Homologous recombination is essential for maintaining genomic integrity. A common repair mechanism, it uses a homologous or homeologous donor as a template for repair of a damaged target gene. Such repair must be regulated, both to identify appropriate donors for repair, and to avoid excess or inappropriate recombination. We show that modifications of donor chromatin structure can promote homology-directed repair. These experiments demonstrate that either the activator VP16 or the histone chaperone, HIRA, accelerated gene conversion approximately 10-fold when tethered within the donor array for Ig gene conversion in the chicken B cell line DT40. VP16 greatly increased levels of acetylated histones H3 and H4, while tethered HIRA did not affect histone acetylation, but caused an increase in local nucleosome density and levels of histone H3.3. Thus, epigenetic modification can stimulate genetic variation. The evidence that distinct activating modifications can promote similar functional outcomes suggests that a variety of chromatin changes may regulate homologous recombination, and that disregulation of epigenetic marks may have deleterious genetic consequences. Homologous recombination depends upon a DNA donor molecule to serve as a template for correction of a damaged recipient Chromatin status contributes to regulation of homologous recombination. Dynamic changes in chromatin structure occur at a site of DNA damage, and are important for maintaining broken DNA ends in close proximity Tethered VP16 or HIRA caused the level of gene conversion to increase by approximately an order of magnitude . While these two tethered factors had similar functional outcomes, the localized changes in chromatin structure that they produced were quite distinct. Tethered VP16 greatly increased levels of acetylated histones, a mark associated with permissive DNA structure. Tethered HIRA did not alter local histone acetylation, but increased nucleosome deposition and caused local ordering of chromatin structure. Thus, different pathways of modification, and therefore different chromatin states, can achieve the same end: promotion of homologous recombination. Epigenetic regulation may be an important mechanism of both preserving and modifying genomic structure.To determine the effects of chromatin structure on gene conversion, we have taken advantage of the powerful physiological model provided by the chicken B cell line, DT40. In the DT40 cell line, which derives from a B cell lymphoma, the Ig heavy (IgH) and light (Igλ) chain variable (V) regions constitutively diversify by gene conversion. Gene conversion is templated by an array of homeologous upstream pseudo-V (ψV) regions , which lTo ask if further enrichment of AcH3 and AcH4 could be achieved, or could affect recombination, we used the DT40 PolyLacO-λ cell line constructed by our laboratory. In this cell line, polymerized lactose operator (PolyLacO) has been inserted into the ψVλ array between ψVλ17–ψVλ20, 17 kb upstream of the expressed Vλ gene . The celR), and the other unrearranged and not transcribed (λU). Allele-specific chromatin modifications were assayed at the rearranged allele of Vλ (VλR); the unrearranged allele of Vλ (VλU); and ψVλ17 (ψVλ17R), where sequence polymorphism was created by insertion of PolyLacO-λ, providing the only site in the ψVλ array at which the rearranged and unrearranged alleles can be distinguished by use of specific PCR primers. Modifications on both alleles were assayed by amplification of five sites, including the region between ψVλ1 and the Vλ gene (ψV1–Vλ); ψVλ1; ψVλ5; ψVλ13; ψVλ24. Strikingly, tethered VP16 increased levels of both AcH3 . There are two λ light chain alleles in DT40 cells, one rearranged and actively expressing λ light chain , comparable to levels of gene conversion documented in DT40 PolyLacO-λ GFP-LacI transfectants . However, the fraction of gene conversion events containing only a single substitution per tract was considerably higher in DT40 PolyLacO-λ GFP-LacI-VP16 transfectants and DT40 PolyLacO-λR HIRA-LacI transfectants  than in DT40 PolyLacO-λR GFP-LacI transfectants (3%). Thus, while essentially all gene conversion tracts in the GFP-LacI control cells contained at least two mutations, acceleration of diversification by either tethered VP16 or HIRA was accompanied by a diminished number of nucleotide substitutions per tract.Sequence analysis of Vλ regions amplified by single cell PCR from cells expressing tethered VP16 or HIRA showed that most diversification was by gene conversion  enrichment of FLAG-H3.3 relative to a control line , which attacks the linker regions between nucleosomes to produce a characteristic ladder. Genomic DNA was then purified, resolved and blotted, and the PolyLacO region probed by hybridization. The MNase digestion patterns of DT40 PolyLacO-λ GFP-LacI and DT40 PolyLacO-λ GFP-LacI-VP16 cells were similar to each other  and to tThe diminished heterogeneity of products of partial digestion of chromatin from DT40 PolyLacO-λ HIRA-LacI cells could reflect more ordered nucleosome phasing. Alternatively, increased nucleosome density may contribute to size homogeneity of partial digestion products. As diagrammed , a decreWe have shown that localized changes in donor chromatin structure can accelerate gene conversion. Our experiments showed two different chromatin modifiers, the