To assess the contribution of different histone modifications to transcriptional activation in vivo, we determined the acetylation patterns on the ecdysone induced Eip74EF and Eip75B genes in Drosophila melanogaster larvae by chromatin immunoprecipitation. We found that acetylation of histone H3 lysine 23 is localized to promoters and correlates with endogenous ecdysone induced gene activation. In contrast, acetylation of lysines 8, 12 and 16 of histone H4 and lysine 9 of histone H3 showed minor differences in their distribution on the regulatory and transcribed regions tested, and had limited or no correlation with ecdysone induced transcriptional activity. We found that dCBP, which is encoded by the nejire gene, acetylates H3 lysine 23 in vivo, and silencing of nejire leads to reduced expression of the Eip74EF and Eip75B genes. Our results suggest that acetylation of specific lysine residues of histones contribute specifically to the dynamic regulation of transcription. Furthermore, along with previous studies identify CBP dependent H3 lysine 23 acetylation as an evolutionarily conserved chromatin modification involved in steroid induced gene activation.Posttranslational modification of histones regulates transcription but the exact role that acetylation of specific lysine residues plays in biological processes  The hereditary material of eukaryotes can be found in a complex structure called chromatin, which beside DNA also contains protein and RNA molecules. The basic building blocks of chromatin are the nucleosomes that consist of a protein core, containing two of each histone proteins H2A, H2B, H3 and H4, wrapped around twice with 146 bp of DNA Acetylation of lysine residues, one of the firstly described histone PTMs in vivo is scarce. Therefore, we designed experiments to reveal histone acetylation patterns associated with gene activation in Drosophila in vivo. Loss of several HAT genes in flies  stage  when the level of 20-hydroxyecdysone is elevated. Therefore, we determined the transcriptional activity profile of the romoters . Promote3) stage . The Eipegulated . The Eipariation . Thus, wEip74EF and Eip75B genes, we collected 1118w (wild-type) larvae for chromatin immunoprecipitation (ChIP) analysis at three time points representing different stages of ecdysone response. We collected synchronized larvae in the middle of the L3 stage (mid-L3), which has low ecdysone level; wandering L3 larvae (w-L3) in which the ecdysone level is elevated; and from larvae with everted anterior spiracles (spev-L3), which are immediately before pupariation and has the highest ecdysone level. The occurrence of nucleosomes and acetylated histones on functionally distinct gene regions was determined by ChIP of larval chromatin samples with antibodies raised against histone H3 or against specific acetylated histones, followed by Q-PCR quantitation , H3K23, H4K8, H4K12 and H4K16 residues could be reliably detected. Thus, we determined the pattern of these PTMs during the late L3 stage ecdysone response.In order to identify chromatin marks present at the Rpl32 control gene, while all other regions exhibited more than ten times lower level of acetylation, indicating that this modification is primarily associated with highly active gene expression  is enriched in this modification compared to the intergenic control region in the mid-L3 sample  controls by western analysis and found that loss of neither of these factors led to decreased H3K23 acetylation  wandering L3 larvae  in nej mutants  it can alter but also by the often contradictory findings different experimental approaches provide. To resolve these discrepancies a two-step model had been proposed by Anamika Xenopus tadpoles Drosophila S2 cells, dCBP associates with the EcR-B1 receptor isoform upon 20E addition, and acetylates the H3K27 lysine on the 5′ region of the Sox14 ecdysone induced early gene, a key regulator of dendrite pruning during metamorphosis Sox14 in ddaC neurons during the white pupal stage and its silencing causes pruning defects 18 hours after pupariation in vivo, and that this chromatin mark is enriched on the promoters of the Eip74EF and Eip75B ecdysone induced genes during the late L3 stage. Although a direct causal relationship between acetylation and gene induction was not demonstrated, the role of dCBP in the regulation of the Eip74EF and Eip75B genes is supported by the finding that both genes are downregulated in nej-RNAi larvae and also by data from the modENCODE project in vitro acetylation assay Steroid hormones regulate the development and cellular and physiological functions of vertebrate and invertebrate species and also play an important role in human health and disease. They exert their effects primarily through inducing transcriptional changes with the aid of their receptors, members of the conserved nuclear hormone receptor family, which act as transcription factors. Besides ligand binding, the activity of these receptors is also influenced by posttranslational modifications, interaction with co-factors and the chromatin environment. Protein acetylation is involved in the regulation of steroid hormone action in at least two levels: acetylation of the receptor and acetylation of nucleosomal histones. Homologs of nejire/dCBP participate in both processes. For example, the human p300 protein acetylates the androgen receptor Drosophila homologue of CARM1, associates with the Ecdysone Receptor and is required for ecdysone induced upregulation of apoptotic genes Our findings along with those of others indicate that CBP dependent histone acetylation at the regulatory region of steroid induced genes might be a conserved chromatin modification in response to the hormone. Furthermore, CARMER, the E333stgcn5, 2enok and 3nej were obtained from the Bloomington Drosophila Stock Center . The nejire RNAi lines KK105115 and 15319R-2 were obtained from the VDRC  or NIG-FLY  stock centers, respectively. The UAS-dCBP and UAS-dCBP-FLAD transgenic lines were provided by Justin P. Kumar . The 14chm and 2mofmutant lines were provided by Jacques Pradel  and John Lucchesi , respectively.Fly strains were maintained and crosses carried out on standard cornmeal – yeast – sucrose Drosophila medium at 25°C unless otherwise noted. The mutant strains 1118w eggs were collected on agar – raspberry juice plates for eight hours and then transferred to standard Drosophila medium. Synchronization was carried out three days later by collecting larvae that molted from second to third instar during a four-hour interval. Synchronized L3 larvae were transferred to a new plate from which larvae were collected every four hours until pupariation. Three independent replicates of the synchronized developmental series were collected.To measure the transcriptional activity of ecdysone induced genes during the third larval instar RNA was prepared from synchronized larvae. Eip74EF and Eip75B genes at reduced nejire levels, we crossed homozygous KK105115UAS-nejire-RNAi females with hs-GAL4/TM6 Tb males at 18°C and heat-shocked the L3 larvae four times for 1 hour at 37°C. KK105115/hs-GAL4UAS-nejire-RNAi and KK105115/TM6 TbUAS-nejire-RNAi control larvae were collected four hours after the last heat shock based on the Tb phenotype.To determine the expression level of the Rp49 ribosomal protein gene. The sequences and chromosomal location of primers are in Larvae were homogenized in Trizol Reagent  and RNA was prepared according to the manufacturer’s recommendation. The RNA samples were quantitated by a NanoDrop 1000 spectrophotometer , and treated with RNAse free DNAseI  to remove genomic DNA contamination. First strand cDNA was generated from 1 µg RNA samples using Taqman Reverse Transcription Reagent  with random hexamer primers. Transcript levels were determined by quantitative real-time PCR (Q-PCR) using gene specific primers with Power SYBR Green PCR Master Mix (Applied Biosystems) in an ABI 7500 Real-Time PCR System (Applied Biosystems). Relative cDNA quantities were calculated by setting Ct values against template calibration curves, and normalizing to the level of the housekeeping 1118 larvae in the middle of the L3 instar (mid-L3), wandering L3 larvae (w-L3) and from late L3 larvae with everted anterior spiracles (spev-L3). Mid-L3 larvae were collected 28–32 hours after the L2/L3 molt as described above, w-L3 larvae were collected based on their wandering behavior, while spev-L3 larvae were collected based on the presence of everted spiracles. Homozygous E333Stgcn5 and heterozygous control chromatin was prepared from w-L3 larvae. Chromatin preparation and immunoprecipitation was performed as described previously Chromatin samples were prepared from wWandering L3 larvae of appropriate genotypes were selected and homogenized with a pestle in homogenization buffer ) using 5 µl buffer per larva. The homogenates were mixed with same amount of 2X reducing Laemmli sample loading buffer containing 5% β-mercaptoethanol, boiled for 5 minutes then centrifuged at 13000 RPM for 10 min at 4°C. The supernatant samples were separated on 10% Tricine-SDS-PAGE Drosophila embryos was performed as described previously Immunostaining of nej mutant and control embryos, hemizygous 3/Ynej embryos were stained together with FM7c, P{ftz/lacC}YH1/Y and 3FM7c, P{ftz/lacC}YH1/nej control siblings, then separated based on anti-β-galactosidase immunostaining. The strength of anti-H3K23ac immunoreactivity was quantitated by calculating the mean pixel intensity of stained embryos using the ImageJ software engrailed-GAL4 UAS-EGFP/+; UAS-dCBP/+ and engrailed-GAL4 UAS-EGFP/UAS-dCBP-FLAD embryos were stained with anti-H3K23ac and anti-GFP antibodies. Micrographs were taken with a Leica SP5 confocal microscope.To determine acetyl-H3K23 levels in Figure S1dCBP acetylates the H3K27 residue in vivo. In engrailed-GAL4 UAS-GFP UAS-dCBP (A) and engrailed-GAL4 UAS-GFP UAS-dCBP-FLAD (B) transgene carrying embryos the expression pattern of the UAS transgenes are visualized by GFP fluorescence. Immunostaining using anti-acetyl-H3K27 specific antibody shows that the level of acetyl-H3K27 is increased in embryos overexpressing UAS-dCBP (C), while it is unchanged in embryos overexpressing the UAS-dCBP-FLAD enzymatically dead construct (D).(TIF)Click here for additional data file.Table S1Oligonucleotides used as PCR primers in transcriptional analyzes and quantitation of ChIP assays.a Chromosomal location data correspond to BDGP/FlyBaseGenBank assembly Release 5.44. b The distance of the 5′ end of the oligonucleotide primer relative to the transcriptional start site of the transcript in parentheses.(DOC)Click here for additional data file.


