Caenorhabditis elegans that permits global identification of the binding sites for transcription factors using chromatin immunoprecipitation and deep sequencing. We describe and validate this strategy, and apply it to the transcription factor PHA-4, which plays critical roles in organ development and other cellular processes. We identified thousands of binding sites for PHA-4 during formation of the embryonic pharynx, and also found a role for this factor during the starvation response. Many binding sites were found to shift dramatically between embryos and starved larvae, from developmentally regulated genes to genes involved in metabolism. These results indicate distinct roles for this regulator in two different biological processes and demonstrate the versatility of transcription factors in mediating diverse biological roles.Transcription factors are key components of regulatory networks that control development, as well as the response to environmental stimuli. We have established an experimental pipeline in  C. elegans transcription factor PHA-4 is a member of the highly conserved FOXA family of transcription factors. These factors act as master regulators of organ development by controlling how genes are turned off and on as tissues are formed. Additionally they regulate genes in response to nutrient levels and control both longevity and survival of the organism. However, the extent to which these factors control similar or distinct gene targets for each of these functions is unknown. For this reason, we have used the technique of chromatin immunoprecipitation followed by deep sequencing (ChIP–Seq), to define the target binding sites of PHA-4 on a genome-wide scale, when it is either functioning as an organ identity regulator or in response to environmental stress. Our data clearly demonstrate distinct sets of biologically relevant target genes for the transcription factor PHA-4 under these two different conditions. Not only have we defined PHA-4 targets, but we established an experimental ChIP–Seq pipeline to facilitate the identification of binding sites for many transcription factors in the future.The  A major scientific endeavor is aimed toward understanding how the regulatory information embedded in the genome is deployed to direct the complex process of development C. elegans.Ultimately, understanding transcriptional regulation of development requires identification of the regulatory network as a whole. The binding sites of many transcription factors under similar conditions must be determined, as well as how binding sites for a given transcription factor change over time as development progresses. To this end, we have developed a high-throughput experimental system to categorize the binding sites of many transcription factors using chromatin immunoprecipitation (ChIP) in the developmental model organism, the nematode C. elegans provides many advantages to deciphering developmental regulatory networks C. elegans provides an excellent framework to interpret how regulatory networks control development. Additionally, the spatial and temporal expression of both transcription factors and their targets can be followed using live GFP imaging techniques. The small size and simple growth conditions of C. elegans facilitate large-scale biochemical analyses such as ChIP. Finally, because the genome is relatively compact, individual genes are small and close together, which simplifies multiple steps of the process, from cloning procedures to downstream bioinformatics analysis.C. elegans transcription factor genes with a fluorescent epitope tag, create transgenic animals expressing a tagged factor, and perform chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) to identify binding sites for that factor C. elegans development and demonstrate new roles for key regulators in diverse biological processes.We have established an experimental system to systematically tag C. elegans  using anti-GFP to collect chromatin preferentially bound by the GFP-tagged factor C. elegans AMA-1, and perform well in ChIP assays We examined whether a transgenic tagged factor could recapitulate the binding sites of the endogenous, untagged factor. To directly compare the binding properties of a tagged factor expressed from a transgene with that of the endogenous protein, we first performed ChIP for both the tagged and native versions of AMA-1, the large subunit of RNA polymerase II (RNA Pol II). AMA-1 is well-suited for this comparison because commercially available antibodies against RNA Pol II recognize C. elegans.We therefore established a transgenic strain that expresses AMA-1:GFP:3xFLAG (referred to as AMA-1:GFP thereafter) in all nuclei, recapitulating the wild type expression pattern . We grewWe next determined the binding sites for a key transcription factor, PHA-4/FOXA. PHA-4 is a master organ identity gene that is required for the specification and formation of the pharynx. The expression of several hundred genes in the developing embryonic pharynx is dependent upon PHA-4, many of which are likely direct targets pha-4(RNAi) or a negative control Cherry(RNAi) and incubated in the absence of food (pha-4(RNAi) animals exhibited a significantly reduced survival rate at 30%, compared to 75% from the negative control (pha-4(RNAi) larvae were healthy, and had not suffered developmental defects (data not shown). Conversely, transgenic expression of pha-4 from its native promoter was sufficient to prolong starvation survival relative to a control, from a mean survival of 8.3±0.2 days in wild type to 9.4±0.2 days in a strain expressing tagged PHA-4  undergoing starvation . L1 anim of food . After e control . Howevered PHA-4 . Thus, Ppha-4(q90) mutants, and rescued the embryonic lethality of these mutants.To identify PHA-4 binding sites in the genome, PHA-4:GFP:3xFLAG (referred to as PHA-4:GFP thereafter) transgenic animals were created via our pipeline. Animals bearing an integrated transgene had nuclear-localized expression in the pharynx and intestine in embryos, and in pharynx, intestine and rectum in larvae, confirming published expression patterns 6 reads per sample. smk-1. smk-1 encodes a potential co-factor for PHA-4 To compare the binding patterns of PHA-4 under different conditions, we collected and crosslinked PHA-4:GFP transgenic animals during embryogenesis when the pharynx is forming, and during the L1 larval stage under starvation conditions. Biologically independent duplicate samples were collected. The samples were immunoprecipitated with anti-GFP to identify PHA-4 binding sites, and also with anti-RNA Pol II antibodies to identify the location of RNA Pol II, which will help to define the transcriptional state of genes associated with PHA-4. The immunoprecipitated chromatin, along with control input DNA from the same animals, was then sequenced to the depth of >10−5; C. elegans genome, in agreement with previously published studies Using a peak-scoring algorithm −13). Moreover, seven of these pharynx-expressed genes had been previously demonstrated to be bound directly by PHA-4 using a gel shift assay We used several methods to validate these binding sites. We first used ChIP-qPCR to directly test whether we could detect enriched binding of PHA-4 at 94 individual candidate sites taken from both embryonic and L1 data sets . We foun−4) (−26). This GAGA element, was previously noted as associated with timing of pharynx development in embryos C. elegans genome.Finally, we examined the sequence underlying PHA-4 binding peaks to identify de novo consensus binding sequences enriched under the peaks relative to the genome. Five of the six consensus sequences identified in either of the two stages were variations of the known PHA-4 binding consensus sequence TRTTKRY −4) . IntriguTo determine the degree to which binding sites change under different conditions, we compared the PHA-4 binding profiles at the two stages . The twoTo globally categorize the types of genes that are differentially regulated, we determined the Gene Ontology (GO) functional categories that are enriched among each set of stage-specific PHA-4 targets . We foun−10) 0–2kb upstream of the gene, in the candidate regulatory region. The subset of those targets that had already been assigned a three-letter name, and presumably had some functional information available, were then divided into common, embryo-only, and starved L1-only sets consisting of 202, 312, and 294 genes, respectively . Additionally, the metabolism-related factors in starved L1s consist largely of multiple regulators of sterol and fatty-acid metabolism, as well as cytochrome P450 and glutathione-S-transferase components. The starved L1 set also include several components involved in acetylcholine metabolism and signaling, which is involved in neuromuscular synapse transmission. Starved L1s also have increased PHA-4 binding at various types of membrane-bound proteins, including several multidrug resistance proteins, P-glycoproteins, tetraspanins, and serpentine receptors. Many fewer of these types of proteins were noted in the shared or embryo sets.Several striking differences were obvious between the two developmental conditions we examined. For instance, the target set in embryos includes many components of G-protein signaling, but the L1 set was devoid of this signaling pathway. Conversely, the L1 set had multiple examples of modulators of the TGFβ-signaling pathway, which is involved in controlling both body size and dauer formation C. elegansbec-1, lgg-1, gpd-2, and unc-51) and found that all four are strongly bound by PHA-4 in starved L1 larvae, but PHA-4 exhibits minimal binding in embryos  is affected by binding of PHA-4 in a stage-specific fashion. Stalling is the accumulation of RNA Pol II at the TSS, and has been experimentally defined as the presence of a peak of RNA Pol II binding at the TSS that is four-fold higher than binding within the gene body C. elegans. This pipeline is designed to take advantage of the stability of fosmid-based transgenes, as well as their reliability in reproducing native expression patterns. The transgenic lines emerging from this pipeline tend to have between one and three copies of the transgene, and exhibit minimal, if any, over-expression . Our initial trials with the RNA polymerase II subunit AMA-1 indicate that the transgenic, tagged version of a transcriptional regulator can indeed successfully recapitulate the DNA binding properties of the native factor. This pipeline can now be used on additional factors, and because the same antibody is used for every immunoprecipitation, will provide fairly uniform investigation of the binding sites of multiple factors, and aid in the dissection of regulatory networks in development.We have established a pipeline to identify transcription factor binding sites in vivo in As a first step toward this major goal, we identified candidate gene targets of PHA-4 in vivo at two distinct developmental stages. We chose PHA-4 as the initial factor for binding site identification for three primary reasons. First, it is a well-characterized factor with fundamentally important, yet distinct, functions at different times in development. Second, a handful of direct transcriptional targets of PHA-4 have been independently identified and validated, providing some key positive controls. Finally, PHA-4, unlike AMA-1, is expressed tissue-specifically, primarily in digestion-related tissues such as the pharynx and intestine. Thus, it provides a test case for whether ChIP can be performed on transcription factors with restricted expression.A little over half of the PHA-4 targets we identified are in common between these two stages, suggesting that PHA-4 does have a general function in regulation of gene expression. However, over 40% are preferentially bound in one stage relative to the other, indicating that the ability of PHA-4 to mediate different processes likely occurs through a shift in the sets of targets it regulates. These data indicate that transcription factors can have diverse and key roles in distinct biological processes and underscore the importance of identifying binding sites under multiple conditions.Several interesting differences in PHA-4 binding were noted between the two stages. For instance, among the many examples listed, several genes encoding members of the dosage compensation complex were preferentially bound by PHA-4 in embryos relative to L1s. During embryogenesis, PHA-4 helps specify the pharynx at the same time that the dosage compensation complex (DCC) is beginning to implement a two-fold reduction of transcription levels