Neural cell fate acquisition is mediated by transcription factors expressed in nascent neuroectoderm, including Geminin and members of the Zic transcription factor family. However, regulatory networks through which this occurs are not well defined. Here, we identified Geminin-associated chromatin locations in embryonic stem cells and Geminin- and Zic1-associated locations during neural fate acquisition at a genome-wide level. We determined how Geminin deficiency affected histone acetylation at gene promoters during this process. We integrated these data to demonstrate that Geminin associates with and promotes histone acetylation at neurodevelopmental genes, while Geminin and Zic1 bind a shared gene subset. Geminin- and Zic1-associated genes exhibit embryonic nervous system-enriched expression and encode other regulators of neural development. Both Geminin and Zic1-associated peaks are enriched for Zic1 consensus binding motifs, while Zic1-bound peaks are also enriched for Sox3 motifs, suggesting co-regulatory potential. Accordingly, we found that Geminin and Zic1 could cooperatively activate the expression of several shared targets encoding transcription factors that control neurogenesis, neural plate patterning, and neuronal differentiation. We used these data to construct gene regulatory networks underlying neural fate acquisition. Establishment of this molecular program in nascent neuroectoderm directly links early neural cell fate acquisition with regulatory control of later neurodevelopment. Formation of the complex vertebrate nervous system is initiated when pluripotent cells of the early embryo acquire a neural fate. This process accompanies induction and patterning of the three germ layers during gastrulation. In the mammalian embryo, uncommitted epiblast cells move through the primitive streak and develop into mesodermal and endodermal derivatives. Anterior epiblast cells that do not enter the primitive streak instead develop into ectoderm, some of which is induced to form the future neural plate13in vivo, blockade of growth factor signaling initiates neuroectodermal fate acquisition of ES cells345689Mouse embryonic stem (ES) cells, derived from the inner cell mass of the preimplantation blastocyst embryo, provide a useful model for understanding neuroectodermal cell fate acquisition at the molecular level. As occurs The nTFs include several Zic zinc-finger and SoxB1 class transcription factors891011128910141516891019898910111221232425Geminin plays essential roles in early embryogenesis. In Xenopus, Gmnn promotes neuroectoderm formation at the expense of non-neural tissues 1429in vitro when recombinant Gmnn is combined with ES nuclear extract and chromatinGeminin can regulate gene expression through direct interactions with both chromatin modifying complexes and homeodomain transcription factors151617in vivo and Gmnn and Zic1 singly or cooperatively promote the expression of genes controlling later neural development. We used the shared set of Gmnn- and Zic1-associated transcription factors to construct gene regulatory networks underlying neural cell fate acquisition. This work defines unique and shared targets of Gmnn and Zic1, which act with other nTFs to link transcriptional control of early neural fate acquisition with activation of gene expression programs driving several aspects of later neural development.Here, we endeavored to understand how Geminin controls neural cell fate through interactions with chromatin and used these data to define gene regulatory networks underlying neural fate acquisition. We used chromatin immunoprecipitation (ChIP) and next generation sequencing (ChIP-seq) to define Gmnn-associated chromatin locations in ES cells and ES-derived neuroectoderm (NE) at a genome-wide level. We compared these Gmnn-associated gene profiles with effects of Gmnn deficiency on histone acetylation of promoters during neural fate acquisition. During this work, we found that Gmnn associates with the gene encoding Zic1 both in ES cells and in NE. Therefore, we also defined Zic1-associated genes in NE by ChIP-seq and compared these data. Gmnn and Zic1 preferentially bind genes that have embryonic central nervous system-enriched expression Examination of Geminin and Zic1 expression across embryonic and adult tissues in the mouse revealed strong expression in embryonic central nervous system (CNS) tissue . Gmnn exTo define Geminin- and Zic1-associated chromatin regions during neural fate acquisition at a genomewide level, we initially performed ChIP followed by microarray analysis (ChIP-chip) to assess Gmnn promoter occupancy in ES cells and ES cell-derived neuroectoderm. As available Gmnn and Zic1 polyclonal antibodies showed variable, lot-dependent performance in ChIP applications, we also used CRISPR-mediated genome engineering for knock-in of a Ty1 epitope tag at the endogenous Gmnn or Zic1 locus. This enabled genome-wide analysis of Gmnn- and Zic-associated chromatin regions by ChIP-seq. Clonal mouse ES lines were generated that expressed amino-terminal tagged Ty1-Gmnn or Ty1-Zic1, under control of each endogenous locus and its regulatory sequences. ES clones with the correct targeting events were selected by genomic DNA and mRNA analyses  and Ty1-Two independent, clonal ES lines each for Ty1-Geminin and Ty1-Zic1 were used to perform ChIP-seq analysis for Gmnn in ES cells and for Gmnn and Zic1 in NE. ChIP-seq read depth and Gmnn- and Zic1-associated peaks and nearest transcription start sites are in the We visualized the ChIP-seq tracks for Geminin and Zic1 in NE  and usedin vitro, as described above. Bound peaks were mapped to the nearest transcription start sites to define gene sets associated with Gmnn in ES and NE. Interestingly, one quarter  of the Gmnn associated genes in ES cells were still associated with Gmnn in NE  or adult cortex. Gmnn-associated genes in both ES and in NE exhibited CNS-enriched expression . We likeTo determine biological functions of these Geminin associated genes, we used MetaCore (Thomson Reuters) to analyze enriched gene ontology (GO) terms. Gmnn-associated genes in both ES cells and in NE were enriched for genes involved in development and nervous system development . SubsetsOur previous work suggested that Geminin over-expression promoted, while Geminin knockdown inhibited, histone acetylation at neural gene promotersin vitro. Gmnn overexpression during three days of ES-NE fate acquisition further increased expression levels of each gene tested  and in ES-derived neuroectoderm. We found that chromatin association of Gmnn changed during the ES-NE transition, but that most Gmnn-associated genes in both contexts exhibited embryonic CNS-enriched expression. These Gmnn-associated genes were preferentially enriched for GO terms associated with neural development, neurogenesis, and neuronal differentiation. Therefore, a major aspect of Gmnn’s role in regulating early cell fate acquisition is to associate with chromatin at neural genes and to promote expression of a gene program controlling neurodevelopment.in vitro model also exhibit diminished expression in the Gmnn-deficient E10.5 neural tube in vivo. Among Gmnn bound and regulated genes shown in in vivo include transcription factors with roles in neurodevelopment  and other genes that control neuronal development or function . Gmnn’s direct association with and ability to promote the acetylation of these genes may represent an early event during neural cell fate acquisition both in vivo and in vitro, activating regulatory networks that promote neural fate acquisition and control later neural development.To define key Geminin targets that may account for its ability to promote neural fate, we intersected genes that are Geminin-associated in NE, undergo Geminin-dependent histone acetylation, and have embryonic CNS-enriched expression. Gmnn deficiency in a conditional mouse model causes neural tube defects through diminished expression of genes involved in neural specification, neurogenesis, neuronal differentiation and regional neural plate patterning (GSE42052)Geminin does not contain a DNA binding domain. Therefore, an interesting question that our genome-wide data raises is how Gmnn associates with chromatin at neurodevelopmental genes to promote their expression. Gmnn interacts both with chromatin modifying complexes (SWI/SNF and Polycomb) and with homeodomain transcription factors, which could mediate Gmnn’s recruitment to specific chromatin locations in a temporal and cell type specific manner151617Here, we defined the promoters subjected to this regulation throughout the genome by defining profiles of H3K9 acetylation with versus without Gmnn knockdown during neural cell fate acquisition. About one quarter of the Gmnn-associated genes in NE also underwent Gmnn-dependent histone acetylation. Most of these genes exhibit CNS-enriched expression and are involved in neural development.in vitro biochemical reconstitution experiments. In the latter work, recombinant Gmnn protein could enhance histone acetylation and chromatin accessibility rapidly in reconstituted in vitro assays. However, this required both use of a chromatin substrate and addition of ES nuclear extract to the reactionIn prior work, we tested mechanisms through which Geminin could influence chromatin acetylation and accessibilityThe finding that Geminin associates with the Zic1 gene in both ES cells and in NE was of particular interest, as several findings suggest a functional relationship between Gmnn and Zic1 during neural cell fate acquisition. Similar to Gmnn’s ability to promote neural fate acquisition of ES cells, Zic1 is required for specification of ES cells as neuronal precursor cells in response to retinoic acid2940Our work here suggests that these common Geminin and Zic1 activities may reflect direct association with and regulation of some shared target genes. We defined regulatory relationships between Gmnn and Zic1 during neural fate acquisition, as Gmnn associates with distinct peaks at the Zic1 gene in ES cells and in NE, while Gmnn over-expression promotes Zic1 expression. Both Zic1- and Gmnn-associated locations in NE were also enriched for Zic1 consensus binding sequence motifs, suggesting that Gmnn-Zic1 functional cooperation could regulate sets of genes involved in neural fate acquisition. While Zic1 targets in post-natal cerebellar development had been determined42Association of Geminin and Zic1 at a common set of genes defines some transcriptional targets that may mediate their shared activities in neural progenitor specification and maintenance. We focused on the subset of Gmnn and Zic1 associated genes that exhibit CNS-enriched expression and encode transcriptional and epigenetic regulatory activities . These iIn addition to Geminin and Zic1, several other transcriptional regulatory activities promote neural fate acquisition and neural progenitor maintenance. Notably, the SoxB1 family transcription factors Sox2 and Sox3, like Gmnn and Zic1, are broadly expressed in nascent neuroectoderm from gastrulation. These nTFs are also involved in neural progenitor formation and maintenance, while another SoxB1 TF, Sox11, acts to promote neuronal differentiation. Genome-wide characterization of their binding sites has defined sequential occupancy of some of the same genomic locations by Sox2, Sox3 and Sox11 in ES-derived neural progenitor cellsCommon transcription factor targets associated with both Geminin and Zic1 in this GRN include: Ascl1, Sox11, Sox13, Irx3, Pax7, Otx1, Hes1, Lhx5, Pou4f1, and Barhl2 and we demonstrated that cooperative over-expression of Gmnn and Zic1 could increase expression levels of several of these transcription factors during neural fate acquisition, while over-expression of either Gmnn or Zic1 alone was not sufficient to induce their expression. Targets of Zic1, Gmnn, and Sox2 include Ascl1, Creb5, Otx1, Mbd2, Phf21a, Smarca2, Bcl6, Sox11, Scrt1 and Meis1, while