Drosophila melanogaster key histone marks, heterochromatin protein 1a (HP1a) and RNA polymerase II (polII). These factors are mapped at 50-bp resolution genome-wide and at 5-bp resolution for regulatory sequences of genes, which reveals fundamental features of chromatin modification landscape shared by major adult Drosophila cell types: the enrichment of both heterochromatic and euchromatic marks in transposons and repetitive sequences, the accumulation of HP1a at transcription start sites with stalled polII, the signatures of histone code and polII level/position around the transcriptional start sites that predict both the mRNA level and functionality of genes, and the enrichment of elongating polII within exons at splicing junctions. These features, likely conserved among diverse epigenomes, reveal general strategies for chromatin modifications.Epigenetic research has been focused on cell-type-specific regulation; less is known about common features of epigenetic programming shared by diverse cell types within an organism. Here, we report a modified method for chromatin immunoprecipitation and deep sequencing (ChIP–Seq) and its use to construct a high-resolution map of the  Drosophila melanogaster, where the wealth of information on genetics and developmental biology awaits systematic epigenetic interpretation on a whole-genome scale. In this manuscript, we report a high-resolution map of key chromatin modifications in the Drosophila genome constructed by the ChIP–Seq approach. This map is derived from all cell types in the adult Drosophila weighted by their natural abundance. It contains key histone marks, HP1a and RNA polymerase II, mapped at 50-bp resolution throughout the genome and at 5-bp resolution for regulatory sequences of genes. It reveals striking features of chromatin modification and transcriptional regulation shared by major adult Drosophila cell types. We anticipate that this map and the salient chromatin modification landscapes revealed by this map should have broad utility to the fields of epigenetics, developmental biology, and stem cell biology.Just as a genome sequence map is indispensible to genetic studies, an epigenome map is crucial for epigenetic research. This is especially true for a sophisticated genetic model such as  Epigenetics refers to the regulation of gene expression that is heritable to daughter cells without alteration of genetic information Drosophila melanogaster. This allowed us to construct a high resolution whole-genome map of Drosophila with these key chromatin modifications and the transcriptional activity mapped at 50 base-pair resolution. Our mapping data are consistent with recent major mapping efforts in Drosophila cell lines and major developmental stages Drosophila weighted by their natural abundance, reveals striking features of the chromatin modifications with important functional implications.There is strong evidence supporting the existence of general features of chromatin modifications that are shared by all types of cells. Perhaps the strongest evidence is the presence of constitutive heterochromatin in centromeres and telomeres — a feature not only present in all types of nucleated cells within an organism but also well conserved during evolution Drosophila chromatin modification, we isolated nuclei from whole adult flies for ChIP-Seq. In order to achieve an unbiased representation of both euchromatin and heterochromatin in the following ChIP, we modified the standard ChIP-Seq method by first treating nuclei with limited amount of micrococcal nuclease (MNase) and then separating chromatin into euchromatic and heterochromatic fractions . The fact that some heterochromatic marks are mostly enriched in repetitive sequences and that these repetitive sequences function in heterochromatic silencing demands the inclusion of these multiple-mapping reads in the ChIP-Seq analyses. To this end, we employed two different calculations in the score generation step of ChIP-Seq analyses: a unique-mapping only method, which calculates the ChIP-Seq scores purely based on unique-mapping reads [ChIP-Seq (U)]; and a method combining both unique-mapping and multiple-mapping reads [ChIP-Seq (U+M)]  Illumina reads, which have unambiguous genomic origins q (U+M)] . In the Drosophila S2 cells Doc retrotransposon, but not with an adjacent copia retrotransposon  in ansposon . Overallansposon . Again, Using the above-described method, we conducted the whole-genome mapping of H3K4me3, H3K9me3, H3K27me3, H3K9ac, HP1a, and RNA polII in euchromatic arms  as well as other sequenced internal scaffolds and unmapped regions . To gain an overview of the distributions of chromatin modifications, we compared their ChIP-Seq (U+M) scores over different genomic features  within the euchromatic genome and all sequenced genome . This coDrosophila genome are transcriptionally silenced whereas a small portion of transposons remain transcriptionally active p = 8.746×10−68). We find H3K9me3 is also co-occcurring with HP1a within transposons , which suggests HP1a is recruited here by this mark. In addition, correlated RNA polII and H3K9ac densities  implicates some transposons, like G6 and Burdock, are transcriptionally active in the Drosophila genome  scores of chromatin modifications on all transposons in the genome. We find that heterochromatic marks H3K9me3, H3K27me3 and HP1a are abundant within transposons . In conta genome .To further investigate the enrichment patterns of chromatin modifications within protein-coding genes, we sorted ∼2.4 million 50-bp windows within euchromatic genomes into 100 percentiles based on their ChIP-Seq (U) scores and calculated the percentages of genomic features for every percentile individually . The relWithin protein coding genes, the top 10% of H3K4me3- and H3K9ac-dense sequences are highly represented in 5′UTRs and CDSs . Specifith∼90th percentiles) are also enriched in intronic sequences but devoid from intergenic regions. This is consistent with the notion that H3K9ac specifically associates with transcriptional activity and can spread over the whole gene body H3K9ac differs from H3K4me3 in two additional features within protein coding genes. First, moderately to highly H3K9ac-dense sequences , Bithorax complex (BX-C), and a 200-kb region between mod(mdg4) and InR, which contains multiple predicted PRE/TREs , is enriched in discrete intergenic regions , but undPRE/TREs . At boarc genome . Expectec genome . H3K27meConsistent with the fact that RNA polII is the central player of transcription, the top 20% of polII-dense sequences are conspicuously over-represented within 5′UTRs and intergenic regions, yet moderately polII-dense sequences (within 40∼80%) are also enriched in CDS . MoreoveAlthough HP1a is predominantly associated with transposons and repeats, about 23% of HP1a ChIP-Seq (U+M) scores are present in genic/intergenic regions. Within these regions, HP1a is particularly enriched in the 5′UTR regions and coding sequences . Within The high levels of agreement between our whole-fly-derived HP1a scores and ChIP-Chip scores generated from embryonic S2 cells indicate HP1a localizations are generally stable during development. Thus, we recruited a published microarray dataset, which contains gene expression data for both wild type third instar larva with and without HP1a-knockdown st∼3rd fold of change percentiles, green dots) are overly high-expressing genes in wild type larva, which are generally short in length and away from centromeres. By contrast, genes highly activated by HP1a knockdown  are generally devoid of any recognizable feature. We find a distinct third class of genes, representing moderately activated genes in HP1a knockdown . This class predominantly contains high-expressing, large genes, characterized by their large numbers of sparsely located exons. Notably, these genes also tend to localize within gene-rich regions. However, none of the above gene classes is correlated to transposon/repeat densities either upstream, downstream or within the gene bodies.To better understand genes regulated by HP1a, we calculated 11 additional features for genes in all percentiles . InteresThe above analyses implicate that HP1a concentrated at TSSs may have a direct function in regulating the expression of its target genes. To understand this function, we asked whether HP1a is specifically enriched at TSSs of its target genes. The HP1a density surrounding TSSs of 10 gene classes grouped by 10% increments of fold of change percentiles was investigated . We findWe further calculated averaged levels of histone modifications over TSS regions (+/−500 bp) for all percentiles but failed to identify any correlation . This suDrosophila genome Hsp70 gene (CG18743), which is the first defined gene with stalled polII Recent studies have revealed that RNA polII is poised or stalled at the TSS regions of about 10% genes in the p = 2.3×10−3; 3′ end: p = 1.7×10−4). This 10-bp difference of RNA polII position may reflect distinct pausing stages during the transition from transcription initiation to fully engaged elongation. It may be used as a signature to predict the transcriptional activity of a gene.To infer the precise positions of RNA polII at different types of TSSs, we calculated the frequency of polII-immunocoprecipitated reads matched to the sense and the antisense strands of genes and binned these reads into 5-bp windows . A similTo understand the relationship between RNA polII stalling and epigenetic regulation, we analyzed the distribution of chromatin modifications within 2-kb regions around different classes of TSSs . InteresDrosophila genes with known expression levels based on similarities of their epigenetic profiles around TSSs  DrosophilaDrosophila genes 3–9 sets the H3K9me3 mark, which recruits HP1a to initiate the heterochromatin formation Drosophila polytene chromosomes Drosophila, posttranscriptional silencing pathways mediated by endo-siRNAs and piRNAs are involved in transposon silencing in the soma and germline, respectively Transposons occupy approximately one third of the Our analysis of protein-coding genes reveals three salient features of chromatin modifications, which reflect distinct histone codes, in all transcriptionally active genes.First, their transcribed regions are all enriched with H3K9ac. This is consistent with the notion that H3K9ac specifically associates with transcriptional