from the entire X chromosome. Little is known about how the dosage compensation complex interacts with tissue-specific programs, and our data suggests that PHA-4 helps to control the levels of the DCC in order to provide more or less dosage compensation in that tissue as needed. Possibly, master regulators in other tissues also regulate DCC levels in order to bring the level of dosage compensation in alignment with the needs of a specific tissue.C. elegans is much expanded relative to other organisms, and many of the ligands for these proteins are unknown. It is possible that a subset of these proteins respond to endogenous steroid hormones generated in response to starvation, and that PHA-4 mediates their induction.We have also demonstrated a novel role for PHA-4 in promoting the survival of larvae during starvation. Reduced PHA-4 levels resulted in decreased survival, while conversely expression of PHA-4:GFP in a wild type background increased survival. In particular, the increased survival indicates that the role of PHA-4 in this process is a regulatable function. This function is in keeping with its noted role in regulating environmental responses, as well as controlling longevity and dauer formation C. elegans.Overall, the experimental ChIP-Seq pipeline we developed has produced global binding data, expanding the view of how PHA-4 works as both a master regulator of organ development and a mediator of starvation survival. PHA-4 primarily functions as an activator in both situations, based on our analysis of gene expression concomitant with binding analysis. It is likely that the different binding patterns of PHA-4 are mediated by potential cofactors such as SMK-1 pha-4 or ama-1 locus, along with flanking regions, was selected from an available fosmid library (http://eleans.bcgsc.bc.ca/). Using recombineering unc-119 was placed into the backbone of the fosmid . The fosmid clones containing the tagged genes were then prepped, and introduced into unc-119(ed3) mutant worms using microparticle bombardment A 30–40 Kb fosmid containing the entire 5′-TAATACGACTCACTATAGGAATTTTCTGTCAGTGGAGAGGGTG-3′ and 5′-TAATACGACTCACTATAGGTCCATGCCATGTGTAATCCCAG-3′ and amplified from bSEM538(pPD126.25). Primer sets for PHA-4 were 5′-TAATACGACTCACTATAGG-3′ and 5′-TAATACGACTCACTATAGGGATCCAACATCCATCACGACC-3′ and amplified from bSEM865. In vitro transcription was performed using PCR products as template with the Ampliscribe T7 Transcription Kit (Epicentre Biotechnologies). RNA was then treated with DNase and extracted using phenol/chloroform and ethanol precipitation. RNA was resuspended in a final concentration of 2 ug/ul.For starvation assays with PHA-4:GFP young embryos were released by bleach treatment and placed into modified S basal medium at 20°C (day zero). Three samples of 30 ul each (representing over 500 worms) were removed daily and plated with food to determine how many animals could mature beyond the L1 stage after two days incubation. For starvation assays using RNAi, embryos were incubated in dsRNA according to Ahringer Gravid hermaphrodites were bleached and embryos harvested and diluted to 100 embs/ul. In one PCR tube 2 ul RNAi soaking buffer , 8 ul dsRNA at 2 ug/ul and 1 ul of embryo suspension was added. Three tubes per sample per day were prepared. Worms were incubated at 20°C for appropriate number of days. Day one was 24 hours after bleaching. To determine viability, three samples were taken and put onto plates with OP50 and are counted for worms bigger than L1 stage 2 days later. Variability in the number of worms per plate occurs because of pipetting variability, so numbers can go above 100% for one plate vs. the starter plate. The difference in buffers between the two types of starvation assays altered the survival times of worms in the two assays; animals incubated in RNAi buffer survived longer than in S basal.Liquid culture of worm strains was performed as described 2O. A 5 ul aliquot of the input DNA was then run on a 2% agarose gel to check the extent of shearing, with an expected range between 200–800 bp. The immunoprecipitated DNA was either interrogated by qPCR or subjected to high-throughput sequencing library preparation (below). All ChIP experiments were completed with two or more biological replicates.Chromatin immunoprecipitation was performed as described Immunoblotting was performed on worm lysates as well as immunoprecipited TF/DNA complexes. Immunoblot analysis of immunoprecipitated AMA-1:GFP and PHA-4:GFP was performed on non-crossed-linked worm lysates that had been subjected to the ChIP protocol until the multiple wash steps. Then 50 ul lysis buffer was added to the immunocomplex bound beads, and the beads were boiled for 5min before loading onto the gel. Ready Gel Precast Gels (4–15% polyacrylamide) from Bio-Rad Laboratories were used according to manufacturer's instructions. For AMA-1:GFP detection, anti-GFP goat polyclonal antibody was used, and for PHA-4:GFP detection anti-GFP from Roche (cat# 11814460001) was used, along with the species-appropriate secondary antibodies.To monitor enrichment of known or newly identified target genes, qPCR amplification of ChIP DNA was performed. Primers used are described in The protocol for library preparation was adapted from the protocol “Preparing Samples for Sequencing Genomic DNA” by Illumina, and optimized with the following alterations. ChIP DNA was end-repaired using the ‘End-It DNA End Repair Kit’ from Epicentre, Cat#ER0720, then an ‘A’ base was added to the 3′ ends of the ChIP DNA using Klenow . The ChIP DNA was then ligated with the adapter mix from the Illumina kit using LigaFast from Promega (Cat#M8221). The DNA was then purified using the QIAquick PCR Purification Kit and protocol between each step. The DNA was isolated from a 2% Invitrogen E-gel (Invitrogen Cat# G5018-02) by cutting a gel slice between 150∼350 bp, which excludes adapter-adapters migrating at ∼120 bp. The DNA was then purified from the gel slice using the Qiagen Gel Extraction Kit, and subjected to PCR amplication with Phusion DNA polymerase (NEB Cat# F-531) and Illumina primers using the following PCR protocol: 30 sec at 98°C,  for 16 cycles, followed by 5 min at 72°C. The DNA was then purified on a QIAquick MinElute column and the 150∼350 bp band gel-isolated. Out of a 20 ul elution, 2 ul were used to measure the DNA concentration (ng/ul) and A260/A280 using a Nanodrop spectrophotometer. DNA with >5 ng/ul concentration is now ready for sequencing.Worms were grown to the desired stage and pelleted as described above. Total RNA was extracted by TRIzol (Invitrogen) according to the manufacturer's protocol (TRIzol: pellet = 2∶1). PolyA RNA was purified using the Applied Biosystem (Ambion) MicroPoly(A) Purist kit. PolyA RNA was fragmented using Fragmentation Reagent (Ambion). First strand cDNA was synthesized from polyA RNA using a mixture of oligo dT and random primer (Invitrogen). Double stranded cDNA synthesis was performed using the SuperScript double stranded cDNA synthesis kit (Invitrogen). RNA-Seq libraries were prepared for sequencing using the Illumina protocol as described To assess the expression level of a given transcript, the DCPM (average depth of coverage per million reads) is calculated from RNA-Seq using a published method C. elegans. The annotation of the genome includes 27,322 transcripts , which were confirmed from a previous study All mapping and analysis are based on genome WS170 of C. elegans genome using Illumina's ELAND program in standalone mode. For each sample, the numbers of total and mapped reads were determined  was used to view images of signal tracks and to overlay them onto the In order to show the concordance of two antibodies (anti-GFP and anti-Pol II) for the AMA-1 binding experiments, we compared the hits from PeakSeq with p value cut-off 0.001. Every PeakSeq hit was divided into 600 bp bins. Then the tag count of each bin was normalized against its background input. The normalized tag counts of two antibodies were correlated significantly .All ChIP-Seq datasets have been submitted to GEO , and all tracks are available for viewing at the modENCODE website , and the least likely are those that are upstream of the binding site (if multiple targets are upstream they are ranked by their distance). The targets are then grouped into the following four bins: (1) target genes which have an internal binding site or that are less than 2kb downstream of the binding site, (2) targets that are within 2kb–5kb downstream, (3) targets that are less than 2kb upstream of binding site, and (4) targets that are within 2kb–5kb upstream. Finally, the binding site is said to target all genes in the first non-empty bin. Examples of how assignment of a binding site to candidate target genes occurs are shown in The high genic density of the To determine whether Pol II is stalled in a gene, we created a differential signal map by subtracting the tag count of the factor from that of the input at each position. This map was used to calculate the average tag count for promoter regions and over the bodies of transcripts. For this analysis, the promoter region is defined as ±300 bp from the TSS. The transcript body is the region 600 bp downstream of the TSS to the end of the transcript. If the ratio of promoter∶body average transcript count is greater than 4, Pol II is considered stalled. For lower ratios, Pol II signal is deemed to be either uniform or absent depending upon whether Peak-Seq detected Pol II enrichment in the transcript. This is the same method used by Zeitlinger et al. −5, was used to define the genes targeted by PHA-4 in embryos and starved L1 stages (http://gostat.wehi.edu.au/cgi-bin/goStat.pl) was used for finding the over-represented and under-represented GO terms ). The second most conserved sequence is TGTBTSY , which is compatible with the published motif, TRTTKRY . The reverse-complementary sequence of TGTBTSY is shown in the figure of embryos. The enrichment of this motif in embryos is 3.2. In starved L1, TRTTKRY compatible motif is ranked at the top, with an enrichment of 2.4.(1.04 MB EPS)Click here for additional data file.Figure S6Examples of PHA-4 binding sites at individual loci. Genes associated with autophagy are shown. ChIP-Seq data acquired with anti-GFP antibody is shown in green and the input signal is shown in blue. (A–C) PHA-4:GFP binds at the promoters of bec-1, lgg-1, and unc-51 at a very high level in starved L1 animals as compared to its binding at the same promoter regions in embryos. (D) PHA-4:GFP binds to the promoter of gpd-2 in starved L1 animals, but it no longer binds to that promoter in embryos.(3.51 MB EPS)Click here for additional data file.Figure S7−6 to 1×10−3, each order of magnitude change in the cutoff changes the number of targets called by about 500. The number of binding sites also changes by about the same amount. For the analyses in this paper, a p-value of less than 1×10−5 was selected unless otherwise specified.Binding site and gene target identification at multiple cutoffs. Chart displaying the number of binding sites and targets as a function of p-value determined by PeakSeq. Genes are defined as PHA-4 targets if the binding site is within the gene or less than 2,000 base pairs upstream to the TSS (transcription start site). At each p-value cutoff to define binding sites, the target calling algorithm was run and the number of total targets for both embryo and L1 samples computed. At stringent cutoffs between 1×10(0.32 MB EPS)Click here for additional data file.Table S1Primer sets and fold enrichment of PHA-4 binding sites.(0.14 MB DOC)Click here for additional data file.Table S2GO analysis of unique PHA-4 target genes in embryos.(0.11 MB DOC)Click here for additional data file.Table S3GO analysis of unique PHA-4 target genes in starved L1s.(0.04 MB DOC)Click here for additional data file.Table S4Individual functional analysis of subset of named genes.(0.06 MB DOC)Click here for additional data file.Table S5Total number of mapped reads of ChIP-Seq experiments.(0.03 MB DOC)Click here for additional data file.Dataset S1Complete target list of PHA-4 in embryos.(0.04 MB XLS)Click here for additional data file.Dataset S2Complete target list of PHA-4 in starved L1s.(0.04 MB XLS)Click here for additional data file.Dataset S3List of subset of named gene targets.(0.04 MB XLS)Click here for additional data file.Dataset S4Complete target list of POLII stalling in embryos.(0.00 MB XLS)Click here for additional data file.Dataset S5Complete target list of POLII stalling in starved L1s.(0.00 MB XLS)Click here for additional data file.