genes associated with Sox2 and Gmnn also include other transcription factors such as Otx2, which acts in nascent neuroectoderm to promote neural and repress alternate mesodermal cell fateThis GRN incorporates relationships between transcription factors that control early acquisition of neural cell fate and those that regulate later aspects of neural development. Some genes are highly interconnected in the GRN, being associated with multiple nTFs and encoding transcription factors essential for later neural development. These may constitute central mediators of the early transcriptional response to establish neural cell fate. Their regulation by multiple nTFs during neural fate acquisition may link events occurring at the onset of neural cell fate acquisition to later neurogenesis, regional neural plate patterning, and neural progenitor maintenance and differentiation, coordinating and executing transcriptional programs that bridge the earliest and subsequent events of neural development.All mouse embryonic stem cell lines used are clonal derivatives of ES-E14TG2a (ATCC #CRL-1821). H3K9ac ChIP was performed in a clonal derivative of A2loxC ATC GG) and Gmnn: T CTC AGT ATG AAG CAG AAG CAA G.To generate clonal epitope tag knock-in lines, ES cells were transduced with a lentiviral vector for co-expression of the “nickase” form of Cas9 (Addgene pX335-U6-Chimeric_BB-Cbh-hSpCas9n(D18A) with addition of a hPGK-PuroR selection cassette) and guide RNA sequences directed against Gmnn (T CTC AGT ATG AAG CAG AAG CAG G) or Zic1 (GGA CCC CAG TAT CCC GCG ATT GG) and also with a donor plasmid to stimulate homology-directed repair after Cas9 cleavage. Donor plasmids contained either Gmnn or Zic1 sequence homology arms with a 3XTy1 tag and glycine linker sequence introduced in frame at the amino-terminus of Gmnn or Zic1. Silent mutations were introduced into these donor sequences (underlined) corresponding to the guide RNA cleavage sites in Gmnn or Zic1, to prevent Cas9-mediated cleavage of the donor plasmid sequences: Zic1: GGA CCC CAG TAT CCC GCGenomic DNA and mRNA obtained from clonal ES lines were screened for the correct targeting event using primers to detect the Ty1-Zic1 junction in genomic DNA (Ty1 Forward: gac gcc gaa gtc cat aca aa and Reverse3-Zic1: gcg cct cga ggt cct aca tta att tcc ata cct g) or to detect the Ty1-Gmnn junction in mRNA (Ty1 forward and R-Gmnn: tct gga cca cag ctt gaa gt) and expression of Ty1 epitope tagged Gmnn and Zic1 was detected in ES cells and ES-derived neuroectoderm by western blotting and immunocytochemistry.−4 M 2-mercaptoethanol (Sigma) and 103 units per ml of leukemia inhibitory factor . Monolayer neural differentiation of ES cells was done as previously described5/cm2 for one day on 0.1% gelatin-coated tissue culture dishes. After 24 hours, cells were plated onto 0.1% gelatin-coated tissue culture dishes at low density (1 × 104 cells/cm2) in N2B27 medium and cultured for 3 days.ES lines were routinely propagated on feeder cells  in DMEM (Invitrogen) supplemented with 15% fetal calf serum (Hyclone), 1 mM sodium pyruvate, 1 mM Non-Essential amino acids, 1mM L-Glutamine (Invitrogen), 10Full length murine Geminin (MR202178) and Zic1(MR207138) cDNAs in expression vectors were purchased from Origene. For transfection and selection, feeder subtracted ES cells were transfected with 5 μg of DNA using Lipofectamine 2000 (Invitrogen) following the manufacturer’s protocol. 6 hrs after transfection the medium was changed to fresh ES medium and 24 hours after transfection the cells were replated on gelatin in ES media with LIF. 24 hrs after replating the cells were selected for stable transfectants using 300 μg/ml G418 for 6 days.Total RNA was extracted using Clontech Nucleospin RNA extraction kit (#740955.250) using the manufacturer’s protocol. cDNA was synthesized using the Bio Rad iScript Reverse Transcriptase Supermix (#170-8841) followed by quantitative RT-PCR analysis using the Fast SYBR green mix from Applied Biosystems (#4385612) and gene-specific primer sequences shown in 6 ES cells was fixed in 1% Formaldehyde (Sigma) in DMEM +5% FBS and incubated with 5 μg of each antibody and Protein G Dynabeads (Invitrogen) as per the manufacturers instructions. For Ty1 ChIP, 1% SDS was also included in the shearing buffer. Antibodies used for ChIP were Gmnn , H3K9ac , and Ty1 (Diagenode C15200054). After washing , elution and cross-link reversal, DNA from each ChIP sample and the corresponding input sample was purified and analyzed further using qPCR as follows: each ChIP sample and a range of dilutions of the corresponding input sample (0.01–5% input) were quantitatively analyzed with gene specific primers using the 7500 FAST Real-time PCR Detection System (ABI) and SYBR Advantage qPCR Premix (Clontech). ChIP qPCR primers are in Quantitative ChIP was done with modifications to a standard protocol (Upstate/Millipore) as follows. For each ChIP reaction, sheared chromatin  from 5 × 10For ChIP-seq sample preparation, two independent biological replicates per clone and two clones for each sample type were sequenced after ChIP for Ty1-Gmnn in ES cells and for Ty1-Gmnn and Zic1 in ES-derived neuroectoderm after 3 days of N2B27 monolayer culture. Control samples sequenced for both ES cells and ES-derived neuroectoderm included input and Ty1 ChIP performed in the E14TG2a ES line that does not express a Ty1-tagged fusion protein; subtraction of these controls after sequencing was used to define specific peaks of Gmnn and Zic1 ChIP enrichment. Samples underwent linear amplification using the SeqPlex whole genome amplification kit (Sigma). Illumina library preparation for sequencing was performed by the Genome Technology Access Center at Washington University School of Medicine and sequencing was performed on the HiSeq 2500 (single end reads).ChIP-chip hybridization to tiled promoter arrays was performed on three independent biological replicates for the following sample types: Gmnn ChIP in ES cells and ES-derived neuroectoderm after 3 days of N2B27 monolayer culture, using the Gmnn N18 antibody (Santa Cruz sc-8449), and H3K9ac  ChIP in ES-derived neuroectoderm with or without inducible Gmnn knockdown by addition of 500ng Dox to ES cells engineered for Dox-inducible Gmnn knockdownIn our present study, high stringency conditions were used for ChIP-seq with the Ty1-tagged Gmnn and Zic1 proteins, since Ty1 is not endogenously expressed in ES cells (see Methods). This resulted in relatively fewer peaks for both data sets, in comparisons with other published ChIP-seq datasets. Furthermore, there was limited overlap with chromatin-associated peaks obtained for Gmnn using the ChIP-chip and ChIP-seq approaches. This may reflect the lower levels of Ty1-Gmnn expression relative to endogenous Gmnn  or more Raw read (SRA) of RNA-seq data was downloaded from the mouse ENCODE projectMotif enrichment analysis in Zic1 and Gmnn binding peaks was performed using the HOMER toolhttp://fantom.gsc.riken.jp/data/)CpG islands and refGene features  were all downloaded from the UCSC Genome Browserwhere nFeature is the number of ChIP peaks that contain genomic annotation features; nPeak is the total identified ChIP peaks; N.Feature is the number of each genomic annotation feature; N.Background is the number of windows in the mouse genome (mm9), which is calculated based on averaged length of each feature .Accession codes: ChIP-seq and ChIP-chip data sets were deposited into GEO as GSE81595 (Superseries of datasets GSE77246 and GSE81450).How to cite this article: Sankar, S. et al. Gene regulatory networks in neural cell fate acquisition from genome-wide chromatin association of Geminin and Zic1. Sci. Rep.6, 37412; doi: 10.1038/srep37412 (2016).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


We investigated the relationship among ERK signaling, histone modifications, and transcription factor activity, focusing on the ERK-regulated ternary complex factor family of SRF partner proteins. In MEFs, activation of ERK by TPA stimulation induced a common pattern of H3K9acS10ph, H4K16ac, H3K27ac, H3K9acK14ac, and H3K4me3 at hundreds of transcription start site (TSS) regions and remote regulatory sites. The magnitude of the increase in histone modification correlated well with changes in transcription. H3K9acS10ph preceded the other modifications. Most induced changes were TCF dependent, but TCF-independent TSSs exhibited the same hierarchy, indicating that it reflects gene activation per se. Studies with TCF Elk-1 mutants showed that TCF-dependent ERK-induced histone modifications required Elk-1 to be phosphorylated and competent to activate transcription. Analysis of direct TCF-SRF target genes and chromatin modifiers confirmed this and showed that H3S10ph required only Elk-1 phosphorylation. Induction of histone modifications following ERK stimulation is thus directed by transcription factor activation and transcription.  •TPA-driven ERK activation induces a common pattern of histone modifications at TSSs•Most ERK-induced histone modifications are dependent on TCF family of SRF cofactors•At these TSSs, induced histone modifications require ERK-dependent TCF phosphorylation•TCF-dependent histone modifications require TCF to recruit the transcription machinery In MEFs, TPA-induced ERK activation induces a common pattern of histone modifications at more than 2,000 TSSs. Modifications at most TSSs are dependent on the TCF family of ERK-regulated SRF cofactors. At these TSSs, induced modifications are dependent both on phosphorylation of TCF and on its ability to recruit the transcriptional machinery. Specific patterns of chromatin modification correlate with gene activation or silencing and can be used to identify gene regulatory elements such as promoters and enhancers . ModificPhosphorylation of H3 at serine 10 and 28, first seen to be associated with mitogen- and stress-induced gene activation , accompaThe transcription factor SRF (serum response factor), which controls many immediate-early genes, provides a system to investigate this issue. SRF associates with two families of signal-regulated cofactors, the ERK-regulated ternary complex factors (TCFs) Elk-1, SAP-1, and NET , and the Rho-actin-controlled Myocardin-related transcription factors MRTF-A and MRTF-B (MKL1 and MKL2 in mouse) to regulate proliferation, cell growth, and cytoskeletal dynamics . StimulaHere we investigated the role of the TCFs in the establishment of ERK-regulated histone modifications at transcription start sites (TSSs), which were identified without prior reference to transcriptional status. TPA stimulation induced an ordered cascade of modifications at these TSSs, whose magnitude correlated well with the increase in transcription. Signal-induced changes at most TSSs were TCF dependent, but similar patterns occurred both at direct TCF-SRF genomic targets and TCF-independent TSSs. Induction of TCF-dependent histone modifications required phosphorylation of the TCF activation domain and its competence to recruit the transcriptional machinery. Analysis of candidate modifiers required for the activation of direct TCF-SRF target TSSs showed that phosphorylation of H3S10 is an early transcription-independent step in the activation process.We sought to identify chromatin changes induced by ERK signaling in mouse embryonic fibroblasts (MEFs) in an unbiased manner, without pre-selecting sites for analysis according to transcriptional activity. Histone modifications at RefSeq TSS regions were quantified genome-wide by chromatin immunoprecipitation sequencing (ChIP-seq) in resting and TPA-stimulated cells, and those TSSs exhibiting significant change were identified using DESeq  Table S. The anaGSE75002). Hierarchical cluster analysis of the five marks suggested that changes in the different marks exhibit a nested relationship, placing them in the order H3K9acS10ph, H4K16ac, H3K27ac, H3K9acK14ac, and H3K4me3, with two clear subsets comprising