activity and can spread over the whole gene body.Second, the TSSs and TxEnds of active genes are further enriched with H3K4me3 , which iThird, RNA polII is over-represented in both promoter and 5′TR of active genes. Moreover, the extent of the over-representation strictly corresponds to the transcriptional activity of the gene.Fourth, stalled and elongating RNA polymerase II are positioned at +35 bp and +45 bp, respectively , as discDrosophila genes according to similarities of their epigenetic profiles around TSSs, indicate the possibility that genes of similar functions are transcriptionally co-regulated by the same histone code set. This type of transcriptional regulation would be conceptually similar to the trans-operon fashion of translational regulation, where many mRNAs sharing common 3′UTR elements are regulated by a common translational repressor Lastly, different active genes with different biochemical functions have distinct signatures of histone code at their TSS region. This finding, based on clustering 7,826 DrosophilaAlthough it has been assumed that transcription initiation is the rate-limiting step in gene expression regulation, recent genome-wide mapping of RNA polII have revealed polII stalling as a critical control mechanism of gene expression during development Drosophila, the predominant arrangement of the 5′ ends of the +1 nucleosome at +62 bp might allow the free access to the TSS by RNA polII at the initiation stage whereas also pose potential blockage downstream of TSS after initiation In addition, we also found a lower but evident level of polII stalled around +45 bp on actively transcribing genes. Intriguingly, the different positions of stalled polII and elongating polII echo the different positions of +1 nucleosome at the 5′ ends of genes. In mammals, active genes (mostly with elongating polII) have the 5′ ends of the +1 nucleosome predominantly peaked at +40 bp, which is in contrast to the +10 bp positioning of +1 nucleosome in the inactive promoters  th chromosomes and led to a “buffering” hypothesis, wherein HP1a and Painting of Fourth (POF) represent counteracting repressing and stimulating factors to achieve a stable expression of their common target genes DrosophilaIn addition to its well-known role in heterochromatin formation in transposon-rich regions, HP1a has been reported to positively regulate the expression of protein coding genes cis-acting regulatory elements on emerging nascent RNA Perhaps, the most unexpected finding in our study is that RNA polymerase II is concentrated on the exon sides of exon-intron and intron-exon junctions. This enrichment clearly indicates that elongating polII moves at a reduced rate within exons. These data provide strong direct evidence to a proposed kinetic model, which suggests that a reduced transcriptional elongation rate may facilitate the recognition of splice sites by the transcription-coupled splicing machinery 1118w) were collected, frozen in liquid nitrogen, and pulverized to a fine powder using a mortar and pestle. The fine powder was resuspended in 5 ml of Buffer A+  and sequentially disrupted with ∼10 strokes in a 7 ml homogenizer (Dounce) and ∼20 strokes in a 15 ml homogenizer (Wheaton). The homogenate was then filtered through two layers of Miracloth, loaded onto 2 ml of Buffer AS  and centrifuged at 3,500 rpm for 12 minutes at 4°C (Beckman Coulter Optima L-100 XP Ultracentrifuge). The cytosolic layer was removed and the nuclei pellet were resuspended in 5 ml of Buffer A . The nuclei solution was transferred to a 7 ml homogenizer (Wheaton) and disrupted with ∼10 strokes of the “loose” pestle. The solution was again loaded onto 2 ml Buffer AS and centrifuged at 3,500 rpm for 10 minutes at 4°C. The crude nuclei were aliquoted into 2 ml siliconized eppendorf tubes and stored at −80°C until ∼5×109 nuclei were collected.Approximately 5 ml of newly eclosed flies  was added to stop the digestion. The nuclei pellets were resuspended in 500 µl Buffer AG , centrifuged at 5,000 rpm. Supernatant containing mono- and di-nucleosomal fraction was separated from the pellets . This extraction was repeated 3 times in total. The pellets after the last extraction were resuspended in 500 µl Buffer AG and pooled together. The polynucleosomal fraction was sonicated ∼30 times of 20 seconds pulses at 30% output (Branson Sonifer 450 with a microtip).The nuclei samples were thawed on ice and pooled. The volume was adjusted with Buffer AC  so that the final ratio of nuclei to Buffer AC equals 8∶3. Pilot experiments determined that 0.1 U micrococcal nuclease  will digest 120 µg chromatin DNA and produce mono-, di-, and poly-nucleosomes in a 5 minute reaction. DNA concentrations of the nuclei solution was determined by AThe mono-, di-nucleosomal fraction and the sonicated poly-nucleosomal fraction were pre-cleared with Protein A Sepharose beads (Millipore) for 1 hour with constant agitation. The fractions were then aliquoted into 15 ml siliconized tubes. The histone antibodies were then added to each tube: 50 µg anti-trimethyl-H3K9 (Upstate), 25 µg anti-trimethyl-H3K27 (Upstate), 50 µg anti-acetyl-H3K9 (Upstate), 50 µg anti-trimethyl-H3K4 (Upstate), 25 µg anti-Histone H3 (Upstate). Chromatin was incubated with antibodies overnight at 4°C with rotation. The ChIP beads were equilibrated overnight with tRNA in Buffer AG (200 µg tRNA/250 µl beads) and washed with Buffer AG for 3 times to remove any excess tRNA. The tRNA-coated beads (5 µl dry beads per1 µg antibody) were added to each sample and incubated for 2 hours at 4°C with rotation. The beads were washed sequentially with Wash Buffer 1 , Wash Buffer 2 , and Wash Buffer 3 . After washing, beads were incubated in 1 ml Elution Buffer  at room temperature for 1 hour. The supernatants were phenol/chloroform extracted in PhaseLocking gel and ethanol precipitated. The precipitated DNA pellets were submitted for Illumina library construction and sequencing.2, 1XPI, 10% Glycerol) in a 50 ml siliconized tube. The nuclei were sonicated on ice for ∼30 second intervals at 30% output for 2 hours. 250 µl Protein A Sepharose beads were used for every 5×108 nuclei. The beads were washed with ChIP Buffer and then equilibrated with tRNA (200 µg/250 µl beads) in ChIP Buffer + 1% BSA for overnight at 4°C. The beads were then washed with ChIP buffer for 3 times to remove any excess tRNA. Antibodies were added and incubated with beads overnight at 4°C: 250 µl crude anti-HP1a antisera (Covance), 160 µg anti-RNA Polymerase II , 200 µg mouse IgG1 . The beads were then washed with ChIP buffer to remove any excess antibody. Chromatin samples were incubated with antibody-bound beads overnight at 4°C. The beads were washed for 5 minutes for each washing buffer: 1. RIPA 150 , 2. RIPA 500 , 3. LiCl Buffer , 4. TE Buffer. The beads were then eluted at room temperature in 500 µl Elution Buffer for 30 minutes. The supernatant was transferred to another tube and the elution was repeated with another 500 µl Elution Buffer. 8 µl Proteinase K (20 mg/ml) was added to the 1 ml combined elute samples and incubated at 37°C for 30 minutes. The ChIP samples were then reversed crosslinked by incubating at 65°C for 4 hours, phenol/chloroform extracted in PhaseLocking gels, and ethanol precipitated. The ChIP DNA pellets were dissolved in TE. Adapters are ligated to the ends of the ChIP DNA and PCR amplified before sequencing on Illumina GA.Formaldehyde was added to a final concentration of 0.1% to the nuclei and incubated at room temperature for 15 minutes. To quench the crosslinking, 2.5 M glycine was added to the nuclei to a final concentration of 0.125 M. Quenching was performed at room temperature for 10 minutes with constant agitation. Pellet nuclei were combined and resuspended into 20 ml ChIP Buffer  by a third-party SOAP program with increasing allowance of mismatches (up to 5 bases) and indels (up to 4 bases), until the majority (>60%) of input reads were mapped to the reference genome. Both unique-mapping tags (mapped to only one genomic locus) and multiple-mapping tags (mapped to more than one genomic loci) were retained and only the best genomic matching site(s) were reported. Numbers of tags (mapped Illumina reads) for each ChIP-Seq library are listed in Sequenced 35 nt reads (with <5 ambiguous bases) and corresponding quality tracks were collected from the Bustard module of Illumina Analysis Pipeline and transformed into FASTQ format. A PERL-coded Illumina ChIP-Seq analysis pipeline was developed to streamline the tag mapping and downstream data collection and statistic analyses. Input reads were iteratively mapped to the Because Illumina only sequences the first 35 nucleotides from the 5′ ends of DNA fragments, we applied a previously published tag extension approach (XSET) to score the genome. Briefly, a scoring matrix, reflecting the probabilities of the length of precipitated DNA fragments, was determined by the intensities of the input DNA on an agarose gel . These pDrosophila melanogaster genome (BDGP R5) by UCSC liftover tools. To correlate ChIP-Chip with ChIP-Seq, the genomic regions interrogated by Nimblgene tiling array (GPL5404) were divided into 1-kb windows sorted based on their ChIP-Chip scores for HP1a. Windows were grouped into 100 percentiles and the corresponding averaged ChIP-Seq (U) scores were calculated. Pearson Product-Moment correlation was performed between ChIP-Chip scores and ChIP-Seq (U) scores for these 100 percentiles. To correlate DamID-Chip with ChIP-Seq, the genomic regions interrogated by Nimblgene tiling array (GPL2678) were divided into 1-kb windows sorted based on their DamID-Chip scores for HP1a. Windows were grouped into 100 percentiles and the corresponding averaged ChIP-Seq (U+M) scores were calculated. Pearson Product-Moment correlation was performed between ChIP-Chip scores and ChIP-Seq (U+M) scores for these 100 percentiles.HP1a ChIP-Chip datasets were collected from Gene Expression Omnibus (GEO) database . HP1a DamID-Chip datasets were collected from GEO database . Genome coordinates from both datasets were changed to the Drosophila GeneChip 2.0 microarray assays in both datasets. Of these, 6,756 genes show consistent relative expression levels  between samples and between datasets. These 6,756 genes were sorted based on the averaged expression values from microarray replicates, and were further classified either into 10 gene expression