activation domain of the transcription factor VP16, and the histone chaperone, HIRA, promoted gene conversion when tethered to the ψVλ donor array in DT40 B cells. These results identify epigenetic modification as a powerful mechanism for the regulation of homology-directed repair. Additionally, it provides both positive and negative regulation, as permissive donor chromatin structure can stimulate or repressive chromatin structure inhibit The DT40 Ig ψVλ donor array normally carries marks typical of transcriptionally active chromatin, including enrichment of AcH3, AcH4, and H3.3. Tethered VP16 or HIRA increased levels of these marks, while activating recombination but not transcription. This suggests that marks that activate recombination and transcription may be overlapping, reflecting dependence of both processes on similarly relaxed chromatin structure. Consistent with this, marks characteristic of activated chromatin correlate with activation of Ig V, D and J segments for V(D)J recombination, a site-specific recombination process that is developmentally regulated, Tethered VP16 increased levels of AcH3 and AcH4. That histone acetylation might promote gene conversion was suggested by evidence that Ig gene conversion was stimulated by culture of cells with the histone deacetylase inhibitor trichostatin A (TSA) Tethered HIRA modulated nucleosome composition by depositing increased levels of H3.3, and appeared to increase local nucleosome density. How might this result in a more permissive chromatin state for gene conversion? Based upon the relative sensitivities of intact nucleosomes to solvent conditions, Jin and Felsenfeld Tethered VP16 or HIRA accelerated clonal diversification rates by promoting gene conversion, but this was accompanied by an increase in the fraction of conversion tracts  that carried only a single nucleotide substitution, a category essentially absent (3%) in GFP-LacI transfectants. This may reflect a decrease in the physical length of conversion tracts, which could in turn be due to limiting levels of factors necessary to promote gene conversion at the elevated rates dictated by tethered VP16 or HIRA. Alternatively, as gene conversion must involve some form of invasion of the donor by the recipient DNA, alterations in chromatin structure induced by tethered VP16 or HIRA may affect nucleosome position in a way that limits the physical extent of sequence accessible for transfer. For example, the increase in nucleosome density caused by tethered HIRA may be accompanied by a decrease in the average linker length; and, if linker regions are preferred templates for gene conversion, shortening of those regions may contribute to decreased gene conversion tract length in the HIRA transfectants. Alternatively, nucleosome phasing may be changed, so that even though chromatin is more accessible for the homology search, the regions within the ψV segments that can participate in gene conversion are shorter. Finally, the tethered factors may create chromatin that is more accessible to mismatch repair, so a significant fraction of mutations could in principle be reverted, to create a large class of mutants with only single base changes.in situ gene correction. The evidence that the same functional endpoint can be achieved by distinct chromatin marks shows that the cell has available multiple, redundant pathways for effecting local alterations of chromatin structure that regulate homologous recombination.Just as epigenetic regulation can activate chromatin for homologous recombination, the disregulation of chromatin structure may promote recombination leading to loss of heterozygosity characteristic of aging cells and of cancer Cell culture and transfection were carried out as described 5) were cytospun onto glass slides and fixed with 2% paraformaldehyde for 15 min. To visualize the nucleus, cells were stained with DAPI . Fluorescent images were acquired using the DeltaVision microscopy system (Applied Precision) and processed with softWoRx software (Applied Precision).For fluorescence imaging, cells . Vλ and β-actin transcripts were amplified following dilution of the template, with Vλ primers + cells were isolated by flow cytometry followed by limiting dilution cloning, expanded for 4 weeks, then approximately 1×106 cells were stained with anti-chicken IgM-RPE , and analyzed on a FACScan with CellQuest software (BD Biosciences). For sequence analysis, sIgM− cells were sorted, aliquoted to single wells, Vλ regions amplified and sequenced, and their sequences compared to the ψVλ donors to determine if mutations were templated or nontemplated. Sequences were derived from at least two independently transfected lines. Only unique sequences were included for classification of the mutations.To quantitate sIgM loss variants ChIP was carried out as previously described Antibodies used were: anti H3 CT-pan, anti-AcH3 (06–599), anti-AcH4 (06–866), anti-dimethylated H3(K9) (07–521), dimethylated H3(K9) (07–030), anti-panH3 (05–928), from Upstate , trimethyl H3(K9) , and anti-FLAG M2-agarose .PCR primers for ChIP were:R: 5′-GCCGTCACTGATTGCCGTTTTCTCCCCTC-3′ and 5′-CGAGACGAGGTCAGCGACTCACCTAGGAC-3′; region between ψVλ1 and Vλ: 5′-CTGTGGCCTGTCAGTGCTTA-3′ and 5′-GCAGGGAACCACAAGAACAT-3′; ψVλ1: 5′-GGGACTTGTGTCACCAGGAT-3′ and 5′-CGCAGTCACATGTGGAATATC-3′; ψVλ5: 5′-GAGCCCCATTTTCTCTCCTC-3′ and 