the first two and the latter three , defined as the average difference between the change in a given modification (the “leading mark”) and that observed for any other mark see . ConsideGSE75667)  data set measuring changes in RNA synthesis conducted in parallel with the histone modification analysis (GEO: SE75667) . First, SE75667) D showed SE75667) E and S2CSE75667) . As the SE75667) F.2 values ranging from 0.07 (H3K9acS10ph) to 0.28 (H3K4me3)   A. We als× 10−16) B and S3CElk1−/−, Elk3δ/δ, and Elk4−/− TKO [triple-knockout] MEFs)  . A similt] MEFs) . TPA-indt] MEFs) , and mett] MEFs) A. We next] MEFs) B, top. Mt] MEFs) C.nonA, which cannot be phosphorylated, or Elk-1ΔFW, which can be phosphorylated but cannot recruit Mediator    . This apSE75667) A. The inSE75667) B. Again,× 10−16) C and S3D× 10−16) D. Taken Signal-induced chromatin modification at sites remote from TSSs is also associated with enhancer activation and enhancer RNA (eRNA) synthesis , so we aOne potential explanation for the nested hierarchy of changes in histone modification upon TPA stimulation observed above is that it at least in part reflects differences in the temporal order of their establishment. We analyzed the time course of TPA-induced H3 phosphoacetylation and H3K4 trimethylation, across the whole TSS population. In addition, we examined H3S10 phosphorylation directly, using an H3S10ph-specific antibody whose cognate epitope is occluded by H3K9 acetylation . AlthougEgr1, Egr3, and Fosl1) and TCF-independent inducible genes , phosphorylation of H3S10ph was readily detectable at 5 min, preceding the other modifications, and well before the onset of Mediator, Cdk9, and PolII recruitment  targeting 50 catalytic subunits of chromatin-modifying and remodeling complexes  for theimulation . The scrmulation A and S6.Egr1, Egr3, and Fosl1. MLL3 and SET7 were detectable by ChIP at Egr1, the latter in a TPA-inducible manner, and are therefore likely to act at the promoter .We used ChIP to assess the roles of these factors in TPA-induced activation of the TCF direct target genes promoter A. Depletpromoter B. Finallalasin D C. None oEgr1, depletion of MLL3 or CHD2 reduced the basal level of H3K4me3 and the TPA-induced H3 phosphoacetylation and K4 trimethylation  B. Thus, achinery , show thachinery B. This sEgr1, Egr3, and Fosl1, even though eRNA synthesis may facilitate activation .Further information and requests for reagents may be directed to and will be fulfilled by the Lead Contact, Dr. Richard Treisman  and immortalized by infection with retrovirus expressing SV40 large T protein  for 30 min or as indicated in the Figure legends. TKO cells were reconstituted with wild-type human Elk-1, or the transcriptionally inactive Elk-1nonA and Elk-1ΔFW mutants using retrovirus infection (see Mouse Embryonic fibroblasts (MEFs) were derived from either wild-type mice (WT) or mice lacking the Elk-1, Net and SAP-1 TCFs (Elk1 protein . MEFs wetion see . For somEgr1 and Fos expression. MEFs were transfected with 20 nMol each siRNA pool using RNAimax (Invitrogen) for 72 hr. Egr1 and Fos transcription was monitored at the pre-RNA or mRNA level before and after TPA stimulation in biological triplicates by qRT-PCR (primers in ON-TARGETplus SMARTpool siRNAs (Dharmacon) were used to screen 50 catalytic subunits of chromatin-modifying and remodelling complexes  for inhiChIP was performed as described , with thnonA protein (aa309-429) ; H3K9ACS10P ; H4K16Ac ; H3K9K14AC ; H3S10P , H3S10P ; H3K27Ac ; Histone H3 ; MED1 ; SRF ; CDK9 ; Pol II 8WG16 . Elk-1 anti-mouse Elk-1 aa309–429 was made in-house and re-purified against a peptide derived from the human Elk-1309-429) . The H3K309-429) . The H3S309-429) . The H3K309-429) , but theDNA samples were end repaired, poly-A tailed and Illumina single-end adapters ligated following the standard Illumina protocol with minor adjustments. Agencourt AMPure XP beads at 0.8x ratio were used to remove adaptor dimers after ligation. The Illumina kit Phusion enzyme was replaced by Kapa HiFi HotStart ready mix. Post PCR, AMPure XP beads were used at a 1:1 ratio to maintain size integrity. DNA fragments size-selected and purified from a 2% agarose gel using the QIAquick gel extraction kit, quality controlled on the DNA 1000 BioAnalyser 2100 chip. Sequencing was on the Hi-seq2500 to generate 150 base read lengths.All ChIP-Seq datasets were cropped to 50 bp and aligned using BWA to the mouse genome (mm9) with the default settings. All ChIP-seq mapped read counts were normalized to 30 million total aligned reads. All annotated Refseq genes were assessed for histone mark coverage across a 3kb window spanning their TSS . This window was chosen to minimize overlap with other regulatory features without compromising identification of changes using DESeq. For DNase I HS sites chromatin changes occurring with ± 2kb windows of the peak summit were analyzed.2 ∼1.0. The complete list of samples and replicates and the normalization factor used are given in To control for technical variation across conditions, we calculated scaling factors relative to one condition for each antibody (MEF_03 replica 1). Scaling factors were retrieved using two independent methods which gave virtually identical results, as assessed by linear regression between normalized samples, which exhibited a slope of 1.00 ± 0.01 and spearman RSequencing read depths across the TSS region were normalized to those of a set of genes which are actively transcribed, and invariant across all the experimental conditions used in the study, which was defined as follows. Invariant expressed genes were defined as those fulfilling the following criteria: (i) they showed at least 6 intronic RNA-seq reads; (ii) readcounts were statistically not significantly different across all conditions, as assessed by DESeq; (iii) the standard deviation across all conditions was less than 15% of the mean. 487 genes fulfilled these criteria.diff and σdiff parameters of the best-fit Gaussian using the dnorm function in R and optimized by maximum likelihood with the optim function. Invariant TSS regions were defined as those with differences in read counts within 1σ from the mean difference (μdiff). This method was used to carefully scale samples of the time course . To directly compare also the 30 min time point (which was part of an independent library preparation and sequencing flow) with these earlier time points, we re-scaled the sample against the signal in the resting condition for the H3S10ph, H3K9acS10ph and H3K4me3 antibodies. For H3S10ph, the maximal signal was detected at DNase I HS, the signals at TSS being weak, so we therefore used the DNase I HS signal to define the scaling index. Scaling indexes are provided both in GEO: GSE75002 and in This method assumed a quasi-normal distribution of invariant TSS region readcounts. The ChIP-seq signal of the histone modifications in each sample was expressed relative to the signal e in MEF_03_replica_1. Since the distribution of invariant TSS region readcounts should be approximatively Gaussian, we obtained the μFor each antibody, normalized readcounts across all RefSeq (release 63) TSS regions in cells maintained in 0.3% FCS or stimulated with TPA for 30’ (each condition run in duplicate) were compared using DESeq . For TSSFor each histone modification, the normalized average readcount density per nucleotide, using a 51bp smoothing window, was used to generate a density plot centered on the RefSeq TSS. Read densities over 150bp on each side of the TSS were removed to reduce distortion of the profiles by the low readcounts at nucleosome-depleted TSS regions. Difference profiles display the difference between the readcount density per nucleotide of the resting and TPA-stimulated samples across the TSS regions.We used hierarchical clustering to organize TPA-induced changes in each histone modification at TSS regions. For each modification the fold-change upon TPA stimulation at each TSS region was calculated. A Euclidean distance matrix across the 5 modifications was applied to the R agglomerative hierarchical clustering method hclust . The nesting pattern generated by hclust was validated through multi-scale bootstrap re-sampling by pvclust  in the RWe also attempted to cluster the TSS regions themselves according to the pattern of relative changes in the 5 modifications. To minimize asymmetry, the TSS regions were separated into subsets as above according to the number of histone modifications that significantly changed upon stimulation. A Euclidean distance matrix was then generated per group of TSS regions. The distance matrix was applied to the R agglomerative hierarchical clustering method hclust, using the ward.D2 linkage method which minimizes the total within-cluster variance . Hierarci > 1, we calculated the cumulative difference DI from any other modification, yi. Thus, for the TSS regions with x > 1, DI = [Σ(xi-yi)]/n for i = 1 to n. The DI values for any paired comparison were annotated into a matrix , defined as the average difference between the degree of TPA-induced increase in a given modification , and that for any other modification (y). For any histone modification that exhibits a positive change xtrix see C and S2.ChIP-seq signals in wild-type and TKO MEFs, and TKO MEFs reconstituted with different Elk-1 mutants, were compared using the iterative method described previously , which cTranscription factor motif analysis was performed using HOMER . SequencTo investigate whether TPA-induced changes in histone modification could be used to model the resulting changes in gene transcription, we performed both linear and multiple regression analysis.0 + β1∗log(x) + ε, a change of 1% in x will lead to a β1% change in y. Linear regression between RNA changes and each mark, considered separately, was done using R  the readcount ratio between TPA-stimulated and un-stimulated conditions (TPA / 0.3%FCS) in wild-type MEFs for each histone modification, at all TSS regions where at least one modification increased following stimulation (n = 2364); and (ii) the fold increase in transcription, defined as the ratio of intronic reads in TPA-stimulated and un-stimulated conditions. For genes lacking intronic reads, the ratio of all reads aligned to their ORF was used. To assess whether the dataset needed to be scaled, we assessed the skewness for each histone modification and the RNA fold-change using the skewness function from the e1071 package in R. The dataset was significantly skewed, and a Log2 transformation was therefore applied to each variable allowing us to investigate the log-log regression between each individual mark (or incombinations) and the RNA fold changes. The coefficients of a log-log regression are easily interpretable: since log(y) = βng R see .Multiple-linear regression was performed using stepwise model selection by AIC (Akaike information criterion) which measures the relative quality of statistical models developed for a given set of data. Models in which histone modifications were considered to be independent of or dependent on each other were developed using the stepAIC function of the MASS package in R  see Fig. This apSee See The raw sequencing files and the processed data are available at the following databases:GSE75002.The accession number for the ChIP-seq analysis of Ras/ERK signal-induced histone modifications in mouse embryo fibroblasts reported in this paper is GEO: GSE75667.The accession number for the RNA-seq analysis of Ras/ERK signal-induced transcriptional changes and the ChIP-seq analysis of SRF and TCF DNA-binding profiles in mouse embryo fibroblasts reported in this paper is GEO: C.E. and F.G. designed, conducted, and interpreted experiments and wrote the paper. F.G., S.H., G.K., P.E., and A.S. analyzed genomic data and wrote scripts. N.M. performed sequence analysis. R.T. conceived the project, suggested and interpreted experiments, and wrote the paper with F.G. and C.E.