groups or 100 gene expression percentiles by ranks in the expression profile.Gene expression information of adult whole flies was obtained from Gene Expression Omnibus . In total, 12,523 genes were interrogated by Affymetrix Drosophila Genome 2.0 Array. These genes were sorted and grouped into 100 percentiles based on the ratios of their expression in HP1a RNAi samples versus wild type samples. Gene expression of males and females were calculated separately. The correlation analyses shown in Gene expression information of wild type and HP1a RNAi third instar larva was downloaded from GEO . In total, 12,521 genes were interrogated by Affymetrix Drosophila melanogaster annotation database R5.5 (ftp://ftp.flybase.net/releases). Genes in different expressive groups were aligned at the same direction at the transcription start sites (TSSs), at the mid points of gene bodies and the transcription end points (TxEnds), respectively. To avoid noises from nearby transposon/repetitive sequences, ChIP-Seq (U) scores were employed in this analysis. Sliding windows of 5 bp were applied in the calculation. For each 5-bp window, scores of all genes within a gene expression group were averaged after trimming off outliers  in both ends. If a gene has more than one annotated TSSs or TxEnds, averaged scores of all TSS and TxEnd were included in the gene expression group that the gene belongs to.Genomic coordinates of TSS, TxEnd, Exon-Intron junctions, Intron-Exon junctions were collected from To classify genes into groups with elongating RNA polII, stalled RNA polII and no polII, RNA polII stalling index was calculated in the same way as previously published Dynamic neural network with an input layer .Flybase IDs of a gene set were analyzed by a web-based Functional Annotation Tool of Database for Annotation, Visualization and Integrated Discovery  adult flies and third instar larva. The band was absent from whole cell lysate made from a HP1a mutant [Su(var)205]. GAPDH was blotted as a loading control. (C) The scoring matrix deduced from the intensity profile of input DNA and used for scoring genome-wide bins. (D) A schematic view of how probability scores are employed to score the genome. A certain part of genome  is divided into 50-bp bins . Two Solexa tags mapped to the forward strand (green) and a Solexa tag mapped to the reverse strand are giving scores to the 50-bp bins based on the score matrix shown in panel B. Accumulative probability scores are shown at below. (E) Accumulative raw scores are normalized based on the numbers of sequenced tags. (F) A schematic view of how to normalize ChIP-Seq datasets based on noise levels before background subtraction. (G) Raw scores of bins  are plotted against numbers of bins  for RNA polII and mock ChIP-Seq datasets. The critical value is defined as the right-most crossing point of RNA polII curve and mock ChIP-Seq curve on this plot. The scores, which are smaller than this critical point, are considered as noises (shaded area). The peak value of mock ChIP-Seq curve (X) divided by the peak value of RNA polII curve (Y) can be used to estimate the background noise normalizer, which maximizes the correlation between two datasets for the noises (within shaded area). (H) The equation used to calculate adjusted scores (enrichment indexes).A new ChIP-Seq analysis method for whole-genome mapping of chromatin modifications. (A) Ethidium Bromide staining of input genomic DNA, which was purified from euchromatic fractions and heterochromatic fractions (after sonication) of wild type whole flies (left panel). Gel image was taken and analyzed by Kodak Gel Logic 200 imager. Intensity profiles of input DNA (combined both euchromatic and heterochromatic fractions) and molecular weight markers are shown (right panel). (B) Specificity test of HP1a antibody from Covance. Only one predominant band was recognized for whole cell lysates made from HP1a wild type ((PDF)Click here for additional data file.Figure S2A correlation analysis compares HP1a localization interrogated by ChIP-Seq and DamID-Chip analysis. 72,842 1-kb genomic bins were ranked into 100 percentiles by their scores in DamID-Chip analysis (PDF)Click here for additional data file.Figure S3Drosophila. (A) Distribution of normalized H3K27me3 ChIP-Seq (U) scores over the euchromatic genome. Red bars denote predicted Polycomb/Trithorax response elements (PRE/TREs) Antennapedia complex (ANT-C), Bithorax complex (BX-C) and a 200-kb region between mod(mdg4) and InR. Red arrow heads denote locations of predicted PRE/TREs Distribution of H3K27me3 over the euchromatic genome of (PDF)Click here for additional data file.Table S1Summary of Solexa Sequencing.(PDF)Click here for additional data file.Table S2H3K27me3-Enriched Genomic Regions.(PDF)Click here for additional data file.Table S3GO Term Enrichment Analysis of Gene Clusters.(PDF)Click here for additional data file.


APP) may play a more important role in AD etiology. The APP promoter possesses a novel 30 nucleotide sequence, or “proximal regulatory element” (PRE), at −76/−47, from the +1 transcription start site that confers cell type specificity. This PRE contains sequences that make it vulnerable to epigenetic modification and may present a viable target for drug studies. We examined PRE-nuclear protein interaction by gel electrophoretic mobility shift assay (EMSA) and PRE mutant EMSA. This was followed by functional studies of PRE mutant/reporter gene fusion clones.Alzheimer’s disease (AD) is intimately tied to amyloid-β (Aβ) peptide. Extraneuronal brain plaques consisting primarily of Aβ aggregates are a hallmark of AD. Intraneuronal Aβ subunits are strongly implicated in disease progression. Protein sequence mutations of the Aβ precursor protein (APP) account for a small proportion of AD cases, suggesting that regulation of the associated gene , nm23 nucleoside diphosphate kinase/metastatic inhibitory protein (PuF), and specificity protein 1 (SP1). These sites crossed a known single nucleotide polymorphism (SNP). EMSA with PRE mutants and promoter/reporter clone transfection analysis further implicated PuF in cells and extracts. Functional assays of mutant/reporter clone transfections were evaluated by ELISA of reporter protein levels. EMSA and ELISA results correlated by meta-analysis.APP gene promoter and that AD risk may be increased by interference with PuF regulation at the PRE. PuF is targeted by calcium/calmodulin-dependent protein kinase II inhibitor 1, which also interacts with the integrins. These proteins are connected to vital cellular and neurological functions. In addition, the transcription factor PuF is a known inhibitor of metastasis and regulates cell growth during development. Given that APP is a known cell adhesion protein and ferroxidase, this suggests biochemical links among cell signaling, the cell cycle, iron metabolism in cancer, and AD in the context of overall aging.We propose that PuF may regulate the  APOE) is linked to a large proportion of cases of AD both by genetic [APP) expression, particularly in a tissue and cell-type specific manner.A diagnostic feature of Alzheimer’s disease (AD) is aggregation of toxic amyloid β peptide (Aβ) into extracellular plaques, suspected of causing or contributing to disease progression ,2. In ad genetic ,10 and c genetic . We hypo′-flanking region of the APP gene, including its promoter [APP promoter [′-UTR [APP promoter is regulated by a variety of factors. It can be stimulated by nerve growth factor, fibroblast growth factor, and interleukin-l [APP gene regulation and pathologies such as AD has been shown, for example, by characterization of two APP promoter polymorphisms associated with the pathogenesis of some forms of AD [Several groups have studied the 5promoter -16. Seripromoter ,17 and 5r [′-UTR  contain r [′-UTR , includir [′-UTR . The APPleukin-l ,21, and leukin-l . A link ms of AD . The morms of AD ,5.APOE[MAPT) [APP promoter in eight different cell lines from five different tissue types in a chloramphenicol acetyltransferase (CAT) reporter construct [APP gene. We examined the nature of DNA-protein interaction with this DNA fragment by gel electrophoretic mobility shift assay (EMSA or gel shift). Notably, use of the PRE as a probe in EMSA showed evidence of DNA-protein interaction with this sequence in multiple cell line nuclear extracts and in mouse brain tissue nuclear extract [Our group has examined regulatory regions of important AD-associated genes, including APOE,25 and mOE[MAPT) . We haveonstruct . We disc extract . HoweverAPP-CAT fusion clone. While we had previously shown that the PRE interacts with nuclear proteins in a tissue-type specific manner, we herein identified TFs that were likely bind to the PRE, specifically activator protein 2 (AP2), nm23 nucleoside diphosphate kinase/metastatic inhibitory protein (PuF), and specificity protein 1 (SP1). We also characterized quantitative and qualitative effects of mutating the PRE vs. DNA-protein interaction in EMSA vs. both NB and rat neuronal pheochromocytoma (PC12) cells and cell nuclear extracts. Functional assays of PRE mutation effects were performed by transiently transfecting the mutant-CAT clones into human neuroblastoma and rat neuronal pheochromocytoma cell cultures. We discovered specific, significant mutation-dependent function differences. We compared the EMSA results to effects of the same mutations in functional mutant-CAT clone transfection assays. Altering the PRE’s ability to bind TF corresponded to functional changes in promoter activity in a cell line-specific manner.We continue our work on the PRE by exploring specific DNA-protein interactions in EMSA, competition EMSA, and antibody-supershift EMSA. Functional effects were measured by creation of a library of mutant PRE sequences within a previously constructed APP-CAT fAPP gene through the PRE. PuF’s better-known function is as an inhibitor of metastasis [APP regulation has already been well demonstrated [′-UTR portions of the APP 5′-flanking region [APP transcription. These two TF sites can be subject to natural variation in the human genome, as they cross a known single nucleotide polymorphism (SNP) [APP increase risk of AD, it would be another similarity between etiology of sporadic/idiopathic neuropsychiatric disorders and oncogenesis, extending our previous work in developing the latent early-life associated regulation (LEARn) model [We determined that PuF and SP1 are candidates for regulation of the tastasis . SP1 actnstrated -33. SP1 nstrated ,32,34 ang region ,36. Our sm (SNP) . The PREn) model ,39 of id′-end of the PRE. The GC box is associated with the binding of several transcription factors, including SP1, basic transcription element binding protein (BTEB)1, BTEB2, and msh homeobox 1 (Msx1). The PRE with an additional 10nt flanking sequence at either end was used with TESS  and MatITo investigate cell type specificity of PRE-protein interactions, we used the PRE fragment in EMSA with nuclear extracts from PC12 and human cervical epithelial (HeLa), SK-N-BE neuroblastoma (NB), and histiocytic lymphoma (U937) cells , AP2, and SP1, respectively. In addition, to demonstrate that the truncated USF1 site at the 3Competition EMSA in HeLa extracts was in TPA-treated extracts , primarily consisting of a single band. As predicted, anti-AP2 and anti-PuF each altered binding of the PRE with NB extracts (lanes 3–4). In addition to reducing the major DNA-protein interaction of un-competed PRE (band III), new DNA-protein interactions (bands V and VI) became visible when anti-AP2 was co-incubated. Co-incubation with anti-PuF produced a similar pattern to anti-AP2, with an additional band (IV). Of particular interest is that co-incubation with both antibodies reduced DNA-protein interaction more than did incubation with either antibody alone, and completely eliminated the interaction at band III (lane 5).Co-incubation with anti-SP1 produced a more classic “shift” response . Co-incubation with anti-USF1 (lane 7) did not result in any changes. Co-incubation with anti-USF2, on the other hand, produced a response similar to that found with anti-AP2 or anti-PuF. In addition, band II appears, but this band may also be already present but masked by the breadth of band III in untreated reactions. Close examination of lane I indicates that the interaction at band VI may also be present in untreated reactions. Bands IV and V, on the other hand, do not appear when the PRE is incubated with NB extracts in the absence of antibody or in the presence of AP1, SP1, or USF1 antibodies. These results indicate that AP2, PuF, SP1, and USF2 are all potential candidates for interaction with the PRE.To ascertain sizes of proteins that participate in some of the observed interactions with the PRE, we performed southwestern blotting with nuclear extracts from NB, PC12, HeLa and TPA-treated HeLa cells Figure . ProbingPC12 also had weaker interactions at 92, 39, and 23 kDa. HeLa nuclear extract (lane 3) shared interactions at approximately 92 and between 33 and 32 kDa, with fainter bands at 64, 60, 51, 39, and 23 kDa. Induction of HeLa with TPA (lane 4) resolved the 33/32 kDa band into a doublet and reduced the strength of weaker interactions. Comparison of the observed southwestern bands with molecular weights of predicted transcription factors suggests the possibility that several of the predicted candidate transcription factors may bind to the PRE , the M1 mutant had significantly higher adjusted signal than wildtype in NB Figure  nuclear CAT gene sequence under the control of an XbaI/BamHI fragment of the rhesus monkey APP gene promoter and 5′-UTR, specifically −309/+104, with +1 being the transcription start site , HeLa or mouse embryo fibroblast (NIH3T3) cells. In addition, these oligomers were assayed with EMSA with nuclear extracts from HeLa, or NIH3T3 cells that had been subject to induction conditions, such as TPA treatment, serum starvation or induction with cytokines such as interleukin-6 (IL6) or transforming growth factor β (TGFβ)  bore some resemblance to those observed with NB and PC12 nuclear extracts specifically for wildtype (lane 9) and M1 (lane 10). However, the M4 and M6 DNA-protein interactions  were noticeably different from both NB and PC12. DNA-protein interactions seen with untreated HeLa nuclear extracts (lanes 13–16) did not apparently vary among PRE variants, but treatment of HeLa with TPA (lanes 17–20) resulted in a pattern of interactions that was more similar to those with NB and PC12 extracts.Untreated HeLa (lanes 13–16) DNA-protein interactions were unlike those found in the other cell lines surveyed. They had an additional band that migrated more slowly than seen for other cell line nuclear extracts. Interaction was very weak with the wildtype oligomer (lane 13), and it appeared as a doublet. The M1 mutant’s interaction was a single band (lane 14), while M4 and M6 interactions were doublets (lanes 14–16).Serum starvation of NIH3T3 (lanes 25–28) may have slightly reduced interaction with the M4 mutant (lane 27) but appeared to have no other effect. Treatment of NIH3T3 with IL6 (lanes 29–32) increases DNA-protein interaction with the M6 oligomer . Of particular interest, treatment of NIH3T3 with TGFβ (lanes 33–36) brought about a dramatic shift in DNA-protein interaction bands for the wildtype PRE and all three mutants. While interaction was visibly weaker than for other NIH3T3 based extracts, it very closely resembled that seen for normal NB (lanes 1–4) and PC12 (lanes 2–8) extracts.APP gene of 35 mammal species that were aligned by WebPrank[To explore the possibility that the PRE is well-conserved, we examined genomic sequences identified or putatively identified as proximally upstream of the  WebPrank as descr WebPrank,46 and aWebPrank protocol. Sequences were taxonomically weighted as described herein and homologies between the human sequence vs. other primates, euarchontoglires, boreoeutheria, eutheria, and all mammals were calculated for the aligned PRE, as were sequence logos [Phylogenetic comparison of the alignment (−326/+202 in the human sequence) led, as expected, to rejection of the molecular clock hypothesis Figure B. DNA chce logos  for thesAPP gene consists of 18 exons and spans more than 300 kilobases on human chromosome 21 [APP gene expression. The APP gene is a likely locus for sporadic, late-onset AD, the most common form of the disease [APP gene in the Down critical region of chromosome 21. In addition, cases of late-onset AD have increased plasma levels of the forms of Aβ [APP gene may also play a role in APP protein or Aβ-related pathogenesis. It is well established that mutations in the APP coding sequence can cause autosomal dominant early onset FAD [APP polymorphisms as predisposing to late onset AD (LOAD). However, there are reports of promoter polymorphisms that increase risk for AD in a non-autosomal fashion [The osome 21 . We hypo disease ,53. Downms of Aβ  specificnset FAD . Some annset FAD  and the nset FAD  rejected fashion ,59, part fashion .APP in the pathogenesis of AD in Down syndrome [In addition, the following results strongly implicate the role of promoter elements in AD. 1) In a genome screen of 292 sib-pairs with LOAD, Hardy’s group identified 12 loci with lod-scores >1 including a region on chromosomes 21 . 2) Usinsyndrome . 5) Younsyndrome ,65.APP promoter has revealed several regulatory elements [APP promoter is regulated by several factors, including but not necessarily limited to nerve growth factor, fibroblast growth factor, and interleukin-l [APP promoter activity [APP gene [APP promoter expression by two GC-elements [Serial deletion analysis of the elements ,17. The leukin-l ,21. Coppactivity . VariousAPP gene ,34,66,67elements .APP promoter with different effects depending upon cell line [APP promoter at −55/−33 by DNAse protection assay. This fragment was predicted to contain AP1 and AP4 binding sites, but both were experimentally excluded [APP promoter resulted in reduced expression of reporter fusion clones [APP promoter fragment, although it did propose but not test a putative SP1 binding site. We do not dispute that USF may play an important role in APP proximal protein regulation but investigate the possibility that other factors and cofactors also operate on this sequence.We previously reported discovering a 30 nt (−76/−47) fragment from a deletion series of the ell line . Our disexcluded . Furthern clones . In addin clones , which wn clones . This ot′-flanking region of the APP gene. Transcription factor binding activity was studied by EMSA with human tissue nuclear extracts, including extracts from human brain, followed by EMSA in four different cell line nuclear extracts under different conditions of stimulation or induction. Binding of specific TFs was tested by competition EMSA and by antibody-supershift EMSA. We also used Southwestern blotting to estimate molecular weights of interaction partners with the PRE and compared these with candidate transcription factors.We sought to more fully characterize the activity of the PRE as a component of the 5APP promoter element in enhanced apoptotic neuronal cell death.We have determined that the PRE has tissue specificity, showing greater DNA-protein interaction with brain and lung extracts than with liver or heart extracts. In addition, the PRE has cell line-specific DNA-protein interactions with cell nuclear extracts, differing among U937, HeLa, U373, PC12, NIH3T3 cell lines. These interactions are subject to reduction, elimination, or qualitative change by conditions such as hypoxia, SR, and induction with TPA or IFN-γ), IL6, or TGFβ. Our results suggest that the −76/−47 region binds to a protein that is upregulated in serum starvation, and downregulated in hypoxia. Because serum starvation contributes to the induction of apoptosis, these results suggest a role of the 30-nt proximal Competition EMSA and antibody-supershift EMSA confirmed predicted interactions between the PRE and AP2, while antibody-supershift EMSA confirmed interaction between the PRE and AP2, PuF, SP1, and USF2. Competition and supershift EMSA appear to contradict each other regarding SP1. Possible biological explanations could include sufficiently high affinity within the PRE for SP1 to overcome competition with the particular commercial probe used. High PRE-SP1 affinity could result in a “negative” competition result but a positive supershift, since the supershift is meant to detect SP1 when bound to the target DNA. Alternatively, our supershift may be interacting with an SP1-like transcription factor that binds the PRE but has a lower affinity with the consensus SP1 site in the commercial competition oligomer. Southwestern blotting indicated possible interactions between the PRE and AP2, SP1, and USF2, among other