5′-GAGATGTGCAGCAACAAGGA-3′; ψVλ13: 5′-CCCTCTCCCTATGCAGGTTC-3′ and 5′-CCCCTATCACCATACCAGGA-3′; ψVλ18: 5′-CCATTTTCTCCCCTCTCTCC-3′ and 5′-TCACCCTACAGCTTCAGTGC-3′; ψVλ24: 5′-CCATTTTCTCCCCTCTCTCC-3′ and 5′-CAGCCCATCACTCCCTCTTA-3′; ψVλ25: 5′-TCTGTTGGTTTCAGCACAGC-3′ and 5′-GCAGTTCTGTGGGATGAGGT-3′; ψVλ upstream flank: 5′-GGCTCCTGTAGCTGATCCTG-3′ and 5′-GTTCTTTGCTCTTCGGTTGC-3′; ψVλ17 at the PolyLacO-targeted allele: 5′-TAGATAGGGATAACAGGGTAATAGC-3′ and 5′-AGGGCTGTACCTCAGTTTCAC-3′; OVA: 5′-ATTGCGCATTGTTATCCACA-3′ and 5′-TAAGCCCTGCCAGTTCTCAT-3′.VλNuclei were prepared and digests were performed with 0, 3, 7, 15, 30, and 60 units of MNase as described Figure S1Sequences of Mutated V Regions from Single DT40 PolyLacO-λ GFP-LacI-VP16 Cells V regions were amplified from single sIgM- cells and then sequenced. Clear blue boxes outline gene conversion events with two or more base changes; blue-shaded boxes outline gene conversion events with one base change; red circles denote point mutations; black dotted boxes indicate insertions; carats denote deletions.(0.06 MB DOC)Click here for additional data file.Figure S2Sequences of Mutated V Regions from Single DT40 PolyLacO-λ HIRA-LacI cells. Notations as in (0.09 MB DOC)Click here for additional data file.


Here we characterize the DNA promoter region necessary for SilA-mediated activation. This site is composed of two direct repeats of 10 bp, separated by a spacer of 11 bp. Fusion of this site to gfp allowed us to systematically introduce single-base substitutions in the repeats region and to assess the relative contribution of various positions to promoter strength. We then developed an algorithm giving different weights to these positions, and performed a chromosome-wide bioinformatics search which was validated by transcriptome analysis. We identified 13 genes, mostly bacteriocin related, that are directly under the control of SilA. Having developed the ability to quantify SilCR signaling via GFP accumulation prompted us to search for GAS and GGS strains that sense and produce SilCR. While the majority of GAS strains lost sil, all GGS strains examined still possess the locus and ∼63% are able to respond to exogenously added SilCR. By triggering the autoinduction circle using a minute concentration of synthetic SilCR, we identified GAS and GGS strains that are capable of sensing and naturally producing SilCR, and showed that SilCR can be sensed across these streptococci species. These findings suggest that sil may be involved in colonization and establishment of commensal host-bacterial relationships.Group A streptococcus (GAS) causes a wide variety of human diseases, and at the same time, GAS can also circulate without producing symptoms, similar to its close commensal relative, group G streptococcus (GGS). We previously identified, by transposon-tagged mutagenesis, the streptococcal invasion locus ( sil). Due to a mutation in the autoinducer peptide-SilCR, it is not produced by this strain. Here we sought to better explore sil and to examine if SilCR can be produced by other GAS strains, or strains of its close relative group G streptococcus (GGS). To this end, we characterized the DNA promoter region responsible for the TCS-mediated activation upon sensing of SilCR, and based on bioinformatics and transcriptome analyses we identified genes that are directly affected by the autoinducer peptide. By converting SilCR response to fluorescence production and turning on the autoinduction circle with minute concentrations of synthetic SilCR, we discovered naturally SilCR-producing GAS and GGS strains, and showed that SilCR can be sensed across these species. Our study describes a novel way of cell-to-cell communications among streptococci.Cell-to-cell communication in bacteria is termed quorum-sensing (QS), which is triggered by signaling molecules called autoinducers. In streptococci, autoinducers are synthesized as immature peptides that are processed, secreted, and then sensed by two-component systems (TCSs). As a result, the autoinducer's own expression is upregulated (autoinduction), subsequently creating an ultrasensitive switch that turns on more genes. Group A streptococcus (GAS) is a human pathogen that causes many infections, including necrotizing fasciitis (NF). Previously, we identified in a NF GAS strain a QS locus termed streptococcal invasion locus ( Group A streptococcus (GAS) is a common human pathogen that has major healthcare and economic impacts. It causes a variety of human diseases ranging from superficial skin and throat infections to severe life-threatening diseases such as necrotizing fasciitis (NF). There are approximately 10,000 cases of NF per year in the USA alone, estimated to cause 2400 deaths annually Little is known about what controls the conversion from a carrier to a pathogenic state in GAS infections. In fact, the distinction between commensals and pathogenic bacteria in general is blurred. This is mainly because both categories of bacteria use common modes of interaction with their hosts In Gram-positive bacteria autoinducers are synthesized as a pro-peptide that is processed and secreted by ATP-binding cassette (ABC) transporters. The mature peptide is then sensed by two-component signal transduction systems (TCSs). This triggers an up-regulated expression of the peptide itself (autoinduction) and often of the TCS and the