Plasmodium-infected mosquito, 10 to 100 parasites are inoculated into the skin and a proportion of these migrate via the bloodstream to the liver where they infect hepatocytes. The Plasmodium liver stage, despite its clinical silence, represents a highly promising target for antimalarial drug and vaccine approaches. Successfully invaded parasites undergo a massive proliferation in hepatocytes, producing thousands of merozoites that are transported into a blood vessel to infect red blood cells. To successfully develop from the liver stage into infective merozoites, a tight regulation of gene expression is needed. Although this is a very interesting aspect in the biology of Plasmodium, little is known about gene regulation in Plasmodium parasites in general and in the liver stage in particular. We have functionally analyzed a novel promoter region of the rodent parasite Plasmodium berghei that is exclusively active during the liver stage of the parasite. To prove stage-specific activity of the promoter, GFP and luciferase reporter assays have been successfully established, allowing both qualitative and accurate quantitative analysis. To further characterize the promoter region, the transcription start site was mapped by rapid amplification of cDNA ends (5′-RACE). Using promoter truncation experiments and site-directed mutagenesis within potential transcription factor binding sites, we suggest that the minimal promoter contains more than one binding site for the recently identified parasite-specific ApiAP2 transcription factors. The identification of a liver stage-specific promoter in P. berghei confirms that the parasite is able to tightly regulate gene expression during its life cycle. The identified promoter region might now be used to study the biology of the Plasmodium liver stage, which has thus far proven problematic on a molecular level. Stage-specific expression of dominant-negative mutant proteins and overexpression of proteins normally active in other life cycle stages will help to understand the function of the proteins investigated.During the blood meal of a  Plasmodium parasite, the causative agent of the disease, has concentrated on the liver stage of the parasite Plasmodium liver stage being the main target of vaccine development against malaria and our knowledge of the biology of the parasite at this particular stage. To facilitate studies on the liver stage of development, we sought to generate a highly specific liver stage reporter.Malaria remains one of the main health burdens in developing countries, especially in sub-Saharan Africa. Much recent work on developing vaccines against the Plasmodium falciparumin vitro investigations thus far have only been conducted on the blood stage of the parasite. Recently, ApiAP2 regulators for sporozoite and ookinete development in P. berghei have been characterized, showing for the first time that there are stage-specific transcription factors governing parasite development P. berghei a liver stage-specific promoter and to verify its stage-specific expression using GFP and luciferase reporter assays.Transcriptomic and proteomic analyses of the parasite at various life cycle stages suggest stage-specific regulation of gene expression but nothing is known about the regulation of transcription during the liver stage. Recently, the ApiAP2 transcription factor family has been suggested to regulate stage-specific gene expression in the human parasite Plasmodium yoeliiP. berghei ortholog of PY05129, PB103464.00.0 (PBANKA_100300 in GeneDB), which we find to also be exclusively expressed during the mid to late P. berghei liver stage . We concluded that the minimal promoter of PB103464.00.0 is located within this region and cloned the −989/+1 gDNA fragment into a P. berghei transfection plasmid upstream of gfp  was chosen as a control for promoter activity  gene 103464RLef1a. As a control, a further plasmid was constructed in which both luciferase genes were under the control of the constitutive promoter (pFLef1aRLef1a)  a mixture of both. Transfection of a single plasmid carrying both luciferase genes has great advantages over traditional co-transfection of two plasmids each containing a single luciferase gene, which results in a mixture of single- and double-transfectants, meaning that cloning must be performed to produce a population where each plasmid is integrated only once. In P. berghei, such limiting dilution cloning requires the use of numerous mice. As transfection with the single plasmids described above results in parasites that contain equal copy numbers of each gene, this strategy greatly simplifies later analysis and also potentially saves large numbers of mice.Although the GFP expression findings supported our mRNA transcription studies, the analysis of GFP expression has its limitations as it does not allow an accurate quantitative analysis of promoter activity. We therefore decided to clone the promoter region in front of the firefly luciferase (FL) gene 103464RLef1α was absent during the blood and mosquito stage and was seen to only be high during the liver stage, confirming the GFP expression results and also the transcription profile of the PB103464.00.0 gene determined by RT-PCR . The PbFLef1αRLef1α parasites, in which both luciferase genes are independently expressed under the pbeef1αa promoter showed constitutive expression of both luciferase genes. Unexpectedly, however, the ratios of FL/RL expression varied at different life cycle stages. The reason for this variation is not clear but since both luciferase genes are transcribed under the control of the same constitutive promoter, it is likely that differing protein stability of the two luciferases at different life cycle stages is responsible.Using the above parasite strains, we determined the relative expression level of FL compared to RL in the blood stage, in oocyst and salivary gland sporozoites and in the liver stage (in infected hepatoma cells) at 48 hpi using a dual-luciferase assay , FL activity of the PbFL103464RLef1α parasites appeared to again decrease, probably reflecting the development of blood cell-infective merozoites.As an additional control, we decided to compare the liver stage-specific promoter to a promoter that is mainly active in another parasite stage. To this end, we first performed database searches and RT-PCR assays and identified PB000869.01.0 , as being expressed at a low level in the liver relative to other stages (data not shown). We cloned the 5′ upstream region of this gene in front of the FL resulting in the plasmid pFLPlasmodium mRNAs often contain long 5′ untranslated regions (UTRs), which are unlikely to provide potential binding sites for transcription factors we first identified the transcription start site (TSS) for PB103464.00.0. Using 5′ RACE technology to amplify the 5′ untranslated region . To analyze the effect of the individual binding sites it is important to determine the basal transcription in the absence of these sites. To this end the −318/+1 region was cloned in front of the FL gene in the dual luciferase plasmid (pFL103464(-318)RLef1α). Transfection of this plasmid into P. berghei resulted in the generation of the parasite strain PbFL103464(-318)RLef1α. This parasite strain did not show a significant FL activity in liver stage parasites (103464(−775)RLef1α to analyze whether the promoter region is positioned between −775 and +1. In this region two of the four predicted PB000252.02.0 ApiAP2 binding sites were found. Two additional sites were found between the excluded region −989 and −775 . We detected a significant but not complete reduction in FL activity in the PbFL103464(−775)RLef1α parasites compared to the PbFL103464RLef1α parasites, suggesting that both the excluded sequence −989/−775 and the −775/+1 region contain functional portions of the promoter. Deletion experiments do not allow the exact identification of transcription factor binding sites and therefore we mutated one predicted ApiAP2 binding site (at position −825/−818), with the sequence TAGAACA Having confirmed a strict liver stage-specific activity of the promoter region of the gene PB103464.00.0 (−989/+1) we sought to determine possible transcription factor binding sites in this region. Since arasites Figure 6Our data have identified a promoter region derived from PB103464.00.0 that is able to direct exclusively liver-stage expression of genes of interest. In future experiments we will investigate the role of the predicted transcription factor binding sites in more detail as well as seeking to identify additional sites by bioinformatic and experimental approaches.In vitro it is only possible to achieve relatively low rates of hepatoma cell infection by Plasmodium sporozoites, which makes biochemical analysis of the liver stage very difficult. Luciferase reporter assays have proved to be extremely useful for the detection of minute numbers of parasites in the blood of infected mice in vitro. Using this very sensitive technique, it is possible to analyze promoter activity of any given gene in all life cycle stages.Several liver stage-specifically expressed genes have been described in the literature Plasmodium parasites have been seen to use other cis-regulatory elements around the TSS, in introns and in the 3′ region of genes to control mRNA expression The results of this study verified that the −989/−318 promoter region of PB103464.00.0 is sufficient for gene expression to be restricted to the liver stage. This is perhaps surprising since We further showed that the deletion of the −989/−775 region caused a significant reduction in but not complete abolishment of luciferase expression, suggesting that the minimal promoter includes distantly situated motifs. Interestingly, the deletion did not result in an altered expression profile in other parasite stages indicating that the remaining −775/+1 region is sufficient to guarantee liver stage-specific expression, albeit at a reduced level.P. falciparum protein PF11_0404. Two were found in the −989/−775 region and the two others in the −775/−318 region. It has been suggested that ApiAP2 transcription factors are involved in stage-specific gene regulation since several P. falciparum ApiAP2 proteins show no detectable gene expression during the blood stage P. falciparum are expressed additionally in the asexual stages, implying that they have roles across diverse stages. Of course, it is possible that other transcription factors might also be involved in regulating expression via the −989/+1 region, including the canonical TATA-box-binding protein that has been identified in the P. falciparum genome Bioinformatic analysis of the entire −989/−318 region revealed the existence of four putative binding sites that could be recognized by the ApiAP2 protein PB000252.02.0, based on homology with the A systematic dissection of the PB103464.00.0 promoter region is a major undertaking since it includes the generation of numerous parasite strains, which must all be generated by transfection of blood stage schizonts, requiring many mice. Additionally, the parasites need passage through mosquitoes before they can finally be used to infect hepatic cell lines. Sequential deletion of promoter regions will provide useful information about the possible transcription factor binding sites. However, since our results suggest that several regions are likely involved in regulating expression and because deletions affecting the distance of putative elements could disturb the functionality of putative control elements, other techniques such as linker scanning approaches may also have to be applied Proteins expressed solely at the liver stage are themselves interesting for study and might be useful candidates for subunit vaccine approaches. These proteins are likely to reveal novel liver stage-specific pathways or metabolic processes that could be targeted to eliminate or attenuate the parasite during this stage. For example, it has recently been demonstrated that fatty acid metabolism is essential only for liver stage parasites but not for other stages Plasmodium liver stage, it is essential to analyze the functions of proteins expressed at this stage. To this end reverse genetics stands out as an excellent tool, although its utility is frequently complicated in Plasmodium. Transfection must be performed during the blood stage and any genes with an essential function here cannot be targeted by traditional knockout approaches Plasmodium falciparum blood stage parasites P. berghei will have a great impact in the analysis of the parasite liver stage, an area fundamentally lacking in understanding.To better understand the biology of the Mice used in experiments were of the NMRI strain, between 6 and 10 weeks of age and were bred in-house at the Bernhard Nocht Institute for Tropical Medicine  or supplied by Charles River Laboratories. All animal work was conducted in compliance with regulations created and approved by the