TF. It also admitted the possibility of PRE-PuF dimer interaction.We mutated the PRE and highlighted a specific effect of the sequence that included the predicted PuF/SP1 binding site. Our mutant expression evidence tends to agree with our EMSA evidence. Of the mutants characterized, M1 was the most consistent in response across NB and PC12x cells and nuclear extracts. Specifically, semi-quantitative EMSA with M1 probe resulted in significant signal loss at the band position that corresponded closely to the major band of wildtype PRE EMSA in both NB and PC12 nuclear extracts. Likewise, M1 mutant promoter/reporter expression clones resulted in significantly reduced levels of CAT reporter protein in both NB and PC12 cells. The M1 mutant deleted the predicted PuF site and both predicted SP1 sites in the PRE.We note that M2 and M4 each also deleted a single predicted SP1 site, the specific site differing between M2 and M4. EMSA analysis of these two mutants showed that M4 consistently had reduced EMSA interaction at band II, while M2 did not. However, CAT reporter levels were not consistently altered between cell types. There-fore, our mutation analysis confirms our earlier conclusion that the PRE is most likely to function as a site of PuF and SP1 activity. Disruption of the shared PuF/SP1 site in our system resulted in reduced levels of reporter gene product, which appears to contradict part of our proposed model. However primary sequence disruption of the site would influence both PuF (repressive) and SP1 (stimulatory) interaction very strongly. In addition, disruption of the AP2 site also resulted in loss of EMSA signal, suggesting that the PRE may also function under induction as well as constitutively.Currently, two DNA sequence polymorphisms have been reported for the PRE, specifically rs200621906 and rs201592736 . Each isi. e., non-molecular clock) change. In particular, primate and mouse/rat sequences diverge the most from each other in our root-to-tip ana-lysis, but with far less difference when considering the PRE, specifically. We propose that this particular short segment of the APP proximal regulatory region has been specifically maintained, as would be expected of an active promoter segment. We have previously stated that other AD-associated gene promoters, such as for APOE, have important differences between mouse and human [MAPT promoter [APP promoter.The PRE is strongly conserved in placental mammals, particularly the PuF/SP1 overlapping site. In addition, this conservation occurs in a promoter region that has undergone significant non-neutral  [The PuF transcription factor/kinase was discovered in the context of inhibiting metastasis . Such inpromoter ,90. Latepromoter . PuF TF promoter ,86. In apromoter , providipromoter . We propCAMK2N1) . CAMK2N1CAMK2N1) . CAMK2 iCAMK2N1) .APP association is that expression of the APP gene in response to iron chelators distinctly differed between neoplastic and normal cell lines [APP gene expression was more common in tumor tissue of oral squamous cell carcinoma patients than in non-cancerous matched tissue samples. More importantly, in those patients who had elevated APP expression, survival at 24 months was 48% vs. 82% for patients with non-elevated APP expression [APP expression, reducing overall results of APP protein’s ferroxidase activity and modulating cancer risk.Of particular note is that the PRE exists within a DNAse I hypersensitive region , and PuFll lines . In cancpression . This suAPP promoter is greatest in neural origin cell lines, and several promoter elements close to the PRE are important for this activity [APP promoter contains binding sites for important TFs, such as purine-rich element binding protein-α (PURα) [Basal activity of the activity . For exaα (PURα)  and earlα (PURα) . Notablyα (PURα) .APP promoter could serve to deregulate APP production. Deletion of the PRE from a complete series of APP promoter clones resulted in a 3 to 4 fold gain of promoter activity in NB cells as measured by levels of reporter gene product [Interference with TF binding to the PRE in the context of the complete  product . While A product ,84.APP expression under normal circumstances, and interference in PuF regulation through the PRE could serve to deregulate APP gene expression, potentially contributing to AD pathogenesis  model of idiopathic neuropsychiatric disorders [n-hit” model of pathogenesis commonly accepted in oncology to “sporadic” neurodegenerative disorders. Given that the predicted PuF site may be structurally vulnerable to GG oxidation, and thus subject to the LEARn model, we conclude that our work suggests connections between processes that lead to cancer etiology and sporadic neurobiological disorders, both conceptually (LEARn vs. n-hit) and mechanistically (PuF regulation of APP vs. PuF regulation of metastasis). In addition to inhibiting metastasis, PuF serves to induce normal cell proliferation ,84. The s Figure . Aβ is aocessing . Therefoisorders ,39, expaUnless specifically noted otherwise, reagents were purchased from Sigma-Aldrich , and enzymes were purchased from New England Biolabs  or Roche Life Science .2 in a 37°C incubator. Cell culture reagents were purchased from Invitrogen/Life Technologies .PC12 and NB cell lines were obtained from ATCC and cultured as described previously . The plaAPP promoter clone pβXbB [32P-ATP  by T4 polynucleotide kinase . In addition, oligomers corresponding to this sequence and its reverse complement were synthesized (Invitrogen) and similarly radiolabeled. The oligomer pair differs from the plasmid fragment in that it does not have a “TCGA” 5′ overhang. This overhang was filled for wildtype and mutant  synthetic double-stranded oligomers. The rhesus monkey ne pβXbB  . PRE oligomer pairs were annealed and radiolabeled as described herein. Radioactive oligomer pairs were incubated with nuclear extracts from PC12, hypoxic PC12, U937, and U937 stimulated with either IFN-γ, TPA, or IFN-γ + TPA. In addition, one sample was incubated with U937 nuclear extracts and 200x molar excess of unlabeled PRE oligomer pairs. Reaction mixtures were analyzed on nondenaturing PAGE and the gel used for autoradiography.Cell nuclear extracts from NB and either HeLa cultures or HeLa treated with TPA were obtained commercially (Active Motif). Oligomer pairs for the PRE were annealed and radiolabeled as described herein. Nuclear extracts and oligomer pairs were incubated as described herein, except that some individual samples were incubated with 200x molar excess of unlabeled oligomer pairs. NB extracts were either uncompeted or competed against unlabeled PRE or commercially-obtained oligomer pairs  known to bind AP1, AP2, SP1, or USF1. EMSA in unstimulated HeLa extracts was not subject to competition. Extracts from TPA-stimulated HeLa were either uncompeted or competed against unlabeled PRE or commercially-obtained oligomers known to bind AP1, AP2, or USF1. Reaction products were separated on 5% nondenaturing PAGE and used for autoradiography as described herein.PRE oligomer pairs were annealed and radiolabeled as described herein. Labeled oligomers were incubated with NB nuclear extracts. Reactions were carried out either without antiserum or separately with antiserum against the nuclear factors AP1, AP2, SP1, PuF, USF1, or USF2 (Santa Cruz Biotechnology). In addition, one reaction was incubated with both of the two antisera against AP2 and PuF. Reactions were analyzed on nondenaturing 5% nondenaturing PAGE and the gel subject to autoradiography.2, 10% glycerol (v/v), 5% dry skim milk (w/v). Hybridization was done in the same buffer reducing skim milk to 0.25% and adding 10 μg poly-dI:dC and 106 CPM/ml radiolabeled probe. Membranes were incubated with probe for 24 hours and washed twice in 50 ml of hybridization buffer lacking poly-dI:dC and probe, 15 minutes per wash, followed by autoradiography.Nuclear extracts from NB, HeLa, TPA-stimulated HeLa, and PC12 cells (5μg of each) were subject to denaturing PAGE on a 10% gel containing 0.1% SDS. Proteins were transferred to 0.2μm nitrocellulose membranes and probed with radiolabeled PRE as we have previously described . BrieflyAPP-CAT fusion clone. This parent vector contains a 408nt proximal fragment of the APP gene promoter and 5′-UTR . Briefly, transfection was carried out with 2.7 μg of DNA of each CAT-reporter plasmid. To monitor transfection efficiency, cells were cotransfected with 0.3 μg pSVβGAL (Promega). Following DNA transfections, cells were harvested, cell extracts prepared, and protein concentration determined by Bradford assay .t.Reporter CAT protein levels in cells transfected by wildtype and each mutated clone were measured with an ELISA kit , and CAT protein levels were adjusted to total protein content of extracts. Each assay was performed as described previously . ResultsNuclear extracts from HeLa; HeLa cultured with TPA; NB; NIH3T3; NIH3T3 cultured under serum starvation (SR), IL6, or TGFβ; PC12; PC12 cultured under hypoxia; U373 cell lines; human brain; or mouse brain were obtained commercially (ActiveMotif) or prepared as previously described . Oligomet[g) between wildtype PRE and each mutant within each assay were also calculated with the equation g, since Ψ expresses effect size in All statistical analysis was done with the R statistical language . Data wet, p ≤ 0.0t with samn−322n−22. SymbolsAPP genes of 35 mammal species ; TGFβ: transforming growth factor β; TPA: 12-O-tetradecanoylphorbol-13-acetate; TSS: Transcription start site; U373: Human glioblastoma-astrocytoma; U937: Human histiocytic lymphoma cell line; USF1: Upstream stimulatory factor 1; USF2: Upstream stimulatory factor 2.AD: Alzheimer’s disease; AP1: Activator protein 1; AP2: Activator protein 2; The authors have no competing interests regarding this paper.DKL participated in design of the study, drafting of the manuscript, and had final approval of the version to be published. BM participated in design of the study and oligomers for EMSA, designed and build mutant expression clones, carried out bioinformatic, EMSA, and functional data analysis, and in drafting of the manuscript. JR participated in reading the manuscript critically and provided useful comments. YG participated in design of the study, carried out EMSA and transfection studies, and assays of reporter protein levels. All authors read and approved the final manuscript.