ABC transporters, thus creating an ultrasensitive regulatory switch that subsequently leads to a change in the expression of an array of genes. These types of systems have been found to regulate various processes in streptococci including virulence, genetic competence, bacteriocin production, acid tolerance and biofilm formation streptococcal invasion locus (sil) sil is composed of nine genes organized in four transcriptional units  transporter system SilD-SilE and the autoinducer peptide SilCR. However, in the NF strain JS95, SilCR is not formed due to a start codon mutation (ATG to ATA) 4 promoter, encodes bacteriocin-like peptides. Finally, the forth monocystronic mRNA initiated from the P2 promoter contains silC that highly overlaps silCR and is linked to the ability of GAS to spread in soft-tissues 3 and P4 promoters is extremely low but abruptly increases when a mature synthetic SilCR peptide is added to the culture medium of JS95. The increased transcription of silE/D/CR is dependent on the dose of the added SilCR peptide and absolutely requires the TCS SilA-SilB By applying transposon-tagged mutagenesis (STM) on a strain isolated from a NF patient (M14 type strain JS95) and using a murine model of human soft-tissue infections, we identified the al units . A unit sil locus silDWe previously hypothesized that loss of SilCR and its regulatory potential might play a role in the highly invasive phenotype of JS95 and in the virulence of other GAS strains containing the Streptococcus dysgalactiae subsp. equisimilis contains several taxonomic units including group G streptococci (GGS) sil has been suspected to be acquired by horizontal gene transfer sil presence in GGS. Here we show that while sil is present only in a small fraction of GAS strains, its prevalence in GGS is much higher. We discovered that GAS and GGS strains naturally produce SilCR and demonstrate, for the first time, that the peptide can be sensed across these streptococci species.3 and the P4, promoters of sil  only in the presence of synthetic SilCR  towards silE (P3) , completely abolished P3 activity, indicating that both repeats of DR1 are necessary to stimulate the transcription from the P3 promoter (To define more accurately the DNA sequence necessary for activation of the PilE (P3)  and S2. promoter . By contpromoter .4 activity. This was achieved by systematically introducing single-base substitutions in 9 of the 10 nucleotides composing the first repeat of DR2 in p4-gfpP, forming a collection of plasmids harboring the desired mutations. Each plasmid was transformed into JS95 and the rates of GFP accumulation in the corresponding transformants were determined in comparison to that of the original p4-gfpP plasmid harboring the WT DNA segment. Substitution of the nucleotides at positions 2, 6 and 10 of DR2 had a marked detrimental effect on P4 activity, whereas the effect of substitutions at positions 1, 4, 5, 7, 8 and 9 was varied and less pronounced  or a nucleotide deletion (one of 6 adenines stretching between positions 14–19) as detailed above. Both modifications completely eliminated P4 activity . We identified a sharp decline in the GC percentage around spy_0482  is highly homologous to that of M4-type strain MGAS10750 (GenBank accession no NC_008024), as shown in When spy_0482 . The regspy_0488 . The goosil among GAS strains ranges between 12 to 18% sil. Nonetheless, all the other genomes possess blpM, spy_0484 and spy_0486, which constitute an integral part of sil  in sil, still retain the bacteriocin-like genes blpM and spy_0484, considered to be a part of sil. Furthermore, they also have genes encoding bacteriocin-like peptides BlpI and BlpJ IS905 transposon element) in the same location where sil would have been in these strains  was also up-regulated but this is probably due to generation of a long read-through transcript from the P4 promoter. To ascertain that the transcription under these conditions is solely regulated via the SilA-SilB TCS, we performed transcriptome analysis using the JS95ΔsilAB mutant, and found that there were no significant changes in gene transcription in the presence and absence of SilCR . We found that besides spy_0416 and spy_0150 (nomenclature of M1 GAS SF370 strain accession no NC_002737) only sil genes were affected .These results taken together show that exposure of a ng sites . To dete4-gfpP to detect SilCR in the nanomolar range  value that was comparable to that obtained by 5 ng ml−1 of synthetic SilCR  was able to produce SilCR  sensitivity of this reporter strain compared to that of JS95 transformed with p4-gfpP  and compared them to JS95 sil . As expected, silCR of IB7 and N3 contains ATG and not ATA as a start codon. Furthermore, these strains have an un-truncated silD. Since other GGS strains that could not produce SilCR possess ATG as the silCR start codon but have a truncated silD  and bacteriocin production (Blp) in the mitis group,  sil locus is more similar to that of the Blp system, and SilA-SilB is more closely related to BlpR-BlpH, SilCR belongs to the family of competence-stimulating peptides S. aureus AgrA bound to a 15 bp double stranded DNA was solved at a 1.6 Å resolution. It was shown that a side chain atom of LytTR forms contact with a nucleotide located at position 10 of the repeat 4sil promoter.Like many response regulators linked to autoinducing