Chromosomal and genome abnormalities at the 3p21.3 locus are frequent events linked to epithelial cancers, including ovarian and breast cancers. Genes encoded in the 3p21.3 cluster include HYAL1, HYAL2 and HYAL3 members of hyaluronidases involved in the breakdown of hyaluronan, an abundant component of the vertebrate extracellular matrix. However, the transcriptional regulation of HYAL genes is poorly defined. Here, we identified the estrogen receptor ERα as a negative regulator of HYAL1 expression in breast cancer cells. Integrative data mining using METABRIC dataset revealed a significant inverse correlation between ERα and HYAL1 gene expression in human breast tumors. ChIP-Seq analysis identified several ERα binding sites within the 3p21.3 locus, supporting the role of estrogen as an upstream signal that diversely regulates the expression of 3p21.3 genes at both proximal and distal locations. Of these, HYAL1 was repressed by estrogen through ERα binding to a consensus estrogen response element (ERE) located in the proximal promoter of HYAL1 and flanked by an Sp1 binding site, required to achieve optimal estrogen repression. The repressive chromatin mark H3K27me3 was increased at the proximal HYAL1 ERE but not at other EREs contained in the cluster, providing a mechanism to selectively downregulate HYAL1. The HYAL1 repression was also specific to ERα and not to ERβ, whose expression did not correlate with HYAL1 in human breast tumors. This study identifies HYAL1 as an ERα target gene and provides a functional framework for the direct effect of estrogen on 3p21.3 genes in breast cancer cells. Family members include HYAL1, HYAL2, and HYAL3, clustered in the 3p21.3 chromosomal region, and HYAL4, SPAM1  and HYALP1, encoded on chromosome 7q31.3. Of these, only HYAL1, HYAL2 and SPAM1 act as eudogene .Increasing evidence supports a role of hyaluronidases in tumorigenesis and metastatic potential mostly associated with changes in hyaluronan breakdown profile. Intriguingly, expression levels of hyaluronidases are variable in a cancer type-dependent fashion, providing them with either oncogenic or tumor suppressor activity. Increased HYAL1 levels were found to correlate with tumor aggressiveness and poor survival in head and neck, prostate and bladder cancer –9, whereAberrant expression of HYAL1, HYAL2 and SPAM1 has also been reported in breast cancer, and in particular upregulation of HYAL1 was observed in infiltrating invasive duct cancer tissues and metastatic lymph nodes , 20. OveTranscriptional regulation of estrogen target genes is mediated through direct interaction with the estrogen receptors ERα (NR3A1) and ERβ (NR3A2), which belong to the nuclear hormone receptor family of ligand activated transcription factors . ERα andIn the current study, we show that the HYAL1 gene is a target of ERα in breast cancer cells. Analysis of the ERα cistrome identified several ERα binding sites within the 3p21.3 cluster, including in the vicinity of the HYAL1 gene, which were associated with histone marks in response to estrogen. Interestingly, among the 3p21.3 genes tested, only HYAL1 was found repressed by estrogen, indicating a selective role of these specific ERα binding elements to differentially support the estrogenic response of 3p21.3 genes in breast cancer cells.left panel). Such estrogenic decrease in HYAL1 expression was shown to take place in a time- and dose-dependent manner (right panel). Addition of the mixed antiestrogen tamoxifen also decreased HYAL1 expression in both cell lines, albeit to a lesser extent than with estrogen, whereas pure antiestrogen ICI 182,780, also known as fulvestrant, had no effect. Corresponding changes in protein levels were observed in MCF-7 and BT-474 cells with a stronger reduction of HYAL1 protein in response to estrogen, compared to tamoxifen and ICI 182,780 , indicating a rapid response of 3p21.3 HYAL1, SEMA3B and SEMA3F genes to estrogen  for ERα or diarylpropionitrile (DPN) for ERβ and analyzed HYAL1 expression. We found that PPT significantly decreased HYAL1 levels in contrast to DPN which had no effect Figure , suggestp < 0.0001, n=1980) between ESR1 and HYAL1 in the whole cohort, as well as in luminal A  and luminal B  subtypes   Figure , whereas) Figure . Further) Figure . In addi) Figure . These fi.e. ERE-900), along with other distal sites, such as ERE-13500 and ERE-32250, located toward respectively HYAL2 and RASSF1.Given the prominent role of ERα in HYAL1 down-regulation, we then performed ERα ChIP-seq data analysis in order to identify putative ERα binding sites in the vicinity of the HYAL1 gene and within the 3p21.3 cluster. Thus, we identified 69452 ERα binding sites in MCF-7 treated cells. Interestingly, our analysis revealed several binding sites occupied by ERα in the 3p21.3 cluster in absence and in presence of estrogen Figure . In parte.g. ERE-13500 and ERE-50130). To address whether these sites correlate with transcriptional repression in accordance with the down regulation of HYAL1 by estrogen . ER-negative human MDA-MB-231 breast cancer cells were transfected with expression vectors for ERα and ERβ and resistant clones were selected with neomycin to generate 231-ERα and 231-ERβ cell lines, respectively. Stable clones were functionally validated for their respective expression of ERα and ERβ by Western analysis and for their estrogenic response by luciferase assay. Human epithelial ovarian cancer TOV21G cells were derived from clear cell carcinoma  and culthttps://genome.ucsc.edu). Amplified fragments corresponding to 1282pb (P1), 1060bp (P1Δ1020), and 746pb (P1Δ900) from HYAL1 transcriptional start site were inserted in front of the luciferase coding region in pBLuc plasmid as described [The HYAL1 proximal promoter fragments were amplified by PCR according to GenBank sequence of the HYAL1 gene contig (NG_009295) and the UCSC hg19 genome assembly  according to the manufacturer's instruction and cDNA was prepared using the iScript cDNA Synthesis kit . Quantitative PCR amplification was performed as described  using a MCF-7 cells were grown to 70-80% confluence and serum-deprived in phenol red-free DMEM/F-12 medium before treatment with vehicle (control), 10nM E2, 100nM 4-OHT or 100nM ICI 182,780 for 45 min. Chromatin was harvested and ChIP and qPCR was performed as described , 62. PriWestern analysis was carried out in MCF-7 and BT-474 cells, and in ERα- and ERβ-231 stable clones treated as above and compared to vehicle (control) treatment. Cells were then harvested as described  and immuThe ChIP-seq data were generated as follow: after trimming , the seqImmunoblotting procedures were done essentially as described , 62. Briwww.cbioportal.org) using the METABRIC breast cancer dataset [Gene microarray expression (Affymetrix U133) for HYAL1, HYAL2, HYAL3, ESR1, ESR2, SEMA3B and SEMA3F were directly downloaded from the cBioportal for Cancer Genomics website ( dataset –27. Gene dataset , 29, wer


MAPT gene was considered for a long time to explain differential tissue specificity and differential response to transcription and growth factors between mRNA transcripts. The alternative promoter usage could explain partly the different tau proteins expression patterns observed in tauopathies. Here, we report on our discovery of a functional alternative promoter for MAPT, located upstream of the gene’s second exon (exon 1). By analyzing genome databases and brain tissue from control individuals and patients with Alzheimer’s disease or progressive supranuclear palsy, we identified novel shorter transcripts derived from this alternative promoter. These transcripts are increased in patients’ brain tissue as assessed by 5′RACE-PCR and qPCR. We suggest that these new MAPT isoforms can be translated into normal or amino-terminal-truncated tau proteins. We further suggest that activation of MAPT’s alternative promoter under pathological conditions leads to the production of truncated proteins, changes in protein localization and function, and thus neurodegeneration.Alternative promoter usage is an important mechanism for transcriptome diversity and the regulation of gene expression. Indeed, this alternative usage may influence tissue/subcellular specificity, protein translation and function of the proteins. The existence of an alternative promoter for  Indeed, APU may modulate (i) alternative splicing, (ii) the tissue specificity2, regional specificity4 and/or subcellular specificity5 of gene expression, and (iii) gene activation during development6. Moreover, APU may alter the N-terminal primary structure of the expressed protein, which in turn may affect the latter’s functional activity or subcellular localization7. For a growing number of genes, APU has been evidenced - especially in the brain, where up to 60% of transcribed genes are concerned4. For instance, the existence of several different promoters has already been described for genes linked to Alzheimer’s disease (AD), such as the apolipoprotein E gene APOE (the main AD genetic risk factor8) and the presenilin-2 gene PSEN2  cleavage and generation of amyloid beta peptide (Aß), which accumulates outside the cell10). After Aß deposition, the second hallmark of AD is the intraneuronal aggregation of hyperphosphorylated tau proteins. Abnormal tau aggregation is also associated with other neurodegenerative diseases, referred to collectively as tauopathies.Along with alternative splicing and alternative transcription, alternative promoter usage (APU) is an important mechanism for transcriptome diversity and flexibility, and the control of gene expression  on chromosome 17. MAPT contains 15 exons, which are usually numbered from 0 to 13. MAPT mRNA transcripts undergo alternative splicing as a function of the developmental stage, tissue and species, with the inclusion or exclusion of six alternative exons . Exons 2, 3 and 10 are specific to the adult brain11, and their alternative splicing generates six different mRNA transcripts and thus six different proteins after translation . The designations 0N, 1N and 2N respectively indicate the absence of both E2 and E3, the presence of E2 but not E3, and the presence of both exons E2 and E3. The designations 3 R and 4R indicate the absence or presence of E10. Some of these isoforms aggregate with specific patterns, which define five classes of tauopathy . These tauopathies also vary with regard to their specific clinical and neuropathological features. However, the mechanisms