ethical committee of Hamburg state authorities (Nr. FI 28/06).5′-AACAGCAATATATCGTCACCAAG-3′ and 5′-GCACACGGAAATCATTTTGTT-3′. As in internal control, P. berghei tubulin cDNA was amplified using the primer 5′-TGGAGCAGGAAATAACTGGG-3′ and 5′- ACCTGACATAGCGGCTGAAA-3′.Total RNA was isolated from 0.05% saponin-treated (Sigma) blood stage parasites, 20 infected mosquito midguts day 14 after infection and infected HepG2 cells 48 hours after infection using the NucleoSpin® RNA Extract Kit II (Macherey-Nagel). First strand cDNA was synthesized using random primers (Invitrogen) and Superscript™II reverse transcriptase (Invitrogen) according to the manufacturer's instructions. Target cDNAs were amplified using GoTaq® DNA polymerase (Promega) and the following primer sets: 103464 was determined by 5′ rapid amplification of cDNA ends (5′-RACE) based on the CapFinder method by Schramm et al., 2000 P. berghei infected HepG2 cells isolated 48 hpi  was reversed transcribed by Superscript™II (Invitrogen) using a gene-specific primer R197 5′-ACATCCGTATTTTTCCTATTGACA-3′ and the CapFinderB 5′-TGCTGTTGTATTTTTGTTTTTCATC-3′ and the 5′-Primer The transcription start site (TSS) of the promoter region 2 cell incubator and split every 3–4 days by trypsinization.Human hepatoma cells (HepG2) were obtained from the European cell culture collection and were maintained in complete MEM (cMEM) with Earle's Salts Medium supplemented with 10% heat-inactivated FCS , 1% L-Glutamine, 1% penicillin/streptomycin . Cells were kept at 37°C in a 5% CO5 HepG2 cells were seeded into glass bottom dishes  for live cell imaging or 5×104 HepG2 cells into each well of a 24 well plate. Sporozoites were prepared from dissected salivary glands of P. berghei-infected Anopheles stephensi mosquitoes and incubated in media with HepG2 cells for 1–2 hours. After washing, the cells were incubated with cMEM, as described above, containing Amphotericin B at 2.5 µg/ml  at 37°C and 5% CO2 for indicated times.1×102.Live imaging was performed with a Zeiss Axiovert 200 inverted microscope and images taken and processed with the Improvision software Openlab 5.0.1. Cell and parasite DNA staining was carried out by incubation with 1 µg/ml Hoechst 33342 (Sigma) for 20 min at 37°C and 5% COP. berghei blood stages, tail blood was taken from an infected mouse, mixed with room temperature cMEM (see above) containing 1 µg/ml Hoechst 33342 (Sigma) and microscopically analyzed. Midguts of infected A. stephensi mosquitoes were dissected for live imaging and microscopically investigated.For live imaging of P. berghei lines, 10 µl of tail blood of an infected mouse was lysed for 15 min at 30°C with 100 µl 1x Passive Lysis Buffer (PLB) obtained from the Dual-Luciferase® Reporter (DLR™) Assay System (Promega). For measuring luminescence in the mosquito stage of the parasite, 5 midguts (day 14 after infection) or salivary glands of three infected A. stephensi mosquitoes were removed and lysed with 100 µl 1x PLB as above. For analyzing the liver stages of the transgenic P. berghei lines, HepG2 cells were infected with sporozoites (see above). At different time points after infection the culture medium was removed and the cells washed once with PBS, before lysis in 100 µl 1x PLB for 15 min at 30°C. Samples were processed according to the protocol of the kit. Briefly, after centrifuging the samples for 30 s at 12,000 g, 20 µl of the supernatant was added to 100 µl of Luciferase Assay Reagent II. Luminescence was measured in a single tube Junior LB 9509 luminometer (Berthold Technologies). After a 10 second measurement period 100 µl 1x Stop & Glo® Reagent was added to the tube to stop the firefly and activate the Renilla luminescence. The output of the luciferase assays was in relative light units (RLU). All assays were performed in triplicate. Either uninfected mosquitoes or HepG2 cells were used as negative controls, as appropriate. Samples can be collected and stored at −20°C to perform one combined dual luciferase assay.To determine the blood stage luciferase expression in the transgenic Renilla luciferase RLUs indicated the activity of the promoter of interest. Promoter activity curves were generated and statistical analysis of the data performed using MS Office Excel and the GraphPad Prism software . Significance levels were calculated with two-tailed unpaired t-tests.For calculation of the promoter activity, the mean RLU value of control samples was subtracted from the mean RLU value of experimental samples. The ratio of the firefly and the GATATCGTTGCATTATCGTCAAAAGTG-3′5′-CG and the reverse oligonucleotide GGATCCTTTTTATGTGTAAAAAAGTAAAATGATT-3′5′-CG were used to amplify a fragment of 989 bp by PCR using Phusion® Taq High-Fidelity DNA polymerase (Finnzyme) from P. berghei gDNA . The promoter region of PB103464.00.0 was used to replace the pbeef1αa promoter in EcoRV-BamHI-digested pL0017 vector (obtained through the MR4 (MRA-786), deposited by C. Janse) to create the plasmid pGFP103464.For analyzing the promoter region of PB103464.00.0, the forward oligonucleotide Renilla (RL) luciferase were generated. The firefly luciferase gene was amplified by PCR from pBI-GL (Clontech) and was used to replace the GFP in the pL0017 vector to generate pFLef1α. The same procedure was performed to generate the plasmid pRLef1α, amplifying the Renilla luciferase (RL) gene by PCR from phRL-CMV (Promega). The pbeef1αa promoter of the pFLef1α plasmid was replaced with the promoter region of PB103464.00.0 to create plasmid pFL103464. For the generation of the double-luciferase plasmid, the entire cassette for RL expression under the control of the pbeef1αa promoter (including the 3′ UTR of Pbdhfr) was amplified by PCR and ligated into pFL103464 and pFLef1α plasmids to generate pFL103464RLef1α and pFLef1αRLef1α, respectively.For the dual-luciferase assay, plasmids with the firefly (FL) and the 869RLef1α was generated similarly having first amplified fragment 869, a 1 kb fragment upstream of PB000869.01.0, by PCR using the primers 5′-GGCCGCGGCCGCGTCTAAAGCATACAATAACTCTTAC-3′ and 5′-CTAGCCTAGGTTTGTATATTTCTGAGATTCCAAAAAAA-3′.The plasmid pFL5′-CGGGATCCTTTTTATGTGTAAAAAAGTAAAATGATT-3′ and either the forward primer GCGGCCGCAAAATAAAACGAATAACGATGTGA-3′5′-GC (truncation -775/+1) or GCGGCCGCATATAAAAAACACACTAAAAATATATAATTAAAT-3′5′-GC (truncation −318/+1) (underlined nucleotides represent NotI restriction site). Mutagenesis PCR was performed to mutate the putative ApiAP2 binding site at −825/−818 of the 103464 promoter from TAGAACAA to TTATTATT. The truncated and mutated promoter fragments were used the replace the original promoter region of PB103464.00.0 in the plasmid pFL103464RLef1α and transfection resulted in the parasites PbFL103464(−775)RLef1α, PbFL103464(−318)RLef1α and PbFL103464(*825)RLef1α. For further analysis of the 103464 promoter region, the 5′-truncation fragments of the promoter were obtained by PCR using the reverse primer P. berghei schizont stages (ANKA strain) were transfected with ApaI-SacII-linearized plasmid DNA (5–10 ng). Transgenic parasites were selected by pyrimethamine treatment Figure S1Detailed cloning strategy for testing activity of the PB103464.00.0. promoter region. The entire region between gene PB103463.00.0. and PB103464.00.0. was cloned in the plasmid pL0017 in front of the gfp cDNA.(0.08 MB TIF)Click here for additional data file.Figure S2P. berghei ApiAP2 transcription factors, the P. falciparum ApiAP2s, which would bind the indicated sequences are depicted.DNA sequence of the PB103464.00.0. promoter region. The transcription start site at position -318 and potential ApiAP2 binding sites are labeled in colours. Since no data are available on (1.30 MB TIF)Click here for additional data file.


We previously reported the efficacy of nonmyeloablative allogeneic transplantation in 2 HIV positive recipients, one of whom received retrovirus transduced hematopoietic stem cells to confer resistance to HIV. Here we report an assessment of retroviral integration sites (RISs) recovered out to 3 years post-transplantation. We identified 213 unique RISs from the patient's peripheral blood samples by linear amplification-mediated PCR (LAM-PCR). While vector integration patterns were similar to that previously reported, only 3.76% of RISs were common among early (up to 3 months) and late samples (beyond 1 year). Additionally, common integration sites were enriched among late samples . Three RISs were found near or within known oncogenes, but 2 were limited to early timepoints. Interestingly, an integration site near the MDS1 gene was detected in long-term follow-up samples; however, the overall contribution of MDS1 integrated clone remained stably low during follow-up. LMO2 gene in patients treated for severe combined immunodeficiency MDS1-EVI1, PRDM16, or SETBP1 integration containing myeloid cells observed in patients treated for chronic granulomatous disease using a similar approach Mds1/Evi1 gene MDS-EVI1 translocation 3∶21 found in human acute myelogenous leukemia (AML) The establishment of safe and effective vector delivery systems for gene therapy applications appears achievable; however, the adverse events reported from recent gene therapy trials have lead to a reassessment of the risks associated with vector insertional mutagenesis TasI enzymes and TaiI enzymes were used , located in a region of frequent homozygous deletions in tumor samples ARL11), a genetic variant of which predisposes to familial cancerMDS1 .We found a total of 15 common integration sites . As the frequency of CISs increased in late phase populations, these results suggest that integrations at CISs dominate gene-modified long-term hematopoiesis. These observations after long term follow-up in a human gene therapy trial are in agreement with an emerging theory that vector integrations may serve as a tool to query genes involved in hematopoiesis in vivo We found total of 15 common integration sites (CISs) . None of the CISs were near or within known oncogenes. Only 14.9% (20 of 134 early RISs) were CISs, while 36.8% (32 of 87 late RISs) were CISs  gene-therapy clinical trials could in part be explained by a lower infused cell dose along with the disease context MDS1 region occurred in a LT-HSC and though theoretically it might impact engraftment or survival of the LT-HSC, it did not result in an abnormal proliferation, clonal expansion, or oncogenesis in our patient. Recent reports In contrast, the clonal dominance of In summary, the retroviral integration pattern observed in our HIV gene therapy trial is similar to that previously observed in model systems and human clinical trials, yet several novel observations warrant emphasis. The pattern of contribution by genetically modified cells is distinct between the early and late phase post transplantation and emphasizes the importance of long-term studies to assess the risk of integrating vectors. Additionally, the enrichment for CISs in the late phase supports the concept that integrations in the LT-HSCs favors genes that may be involved in “stemness” www.clinicaltrials.gov (NCT 00005785), and are described here briefly. An HIV positive patient with treatment-related AML underwent nonmyeloablative allogeneic transplantation from an HLA-matched sibling. Half of the donor cells were genetically modified with a Moloney murine leukemia virus (MoMLV) based HIV resistance vector containing a transdominant negative mutant Rev (TdRev) 8 cells) or a control vector MoMLV based vector encoding gp91phox (4.04×108 cells). The transduction efficiency was estimated by PCR, with 80% efficiency achieved from the TdRev aliquot and 90% for the gp91phox aliquot 3 long-term while continuing on the same highly active antiretroviral therapy (HAART) regimen until her death from thrombotic thrombocytopenic purpura 3 years and 4 months post transplant. Vector-transduced cells remained detectable at low levels. DNA was isolated from patient blood sample as previously described phox and TdRev vectors in both lymphoid and myeloid cells at extended follow up The protocol was approved by the Institutional Scientific Review Committee and the Institutional Review Board of the National Heart, Lung, and Blood Institute, the Recombinant DNA Advisory Committee, and the Food and Drug Administration. All the study subjects gave written informed consent. The study design and outcome have been previously published To identify genomic-proviral integration sites, LAM–PCR was performed as previously described MDS1, PCR was performed on 10 ng DNA using the primer set in MDS1 integrated clone's contributions over time after engraftment was determined by Real-time PCR analysis (QPCR) with Taqman probes as previously described To confirm the presence of an insertion near Table S1(0.04 MB DOC)Click here for additional data file.Table S2(0.13 MB DOC)Click here for additional data file.Table S3(0.09 MB DOC)Click here for additional data file.Table S4(0.04 MB DOC)Click here for additional data file.


