids , thus fuIn summary, we have identified elevated levels of acetylated lysine 18 on histone 3 in the epithelium of asthmatic as compared to healthy subjects. This does not exclude differences in various histone modifications at the gene-specific level, but it does provide a starting point for a possible epigenetic target for overexpressed genes in the airway epithelium of asthmatics. This is especially relevant as we identified elevated association of H3K18ac at the TSS of three genes which have been demonstrated to be dysregulated in the asthmatic epithelium, specifically ΔNp63, EGFR, and STAT6. However, the HDAC inhibitor TSA did not significantly alter the expression of these genes which may suggest a more complex mechanism of epigenetic control of gene expression in AECs. This study therefore highlights the need for development of more specific therapeutic epigenetic modifying agents to further understand the complexity of epigenetic modulators in asthma.


The inhibition of thyrotropin  by thyroid hormone (T3) and its receptor (TR) is the central mechanism of the hypothalamus-pituitary-thyroid axis. Two transcription factors, GATA2 and Pit-1, determine thyrotroph differentiation and maintain the expression of the β subunit of TSH (TSHβ). We previously reported that T3-dependent repression of the TSHβ gene is mediated by GATA2 but not by the reported negative T3-responsive element (nTRE). In thyrotrophs, T3 also represses mRNA of the type-2 deiodinase (D2) gene, where no nTRE has been identified. Here, the human D2 promoter fused to the CAT or modified Renilla luciferase gene was co-transfected with Pit-1 and/or GATA2 expression plasmids into cell lines including CV1 and thyrotroph-derived TαT1. GATA2 but not Pit-1 activated the D2 promoter. Two GATA responsive elements (GATA-REs) were identified close to cAMP responsive element. The protein kinase A activator, forskolin, synergistically enhanced GATA2-dependent activity. Gel-shift and chromatin immunoprecipitation assays with TαT1 cells indicated that GATA2 binds to these GATA-REs. T3 repressed the GATA2-induced activity of the D2 promoter in the presence of the pituitary-specific TR, TRβ2. The inhibition by T3-bound TRβ2 was dominant over the synergism between GATA2 and forskolin. The D2 promoter is also stimulated by GATA4, the major GATA in cardiomyocytes, and this activity was repressed by T3 in the presence of TRα1. These data indicate that the GATA-induced activity of the D2 promoter is suppressed by T3-bound TRs via a tethering mechanism, as in the case of the TSHβ gene. Negative feedback regulation in the hypothalamus-pituitary-thyroid (H-P-T) axis is the central mechanism for the homeostasis of thyroid function . In thyrD2 activity in thyrotroph is inhibited by T3 mainly at the transcriptional level ,16,17. TBecause no nTRE has been reported in the D2 gene ,28, we wThe firefly luciferase-based reporter gene may be artificially suppressed by T3/TR ,33. This5 cells per well were transfected with 1.0 μg of the hD2-CAT reporter gene, 0.2 μg of pCB6-hPit-1, pcDNA3-mGATA2 and pCMX-rTRβ2 together with 0.9 μg of the β-galactosidase expression vector, pCH111 . The total amount of expression plasmid was adjusted with the empty pCMX vector . After cells were exposed to calcium phosphate/DNA precipitates for 20 h, the medium was replaced with fresh DMEM containing 10% FCS depleted of thyroid hormone  supplemented with protease inhibitors. Chromatin solutions (2 ml) were precleared with 60 μl 50% protein G-Sepharose/salmon sperm DNA slurry , and incubated with 4 μl antiserum against GATA2 overnight at 4°C. Immunoprecipitated proteins were recovered with 20 μl 50% protein G-Sepharose/salmon sperm DNA for 2 h and washed with low-salt buffer . Pellets were washed with high-salt buffer , followed by one wash with LiCl wash solution , and two washes with Tris-EDTA. Protein-DNA complexes were eluted with the elution buffer , and cross-linking was reversed by heating at 65°C for 4 h. DNA was extracted with phenol-chloroform-isoamylalcohol (25:24:1) and precipitated with 20 μg of glycogen as a carrier. Samples were dissolved in 20 μl of TE. Using the SYBR Green I kit and a Light Cycler , the precipitated DNA was quantified by real-time PCR with primers designed to encompass u- and d-GATA-REs in the human D2 promoter . The thermal cycling conditions were 10 min at 95°C, followed by 40 cycles of 10 sec at 95°C for denaturing, 10 sec at 62°C for annealing, and 7 sec at 72°C for extension. PCR signals were analyzed using Light Cycler software version 3.5 (Roche Diagnostics).Approximately 10Each CAT or Renilla luciferase reporter assay was performed in duplicate three or more times, and each result was expressed as the mean ± S.E. Significance was examined by ANOVA and Fisher’s protected least significant difference test using Stat View 4.0 software . A value of P<0.05 was considered significant.Because cDNA sequence of firefly luciferase can mediate artifactual negative regulation by T3 ,33,34, w32P-labeled DNA probe encompassing these two sequences and nuclear extract from CV1 cells transfected with the GATA2 expression plasmid. As shown in To identify the functional GATA-RE, we performed deletion analysis of hD2-CAT . TruncatWe also examined the involvement of u- and d-GATA-REs in the transcriptional control of the D2 gene using the choriocarcinoma-derived cell line, JEG3 , which eBecause the GATA-REs exist in the vicinity of the CRE, which mediates PKA signaling and is critical for expression of the D2 gene in several cells and tissues ,8,16, weBased on the observation that TRβ2 directly interacts with GATA2 , we haveAccording to Christoffolete et al. , T3 reprHere, we showed that the D2 promoter is activated by GATA2, which is one of the determinants for the thyrotroph differentiation , via newIt is known that PKA stimulates the D2 promoter via its CRE ,45. HereAlthough no nTRE has been identified ,28, T3-bIn the context of the TSHβ gene, our co-immunoprecipitation and glutathione-S-transferase pull down assays demonstrated the protein-protein interaction of TRβ2 DBD with GATA2 Zn-finger domain . GATA2-TThe physiological relevance of T3-induced repression of D2 in thyrotrophs has not been fully clarified ,62,63. T