underlying the expression of specific MAPT transcripts and proteins have yet to be characterized.Tau proteins are encoded by the microtubule-associated protein tau gene MAPT. The existence of an additional promoter has been suggested by Andreadis11, with a view to explaining tissue-specific differences in MAPT mRNA profiles and the MAPT gene’s transcriptional response to transcription and growth factors. Interestingly, our study of tissue from the frontal cortex of patients with progressive supranuclear palsy (PSP) previously highlighted significant hypomethylation of a CpG site located in the CpG island shore 13kb upstream of E113. This region contains several putative regulatory features, such as a CpG island, DNase I clusters, binding sites for the transcription factor CCCTC-binding factor, and the histone mark H3K27Ac. The presence of these features is compatible with the existence of an enhancer linked to another promoter downstream. Furthermore, the supposition of an alternative promoter is strengthened by reports of shorter MAPT mRNAs (starting from exon 1) in genome databases14.To date, only one promoter (located around exon 0) has been described for MAPT contains an alternative promoter within intron 0, and that expression of this promoter is deregulated in a context of disease. Moreover, APU might lead to the transcription of shorter transcripts, which would encode proteins with different tissue specificities and functions (as has been reported for PSEN2 products). Shorter translation products might then be involved in the pathogenesis of tauopathies. Our present results show that a second MAPT promoter is located upstream of exon 1. We described its sequence and the transcription start sites for shorter transcripts (starting at exon 1). Moreover, we found that levels of these shorter transcripts are elevated in brain tissues from patients suffering from tauopathies AD or PSP.Our starting hypothesis was that MAPT transcripts beginning at exon 1  sequence. This observation suggested the presence of an additional mechanism for transcriptional regulation. When looking at the human genome issue Hg19 with the ECR browser (https://www.ecrbrowser.dcode.org), we found that the region of the MAPT gene encompassing the 5′ intronic region upstream of exon 1 and then exon 1 itself is conserved among mammals  revealed a specific feature of promoters for Sp family transcription factors: a GC box 141 bp upstream of exon 1. The Promoter 2.0 Prediction server  (http://www.cbs.dtu.dk/services/Promoter/) predicted a promoter at 900 bp (score: 1.127) and 500 bp upstream of exon 1 (score: 0.53), and at the first codon of exon 1 (score: 0.55). The Neural Network Promoter Prediction server  (http://www.fruitfly.org/seq_tools/promoter.html) indicated the presence of promoters at 1382 bp (score: 0.84), 568 bp (score: 0.95) and 153 bp (score: 0.92) upstream of exon 1. Lastly, the Regulatory Sequence Analysis Tools  (http://rsat.eu), Nsite  (http://www.softberry.com/berry.phtml?topic = nsite&group = help&subgroup = promoter) and P-Match-1.0  (http://gene-regulation.com/pub/programs.html) software tools predicted a large number of cis-regulatory elements and transcription factor binding sites (e.g. YY1 and E2F) in the 2000 bp upstream of exon 1 , Gencode V19 setting and Ensembl (GRCh37) databases contained reports of five shorter n 1 Fig. . These Mals Fig. . Moreoven 1 Fig. .Figure 1MAPT exon 1 (promoter B) to drive the expression of the luciferase gene in transiently transfected HeLa and SH-SY5Y cells  – thus confirming promoter B’s functionality  and cloned the shortest  12 Fig. , and ena 12 Fig. . InteresMAPT sequence revealed the presence of three ATG codons respecting the consensus Kozak sequence. The first translation initiation site is located at the 18th nucleotide in exon 1 ; this is the conventional initiation start site for tau proteins. The second translation initiation site is located at the 48th nucleotide in exon 1 (c.31), and the third and last is located at the 6th nucleotide in exon 5 (c.379). With reference to the 2N4R tau isoform containing 441 amino acids , these three translation initiation sites correspond to methionines (Met) 1, 11 and 127, respectively. These new isoforms might subsequently be translated into normal or N-terminal-truncated tau proteins.A bioinformatics analysis of the MAPT transcripts, we used TaqMan® quantitative reverse transcriptase-PCRs (qRT-PCR) with a different set of probes. Firstly, we measured the expression level of total MAPT transcripts  by using a probe shared by all known coding transcripts (the exon 12/13 junction)   but not in the occipital cortex (which is free of neurofibrillary degeneration)   Fig. . Secondlon) Fig. . In AD prea Fig. , but werns) Fig. . In sampon) Fig. . However70) Fig. . The disMAPT transcripts of different lengths. These appeared to be the major transcripts in the brain tissue. In all patients , shorter transcripts starting at exon 1 were revealed (i) by the 5′RACE-PCR using GSP1 as a faint band of around 190 bp and (ii) by the 5′RACE-PCR using GSP4 as bands of between 240-300 bp. The electrophoresis gel and its interpretation are described in detail in Supplemental Figures MAPT transcripts in the brain start at exon 1.Based on the results of the 5′RACE cloning and qPCR experiments, we next sought to directly measure the expression levels of transcripts beginning at exon 1 and thus assess their putative involvement in AD and PSP. Hence, we performed two independent 5′RACE-PCRs with mRNA from 34 brain samples . In line with the results of the 5′RACE-PCR using gene specific primer 11-12 (GSP 11-12), we observed a large number of exon-0-containing p = 0.008 in the AD brain and p = 0.085 in the PSP brain) and GSP4 .Semi-quantitative assessment using Fiji ImageJ software showed significant greater levels of shorter transcripts in the frontal cortex from AD and PSP brains than in controls. This difference was observed in 5′RACE assays using GSP1  of MAPT has an alternative promoter. This promoter is located upstream of exon 1 and is active in brain tissue. Moreover, our analysis of brain tissue samples from control individuals, AD patients and PSP patients revealed (i) new, shorter transcripts issued from this alternative promoter, and (ii) additional transcripts starting from exon 0 with different transcription start sites. Lastly, we showed that MAPT’s alternative promoter is active in brain tissues affected by the tauopathies AD and PSP.Our present results showed that like many genes expressed in the brain, MAPT, it has already been reported that the constitutive promoter in exon 0 is a TATA- and CAAT-less promoter15. Accordingly, we did not expect the alternative promoter to contain a TATA box. We therefore focused our attention on transcription factor binding sites and elements indicating the presence of a promoter in the exon 1 region. Interestingly, we observed an accumulation of transcription factor binding sites at the start of the exon 1; these included Sp1 (a transcription factor that binds to GC-rich motifs in many promoters), E2F and YY1 . This type of element might therefore exert epigenetic control over a promoter located near to exon 1.Although we queried three promoter prediction programs, only one predicted a promoter in exon 1. Hence, promoter prediction is a valuable tool but the outputs must be interpreted with a degree of caution. In fact, these prediction techniques are based on the accumulation of indirect markers of the presence of a promoter . In the case of 18. For example, the APOE gene (the main risk factor described for AD) has many promoters and is reportedly down-regulated by a factor of 2.13 in the AD temporal lobe - a region in which three transcriptional isoforms are expressed8. One of these isoforms is generated by an alternative promoter upstream of the second exon, and two transcription start sites (TSSs) are identified. These isoforms are specifically and differentially regulated in the AD temporal lobe - constituting a switch in promoter usage in healthy vs. AD brains. The PSEN2 gene is also associated with an inherited predisposition to AD. The gene’s two promoters (P1 and P2) drive two alternative transcripts that differ with regard to their 5′ UTR10. Although most tissues express both transcripts, some tissues only express one - suggesting that TSS usage may be regulated in a tissue-specific manner9. Moreover, P1 and P2 are regulated by distinct transcription factors . Egr-1 can induce a partial shift in promoter usage by downregulating P1’s activity two-fold in neuronal cells. One can imagine that a similar mechanism applies to APU for MAPT, i.e. the activation of a secondary promoter in a particular cell type under pathological conditions. Alternatively, an enhancer sequence upstream of the promoter B (i.e. a sequence missing from our construct) might potentiate MAPT’s activity in vivo. Indeed, we recently characterized a regulatory region in intron 0 (upstream of a short CpG island and containing a CpG site that is hypomethylated in patients with PSP13), located 13kb upstream of exon 1. We suspect that this site influences MAPT expression, as has already been described for other elements  in intron 022.Although luciferase expression assays showed weak activity for promoter B, the results are consistent with the weak expression observed for the short transcripts initiated by the alternative promoter in our 5′RACE-PCR. Moreover, a weak activity has already been observed for alternative promoters, and is often associated with tissue-specific expressionMAPT transcripts; short tau isoforms have already been attracting increasing attention in the field of neurodegenerative disorders. Indeed, Western blotting with antibodies against the C- or N-terminal end of the tau proteins revealed products that were initially considered to be degradation products or artifacts. Truncated tau proteins have been detected in patient brains and in murine disease models25, and induced a neurofibrillary pathology in the brain of transgenic rats27. It has been suggested that truncated tau may seed the aggregation of the full-length protein28. Interestingly, it has been shown that a 35 kDa C-terminal tau fragment lacking the N-terminus but containing four microtubule binding-repeats is over-represented in PSP and in neurodegenerative disorders in which 4R tau isoforms predominate but not in AD29. These observations confirm