Immunoprecipitated crosslinked protein-DNA fragments typically range in size from several hundred to several thousand base pairs, with a significant part of chromatin being much longer than the optimal length for next-generation sequencing (NGS) procedures. Because these larger fragments may be non-random and represent relevant biology that may otherwise be missed, but also because they represent a significant fraction of the immunoprecipitated material, we designed a double-fragmentation ChIP-seq procedure. After conventional crosslinking and immunoprecipitation, chromatin is de-crosslinked and sheared a second time to concentrate fragments in the optimal size range for NGS. Besides the benefits of increased chromatin yields, the procedure also eliminates a laborious size-selection step. We show that the double-fragmentation ChIP-seq approach allows for the generation of biologically relevant genome-wide protein-DNA binding profiles from sub-nanogram amounts of TCF7L2/TCF4, TBP and H3K4me3 immunoprecipitated material. Although optimized for the AB/SOLiD platform, the same approach may be applied to other platforms. ChIP-seq has become the method of choice for studying functional DNA-protein interactions on a genome-wide scale. The method is based on the co-immunoprecipitation of DNA binding proteins with formaldehyde cross-linked DNA, followed by deep-sequencing of the immunoprecipitated chromatin fragments. This allows for the genome-wide identification of binding sites with high accuracy To address these limitations we applied a strategy with a first gentle shearing step before immunoprecipitation and a second more intensive shearing of purified de-crosslinked DNA after immunoprecipitation to additionally fragment all material into small fragments suitable for next-generation sequencing. We have optimized our protocols for sequencing on the SOLiD/AB platform, with an optimal fragment size of 100–200 bp, but this size range can be adapted at will. Furthermore, we show that the size range after the second fragmentation step is so narrow that it is possible to skip a laborious size selection in the library preparation procedure.To demonstrate general utility, we performed ChIP-seq according to this protocol for well-characterized factors such as TBP, H3K4me3, and TCF7L2/TCF4, one of the members of the Tcf/Lef family of Wnt pathway effectors When shearing cross-linked DNA, a significant part of cross-linked chromatin remains too long for direct processing for next-generation sequencing, irrespectively of the fragmentation procedure . As a coThree independent TCF4 ChIP samples obtained from the human colon cancer cell line Ls174T were prepared at different time points as described previously The results from all libraries showed a strong overlap with each other and with a previously published set of peaks that were obtained by ChIP-on-chip To demonstrate general utility of the described method we processed chromatin immunoprecipitation samples of TATA-binding protein (TBP) and H3 lysine 4 tri-methylation histone mark (H3K4me3) in the same way . Since vThe double fragmentation ChIP-seq approach was found to provide a very high resolution with clear substructures in the larger peaks . As the Indeed, we found that the substructure pattern readily allows for the identification of TCF4 binding positions . IndividCisgenome To explore the evolutionary conservation of the observed TCF4 binding sites we used the phastCons In contrast to ChIP-chip, ChIP-seq has a very high dynamic range and allows for semi-quantitative estimation of DNA-protein interaction strength (as a function of the number of sequencing reads which mapped to the binding region) The genome-wide distribution of TCF4 binding sites with respect to TSS of the nearest gene shows a similar distribution as previously reported Starting from sub-nanogram amounts of immunoprecipitated chromatin we show that the double-fragmentation ChIP-seq protocol allows for the accurate determination of genome-wide binding patterns at high resolution. We show that the method is highly reproducible and versatile and can serve as an alternative for current ChIP-seq protocols especially when limited amounts of immunoprecipitated material are available. Although optimized for the AB/SOLiD platform, shearing settings could be adjusted for the optimal size range for other platforms (e.g. Illumina/Solexa) as well. Most importantly, the biological relevance of the resulting datasets was firmly demonstrated by in-depth analysis of TCF4 binding regions.Ls174T human colon cancer cells carrying an activating point mutation in beta-catenin were used throughout this study. Ls174T-L8 cells carry a doxycyclin-inducible dominant-negative TCF4 transgene; Ls174T-pTER-β-catenin cells carry a doxycyclin-inducible shRNA against β-catenin; they allow for complete and specific blocking of the constitutively active Wnt pathway 6 cells with 150 µl of protein G beads (Upstate). The beads were successively washed 2 times with buffer 1 , one time with buffer 2 , one time with buffer 3 , and two times with buffer 4  for 5 min each at 4°C. The precipitated chromatin was eluted by incubation of the beads with elution buffer  at room temperature for 20 min, the eluted fraction was reconstituted to 0.3% SDS with ChIP incubation buffer and the immunoprecipitation repeated with half the amount of antibody. After washing and elution, the immunoprecipitated chromatin was de-cross-linked by incubation at 65°C for 5 h in the presence of 200 mM NaCl, extracted with phenol-chloroform, and ethanol precipitated. Measurement of chromatin concentration was done by high-sensitivity Qubit quantitation (Invitrogen).Chromatin immunoprecipitation was performed as described previously 2, 0.1 mM CaCl2, 10 mM Tris, pH 7.5) and digested with 0.5 mU of DNaseI for 5 minutes at room temperature. The reaction was stopped by adding EDTA to a final concentration of 50 mM. Chromatin was immediately extracted using phenol/chloroform and precipitated. After fragmentation, the fragments were blunt-ended and phosophorylated at the 5′ end using the End-it Kit (Epicentre) according to the manufacturer's instructions. Ligation of double stranded adapters compatible with SOLiD sequencing was performed using Quick ligation kit (New England Biolabs) with 750 nM P1 and P2 double-stranded adaptors (Applied Biosystems), 11.7 µl of 2× Quick ligation buffer, 1 µl Quick Ligase in a total volume of 23.4 µl. Samples were purified using Ampure beads (Agencourt) and separated on a native 6% polyacrylamide gel. Fragments ranging from 140 to 190 bp were excised; the gel piece containing the selected DNA fragments was shredded and dispersed into 400 µl of Platinum PCR Supermix with 750 nM of each P1 and P2 PCR primer, 2.5 U of Pfu (Stratagene) and 5 U Taq (Bioline). In case of TBP and H3K4me3 samples, the acrylamide gel-based size selection step was skipped and the adapter-ligated library was directly further processed by PCR. Prior to ligation-mediated PCR the sample was incubated at 72°C for 20 minutes in PCR mix to let the DNA diffuse out of the gel and to perform nick translation on non ligated 3′-ends of DNA fragments. After 17 cycles of amplification the library was purified using Ampure beads and was quality checked on 2100 Bioanalyzer (Agilent) for the absence of possible adapter dimers and heterodimers. Concentration of double-stranded DNA in the final sample was determined by Qubit fluorometer (Invitrogen).Immunoprecipitated chromatin was dissolved in 100 µl of 10 mM Tris pH 8.0 buffer and sheared for a second time for 6 minutes using the Covaris sonicator  to obtain suitable shorter fragments (75–125 bp). To exclude a shearing bias as a possible source of the observe binding site substructure, half of TCF4 Sample 3 was processed with partial digestion using DNaseI as an alternative to shorten the fragments for one control ChIP-seq library and one input library. The second half of the sample was processed without second fragmentation. For DNaseI treatment, chromatin was resuspended in 45 µl of freshly prepared reaction buffer (10 mM MnCl2 and 1.6 billion SOLiD sequencing beads (Applied Biosystems). PCR mix was added to SOLiD ePCR Tube containing 9 ml of oil phase and emulsified using ULTRA-TURRAX Tube Drive (IKA). Emulsion was dispensed into 96-well plate and cycled for 60 cycles. After amplification emulsion was broken with butanol, beads were enriched for template positive beads, 3′-end extended and covalently attached onto sequencing slides. Four physically separated samples were deposited on one sequencing slide and sequenced using standard settings on the SOLiD system version 2 to produce 35 nucleotide long reads. TBP and H3K4me3 libraries were sequenced using AB/Solid version 3 to produce 50 bp long reads.To achieve clonal amplification of library fragments on the surface of sequencing beads, emulsion PCR (ePCR) was performed according to the manufacturer's instructions (Applied Biosystems). 600 pg of double stranded library DNA was added to 5.6 ml of PCR mix containing 1× PCR Gold Buffer (Applied Biosystems), 3000 U AmpliTaq Gold, 20 nM ePCR primer 1, 3 µM of ePCR primer 2, 3.5 mM of each deoxynucleotide, 25 mM MgClSequencing reads were quality trimmed by clipping at 3 consecutive nucleotides with quality score less than 10. Reads shorter than 18 nucleotides were discarded and the remaining reads were mapped against the human reference genome  using SHRiMP package The Cisgenome software package de novo binding motif discovery, evolutionary conservation analysis and known motif mapping was performed using Cisgenome software packages The analysis of sequencing reads and TCF4 binding regions with respect to gene structure and distance to closest TSS, 6 Ls174T-L8 or Ls174T-pTER-β-catenin cells were grown in the presence or absence of doxycycline for 24 hours for Ls174T-L8 or 72 hours for Ls174T-pTER-β-catenin cells. Total RNA was extracted using TRIzol reagent (Invitrogen) according to the manufacturer's instructions. RNA concentration was determined using the NanoDrop ND-1000 and quality was determined using the RNA 6000 Nano assay on the Agilent 2100 Bioanalyzer (Agilent Technologies). For Affymetrix Microarray analysis, fragmentation of RNA, labeling, hybridization to HG-U133 Plus 2.0 microarrays, and scanning were carried out according to the manufacturer's protocol (Affymetrix Inc.). The expression data were normalized with the MAS5.0 algorithm within the GCOS program of Affymetrix. Target intensity was set to 100 (α1 = 0.04 and α2 = 0.06). Changes in the expression (logfolds and significance of change) for each of the comparisons were determined using the ‘Comparison Analysis’ from the GCOS program. All data were summarized using custom build Perl scripts. Genes were divided into three categories according to microarray expression data. Wnt upregulated genes - genes significantly down-regulated after suppressing Wnt dependent transcription by both ways in LS174T cells, in all 3 biological replicates (n = 647), ii) Wnt downregulated genes - genes significantly up-regulated after suppressing Wnt dependent transcription by two ways in all 3 biological replicates (n = 576) and iii) non-Wnt-regulated genes - genes consistently without significant expression change after suppressing Wnt-dependent transcription (n = 3936) (Approximately 10 = 3936) .Table S1List of peak coordinates and ranks for TCF4, TBP, and H3K4me3 ChIP-seq experiments and Tcf4 up- and down-regulated genes.(XLS)Click here for additional data file.Figure S1Fifteen most overrepresented motifs found in Tcf4 binding regions.(DOC)Click here for additional data file.Figure S2Examples of de novo called motifs enriched in peaks.(DOC)Click here for additional data file.Figure S3Indirect immunoprecipitation of interacting regions.(DOC)Click here for additional data file.Figure S4Example of peaks called from Tcf4, TBP and H3K4me3 dataset.(DOC)Click here for additional data file.