peptides, SilA belongs to the LytTR family sil acts as an autonomous unit and contains almost all the genetic information necessary for its regulation by a QS mechanism. It is not known what controls the P1 promoter initiating the transcription of the silA/B TCS, however recent work shows that it is upregulated within the host sil is an autonomous unit supports the hypothesis that sil might represent an ancient mobile island that may have been acquired before GAS speciation. In GAS but not in GGS, subsequently a DNA segment stretching from the 5′ end of sil up to silE was lost from most strains. The presence of two truncated transposases (IS1562 and IS904a) within sil, a truncated silB gene located at the 5′ border of sil, and the fact that the truncated blpA gene is highly homologous to silE  may indicate that this location underwent an extensive genomic rearrangement. Furthermore, all GAS genomes that lost sil contain the same DNA segment, encoding the two bacteriocins, BlpI and BlpJ IS905 transposon, which is located at the same genomic position . GAS and GGS were cultured in Todd-Hewitt medium  supplemented with 0.2% yeast extract  (THY media) at 37°C in sealed tubes without agitation. To produce solid media, Bacto™ Agar  was added to a final concentration of 1.4%. When necessary, antibiotics were added at the following concentrations: for GAS and GGS: 250 µg ml−1 kanamycin (Km), 50 µg ml−1 spectinomycin (Spec) and 1 µg ml−1 erythromycin (Erm); for E. coli: 100 µg ml−1 ampicillin (Amp), 50 µg ml−1 Spec, 750 µg ml−1 Erm and 50 µg ml−1 Km. All the antibiotics were purchased from Sigma-Aldrich .All GAS and GGS strains used in the study are described in E. coli, GAS and GGS strains by electroporation as described previously Plasmids and primers used in this study are listed in silAB mutant in the JS95 and IB7 strains, a 2222 bp DNA segment containing silA and silB was PCR amplified using the primers silA-f and silB-r  silAB-ΩKm  according to manufacturer's protocol. Briefly, an exonuclease III sensitive blunt end was generated by digesting p3-gfpP with StuI (near P4). Then, an exonuclease III non-sensitive 3′ overhang end was created by NspI-digest, that also destroyed Spec-resistance in p3-gfpP. The silE-blpM intergenic DNA segment was progressively digested towards P3 with exonuclease III, upon incubating the reaction mixture at 4°C for short times ranging from 30 to 90 seconds. The lengths of the remaining undigested DNA segments in the resulting E. coli transformants were examined by colony PCR, using a fluorescently-labeled primer with FAM, followed by separation of the labeled products on a sequencing gel. To this end, we used the gfp-r and FAM-spec-r primers  according to manufacturer's protocol. The p600 = 0.2, the cultures were divided among several tubes and the desired amount of synthetic 96% pure SilCR  was added to each tube, which was then incubated for 10 min at 37°C. Alternatively, bacteria were grown to the desired growth phase with or without 10 µg ml−1 of SilCR that was added at the beginning of culture growth. Total RNA from bacteria was isolated by hot acidic phenol extraction as previously described RNA was purified by applying one of two procedures. JS95 or its derivative mutants were grown in THY to ODgyrA) was used to normalize expression data for each target gene. Each assay was performed in duplicates with at least two RNA templates prepared from independent bacterial cultures grown on different days. The data were analyzed according to the standard curve method  and are presented as abundance of transcript amount relative to that of gyrA.RNA (4 µg) was treated with RQ1 DNase  and subjected to cDNA synthesis using MMLV reverse transcriptase , according to the manufacturer's protocols and as described previously gfp .To measure promoter strength, the initial rates of GFP accumulation were calculated. For this purpose, cultures were grown to an OD−1 of SilCR until late log phase (OD600 = 1). Then, the cultures were centrifuged for 10 min at 14,000 g and the supernatants were diluted 10 or 3-fold into the culture media of JS95p4-gfpP or N9p4-gfpP (respectively) which served as “reporter strains”. Relative fluorescence of the “reporter strain” was determined after an additional incubation of 2 h at 37°C, as described above.For the “Jump start” experiments strains were grown in THY supplemented with 10% (V/V) of fetal bovine serum  in the presence of 5 ng ml(M). This matrix assumes independence between the different positions of the binding site, and accordingly the probability L is the length of the binding site and i. The probability matrix that takes into consideration the relative weights of the positions in the binding site motif is sil (GenBank accession no NC_008024) q(cytosine) and q(guanine) were designated as 0.192 and q(adenine) and q(thymine) were designated as 0.308. The relative weights of the positions in the binding site motif were based on the results of the point mutations in DR2, shown in 4 activity for the specific mutant to that of the WT promoter. Although the mutation experiments were performed only on the first repeat, the weights were assumed to be suitable also for the second one. Mutating position 3 of the binding site was not successful, therefore iw can result in a deprecated algorithm, therefore we also verified that the most probable