that (i) smaller tau isoforms can be expressed in various neurodegenerative diseases, and (ii) specific aggregative mechanisms may be linked to the isoform’s structural features. To date, it has been assumed that these small tau isoforms resulted from post-translational truncation at several sites within the full-length protein; however, the proteases responsible for this fragmentation have not been fully identified and characterized  or in exon 5 (corresponding to Met127). These isoforms have already been described31. By using a proteomics approach to study human brain tissue, Derisbourg et al. identified N-terminally truncated tau isoforms starting from Met11 and Met127. Lastly, we identified several transcripts with an atypical exon start or splicing sites that are not in frame. We cannot assume that these unusual transcripts are necessarily expressed in brain tissue. Indeed, they might be targeted by the nonsense-mediated decay pathway. It should be noted that some in-frame transcripts lacked exon 4, which is not supposedly an alternative exon in the literature.Our work described new shorter MAPT gene. In fact, APU diversifies the transcriptional regulation of a gene by modulating alternative splicing37, tissue specificity2, regional specificity4, subcellular specificity5, and/or the expression level. As suggested in the review by Davuluri et al.38, APU probably enables the mammalian genome to produce the required mRNA isoform in the right place at the right time. Our hypothesis is that under pathological conditions associated to epigenetic changes at the MAPT locus, a promoter switching occurs and could lead to a harmful process. Moreover, this APU could drive a specific splicing of the shorter transcripts. Indeed, it is now well established that splicing is physically and functionally coupled to the transcription and can be modified by the transcriptional rate . The promoter B usage could promote a preferential exclusion or inclusion of exon 10 for instance, thereby altering the 3 R:4 R tau proteins ratio.These observations raise the question of the functional consequences of APU and alternative transcription start sites for the MAPT gene has two promoters: a more active constitutive promoter, plus an alternative promoter associated with elevated expression under pathological conditions. The function of the shorter transcripts initiated by this second promoter has yet to be established. However, we propose a new model in which the previously observed truncated tau isoforms are generated by APU and the use of alternative transcription start sites, rather than by post-translational modification. The present study’s main finding is the identification of an alternative promoter that could become a specific therapeutic target. A detailed understanding of the alternative promoter’s regulatory sites and factors might therefore enable specific blockage of the APU and  the neurodegenerative process.Our preliminary study is the first to show that the 13.Post-mortem brains were obtained from brain banks at university medical centers in Lille (France), Paris (France) and Geneva (Switzerland), following approval by the local institutional review board and the provision of written, informed consent by the donor’s family. All methods were performed in accordance with the relevant approved guidelines and regulations. Frontal and occipital brain regions were dissected by trained neuropathologists and then frozen at −80 °C prior to sample preparation and genetic analysis. The present study included brain tissue samples from 35 patients (22 with AD and 13 with PSP) and 18 non-clinical controls. Most of these cases have been described previouslyn = 34) were selected for the various 5′ rapid amplification of cDNA ends (RACE)-PCRs.DNA and RNA were extracted from 50 mg samples from the frontal lobe (Brodmann area 10) and the occipital lobe (Brodmann area 18). Genomic DNA was obtained by phenol-chloroform extraction. Total RNA was isolated using the RNeasy® Lipid Tissue Mini Kit , according to the manufacturers’ instructions. Assessment of the RNA quality was based on the RNA integrity number (RIN) given by the Agilent Bioanalyzer 2100 and a RNA 6000 Nano Kit . All samples had a RNA concentration > 100 ng/µl and only samples with a RIN ≥ 5 were used for subsequent qRT-PCRs. Only frontal lobe samples with a RIN ≥ 7 , we first cloned a 2 kb region encompassing this putative sequence . As a positive control, we cloned a 1.8 kb region encompassing the constitutive promoter upstream of exon 0 (referred to here as promoter A); 1509 bp upstream of exon 0 and the first 302 bp of exon 0; forward primer: AGGTCTTGAACTAGGATGGTGGC; reverse primer: GATAGTCGACAGAGGCGAGGAC. Both sequences were obtained from a control individual by using long-range PCR with Takara LA Taq DNA Polymerase . To define the minimal essential region for promoter B, we prepared four sequential 5′-truncated constructs  from the full-length sequence. After purification with the NucleoSpin® Gel and PCR Clean-up kit , PCR products were cloned into pGL3-Basic vector  using the In-Fusion® HD cloning kit (Clontech). Constructs were purified using the Nucleobond® Plasmid No Lid kit (Macherey Nagel) and sequenced by GATC Biotech .2 incubator. Cells grown to a confluence of ~60% were transiently cotransfected with 2 μg of plasmid DNA  and the pRL-TK Renilla Luciferase Control Reporter Vector as a control (test vector/co-reporter vector ratio: 10:1), using the Transporter™ 5 Transfection Reagent . Luciferase activity was analyzed 72 h post-transfection with the Dual-Luciferase® Reporter Assay System (Promega) on a Mithras LB 940 Multimode Microplate Reader device . Each experiment was performed in triplicate on at least three independent culture passages. The pGL3-promoters’ activities were normalized against that the pGL3-basic vector lacking an insert.HeLa and SH-SY5Y cells were cultured as monolayers in six-well plates using Dulbecco’s Modified Essential Medium  supplemented with 10% fetal bovine serum and 0.5% penicillin/streptomycin, at 37 °C in a humidified 5% COMAPT expression levels were determined by qRT-PCR, using TaqMan® Gene Expression Assays, TaqMan® Universal PCR Master Mix II, and uracil-N glycosylase . To quantify total MAPT mRNA levels, we used the Hs00902194_m1 probe located at the junction between exons 12 and 13 . To assess the cDNA expression of transcripts from promoter A, we designed a custom qPCR TaqMan® assay with a probe overlapping exons 0 and 1. UBC (Hs00824723_m1) was used as a control housekeeping gene. For each sample, all qRT-PCRs were performed in triplicate on an ABI PRISM® 7900 HT instrument (Applied Biosystems), according to the manufacturer’s protocol. The comparative CT method (2−ΔΔCT) was used to calculate relative mRNA expression levels.One µg of total RNA was used to generate cDNA by using the High-Capacity cDNA Reverse Transcription Kit  with Multiscribe Reverse Transcriptase and random primers. MAPT-specific-primer (GSP11-12: GATTACGCCAAGCTTCTGGCCACCTCCTGGTTTATGATGGAT) designed for use in a 5′RACE reaction was complementary to a specific mRNA sequence for the overlap between exons 11 and 12. Positive and negative controls were prepared according to the manufacturer’s protocols. The 5′RACE products were separated by electrophoresis on a 2% agarose gel (18 h at 50 mV). The smaller bands (corresponding to transcripts lacking exon 0) were cut out, and the DNA contained therein was extracted using the NucleoSpin® Gel and PCR Clean-up kit (Macherey Nagel). Transcripts were then cloned into a pRACE cloning vector (Clontech) with the In-Fusion® HD Cloning kit (Clontech). Plasmid DNAs were purified using the Nucleobond® Plasmid No Lid kit (Macherey Nagel) and sequenced by GATC Biotech.To avoid the selection of patient-specific isoforms, we pooled the patients’ RNAs in equimolar concentrations. Only patients with a RIN≥7 were selected. Hence, the three pools corresponded respectively to 15 controls, 10 AD patients and 11 PSP patients. Rapid amplification of cDNA ends was carried out using a SMARTer™ RACE 5′/3′ kit (Clontech), according to the manufacturer’s instructions. For cDNA synthesis, 500 ng of total RNA was converted into RACE-ready first-strand cDNA. A 50 μl PCR reaction mixture was then prepared. It was composed of 2.5 μl 5′-RACE ready cDNA, 5 μl of 10X Universal Primer Mix, 1 μl of 10 μM gene-specific primer (GSP), and 41.5 μl of Master Mix (Clontech). The MAPT mRNA isoforms, we perform two 5′RACE-PCRs using the protocol described above. The primers were GSP1 (GATTACGCCAAGCTTCCCTCTTGGTCTTGGTGCATGGTGTAGC) and GSP4 (GATTACGCCAAGCTTACCAGCAGCTTCGTCTTCCAGGCTG), located in exons 1 and 4, respectively. The PCR products were separated on an 8% polyacrylamide gel. For each individual and each of the two 5′RACE-PCRs, we used Fiji ImageJ software to measure the intensity of the bands for the different MAPT transcripts40. For GSP1, the transcripts (starting at exon 1) were expected to be 194 bp or less in length. For GSP4, the expected lengths were 270, 357 and 444 bp, depending on whether or not the alternative exons 2 and 3 were included. The values correspond to the ratio between the area under the curve (AUC) for transcripts starting at exon 1 and the AUC for total MAPT transcripts (expressed as a percentage).In order to select short t test. Comparisons of MAPT expression levels  between controls and each disease groups were performed using analysis of variance (ANOVA) with post-hoc Dunnett’s test; normality of residuals were checked using histogram and Shapiro-Wilk test. Statistical testing was performed at the 2-tailed α level of 0.05. Data were analyzed using the software package SAS, release 9.3 .The luciferase activities of the promoter B constructs were compared to the empty pGL3-basic vector  using one sample Student’s Supplemental Figure S1 and S2 and Table S1.Supplementary Table S1