Making the correct choice between transcription elongation and transcription termination is essential to the function of RNA polymerase II, and fundamental to gene expression. This choice can be influenced by factors modifying the transcription complex, factors modifying chromatin, or signals mediated by the template or transcript. To aid in the study of transcription elongation and termination we have developed a transcription elongation reporter system that consists of tandem luciferase reporters flanking a test sequence of interest. The ratio of expression from the reporters provides a measure of the relative rates of successful elongation through the intervening sequence.Size matched fragments containing the polyadenylation signal of the human β-actin gene (ACTB) and the human β-globin gene (HBB) were evaluated for transcription termination using this new ratiometric tandem reporter assay. Constructs bearing just 200 base pairs on either side of the consensus poly(A) addition site terminated 98% and 86% of transcription for ACTB and HBB sequences, respectively. The nearly 10-fold difference in read-through transcription between the two short poly(A) regions was eclipsed when additional downstream poly(A) sequence was included for each gene. Both poly(A) regions proved very effective at termination when 1100 base pairs were included, stopping 99.6% of transcription. To determine if part of the increased termination was simply due to the increased template length, we inserted several kilobases of heterologous coding sequence downstream of each poly(A) region test fragment. Unexpectedly, the additional length reduced the effectiveness of termination of HBB sequences 2-fold and of ACTB sequences 3- to 5-fold.The tandem construct provides a sensitive measure of transcription termination in human cells. Decreased Xrn2 or Senataxin levels produced only a modest release from termination. Our data support overlap in allosteric and torpedo mechanisms of transcription termination and suggest that efficient termination is ensured by redundancy. While it is unclear precisely what percentage of human RNA polymerases initiate and successfully complete gene transcription, live cell imaging has been used to estimate that it is on the order of 1% An elongating polymerase must maintain a balance between being too readily terminated such that it cannot reach the end of a gene, and being an unstoppable juggernaut. Continued transcription past the end of a gene is not desirable. When an RNAP II molecule in the cell engages in such nonproductive elongation, it not only wastes energy but also risks interfering with the expression of neighboring genes Currently, there are several models for polyadenylation associated transcription termination; the allosteric model, the torpedo model, and the combined allosteric/torpedo model. The original formulation of the allosteric, or anti-terminator model, posits that polyadenylation signals cause a change in the complement of anti-termination factors associated with RNAP II, making it more susceptible to termination in vitro. RNA labeled by RNAP II in this way is then hybridized to specific targets to assess the relative level of actively transcribing RNA polymerases within those regions at the time the nuclei were prepared 7 cells per sample and a strong promoter to work. Most single copy mammalian genes do not have expression levels sufficient to produce reliable signals Transcription termination is an important, yet under-studied aspect of gene regulation. In many cases, transcription elongation remains a rate-limiting step in gene expression. To some degree, the current shortage of information on transcription termination reflects the difficulties involved in its study. The classic standard of transcription elongation and termination research has been the nuclear run-on assay (NRO), in which engaged RNAP II complexes in prepared nuclei incorporate a radiolabeled rNTP as they “run-on” for some distance during incubation In short, transcription termination is an important step in gene expression, but can be difficult to measure in mammalian cells. To address this difficulty, we built a novel tandem reporter construct capable of assaying transcription termination from a single copy integrated into a human chromosome. The ratio of expression from the downstream reporter compared to the control reporter upstream provides a measure of the relative rates of successful elongation through the intervening sequence. Here we use this system to measure the efficiency of termination orchestrated by multiple elements contained within fragments of the human β-actin (ACTB) and human β-globin (HBB) terminator regions. We find that our system provides a sensitive ratiometric measure of transcription termination in live cells compatible with high throughput approaches.We sought to probe the relative contributions of the torpedo and allosteric models of transcription termination using this system. Our system did not support a dominant role for any model or factor tested, such as XRN2 or Senataxin, in termination mediated by HBB or ACTB sequences. Rather, our findings suggest a cooperative effect among multiple elements contribute to termination, with efficiency mediated by redundancy.We designed a tandem reporter construct to measure the rate of transcription termination in living cells. Our goal was to express two quantifiable reporters in tandem from an inducible promoter in a construct located within a single, unique chromosomal location. Transcription initiates at a tetracycline-inducible promoter, proceeds through the first reporter (FLUC), and then must traverse the test termination sequence before reaching the second reporter (hRLUC) . The 1.732 tract just 5′ of the self-cleaving ribozyme aids in translation of the 5′ FLUC expression cassette . FLUC functions as the control reporter and is expressed independently of the inserted sequence. The downstream hRLUC reporter lacks a 5′ cap but translation is aided by the presence of an internal ribosome entry site (IRES). Because a chromosomal location may more closely represent a native gene than would an episome or transient transfections, we adopted the Invitrogen Flp-In™ T-REx system. The constructs were introduced by the site-specific Flp recombinase into a single genomic location to make stable cell lines. The chromosomal location and orientation is consistent for all tested inserts, removing a potentially significant variable.The first reporter mRNA fragment contains firefly luciferase (FLUC) and has a 5′ cap but lacks a polyadenylation signal and hence, a poly(A) tail. An AThe constitutive expression of the tet-repressor in the T-REx HEK 293 cell line represses the construct promoter in the absence of tetracycline. To test the ability of a single integrated copy of the tandem construct to express both reporter genes simultaneously and reproducibly upon induction, extracts representing 15,000 cells from three independently isolated clonal lines bearing tandem reporters were assayed for luciferase activities . Extractin vitro transcription reactions by our group and others The self-cleaving hammerhead ribozyme used in these constructs has been shown to cleave itself efficiently during To test the effectiveness of our system in measuring transcription termination, we chose to use two well-characterized polyadenylation/termination regions of human origin. The relationship between transcription termination and polyadenylation has been well established in both the human β-globin (HBB) gene All the ACTB constructs showed a robust degree of transcription termination in our system. The TAN ACT1 construct contained only 400 bp of the ACTB poly(A) region, yet terminated over 98% of transcribing polymerases, as measured by the change in hRLUC/FLUC expression ratio compared to the tandem construct with the dsred tetramer control insert . The ACTHBB gene sequence that includes a putative co-transcriptional cleavage (CoTC) site Analysis of the human HBB poly(A) region showed a similar trend with increased termination correlating with increased sequence length . When thSince the shortest ACTB sequence that we tested, TAN ACT1, was very effective at terminating transcription elongation in just a few hundred basepairs, we decided to test a minimal polyadenylation signal (MnipA) derived from the core of ACTB. The 59 base-pair sequence contained the AATAAA hexamer signal, the poly(A) addition site and the most proximal downstream GT-rich tract. The MnipA sequence showed a 25% decrease from the TAN dsred control construct . MnopA, The ‘torpedo’ model of transcription termination, predicts that an exonuclease or helicase enters the nascent transcript at the poly(A) cleavage point and contributes to termination It has been demonstrated that the yeast homologue Rat1p prefers RNA with a 5′ monophosphate as a substrate, which explains why intact, capped messages are not a target Surprisingly, the presence of dsred sequence 3′ to the poly(A) regions decreased the effectiveness of transcription termination in all tested constructs . The effTo confirm that the luciferase reporters are representative of FLUC and hRLUC mRNA levels, and are not a reflection of changes in overall translation attributed to the addition of dsred sequence, we utilized real-time PCR to quantify luciferase mRNA . Our datTranscription termination in our constructs is generally less effective with the addition of the dsred sequence downstream, counter to what we expected if the Xrn2 ‘torpedo’ model was a major contributor to termination. In order to determine to what degree Xrn2 contributed to termination in our system, we used shRNA to knock down Xrn2 and evaluated the effects in our cell lines. Knockdowns in our cell lines were done using a commercially available expression plasmid (pLKO), and insert sequences developed by the RNAi Consortium (TRC) and chosen from the NCBI probe website  . Act1/dsWhile decreased Xrn2 does affect transcription elongation in some of our constructs, it provided only a modest increase in read-through, indicating a role for other proteins that are involved in transcription termination. Senataxin (Sen1) has considerable homology to Sen1p, a helicase essential for processing RNA in yeast Senataxin levels were also knocked down using pLKO and TRC shRNA sequences. Our available antibodies to human senataxin did not prove to be reliable in western blot applications, so we confirmed knockdown of senataxin using real-time PCR. Quantitative PCR indicated that senataxin levels in the shRNA treatment were less than 20% of pLKO.1 treated cells (16±3%). Knockdown of senataxin in the cell lines increased transcription elongation in the absence of the dsred spacer sequence for poly(A) containing constructs ACT1, HBB1, and HBB3, but not ACT3 . When a In sum, we have developed a system capable of probing template-mediated influences on the elongation/termination decision by RNAP II. As a test of this system, we measured the termination associated with two well-characterized polyadenylation signals. We compared defined regions surrounding the human β-actin and β-globin polyadenylation sites and confirmed that even short tracts were effective at terminating transcription. Using shRNA we knocked down two candidate proteins involved in transcription termination but only saw modest effects. While we had thought that addition of a length of heterologous sequence downstream of the polyadenylation signals would increase termination, the reverse was true. In addition, the magnitude of the response