binding sites found are not coincidental by computing a p value based on a comparison to random sequences  from the query, shuffled each of them and computed the score of each shuffled sequence. For each candidate binding site in the original genome sequence, the p-value of its score was obtained by the fraction of random 31-mers that exceeded this score. The candidate sites with a p-values lower than 10To enable study of gene expression profiles for non-sequenced GAS strains, we designed, together with Roch NimbleGen Systems GmbH, a “universal” GAS expression array. The design of this array is based on the identification of unique ORFs. An ORF is considered unique when it differs from homologous ORFs by even a single nucleotide. This resulted in 17,047 unique ORFs, identified by screening 12 GeneBank available GAS genomes: , and the partially annotated chromosome of M49-type strain 591. A number of sequenced ORFs from the M14-type strain JS95 were added as controls. Probes could not be designed for 306 unique ORFs mainly due to low complexity sequences. The remaining 16,741 ORFs are represented by 9299 exemplars (i.e. distinct probe sets), 16,565 of them are covered by 7 probes and 176 are covered by 1 to 6 probes. Altogether, the array contains 64318 60-mer experimental probes as well as a number of internal quality controls.Using this array we performed two-color cDNA experiments and compared relative levels of gene expression. cDNA was produced with random hexamer primers (6 µg) from 2 µg of total RNA using the superscript III reverse transcriptase . The reverse transcription reaction was carried out at 42°C for 16 h with aminoallyl (aa) labeled dUTP. Unincorporated aa-dUTP and free amines were removed using Microcon YM-30 filters  according to the manufacturer's recommendations. Coupling of aminoallyl labeled cDNA to Cy-dye esters was performed in 0.1 M sodium carbonate buffer (pH = 8.6) for 1 h at room temperature. Free dye was then removed from the samples using the Qiagen QIAquick PCR purification columns, after which hybridization efficiency was measured using a spectrophotometer , and labeled cDNA concentration was calculated. Cy3-labeled sample (1 µg) was mixed with an equal amount of Cy5-labeled sample, and the mixture was dried using a DNA concentrator. Hybridization was performed according to NimbleGen protocol  at 42°C for 16 h using the NimbleGen MAUI hybridization system. Hybridized arrays were washed, and the slides were scanned using Axon GenePix 4000B scanner (Axon Instruments) with settings adjusted to obtain similar green and red intensities. Scanned images were imported separately for each color (wavelength 532 nm for Cy3 and 635 nm for Cy5) into NimbleGen's NimbleScan software (Nimblescan™ 2.3). Using the software each image was gridded and a pair report was created containing the raw data listing the intensity of each probe.The two pair reports of each two-color experiment were imported into a specially written MatLab (R2007b) program. The data underwent a process of flooring . Then, a scatter plot was created, plotting log10 of the product of the Data X and Data Y intensities against log2 of their intensity ratios. This was subjected to Lowess normalization method using a linear fit with a window of 0.05 (5%). Since for most of the ORFs there are 7 probes the data was reshaped so that each row contained all the data per each ORF (7 readings of CY3 followed by 7 readings of CY5). At this point a t-test was performed on each row and a p-value was calculated using 1000 permutations. The log2 ratios of the average 7 readings of CY5 divided by the average of 7 readings of CY3 was calculated for each ORF row. The ORF data was then presented in a Volcano plot using the vertical axis for the p-values and the horizontal axis for the log2 ratio values. By using a threshold of less than 0.05 for the p-values, and a fold change of + or − 2 for the absolute log2 ratios, ORFs with the largest statistical significant expression change could be selected. The data was submitted to NCBI Gene Expression Omnibus (GEO) accession no GSE16961.freak software  accession no GSE1696.Table S1Strains(0.07 MB DOC)Click here for additional data file.Table S2Plasmids(0.04 MB DOC)Click here for additional data file.Table S3Primers(0.07 MB DOC)Click here for additional data file.Table S4Predicted SilA binding sites and their genetic context(0.05 MB DOC)Click here for additional data file.Table S5Microarray analysis(0.10 MB DOC)Click here for additional data file.Table S6sil in GGS isolates. sil presence was verified by PCR using the SP-02 and SP-04 primers. The silCR start codon and the intactness of silD were tested by amplifying the corresponding regions by PCR using the SP-02 and SP-04, and silE-04-r and ABC-KO-f primers, respectively, followed by sequencing using the same primers. To test the ability to respond to exogenous SilCR, the indicated strains were transformed with p4-gfpP and induction of GFP production was measured in the presence of 10 µg ml−1 SilCR as described in “Characterization of (0.04 MB DOC)Click here for additional data file.Figure S14 activity on SilCR concentration in the GAS JS95 and GGS N9 strains. To calculate promoter activity, JS95 (A) or N9 (B) harboring p4-gfpP were grown to OD600 = 0.2, then SilCR was added to the indicated concentrations and the cultures