Candida albicans. Hyphal formation is controlled by a multilayer regulatory network composed of environmental sensing, signaling, transcriptional modulators as well as chromatin modifications. Here, we demonstrate a novel role for the replication-independent HIR histone chaperone complex in fungal morphogenesis. HIR operates as a crucial modulator of hyphal development, since genetic ablation of the HIR complex subunit Hir1 decreases sensitivity to morphogenetic stimuli. Strikingly, HIR1-deficient cells display altered transcriptional amplitudes upon hyphal initiation, suggesting that Hir1 affects transcription by establishing transcriptional thresholds required for driving morphogenetic cell-fate decisions. Furthermore, ectopic expression of the transcription factor Ume6, which facilitates hyphal maintenance, rescues filamentation defects of hir1Δ/Δ cells, suggesting that Hir1 impacts the early phase of hyphal initiation. Hence, chromatin chaperone-mediated fine-tuning of transcription is crucial for driving morphogenetic conversions in the fungal pathogen C. albicans.Morphological plasticity such as the yeast-to-hyphae transition is a key virulence factor of the human fungal pathogen  Candida albicans3. C. albicans, a normal commensal colonizer of most healthy individuals, is present on skin, gut and mucosal surfaces, and thus well-adapted to host niches with distinct immune surveillance6. However, immunosuppression can trigger C. albicans to switch into an invasive pathogenic mode, causing more than 400,000 life-threating invasive infections worldwide per year. Remarkably, together with other major pathogens, fungal infections claim about 1.5 million lives each year7.Chromatin plays fundamental roles in gene regulation during most cellular differentiation processes. Of note, chromatin architecture and functions have been conserved from human embryonic development to morphogenetic cell fate decisions in unicellular eukaryotes including the fungal pathogen C. albicans. The genomic plasticity is manifested by a transcriptional plasticity that enables a switch between a unicellular yeast-like morphology and the pseudohyphal/hyphal growth phases, which display characteristic septated filaments10. Hyphal formation is triggered by various environmental host signals. For instance, elevated temperatures, serum, nutrient availability, carbon dioxide, certain amino acids or N-acetyl glucosamine (GlcNAc) activate a complex signaling network, including the mitogen-activated protein kinase (MAPK) cascades and the cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA) signaling pathway, resulting in the activation of a panel of dedicated transcription factors such as Efg115. Of note, besides the induction of transcriptional activators, hyphal triggers occlude transcriptional repressors of hyphal-specific genes (HSGs) such as Nrg1 from target promoters16. To sustain hyphal development, additional transcription factors such as Ume6 and Brg1 are recruited to HSGs, whereas prolonged binding of Nrg1 is inhibited. Thus, two distinct transcriptional phases modulate filamentation, involving both decoration and exclusion of transcriptional modulators to initiate and maintain hyphal growth17.The ability to undergo morphogenesis arguably constitutes one of the major virulence traits of 20. Moreover, Efg1 cooperates with the NuA4 histone acetyltransferase (HAT) complex and the ATP dependent chromatin remodeling complex SWI/SNF during hyphal initiation21. In addition, the Set3 histone deacetylase (HDAC) complex controls the threshold sensitivity of the cAMP/PKA pathway to hyphal stimuli22, while the Hda1 HDAC functions in prolonged hyphal growth17. Hence, the dynamic interplay of transcription factors and chromatin modification status integrates diverse triggers from upstream signaling cascades to set levels of coordinated transcriptional responses required for morphogenetic cell fate decisions.Recent studies suggest a pivotal role for chromatin modification and organization in controlling fungal morphogenesis23. The central hub for histone H3 and H4 turnover in the cytoplasm is the histone chaperone Asf124. Newly synthesized histone H3/H4 dimers are acetylated by the HAT Hat1 at H4K5 and K12 and delivered to Asf125. The dimer is further acetylated by the Rtt109 HAT at H3K56 in Saccharomyces cerevisiae26. Asf1 shuttles modified H3/H4 dimers into the nucleus to a panel of other histone chaperones for chromatin assembly coupled to DNA replication, DNA damage repair, heterochromatin maintenance or transcription27. For instance, the CAF-1 histone chaperone complex incorporates histones H3 and H4 into chromatin coupled to DNA-replication28. Notably, CAF-1 is involved in epigenetic white-opaque switching and in the oxidative stress response in C. albicans30. The HIR histone chaperone complex consists of four subunits in S. cerevisiae and assembles nucleosomes in a replication-independent manner33. The complex was originally discovered in S. cerevisiae as transcriptional repressor for 6 out of 8 histone genes34. Of note, functions of HIR related to non-histone gene regulation have been proposed, including cryptic promoter repression and suppression of Ty elements35. Interestingly, loss of the HIR complex subunit Hir1 decreases nucleosome occupancy at various gene promoters36. Hence, Hir1 might affect the fine-tuning of transcriptional responses by regulating local chromatin architecture in target genes, thereby altering affinities of dedicated transcriptional regulators to cognate cis-acting sites, as well as the decoration by and displacement of transcriptional co-factors and modulators.The functional status of chromatin as well as its architecture can be altered by chromatin modifications including chromatin remodeling through the concomitant assembly and disassembly of nucleosomes. This process is guarded and facilitated by conserved histone chaperones acting in replication-dependent and –independent pathwaysC. albicans morphogenesis is accompanied by massive transcriptional changes affecting up to 15% of the genome37. Hence, we hypothesized that defects in replication-independent chromatin assembly may deregulate HSG expression and thus, influence the C. albicans yeast-to-hyphae transition. Indeed, here we show that chromatin assembly during filamentation is facilitated by HIR1, but not by the replication-dependent CAF-1 machinery. We find that HSG transcriptional amplitudes dramatically change upon genetic removal of HIR1. Furthermore, we provide compelling evidence that the HIR complex acts downstream of cAMP/PKA signaling, possibly in concert with other transcriptional activators such as Efg1, to regulate the initial onset of hyphal growth. Surprisingly, transcriptomics of HIR1-deficient cells revealed that the gene expression profile in cells lacking HIR1 was qualitatively very similar to the wild type (WT) following hyphal induction. However, the maximal transcriptional amplitudes are remarkably altered in the HIR1 mutant compared to the WT, which results in strongly decreased sensitivity of cells to filamentation signals. Strikingly, ectopic expression of Ume6 bypasses the requirement of Hir1-mediated transcriptional initiation for hyphal differentiation, which further substantiates our conclusion that Hir1 plays an important role during early steps of hyphal initiation. Our data are of general relevance, since they suggest a novel mechanism whereby chromatin chaperones like the HIR complex can impact fine-tuning of transcription to establish minimal threshold transcriptional levels required for triggering developmental changes or morphogenetic cell fate decisions independently of DNA replication or cell cycle control.Initiation of 38. Moreover, recent work also uncovered a role of the HIR histone chaperone member Hir1 in white-opaque switching29 and azole tolerance30 in C. albicans. Hence, we reasoned that a functional connection may exist between hyphal formation and chromatin assembly mediated by the HIR histone chaperone complex. Thus, we genetically removed HIR130 and subjected the hir1Δ/Δ mutant to filament-inducing conditions. Strikingly, loss of Hir1 strongly decreased hyphal formation on solid YPD containing 10% serum at 37 °C as indicated by smooth colony morphology . Hence, hyphal induction rather requires mainly HIR-mediated replication-independent chromatin assembly.Since chromatin assembly uses two distinct pathwaysion Fig. . By cont46, and relief from Tup1 and Nrg1 repression47 as shown in Fig. S. cerevisiae, the Hir1-containing HIR complex acts as transcriptional repressor48. Hence, we reasoned that transcriptional repressors of HSGs may become deregulated and thus overexpressed in the absence of HIR1. A well-characterized transcription factor for hyphal formation is Nrg1, which represses filamentation. Consequently, its removal leads to constitutive filamentation49. First, we tested whether deletion of HIR1 could alleviate the hyperfilamentation phenotype of nrg1Δ/Δ cells. Epistasis analysis of the hir1Δ/Δ nrg1Δ/Δ double mutant revealed that deletion of HIR1 in the nrg1Δ/Δ background failed to ameliorate the hyperfilamentation phenotype of nrg1Δ/Δ cells  or ECE1 transcript abundance  were also among the most up- as well as downregulated genes in hir1Δ/Δ hyphae when compared to WT hyphae  and anti-oxidative enzymes (SOD5 and GPX2). Furthermore, genes associated with DNA repeat maintenance and various transcription factors showed altered expression upon HIR1 deletion  were mapped to a well-characterized GO category.The RNA-seq data of e Figure . Gene onn Figure . Of noteHIR1 were more severe during hyphal initiation than during the yeast phase . Moreover, only one fifth of all downregulated genes upon hyphal initiation in hir1Δ/Δ cells were also found in the yeast phase of the mutant  and in response to hyphal stimuli (hir1-h). We found that the median upstream intergenic regions of hir1-y- and hir1-h-affected genes are above-average in size when compared to all expressed genes in our RNA-seq dataset   Fig. . These dhir1Δ/Δ cells suggested that HIR1-deficiency strongly affects the transcriptional amplitudes of regulated genes during hyphal formation. Hir1 and homologues are thought to act in promoter regions of actively transcribed genes to aid deposition of histone H3/H4 dimers32. Therefore, we hypothesized that the loss of HIR1 might result in an altered chromatin state at gene promoters including HSGs. Since histone enrichment in the HWP1 promoter revealed chromatin dynamics during hyphal formation17, and because HWP1 showed highest induction upon hyphal stimuli in WT and hir1Δ/Δ cells  for triggering hyphal induction  to developmental genes upon differentiation stimuli depends on HIRA-mediated H3.3 deposition in mouse embryonic stem cells84.Here we show that although 85, RNA Polymerase II and potentially even naked DNA86. We identified six transcription factors  with target genes differentially regulated only in hir1Δ/Δ yeast or hyphal cells