OPN mRNA and its promoter methylation changes by the 5-aza-dc treatment in fibroblast cell and promoter assay. Aberrant methylation of porcine OPN was frequently found in different tissues of somatic nuclear transferred cloning pigs, and bisulfite sequence data suggested that the OPN promoter region −2615 to −2239 nucleotides (nt) may be a crucial regulation DNA element. In pig ear fibroblast cell culture study, the demethylation of OPN promoter was found in dose-dependent response of 5-aza-dc treatment and followed the OPN mRNA reexpression. In cloned pig study, discrepant expression pattern was identified in several cloned pig tissues, especially in brain, heart, and ear. Promoter assay data revealed that four methylated CpG sites presenting in the −2615 to −2239 nt region cause significant downregulation of OPN promoter activity. These data suggested that methylation in the OPN promoter plays a crucial role in the regulation of OPN expression that we found in cloned pigs genome.Cloned animals usually exhibited many defects in physical characteristics or aberrant epigenetic reprogramming, especially in some important organ development. Osteoponin (OPN) is an extracellular-matrix protein involved in heart and bone development and diseases. In this study, we investigated the correlation between  Nowadays, many of pathogenesis of diseases have been determined –3. MethyOPN is an extracellular matrix protein and hydrophilic glycoprotein identified firstly in the bone as a sialoprotein. It contains a thrombin and transglutaminase cutting site, and the molecular weight is about 25 kDa to 75 kDa; in pig, the molecular is about 67 kDa; it contains numerous isoforms -ATP was added, and the mixtures were incubated at room temperature for 30 min. The reaction mixtures were resolved on 6% polyacrylamide gels. The gels were dried and subjected to PhosphorImager analysis using a Typhoon system and ImageQuant TL software .Nuclear extracts were prepared from HEK293T cells. Two probes were designed for methylation binding activity test. Two probes containing either 6–8 CpG sites or 13th CpG site in the −2615 to −2239 of the OPN promoter area and provides the binding domain for RNA-polymerase II initial binding transcription factor (TFIIB) in this study. Therefore, we first utilized the Z-DOCK program to simulate the structures of c-Jun and TFIIB. After that, we further used molecular dynamics (MD) to validate the stability of c-Jun and TFIIB complex under the GROMACS 4.5.5 program [The molecular docking was then further analyzed for proving the further mechanism of our findings; we further surveyed the interaction of AP1 (c-Jun) and TFIIB by computational biology. The AP1 (c-Jun) is possible higher spot for hypermethylation in program  with chaThe Particle mesh Ewald (PME) is also used for calculate the coulomb type of electrostatics. The Van der Waals (VDW) interactions are set as 1.4 nm cut-off distance for nonbound interaction. The first step is set on the 5,000 cycle steps performed in the manner of Steepest Descent algorithm for energy minimization. And then, equilibration was performed with a time period of 1 ns for position restraints set under the constant temperature dynamics (NVT type) conditions. The third step is calculating the production run for 5000 ps under constant pressure and temperature dynamics (NPT type). All the MD systems are set by 310 K temperature during all simulation times. MD frames data were saved every 20 ps for all production runs.First we survey the stability of all atoms performed by using the GROMACS 4.5.5 software though the commands of g_rms and g_gyrate to calculate root mean square deviation (RMSD) and radius of gyration (Rg), respectively. Secondly, we calculate the total energy for all the systems by the command of g_energy. Thirdly, we further calculate root mean squared fluctuation (RMSF) for each protein residue by commands of g_rmsf. Fourthly, the distance between c-Jun and TFIIB and movement analysis are calculated by the g_dist program. Fifthly, the migration of dock protein (c-Jun and TFIIB) is presented by mean square displacement (MSD) under the command of g_msd module in GROMACS during all the simulation times. Sixthly, the g_cluster program is selected for further calculation of the representative structure from all MD frames, and the representative structure is taken for further snapshot analysis. We also employed DSSP analysis and matrices of the smallest distances between each residue to investigate the stability of the protein structure. The principle component analysis (PCA) is then applied to observe the protein motion changes during all the MD