were further incubated for 1 h. Fluorescence intensities were determined at time 0 and then every 15 min as described in “2>0.95) and depicted here as promoter activity. The values shown are the mean±the standard deviation results of at least two independent experiments.The dependence of P(0.04 MB JPG)Click here for additional data file.Figure S2silE-blpM intergenic region. The sequence between silE and blpM start codons (red letters and arrows) is shown. DR1 and DR2 sequences are marked in blue. Transcription start sites are indicated by yellow circles 3-gfpP and p4-gfpP are indicated by black bended arrows. The location of exonuclease III digestion stop points, described in The (0.10 MB JPG)Click here for additional data file.Figure S3600 = 0.3 in the presence of 10 µg ml−1 of SilCR were prepared as described in “6 promoter. Transcript amounts of the blpU and the three downstream genes (ORF2-4) relative to that of gyrA were measured by real-time RT-PCR for the JS95 strain grown with or without 10 µg ml−1 SilCR to OD600 = 0.3. To demonstrate that the upregulation in the transcription is dependent on the SilA-SilB TCS, we also measured the transcript of blpU in the JS95ΔsilAB mutant, which was grown in the presence and absence of SilCR as described above. The values shown are the mean±the standard deviation of at least two independent experiments.Analysis of the transcript initiated from the P6 promoter (A) Transcript analysis. Chromosomal DNA and cDNA of bacteria grown to OD(0.08 MB JPG)Click here for additional data file.Figure S44 activation by anti-SilCR antibody. Anti-SilCR antiserum was added to JS95p4-gfpP culture medium at serial dilutions of 100 and 1000-fold before the addition of SilCR. Cultures containing 0, 10 and 100 ng ml−1 SilCR were then grown to an OD600 = 0.3 and the relative fluorescence was determined as described in “Blocking of SilCR-mediated P(0.05 MB JPG)Click here for additional data file.


Drosophila genome, providing insights into initiation patterns and spatiotemporal conditions.A map of transcription start sites across the  Transcription initiation is a key component in the regulation of gene expression. mRNA 5' full-length sequencing techniques have enhanced our understanding of mammalian transcription start sites (TSSs), revealing different initiation patterns on a genomic scale.Drosophila melanogaster, we applied a hierarchical clustering strategy on available 5' expressed sequence tags (ESTs) and identified a high quality set of 5,665 TSSs for approximately 4,000 genes. We distinguished two initiation patterns: 'peaked' TSSs, and 'broad' TSS cluster groups. Peaked promoters were found to contain location-specific sequence elements; conversely, broad promoters were associated with non-location-specific elements. In alignments across other Drosophila genomes, conservation levels of sequence elements exceeded 90% within the melanogaster subgroup, but dropped considerably for distal species. Elements in broad promoters had lower levels of conservation than those in peaked promoters. When characterizing the distributions of ESTs, 64% of TSSs showed distinct associations to one out of eight different spatiotemporal conditions. Available whole-genome tiling array time series data revealed different temporal patterns of embryonic activity across the majority of genes with distinct alternative promoters. Many genes with maternally inherited transcripts were found to have alternative promoters utilized later in development. Core promoters of maternally inherited transcripts showed differences in motif composition compared to zygotically active promoters.To identify TSSs in Drosophila TSSs and the conditions under which they are utilized. Distinct differences in motif associations with initiation pattern and spatiotemporal utilization illustrate the complex regulatory code of transcription initiation.Our study provides a comprehensive map of  It is mediated in large part through the binding of transcription factors (TFs) to DNA sequence motifs. The majority of eukaryotic genes (protein-coding genes and many regulatory RNAs) are transcribed by RNA polymerase II (RNA pol II), an enzyme that contains various subunits and can exist in a holoenzyme complex with several basal TFs, including TFIIB and TFIIF [Transcription is a crucial part of gene expression that involves complex interactions of nd TFIIF . As RNA nd TFIIF -4. The sRecent high throughput sequencing efforts based on 5' capping protocols have now generated capped transcripts for human and mouse on a high throughput scale under numerous conditions . These 'Drosophila genomes [D. melanogaster using 5' capping technology [D. melanogaster: developmental regulation, housekeeping, and tissue-specific differentiation [Until recently, data comparable in scope to the capped analysis of gene expression (CAGE) sets for mouse and human have not been available for  genomes ,15, but chnology . Using tchnology . Each ofchnology ,19. GO achnology . These mntiation . Such funtiation .D. melanogaster: TBP-related factor 2 (TRF2) regulation of TATA-less transcription, including the genes encoding linker histone H1; and TBP-regulated transcription, including transcription of promoters of the core histones H2A/B, and H3/H4 [D. melanogaster.The core promoter elements and modules also offer deeper insight into the higher level