and also genes that are differentially expressed in both growth phases. Interestingly, Ndt80, Tec1, Sfl2 and Fkh2 are implicated in hyphal formation and TEC1 and SFL2 expression seems to depend on Hir1 action, since both genes are downregulated upon HIR1-deletion. Further experiments are still required in order to reveal to what extent HIR modulates the affinity of transcription factors or the general transcription machinery to HSGs. Since only half of all differentially expressed genes in the hir1Δ/Δ mutant are altered in a hyphal-specific context, it will be of great interest to investigate how Hir1 affects the chromatin architecture and to unravel the precise mechanism of Hir1 recruitment to target genes in C. albicans. Of note, we were unable to perform ChIP experiments with the Hir1-myc tagged strain to show a direct interaction of Hir1 with HSG promoters. However, this could be explained by transient nature of interactions, insufficient cross-linking of Hir1 and target DNA caused by a possible as yet unknown intermediate regulatory factor recruiting Hir1, as well as by high off rates of regulators.Hir1/HIRA may be recruited via different components, including transcription factorsC. albicans yeast-to-hyphae transition. The HIR complex seems to contribute to the regulation of the initial phase of hyphal formation, where it might control signal sensitivity by acting as a valve or clutch that controls transcriptional loads via chromatin homeostasis. This way, the HIR complex could assist in the swift execution of responses to stimuli, and in the case of C. albicans, ascertains rapid adaptions to changing host environments. Importantly, the replication-independent nature of HIR function offers a major advantage for fungal cells, since it enables adaptive changes in gene expression without involving excessive and energy-intensive replication or cell cycle control. Hence, further exploring the general relevance of HIR-dependent transcriptional regulation will provide exciting new insights into C. albicans pathophysiology and host adaption as well as fungal virulence.Taken together, our study provides evidence for the necessity of the tight control of gene expression amplitudes upon encounter of changing environmental conditions exemplified here with the 87. Spider medium contained 1% Bacto yeast extract , 1% mannitol , 0.2% KH2PO4, 2% histidine, 2% leucine  and 2% Bacto agar (BD Biosciences) for solid medium. C. albicans strains were routinely grown on YPD at 30 °C. For hyphal induction, a fresh saturated overnight culture was harvested, washed once with distilled water, resuspended in an equal volume corresponding to the starting overnight culture and diluted 1:10 in pre-warmed fresh YPD containing 10% fetal calf serum 39. These cultures were then further grown at 37 °C for the indicated periods of time. Cultures were either used directly for further analysis or snap-frozen at −80 °C.Rich medium (YPD) was prepared as described previously600 of 0.1 in fresh YPD and then propagated to the logarithmic growth phase. Cells were counted on a CASY® cell counter and approximately 50 (10 cm dishes) or 10 (6 cm dishes) cells were plated on YPD agar plates supplemented with FCS, N-acetyl glucosamine (GlcNAc), 3′,5′-Cyclic adenosine monophosphate (cAMP)  or Spider medium.To investigate hyphal induction on solid medium, overnight cultures were diluted to an OD22. For quantification of the yeast and hyphal fraction of a population, at least 200 cells were counted.Colony morphology and microscopic inspection of single cells was performed as described previouslyC. albicans strains, primers and plasmids used in this study are listed in Table C. albicans strains were derived from the MTLa/α clinical isolate SC531488. The strains lacking HIR1, CDC35, CAC2, RTT106, CPH1 and EFG1 have been reported earlier89.The HPC2 and HIR3-deficient mutants were generated using a modified SAT1-flipper technique90. Briefly, approximately 500 bp up- and downstream sequences of the target gene ORF were PCR amplified and cloned into the plasmid pSFS3b using ApaI, KpnI and BglII, NotI, respectively. Deletion of NRG1 was done in a similar way using the plasmid pSFS2a91. The plasmid for HIR2 deletion was constructed by fusing approximately 500 bp up- and downstream region of the target gene, the FLP-FRT-NAT1-FRT marker from pSFS3b and the pSFS3b backbone by an in vivo cloning approach in E. coli EL350 as described in ref. UME6 was accomplished by the tet-ON system using the pNIM1 plasmid described earlier70. Gene-complemented strains were generated by cloning the HIR1 ORF with ApaI and KpnI upstream of the FLP recombinase and NAT1 into pSFS3b. 9myc epitope-tagging of HIR1 and NRG1 alleles was carried out by fusion PCR93 using plasmid pFA6a-9myc-NAT1 as a template. Correct genomic integration of the deletion cassette and re-integration constructs was verified with colony PCR, Southern Blot  and/or immunoblotting (for epitope-tagged strains only).The 90. For detection of Nrg1-9myc, a mouse monoclonal anti-myc antibody  was used. An anti-PSTAIRE antibody recognizing Cdc28  was used as a protein loading control. Protein bands on the nitrocellulose membrane were visualized using an Odysee® CLx scanner . Cells were prepared for immunoprecipitation exactly as described previously90. Whole-cell extracts corresponding to 50 OD600 units were incubated with 4 µl of the monoclonal anti-myc antibody. After an overnight incubation at 4 °C, 30 µl of Protein-G-coupled Dynabeads  were added for 2 hours at 4 °C. Subsequent washing steps were performed as described for the ChIP experiments, except that PBS instead of 1xTE was used for the final washing steps. The beads were then resuspended in Laemmli buffer for SDS-PAGE analysis. Silver staining of 10% SDS-PAGE gels was performed essentially as described elsewhere94. To identify resolved proteins, protein bands were cut out from the silver-stained gel, digested with trypsin and separated using an LC system for subsequent mass spectrometry analysis. Mass spectrometry analysis was carried out at the mass spectrometry facility at the Vienna Biocenter. The raw spectra were matched against the Candida albicans genome database (http://www.candidagenome.org/).Whole-cell-free extracts and immunoblotting was performed exactly as described earlier37. For histone ChIP, 1 mg cell free protein extract was incubated with 1 µl of anti-Histone H3 antibody . After overnight incubation at 4 °C, 30 µl of Protein-G-coupled Dynabeads (Invitrogen) were added for 2 hours at 4 °C. Subsequent washing steps and DNA purification were performed as described previously using minor modifications95. Input and ChIP DNA were incubated with 5 µl of 10 mg/ml DNase-free RNase A at 65 °C for 16 hours and recovered using a MiniElute® PCR Purification Kit . Input DNA was quantified on a NanoDrop-2000 spectrophotometer  and ChIP DNA concentration was measured using the Quantifluor® dsDNA System  in accordance to the manufacture’s protocol. Histone density at the HWP1 promoter was analyzed using primers amplifying the region ranging from −243 to −106 and from −1299 to −1195 with respect to the start codon. To analyze the UME6 promoter region, primers ranging from −4534 to −4676 and from −5210 to −5371 relative to the start codon were used. For the NRG1 and CAT1 promoter, a region ranging from −1702 to −150237 and −162 to −30630, respectively, was inspected. Input and IP qPCR signals were normalized to an intergenic region on chromosome R (RT5_tC_inter and RT3_tC_inter primers), before calculating the Input/IP ratio. The displayed “H3 density” in Figs ChIP was performed essentially as described earlier90. Relative quantification of mRNA levels was done by qPCR using the efficiency corrected ΔΔCt method96. RIP1 was used as a reference gene22. Statistical analysis was performed in Excel (Microsoft). DNase-treated RNA was subjected to rRNA depletion using the RiboMinusTM Eukaryote System v2  adhering to the recommended protocol. The efficiency of rRNA depletion was checked using a Bioanalyzer with a RNA6000 Nano chip . Fragmentation of rRNA-depleted RNA was done using the NEBNext Magnesium RNA fragmentation module  following the manufactures instructions. Samples were incubated at 94 °C for 4 minutes in a thermocycler. Fragmented samples were recovered using the RNeasy MiniElute Cleanup Kit (Qiagen) and subjected to 1st strand synthesis using SuperScript III Reverse Transcriptase (Life Technologies) and 3 µg random primers . Mini Quick Spin columns (Qiagen) were used to clean up the single-stranded cDNA, which was subsequently subjected to 2nd strand synthesis using the NEBNext mRNA Second Strand Synthesis Module (New England BioLabs) following the manual. Additionally, T4 DNA polymerase (New England BioLabs) was added for the last 5 minutes to polish overhanging ends. Double-stranded cDNA was cleaned up using a MiniElute PCR Purification Kit (Qiagen). DNA concentration was measured using the PicoGreen® dsDNA quantification reagent .RNA isolation, cDNA synthesis and qPCR analysis was performed exactly as described previouslyhttp://www.csf.ac.at). Two biological replicates for the WT and the hir1Δ/Δ cells during yeast growth or hyphal induction were subjected to RNA-seq analysis.Double-stranded cDNA was further processed and sequenced on a HiSeq. 2500 instrument  by the Vienna Biocenter Campus Support Facility CSF . Differential gene expression was analyzed using edgeR99. P-values were adjusted to determine differentially regulated genes100. Venn diagrams were created by Venny 2.0.2 (http://bioinfogp.cnb.csic.es/tools/venny/index.html)101. GO analysis was carried out with FungiFun2 (https://elbe.hki-jena.de/fungifun/fungifun.php)102. The whole dataset of detected protein-coding genes and their expression can be found in Table RNA-seq reads were mapped to the C. albicans ORFs plus intergenic up- and downstream sequences were retrieved from the Candida genome database . Putative transcriptional regulators of differentially expressed genes in HIR1-deficient yeast and hyphal cells were identified using the PathoYeastract Database “Rank by TF” tool, allowing only for hits with verified target binding and expression data103.Sequence information for all The authors confirm that all data underlying the findings are fully available without restrictions. All relevant data are within the paper and its Supporting Information files.Supplementary InformationTable S2