Epigenetic inactivation of chromatin plays an important role in determining cell phenotype in both normal and cancer cells, but our knowledge is still incomplete with respect to any potential monoallelic nature of the phenomenon. We have genotyped DNA isolated from chromatin of two colorectal cancer-derived lines and a culture of normal human intestinal epithelial cells (HIEC), which was immunoprecipitated with antibodies to acetylated vs. methylated histone H3K9, and presented the data as B allele frequency differences over multiple single-nucleotide polymorphism (SNP) moving window averages. . Three different validation tests confirmed that peaks exhibiting differences represented monoallelic domains. These complementary tests confirmed the following: 1) genes in the regions of high B allele frequency difference were expressed monoallelically; 2) in normal cells all five imprinting control regions which carried heterozygous SNPs were characterized by B allele difference peaks; and 3) the haplotypes in the B allele difference peaks were faithfully maintained in the chromatin immunoprecipitated with the respective antibodies. In both samples most of the monoallelic domains were found at the boundaries between regions of open and closed chromatin. With respect to the cancer line, this supports the established concept of conformation spreading, but the results from the normal cells were unexpected. Since these cells were polyclonal, the monoallelic structures were probably not determined by random choice as occurs in X-inactivation, so we propose that epigenetic inactivation in some domains may be heritable and polymorphic in normal human cells. Epigenetic control of gene expression is an important source of phenotypic variation in cancer. At the chromosomal level, this control is manifested by alterations in chromatin conformation associated with histone modifications, such as methylation and/or acetylation of lysine residues in N-terminal tails of histones, and with methylation of C residues in CpG-rich islands in or near gene promoters. These alterations have been used extensively as markers to determine the epigenetic status of a given gene, and recent advances in genome technology have allowed assessment of epigenetic inactivation over megabase ranges; it is now thought that these changes may spread across long stretches Another aspect of this phenomenon which has remained relatively unexplored is the degree to which epigenetic inactivation may be restricted to one allele. Within normal cells, allele-specific gene inactivation is known to occur at a number of loci, including genes within imprinted domains , most genes on one X-chromosome in female cells, odorant receptors, and at a number of genes involved in inflammation and the immune response  and histone H3 tri-methylated at K9 (H3M) in ChIP experiments on two colorectal cancer-derived lines (HCT116 and Colo205) and a culture of human intestinal epithelial cells (HIEC), which are non-immortalized and polyclonal. These histone marks are associated with open and closed chromatin conformation, respectively, and were selected from among several known to be associated with conformation in part because the modifications are mutually exclusive and there may be a greater chance that the data would be unequivocal. This also simplified the determination of allelic bias in conformation at each SNP used to genotype the DNA extracted from the immunoprecipitated chromatin, since we could calculate the difference in B allele frequencies determined at each SNP of the HAP550k microarrays. Not unexpectedly, long ‘gene deserts’ were found to be characterized by stretches of generally closed chromatin in both normal and cancer cells. Of interest, we found that monoallelic conformation was preferentially localized at the boundaries of these long stretches of closed chromatin conformation, suggesting spreading of the inactive (or active) conformation.Mb domain of Chr5 harbouring fewer than 10 genes, five of which are members of the cadherin family. In the normal cells  these regions were typically interrupted by small islands of open conformation marked by peaks of the anti-H3Ac plot, mirrored by troughs of the anti-H3M plot. Sometimes but not always, these corresponded to the promoters of the rare genes in the domain . The peaks in these domains were often flattened in the cancer-derived lines, and the plot presented in CDH6 is in closed chromatin in HCT116 cells. It is possible that this apparent shifting is at least sometimes part of the process of tumour progression (see below).To generate long-range images of chromatin conformation, the fluorescence intensity values, expressed as LogR ratios, were averaged over moving windows comprising 21 or more SNPs, and plotted against chromosomal position. As expected, based on data provided in the UCSC epigenome browser, gene-poor genomic regions were characterized by stretches of low LogR for anti-H3Ac-precipitated chromatin and correspondingly high LogR for anti-H3M. This is illustrated in Mb, 82Mb, 105Mb) are characterized by low LogR values of anti-H3Ac interrupted by localized peaks which are occasionally flattened in the cancer lines (H3M data are not included in the main part of the figure for simplicity). In the inset of The patterns of LogR ratios for the whole of chr9 are shown in Mb at a stretch in the cancer-derived line HCT116. About 35 such peaks were observed in the HIEC cells, the widest covering a range of about 400kb , expressed as B allele frequency (BAF) difference between the two ChIP samples averaged over 11-marker moving windows see . We foun−45 for HCT116, 5.8×10−11 for HIEC; data in Mb of chromosome 15  fall into this category, along with about one-quarter of the rest of these peaks throughout the genome. As many as two-thirds of the peaks, however, occurred at the boundaries between low and high LogR values, that is, between domains of open and closed chromatin conformation. Peaks I, II, V – VII and perhaps IV are in this category (kb). The boundary at peak II can also be considered as displaced, by a longer distance of about 2Mb.When the LogR ratios and BAF differences of HCT116 cells were plotted together two general patterns were observed , even though H3K9 acetylation/methylation is involved in X-inactivation MGMTTo what can we attribute this apparent spreading? The polyclonal nature of HIEC allows us to rule out some possibilities. First, it is unlikely to be due to the same mechanism as the widespread monoallelic expression described by Gimelbrant et al. IGF2R site on chr6q is polymorphic, and perhaps some elements of heritable epigenetic control of chromatin conformation may exist, which manifest themselves as the domains of monoallelic conformation that we have documented. An unexplained phenomenon, which may be related is transgenerational inheritance Our study breaks new ground in two respects. First, it localizes a significant source of monoallelic chromatin structure to regions immediately adjacent to domains of closed chromatin conformation. As such, it suggests a mechanism for this epigenetic polymorphism, which may resemble a controlled version of the spreading that we and others propose to be a significant source of phenotypic variation in cancer. Second, if our interpretation is accurate, it raises the prospect of a genetic component to this source of epigenetic variation. It is known that imprinting at the HIEC-6 are polyclonal non-immortalized intestinal epithelial cells cultured from a female 20-week embryo. They were kindly furnished at passage 17 by Jean-François Beaulieu, and were grown according to published methods in vivo; they were then washed and scraped into ice-cold PBS and resuspended in lysis buffer  supplemented with a complete protease inhibitor tablet . Following passage through a 21-G needle three times, the nuclei were harvested, resuspended in one packed nuclear volume of lysis buffer, and sonicated until DNA fragments of <1 kb were obtained. Chromatin size was monitored by electrophoresis. Immunoprecipitation (IP) was carried out as previously described, with the following modifications: Briefly, sheared chromatin lysates (500 µg) were pre-cleared by incubation with 50 µl of protein A/G agarose  to reduce background caused by non-specific adsorption to the beads, incubated for 6 h with either 20 µg of anti-acetylated H3K9/14 (Upstate), anti-trimethylated H3K9 (Upstate) or normal rabbit serum (NRS) at 4°C with constant rotation. Protein A/G agarose (50 µl) was added and incubated overnight at 4°C. The pelleted beads were washed successively twice with 1 ml of lysis buffer for 15 min each at 4°C, followed by 1 ml of WB1 , 1 ml of WB2  and 1 ml of sterile TE. The beads were resuspended in 200 µl TE/1% SDS, incubated at room temperature (rt) for 15 min and centrifuged at 3000 r.p.m. for 1 min at rt. Half of the supernatant was then incubated overnight at 65°C to reverse the cross-links, followed by 100 µg of proteinase K at 55°C for 2 h. The DNA was purified using QIAquick PCR purification kit  and eluted in 100 µl TE.The procedure followed was that described by M duo array, according to the manufacturer’s instructions. To account for the difference in microarray manufacture, we multiplied the LogR ratios from the 1M array by 2.0 for presentation with those plots generated from the HAP550 array. This allowed presentation of plots with equivalent amplitude. Microarray data are deposited in Dryad (doi:10.5061/dryad.43h8c).DNA from HIEC and HCT116 was genotyped on the Illumina HAP550 microarrays by the genotyping service of Genizon Biosciences Inc., according to the manufacturer’s instructions and as has been described We plotted B-allele frequency (BAF) differences against chromosomal position, presenting the data in two ways. First we calculated the deviation from the BAF of the control chromatin preparation precipitated with normal rabbit serum for each of the two immunoprecipitated samples. The difference between these values was calculated at each SNP, the absolute value was derived and 11-marker moving window averages were plotted vs. chromosomal position. Second, for each SNP we simply subtracted BAF for the H3Ac sample from that for the H3M sample  and the absolute values of these differences were averaged over 11-marker moving windows as above and plotted vs. position. There was essentially no difference between the two methods of calculation, and we present only data derived by the second of the two methods. Three tests were performed to validate the results, as described in the following section.−45 for HCT116, 5.8×10−11 for HIEC; data for several LD blocks within two peaks are given in Mb of chromosome 15  were found for which HapMap data showed very high LD (r2 more than 0.9 throughout). The major allele frequency was plotted for anti-Ac (blue) and anti-Me  for each SNP within the identified run of high LD. For every SNP, the anti-Ac ChIP yielded a higher BAF than the anti-Me ChIP, indicating perfect concordance between haplotype and immunoprecipitated material. Figure S2.Validation that BAF difference peaks reflect contiguous domains in HIEC. See legend to Figure S1. Three regions of high LD on chr7 are shown. Again perfect concordance was observed between haplotype and immunoprecipitated material. Figure S3. Validation that BAF difference peaks represent domains of monoallelic expression at SPRY2 . Genomic DNA and cDNA around rs504122 (C/T heterozygous in both HCT116 and HIEC) were amplified from both lines and sequenced. Upper panels, both alleles are expressed in HIEC, only the C in HCT116. Lower panel, BAF differences plotted for both cell lines, showing HCT116, but not HIEC, with BAF differences.(DOC)Click here for additional data file.