to the downstream sequence was gene dependent, with the ACTB sequences showing a greater release from termination.Restriction enzymes were from New England Biolabs . All other chemicals were from Sigma unless otherwise stated. All tissue culture reagents were from Invitrogen  unless otherwise stated.We assembled a tandem reporter construct in pcDNA5/FRT/TO . The CMVIE promoter in pcDNA5/FRT/TO contains two tet-operator sequences at the start of transcription and works in conjunction with the constitutively expressed tetracycline repressor in the T-REx cell lines (Invitrogen). To insert our reporters downstream of the pcDNA5/FRT/TO promoter the plasmid was digested with HindIII & BamH1 and a HindIII & BamH1 fragment containing firefly luciferase (FLUC) from pGL3-control  was inserted to make pcDN/FRT/FL. A 160 bp self-cleaving ribozyme sequence that we have used extensively Coding sequence spacers: PCR was used to add XbaI to one side of a fragment of GFP coding sequence from pIRES2-EGFP  and the sites NotI, NheI, and BamH1 to the other side. This PCR product was cut with XbaI & BamH1 and inserted into pREX The polyadenylation regions of the human β−globin  and β−actin  genes were isolated using PCR. A first round of PCR used primers generated by Primer3 A minimal poly(A) addition site (MniACT) taken from the core of the ACTB site was made by annealing the following two oligodeoxyribonucleotides:AAagtgcacaccttaaaaatgaggccaagtgtgactttgtggtgtgGGCCagttgAATAMniACTpA1 TTTATTcaactCTAGcacaccacaaagtcacacttggcctcatttttaaggtgtgcactMniACTpA2 A version of this with the polyadenylation signal mutated was put together with the following two oligodeoxyribonucleotides:TTagtgcacaccttaaaaatgaggccaagtgtgactttgtggtgtgGGCCagttgAATAMni0ACTpA1 AATATTcaactCTAGcacaccacaaagtcacacttggcctcatttttaaggtgtgcactMni0ACTpA2 The poly(A) hexamer signal is in capitals, and the mutated bases are bolded.In order to integrate our constructs into a stable cell line in a consistent chromosomal location, we utilized the Invitrogen Flp-In T-REx system as described previously Cells were plated in a 24-well plate and transfected with 250 ng of the shRNA construct using lipofectamine 2000 (Invitrogen) as per the manufacturer's protocol. The shRNA constructs cloned into the pLKO.1 vector were from Open Biosystems.XRN2 shRNA: TRCN0000049899 (NM_012255 mRNA)SETX shRNA: TRCN0000051517 (NM_015046 mRNA)Transfected cells were split into a 100 mm tissue culture dish 24 hours post-transfection and selected with 1 µg/ml of puromycin for 5 days. Knockdowns were confirmed using western blots and qRT-PCR for XRN2 and SETX respectively.Cells were scraped and lysed in 2X Laemmli Buffer , fresh 125 mM DTT). XRN2 western blots were performed by resolving 150 µg of protein on an 8% SDS-PAGE gel (37.5∶1) (Bio-Rad Mini Protean™ system). The samples were transferred to Immobilon-P membrane (Millipore) using a Bio-Rad semi-dry transfer apparatus. Membranes were blocked for an hour at room temperature in 20% evaporated Carnation Milk/PBS mixture followed by overnight incubation at 4°C with the primary antibodies.Rabbit anti-human XRN2 (Bethyl labs) and mouse anti-β-actin primary antibodies (Sigma) were used at 1∶250 and 1∶5000 dilutions respectively. Goat anti-rabbit HRP conjugated secondary antibody (Pierce) and goat anti-mouse HRP conjugated secondary antibody (Molecular probes) were used at a dilution of 1∶10000, followed by visualization using ECL Advance™ (Amersham). Images were obtained with the Kodak Gel Logic 440 Imaging system and analyzed with Kodak Molecular Imaging software (Version 4.0).The dual luciferase reagent (DLR) kit from Promega was used according to the manufacturer's directions as described previously Synthesis of cDNA to quantify FLUC and hRLUC expression in the TAN and TAN/dsred cell lines was done directly from cell lysates using the SuperScript™ III Cells Direct cDNA Synthesis System (Invitrogen). To quantify the senataxin knockdown, RNA was obtained using TRI-Reagent . First strand cDNA synthesis was done with 5 ng of RNA template using the Sidestep™ II QPCR cDNA synthesis kit (Stratagene).FLUC sense aagattcaaagtgcgctgctggtg; FLUC antisense, ttgcctgatacctggcagatggaa; hRLUC sense, aatggctcatatcgcctcctggat; hRLUC antisense, tggacgatcgccttgatcttgtct; SETX sense, ctcaagacctgtgcctgtca; SETX antisense, ggttccgactacccaacaga; 18S rRna sense, attcgaacgtctgccctatca; 18S rRNA antisense, gtcacccgtggtcaccatg, were purchased from IDT  and used at a final concentration of 400 nM. The iQ SYBR Green Supermix was used according to the manufacturer's recommendations . Cycling conditions were 10 min at 95°C, and then 40 cycles of 95°C for 30 sec, 55°C for 1 min and 72°C for 30 sec. Standard curves for the FLUC and hRLUC primer set were made with dilutions of the Tandem dsred tetramer control plasmid as described {The primer sets:


This work demonstrates that the regulation of transcription elongation is a widespread, gene class–dependent phenomenon that also affects housekeeping genes.Transcription elongation by RNA polymerase II was often considered an invariant non-regulated process. However, genome-wide studies have shown that transcriptional pausing during elongation is a frequent phenomenon in tightly-regulated metazoan genes. Using a combination of ChIP-on-chip and genomic run-on approaches, we found that the proportion of transcriptionally active RNA polymerase II  present throughout the yeast genome is characteristic of some functional gene classes, like those related to ribosomes and mitochondria. This proportion also responds to regulatory stimuli mediated by protein kinase A and, in relation to cytosolic ribosomal-protein genes, it is mediated by the silencing domain of Rap1. We found that this inactive form of RNA polymerase II, which accumulates along the full length of ribosomal protein genes, is phosphorylated in the Ser5 residue of the CTD, but is hypophosphorylated in Ser2. Using the same experimental approach, we show that the  Saccharomyces cerevisiae, one of the main experimental systems in modern biology. By comparing the genomic distribution of RNA polymerase molecules with the actual transcriptional signal across the genome, we have detected that many genes are regulated at the elongation level. We show that yeast cells use this step to modulate the expression of several groups of genes, which have to be simultaneously regulated in a very coordinated manner. Genes encoding essential functions, like those related to protein synthesis and respiration, change their transcriptional activities in response to environmental stimuli, without changing in the same extension the amount of RNA polymerase that is physically associated to them. We also show that this kind of regulation, in spite of taking place during the elongation step, can be mediated by promoter-binding transcription factors.Transcription of DNA–encoded information into RNA is the first step in gene regulation. RNA polymerases initiate transcription at the promoter region and elongate the transcripts traveling throughout the gene until reaching the termination sequences. Classical models of transcriptional regulation were focused on the initiation step, but there is increasing evidence for gene regulation after initiation. We have investigated the importance of elongation in gene regulation using the yeast  Mutations affecting the integrity of the yeast THO complex, involved in transcription elongation and mRNP biogenesis, decrease the expression levels of long transcription units, but do not significantly influence the mRNA levels of the shorter ones driven by the same promoter CUP1 gene, which can be transcribed by a mutant version of RNA Pol II lacking the CTD The transcription of the p53-dependent gene p21 does not require the phosphorylation of the carboxy-terminal domain of RNA pol II (CTD) in the serine residue situated at position 2 (Ser2). This indicates that the requirement of P-TEFb for transcription elongation is also gene-specific In this work, we investigated the distribution of actively elongating and total RNA pol II by means of a new methodological approach that combines genomic run-on (GRO) and ChIP-on-chip. We detected significant gene-specific differences in the proportion of active RNA pol II present in the transcribed regions. The effect of FACT depletion was also differential for some gene functional categories such us those encoding mitochondrial proteins, or housekeeping genes encoding cytosolic ribosomal proteins and factors involved in ribosome biogenesis. We found that the transcription elongation of ribosome-related genes responds to regulatory stimuli mediated by the protein kinase A pathway, and by the Rap1 transcription factor for those genes that encode structural ribosomal proteins. We also found that an inactive form of RNA polymerase II, which is phosphorylated in the Ser5 residue of the CTD but is hypophosphorylated in Ser2, accumulates along the full length of these genes, during standard growing conditions.RNA pol II ChIP-on-chip experiments . All normalized and processed genomic data are included in We measured the association of RNA pol II with yeast genes in exponentially grown cells in YPD by performing We reason that the difference between the GRO and the RPCC data, reflected in the ChIP/TR ratios, could be due to the different degree of accumulation of non-actively elongating RNA pol II either in a step prior to initiation or arrested during elongation (likely back-tracked). Our data indicate that the inactive form of RNA pol II  which accumulated in RP genes was phosphorylated in the Ser5 residue of the CTD. Therefore, we conclude that it should have passed the initiation step of transcription.The detected imbalance between the amounts of RNA pol II bound to RP genes and their TR may either be an intrinsic feature of these genes or reflect the occurrence of a novel mechanism that regulates their expression. In order to test these two possibilities, we calculated the ChIP/TR ratios in three different culture conditions: i) exponential growth in glucose medium, ii) 2 h after transferring glucose-grown cells to galactose-containing medium (non growing cells due to the metabolic shift), and iii) exponential growth in galactose medium . Then we did a clustering analysis to group genes in accordance with their ChIP/TR patterns. As shown in In the first step of the experiment (2 h), the TR and the amounts of RNA pol II binding to most genes, including the RP regulon, sharply decreased . This reΔtpk1 mutant. Tpk1 is one of the three PKAs present in yeast and it is physically located on those genes which are highly transcribed Δtpk1 when compared to an isogenic wild type grown in YPD. The results of Δtpk1 resembled those of the wild type in galactose  by ChIP . We found that most of the RP genes present in this array presented a higher RPCC 5′/3′ ratio in glucose than in galactose . This serap1Δsil mutant. However, and importantly, they were more transcribed in rap1Δsil than in the wild type  coordinately changes the fraction of RNA pol II that is effectively active during their transcription.Genome-wide analysis has shown that TOR and PKA pathways co-regulate several gene regulons in yeast, including RiBi, RP and respiration-related genes RPS3 and RPL25, accumulate inactive RNA pol II along the length of their bodies with only some bias toward their 5′ moiety. This accumulation correlates with a decrease in Ser2-phosphorylated RNA pol II along these genes.The importance of gene-specific regulation during elongation across metazoan genomes can be deduced