frames. Finally, in order to observe the compactness between c-Jun and TFIIB, Caver 3.0 software  was used OPN promoter region. One putative CpG island was found  by MethPrimer program.There are dense CpG sites existing in the front of the OPN mRNA expression was investigated in the WT pig tissues and cloned pig tissues. Data showed the various expression levels in different tissues. Particularly, Copy1 brain overexpressed the OPN and Copy2 ear with no expression of OPN relative to its wild-type tissue, respectively . This is thought that the methylation of OPN promoter in the aforementioned tissues may be involved with OPN transcript regulation mechanism.In order to realize whether the methylatedo 2.0 μM . The res OPN promoter is affected by methylation in the CpG site, bisulfite sequencing was performed to dissect the methylation status of CpG sites in the OPN promoter. In the brain tissue, bisulfite sequencing of Copy5 and Copy1 brain exhibited the saturated status in their methylated region while WT brain exhibited fragmentary methylated CpG sites. The 18.06% methylation percentage of Copy5 brain was more than the WT brain, 14.25%  were used to prove the hypothesis  sequence frequently appeared in our molecular laboratory study. Then we further validated that the c-Jun methylation will cease the further mRNA production by inhibiting the binding of RNA-polymerase II initiation factor TFIIB. We do the further computational modelling for mechanism survey between the c-Jun and TFIIB. By the Z-DOCK analysis, we found the c-Jun and TFIIB could combine tightly .Protein complex RMSD analysis proved that the c-Jun and TFIIB were stable from 3000 ps to 5000 ps. In addition, we found the TFIIB are easier to be stable during the molecular dynamics . We alsoTo analyze the flexibility of residues on protein structure, the RMSF calculation was used to observe the flexibility of each residue;  OPN transcription started from TFIIB binding to chain A of c-Jun.The hydrophobic area was then calculated by SASA in  OPN was analyzed in transcription factor binding sites except the region −2615 to −2239. Interestingly, this region of porcine OPN promoter is rich in CpG sites compared to human, mouse, and bovine genome. Sakata also proved that OPN promoter transcription activity is regulated by some specific DNA modification mechanism of rearrangement of chromatin structure [Previous study has shown that DNA element (GGGTCATATGGTTCA) located in osteopontin promoter −2245 to −2259 nt can be regulated by vitamin D3 . This DN OPN expression or incompletely epigenetic modification in OPN promoter , heart (11.5% downregulation), and ear (18.03% downregulation)  . OPN mRNc stages . The ovefarction , 30. Sil OPN gene expression may be affected by treatment of TSA (a histone deacetylase inhibitor). The results applied that OPN promoter could be regulated by epigenetic mechanism [ OPN methylation profile after 5-aza-dc treatment. The results indicated that mRNA expression of OPN is directly affected by adding methyltransferase inhibitor 5-aza-dc  were used for analysis. Obvious downregulation in methylated −2615-luc (HpaII and HhaI methyltransferase) was observed. Compared to the deletion of this control region (~390 nt) in front of OPN promoter, the decreasing level of promoter activity is not as obvious as −2615 M-luc construct  was identified as a methylated insulator region in human blastoma cell line [ OPN promoter showed that CpG 1st binding site contained the specific binding site sequence. While in our interesting DNA regulation region range from −2615 to −2239 nt of OPN promoter also exhibited little block access in the competition of probe. It is suggested that CpG 1st and CpG 13th play an important role in methylation controlled mechanism to regulate gene expression. We finally utilize Z-dock program [ OPN promoter region and cause AP1 to be hypermethylated consequently ceasing the OPN mRNA expression [Our data revealed that DNA methylation of CpG sites inell line . Analyze program  to analy program  to see ipression . OPN promoter binding sites is c-Jun. The chain A of c-Jun could be encompassed more tightly by inward rotational structure change of TFIIB during the MD process  methylation will affect transcription binding and could be the treatment for genetic developing errors in the future.Further mechanical studies by the computational biology also pointed out that the DNA sequence for hypermethylation of process . Therefo OPN gene was frequently found in different tissues of somatic nuclear transferred cloning pigs and bisulfite sequence data suggested that the OPN promoter region of −2615 to −2239 nt may be a crucial regulation DNA element. In pig ear fibroblast cell culture study, the demethylation of OPN promoter was found in dose-dependent response of 5-aza-dc treatment and followed the OPN mRNA reexpression. In cloned pig study, discrepant expression pattern was identified in several cloned pig tissues, especially in brain (99.75% up-regulation), heart (11.5% down-regulation), and ear (18.03% downregulation). Promoter assay data revealed that four methylated CpG sites presenting in the −2615 to −2239 nt region cause significant downregulation (approximately 75%) of OPN promoter activity (P < 0.001). EMSA data also suggested that CpG 13th and 1st sites showed methylation noncompetition phenomenon which had influence on binding with transcription factor.In conclusion, aberrant methylation of porcine