Saccharomyces cerevisiae NMD mutants accumulate 5′–extended RNAs (CD-CUTs) of many subtelomeric genes. Using the subtelomeric ZRT1 and FIT3 genes activated in response to zinc and iron deficiency, respectively, we show that transcription of these CD-CUTs mediates repression at the bona fide promoters, by preventing premature binding of RNA polymerase II in conditions of metal repletion. Expression of the main ZRT1 CD-CUT is controlled by the histone deacetylase Rpd3p, showing that histone deacetylases can regulate expression of genes through modulation of the level of CD-CUTs. Analysis of binding of the transcriptional activator Zap1p and insertion of transcriptional terminators upstream from the Zap1p binding sites show that CD-CUT transcription or accumulation also interferes with binding of the transcriptional activator Zap1p. Consistent with this model, overexpressing Zap1p or using a constitutively active version of the Aft1p transcriptional activator rescues the induction defect of ZRT1 and FIT3 in NMD mutants. These results show that cryptic upstream sense transcription resulting in unstable transcripts degraded by NMD controls repression of a large number of genes located in subtelomeric regions, and in particular of many metal homeostasis genes.Nonsense-mediated mRNA decay (NMD) prevents the accumulation of transcripts bearing premature termination codons. Here we show that  S. cerevisiae, repression of many genes relies on transcription of long extended RNAs upstream from where transcription normally initiates. These long extended RNAs are degraded by a machinery that recognizes that these RNAs do not encode any functional proteins. Using genes involved in controlling the uptake of the essential elements zinc and iron, we find that transcription of these long extended non-coding RNAs represses transcription by preventing the binding of the transcriptional machinery to the normal transcriptional control elements. Our findings show that repression of transcription of many genes relies on the transcription of unstable long RNAs and that this mechanism of control is particularly prevalent for genes involved in controlling the level of metals inside cells.Precise expression of genes relies on their accurate and timely transcription and on turning off these genes when production of the proteins is not required. Our study describes that in the baker's yeast,  S.cerevisiae, the first and best-documented example is the SRG1 ncRNA, which regulates transcription of the SER3 gene involved in serine metabolism through transcriptional interference SRG1 ncRNA is transcribed in the sense direction upstream of its target gene, most ncRNAs found to regulate S.cerevisiae transcription are antisense transcripts, such as the ones described for the PHO84, Ty-1 and GAL10 loci ICR1 ncRNA has been found to regulate the FLO11 gene A large fraction of eukaryotic genomes is transcribed, even in the non-coding regions . In the case of ADH4 and ZRT1, increase of signal in the upstream regions correlated with a decrease of signal in the downstream regions .We previously used tiling microarrays to show that NMD controls the degradation of inefficiently spliced  protein . Many ge regions . Northerme  or the upstream (UP) regions  and PHM7 (YOL084W), which are not localized in subtelomeric regions and do not exhibit CD-CUTs (data not shown) was unaffected by Upf1p absence . This analysis showed that the major ZRT1 CD-CUT  than in the absence of Upf1p (t1/2 = 20–30 min.). Because the turnover rate of these species is strongly decreased when NMD is inactivated, we conclude that these CD-CUTs are directly targeted by NMD for their degradation.To gain further evidence that the turnover of CD-CUTs is directly dependent on NMD, we replaced the region upstream from the site of transcription initiation of the 1 CD-CUT  or of th3 CD-CUT  showed tZRT1 is derepressed in the rpd3Δ strain and that Sir2p played a role antagonistic to Rpd3p in ZRT1 expression ZRT1 by modulating the expression of its CD-CUT, we inactivated Upf1p in rpd3Δ or sir2Δ backgrounds and studied the induction of ZRT1 in these strains. ZRT1 was strongly derepressed in the rpd3Δ strain . However the genetic data shown above strongly suggest that Rpd3p mediates the repression of ZRT1 through the modulation of the transcription of the CD-CUT.To investigate the specificity of the effect observed with Rpd3p on the deletion . Neitherdeletion , nor Hdadeletion  were fouZRT1 gene, we predicted that the replacement of its upstream region by the GFP-HIS3 coding cassette  at 3 positions upstream from ZRT1  or −184 (C) resulted in a derepression of ZRT1 , and within the ZRT1 ORF (+905 to +1021), using chromatin immunoprecipitation (ChIP) of the Rpb3p subunit. We found slightly above background levels of occupancy of the polymerase in conditions of zinc repletion in both regions in wild-type and upf1Δ strains  in conditions of repression in both strains  was shown to result in a constitutive expression of FIT3FIT3 CD-CUT on the derepression of FIT3 induced by this Mediator component mutation. We inactivated Xrn1p in a strain carrying the med2-S208A mutation (kind gift of F.Holstege) and analyzed the expression of FIT3. FIT3 derepression was observed in the med2-S208A mutant grown in normal medium . CD-CUTs accumulating in NMD-deficient strains are different from the CUTs accumulating in nuclear exosome or TRAMP complex mutants ADH4 CD-CUT, which is efficiently degraded only when both NMD and the nuclear exosome is inactivated . A recent study showed that transcription of the sense upstream ncRNA ICR1 mediates transcriptional control of the subtelomeric FLO11 gene FLO11 gene encoding ICR1 shows elevated RNA levels in the upf1Δ strain . Insertion of the terminator at position C relieves repression, but also inhibits ZRT1 induction even when NMD is active . Strains in which the 2. Growth in condition of low zinc gene induction was performed in either a Chelex-treated synthetic complete medium (CSC) or a SC medium containing 1 mM EDTA, pH adjusted to 4.4 with 20 mM citrate. CSC was prepared as described 600 = 0.5, washed twice in sterile water, and shifted into YPD medium with BPS (low iron shift) or SC+EDTA medium (low zinc shift) for the indicated times. For the experiments including overexpression of Zap1p, WT or upf1Δ strains containing the vector pUG35 or pIT31 (see below) were grown in SC medium without Uracil (SC-URA) supplemented with 2 mM Zn. At OD600 = 0.45, cells were washed twice in sterile water and shifted in SC-URA without methionine (SC-URA-MET) supplemented with 2 mM Zn for 2 hours to overexpress Zap1p prior to zinc starvation. After 2 h, cells were washed twice in sterile water and maintained in log phase in SC-URA-MET medium containing 1 mM EDTA. Kinetics of induction were performed as described above.Strains were grown in conditions of non-induction in either YPD or Synthetic Complete medium (SC) supplemented with 2 mM ZnClZAP1 gene was generated from genomic DNA with primers containing the restriction sites ClaI and SalI and inserted in the vector pUG35 digested by the same restriction enzymes. After transformation and amplification in E. coli, the plasmid (pIT31) was confirmed by sequencing. The aft1-up expression plasmid was obtained from J.Kaplan (U.of Utah).A PCR product corresponding to the ADH4 ORF probe (65°C).Tiling Arrays used in this study were described previously ChIPs using anti-Rpb3 RNA polymerase II subunit and a myc-tagged version of Zap1p inserted at the chromosomal locus were performed as described Figure S1ZPS1 and FLO11. A. Tiling array profile in the region of the ZPS1 gene. Shown is the log2 ratio of signal detected for the upf1Δ strain divided by the signal for the wild-type strain. B. Tiling Array profile of the upf1Δ mutant compared to the wild-type strain in the right subtelomeric region of Chr IX containing the FLO11 gene. The FLO11 gene is localized on the Crick strand (transcribed right to left) from positions 393,672 to 389,569. The increase of signal in the upf1Δ mutant upstream from the FLO11 gene is indicative of higher levels of the ICR1 ncRNA controlling FLO11. Note that the neighbor genes MRS1 and SEC11 located in region 397,000–399,000 are not affected by the upf1Δ deletion.Tiling array profiles of (TIF)Click here for additional data file.Figure S2ZRT1 (A) and ADH4 (B) genes by northern blot analysis. The ZRT1 probes cover the following nucleotides: Probe 1: −2410 to −2089; Probe 2: −800 to −211; Probe 3: −257 to −84; Probe 4: +931 to +1131; Probe 5: +1141 to +1341 (downstream from the ORF).Mapping of the CD-CUTs of (TIF)Click here for additional data file.Figure S3upf2Δ and upf3Δ strains after a shift to a medium lacking zinc. Gene induction was monitored by northern blot using probes hybridizing to the corresponding genes. SCR1 was used as a loading control. B. Analysis of ZAP1 mRNAs levels in wild-type and upf1Δ strains. ZAP1 mRNA levels were analyzed by northern blot from cells grown in SC+2 mM Zn (time zero), or after a shift to SC+EDTA (low Zn). An RNA sample from a zap1Δ strain was included as a negative control for the detection of the ZAP1 mRNA.Analysis of zinc regulon genes induction in NMD mutants. A. Kinetics of induction of zinc regulon genes in wild-type, (TIF)Click here for additional data file.Figure S4FIT3 induction in strains lacking Xrn1p, Upf1p or in the double mutant xrn1Δrat1-1. Shown is a northern blot analysis of FIT3 expression in the indicated strains using a probe complementary to FIT3.Kinetics of (TIF)Click here for additional data file.Figure S5ZRT1 and ADH4. A. Schematic representation of the ZRT1 and ADH4 genes and location of the GFP-HIS3 cassettes deletions/insertions . The dashed lines represent the regions replaced by the cassettes. B. GFP mRNA levels analyzed by northern blot in the different insertion strains. Levels were normalized to SCR1. A strain without GFP insertion was included as negative control. C. Effects of the deletion of the upstream region and of the insertion of a GFP-HIS3 cassette on the kinetics of induction and shutoff of ZRT1. Insertion of the GFP-HIS3 cassette upstream from ZRT1 (zrt1-up1) results in a three-fold increase in the ZRT1 mRNA peak in the upf1Δ strain during zinc deficiency. ZRT1 induction was faster in the strain carrying this insertion compared to the wild-type, as shown by the amount of the ZRT1 mRNA expressed after 30 to 120 minutes. After 4 hours of induction, the kinetics of disappearance of ZRT1 upon shifting back to zinc-containing medium was also monitored in these strains (+zinc), and samples were harvested at the indicated times after addition of zinc to the medium. RNAs extracted from all four strains were loaded on the same gel and analyzed on the same membranes exposed to the same times, but each strain is shown as a separate panel for clarity and space purposes.Insertion of GFP cassettes upstream from (TIF)Click here for additional data file.Figure S6ZRT1 induction in wild-type, hda2Δ hda3Δ, upf1Δ, hda2Δupf1Δ and hda3Δupf1Δ strains.Kinetics of (TIF)Click here for additional data file.Table S1S.cerevisiae ORFs for which 5′ extended species were observed by tiling microarrays in the upf1Δ and/or xrn1Δstrains.List of (XLS)Click here for additional data file.