from the occurrence of RNA pol II pausing, which is a frequent phenomenon mainly affecting tightly regulated genes hsp70 gene upon depleting the TFIIS cleavage factor The experimental evidence described in this work reveals that an excess of RNA pol II, phosphorylated in Ser5, accumulates on the yeast RP genes in glucose. This situation is only compatible with a post-initiation form of RNA pol II. However, the absence of a comparably high run-on signal indicates that this extra amount of RNA pol II, which accumulates in glucose media, should be arrested after backtracking. A similar situation occurs in the Drosophila Drosophila genes Regulation of ribosome synthesis is a key element in controlling cell homeostasis, cell size and proliferation A feedback regulation mechanism operating at the intron splicing level has been demonstrated for certain RP genes CYC1 transcription after RNA pol II recruitment RP and RiBi regulons show different RNA pol II- and FACT-ChIP/TR ratios, which suggest that their regulation mechanisms are not identical. We have also detected this kind of regulation in the group of mitochondria-related genes, thus confirming the previously described control of We provide evidence for the specific involvement of the silencing domain of Rap1 in the mechanism required to maintain significant levels of inactive RNA Pol II on RP genes. We also show that the absence of either Tpk1 or Tpk2 produces the same phenotype on RP transcription. These results indicate that the proportion of inactive RNA pol II on RP genes is controlled by the factors that specifically regulate the transcription of RP genes. In such a scenario, Rap1 would regulate the transcription of RP genes at both the RNA pol II recruitment and transcription elongation levels .rap1Δsil deletions. Our results indicate that it is in fact a transcriptional effect since the silencing domain has a negative influence on the TR of both subtelomeric , which has been argued to deal with the presence of an H2AZ-containing positioned nucleosome In The Rap1-dependent control that we propose for RP genes should not be the only one acting at the elongation level across the yeast genome as we have shown that at least two other functional groups of genes, RiBi and mitochondria-related genes, display a regulated variation in the proportion of active RNA polymerases. This variation is controlled by PKA, but does not depend on the silencing domain of Rap1. It is tentative to hypothesize that the PKA pathway regulates a plethora of genes during the elongation step of transcription by using different chromatin-related factors.600 = 0.5. In the experiment done in the galactose medium, cells were harvested and changed to YPGal  and grown for 2 h (lag phase) and 14.5 h .The yeast strains used in this work are described in SPT16 shut-off experiments, 5 µg/ml doxycycline was added to exponentially growing SJY6 cells (OD600 = 0.1). Since the experiments in this work were performed in rich media (YPD), shorter times of incubation with doxycycline were required to reach the same level of Spt16 depletion described in For the Genomic run-on (GRO) was done essentially as described in To determine the intragenic distribution of elongating RNA pol II molecules, we used macroarrays containing 300 bp probes from the 5′ and 3′ ends of the coding regions of 377 yeast genes. These 5′-3′ macroarrays were manufactured by printing PCR products onto a nylon Hybond N+ membrane, similarly to that described for whole genome ORF macroarrays RPS3 and RPL25 was done as in GRO experiments, but using miniarrays on nylon Hybond N+ membranes. These miniarrays were done by printing the PCR products as described above using the amplicons listed in PRI2, a gene whose run-on levels were not influenced by any of the elements tested in the GRO experiments, were included for normalization.The run-on analysis of A detailed protocol of RPCC will be published elsewhere . A preliminary description of it is included in the supplementary materials and methods .ChIP experiments of selected genes were performed as previously described qPCR were performed to quantify immunoprecitation, using a 1∶1500 dilution for the input samples or a 1∶10 dilution for the immunoprecipitated samples. Immunoprecipitation was defined as the ratio of each probe specific product in relation to that of a non-transcribed region . Primers used are listed in tpk2 mutant that was analyzed in duplicate. All the group functional enrichment analyses were done using the Fatiscan application from Babelomics All the experiments were done in triplicate except for the http://vydbase.uv.es/) and GEO databases. The GEO accession number for the set of hybridizations is GSE14084.Genomic data are stored in the Valencia Yeast  Rpb1-Myc levels, measured by ChIP-on-chip using an anti-Myc antibody, correlate with TR, measured by GRO. The RP genes are enriched in Rpb1-Myc, in relation to their TR. (B) The RP ChIP/TR ratios distribution (blue bars) is displaced toward higher values compared to the overall genome distribution (Gaussian line). Other symbols and the text insert are as in (0.46 MB TIF)Click here for additional data file.Figure S2RP, RiBi, and respiratory genes show specific changes in the levels of RNA pol II present and in the proportion of active RNA pol II, upon the carbon source shift. The proportion of RNA pol II that is active on RP and RiBi, reflected inversely by the ChIP/TR ratio, increases when cells are shifted from glucose (YPD) to galactose medium  for two hours (A) and continues increasing when cultivated further in galactose medium for 14.5 hours (B). Mitochondria-related genes show the opposite pattern. The relative levels of RNA pol II on RP and RiBi genes are lower in galactose than in glucose, whereas they are higher in glucose than in galactose for mitochondria-related genes (C). The relative distribution of all three groups of genes with regard to the overall population in TR values do not change when comparing cells exponentially growing in glucose and in galactose (D). Symbols are as in (1.50 MB TIF)Click here for additional data file.Figure S3Correspondence between the presence of Spt16 and Rpb1 and the observed TR. (A) Spt16-Myc and Rpb1-Myc, measured by ChIP-on-chip, show a similar correlation with TR as measured by GRO. A smoothness of the data, using 100 genes sliding windows, is represented. As expected, NA (no antibody) does not correlate with TR. (B) The distribution of the Spt16-ChIP/TR ratios for the RP genes (blue bars) is displaced toward higher values, in relation to the overall genome distribution (Gaussian line). (C) The Spt16/Rpb1 ratio does not depend on the transcription rate (TR). The RP genes (blue triangles) show the same average Spt16/Rpb1 ratio as the rest of the genome.(0.80 MB TIF)Click here for additional data file.Figure S4Effects of FACT (Spt16) depletion on yeast transcription. (A) Overall levels of mRNA amounts and TRs during Spt16 depletion. mRNA amounts were calculated as poly(A) per cell, while TR is the total of the GRO signals corresponding to the RNA pol II-dependent genes present in the arrays, as described in M&M. Both were normalized to time 0. (B) Overall distribution of TRs before and after Spt16 depletion.(0.46 MB TIF)Click here for additional data file.Figure S5The changes in TR upon Spt16 depletion do not correlate with the ORF length, G+C content, intron presence or absolute TR. (A) No indication of the dependence of the TR decrease on the gene length after 5 or 7 hours of depletion was observed. Individual genes are shown as gray dots and the tendency line for the sliding mean is shown as a red line. (B) G+C content does not influence TR sensitivity to Spt16 depletion. (C) The presence of introns does not preclude the sensitivity of TR to Spt16 depletion. Among intron-containing genes, only RP show resistance to Spt16 depletion at 5 h after doxycycline addition. (D) After 5 or 7 h of Spt16 depletion, the linear relationship with the control TR shows that absolute TR has no influence on the transcriptional effect of Spt16 depletion.(1.03 MB TIF)Click here for additional data file.Figure S6RPL25 gene. (A) Amplicons/probes used for RNA pol II ChIP and run-on analyses of RPL25. (B) ChIP distribution of total RNA pol II (upper panels) and its phosphorylated CTD forms, in Ser5 (second line panels) and Ser2 (third line panels) in cells exponentially growing in glucose (blue bars) or galactose (red bars). (C) Profile of intragenic RNA pol II distribution in RPL25 in glucose, in relation to its distribution in galactose and to the levels of RNA pol II present in the promoter region. (D) Relative distribution of phosphorylated forms of RNA pol II CTD relative to the total amount measured by ChIP. (E) The intragenic distribution of RNA pol II in RP genes, measured by run-on using an array of 5′ and 3′ probes, is not biased toward the 5′ end of the coding region in glucose, relative to the distribution in galactose. Symbols as in Intragenic distribution of different forms of RNA pol II in (0.48 MB TIF)Click here for additional data file.Figure S7rap1Δsil on the presence of RNA pol II in the RiBi regulon and mitochondria-related genes. The rap1Δsil mutation slightly increases the RNA pol II levels (A) and transcription rates (B) in the RiBi genes (red dots) without affecting their ChIP/TR ratios (C). No effect on either the RNA pol II levels or transcription rates was detected in mitochondria-related genes (orange diamonds).Effect of (1.17 MB TIF)Click here for additional data file.Figure S8rap1Δsil mutation increases the proportion of active RNA pol II in subtelomeric genes. The rap1Δsil mutation does not produce significant changes along the length of the chromosome at the total RNA pol II levels, measured by ChIP-on-chip . It does not produce an increase of active RNA pol molecules along length of the the chromosome length either (C), except within the 10 kb region near the telomeres (extended resolution in D). The red and blue lines represent the averages of the values using a sliding window of 50 genes. Horizontal lines represent the upper and lower limit for this mean using a Shewhart chart with a confidence range of 0.999.The (1.22 MB TIF)Click here for additional data file.Figure S9rap1Δsil on the presence and activity of RNA pol II in RPL25. There is no significant difference in the distribution of RNA pol II molecules within the RPL25 gene (A), but there is a significant increase of active RNA pol II molecules toward the 3′ end of the gene in the rap1Δsil mutant with regard to the wild type RAP1 (B).Effect of (0.10 MB TIF)Click here for additional data file.Table S1Excel file containing all the normalized and processed data.(5.92 MB XLS)Click here for additional data file.Table S2Excel file containing the statistically significant GO categories found in all the genomic experiments.(3.49 MB XLS)Click here for additional data file.Table S3Yeast strains used in this work.(0.04 MB DOC)Click here for additional data file.Table S4Oligonucleotides used for the PCR amplification of the first set of probes printed on the 5′/3′ arrays XLS.(0.11 MB XLS)Click here for additional data file.Table S5Oligonucleotides used for the PCR amplification of the second set of probes printed on the 5′/3′ arrays.(0.05 MB XLS)Click here for additional data file.Table S6RPL3 and RPL25.Oligonucleotides used for PCR amplification during the detailed studies of (0.01 MB XLS)Click here for additional data file.Text S1Supplementary Materials and Methods.(0.04 MB DOC)Click here for additional data file.