organization of core promoter architecture. Genomic analyses are increasingly complemented by the elucidation of epigenetic patterns, such as the positioning of nucleosomes and the presence of certain histone marks ,24. Prevnd H3/H4 . HoweverDrosophila core promoters is so far mostly unclear. Several well-known D. melanogaster genes are known to use well-separated alternative promoters under different conditions. For instance, the transcriptional activator Hunchback (Hb) has two isoforms with different maternal  and zygotic  patterns of initiation [Adh) utilizes two promoters, one during embryonic development and the second in adulthood [In addition to the variability of initiation observed at a small scale at many individual start sites, a wide range of animal genes also possess clearly separated alternative promoters that are associated with specific functional consequences . The extitiation ,28. Alcodulthood . As the dulthood ,31. Howedulthood , in varidulthood , neglectdulthood ,35. It iIn this work, we use available large-scale data to provide an extensive, high-quality mapping of alternative TSSs across the fruit fly genome. We show that core promoter elements and their corresponding modules are associated with peaked and broad patterns of transcription initiation. We also confirm that motif matches are highly conserved in the peaked promoters of TSSs, but show considerable variation in the broad promoters of TSS cluster groups. Next, we identify distinct associations of TSSs with spatiotemporal conditions based on the Shannon entropy of EST frequencies from different libraries. We investigate the specificity of alternative promoters at higher temporal resolution using available expression data from tiling arrays during embryonic development. Lastly, we identify intriguing trends of core promoter elements and their corresponding modules in maternally and zygotically utilized sites. Our analysis demonstrates that sequence elements in core promoters are directly associated with initiation patterns and the spatiotemporal conditions under which they are utilized.Drosophila promoters have often been based on the analysis of upstream sequences extracted from a genomic resource such as Flybase [Previous studies on  Flybase , using t Flybase , the use Flybase ,7. TheseD. melanogaster were based on high quality TSSs, but were smaller in size and depth. For instance, our previous core promoter study covered 1,941 TSSs, but did not include alternative start sites [Thus, we are not confident in the reliability and quality of TSS data extracted from general-purpose genomic annotations because we cannot be sure which of the annotated 5' ends reflects a complete transcript, and which ones accurately capture a true and consistently used TSS. Other previous analyses in rt sites . The Eukrt sites . Here, wD. melanogaster ESTs in the Berkeley Drosophila Genome Collection  [Drosophila. We mapped the BDGC ESTs derived from 15 different libraries to 8 distinct conditions: embryo, larva/pupa, head, ovary, testes, Schneider cells, mbn2 hemocytic cells, and fat body. A broad adult stage can be accounted for by combining the promoter associations of the head, ovary, testes, mbn2 hemocytic cell, and fat body. Additional libraries from more than one body part or time period, an unknown source, or additional conditions to those examined here were assigned to one default condition called 'diverse'. By using independently generated cDNA libraries, we expect to reduce potential experimental biases from any one library due to incomplete reverse transcription . This list of EST-library derived conditions is certainly limited, but it enables an initial analysis of promoter utilization in different life stages and differentiated tissues.To minimize experimental error and clearly distinguish true TSSs from background noise, it is essential to filter available 5' transcript data. To accomplish this, we started from the large dataset of  file 1) ,39. A siD. melanogaster genome. We filtered this initial set to a reduced set of 157,093 unique EST alignments with high confidence of mapping to the 5' ends of transcripts . These unique EST alignments map across the Drosophila chromosomes and were derived from libraries of different sizes and conditions , nearly three times the number of TSSs and twice as many genes as in our earlier study . More thWhen TSS locations were considered individually, there were 2,765 genes (69%) with one TSS, and 1,225 genes (31%) with alternative TSS locations. The 1,225 genes with alternative TSS locations were evaluated according to the initiation patterns of their promoters, and for 685 genes (56%) the alternative TSS locations were in one broad promoter, while for 540 genes (44%) the alternative TSS locations were in alternative promoters of the peaked or broad type, or any combination thereof. Genes with alternative promoters were distributed across chromosomes 2L, 2R, 3L, 3R, and X . There may be additional alternative initiation sites upstream or downstream of those listed here that were not considered due to a lack of EST support.et al. using the most 5' ESTs to define sites of transcription initiation, rather than our use of the most highly utilized locations as TSSs. For genes with a consistent downstream start codon annotation, 141 TSSs were more than 10,000 bp upstream of the closest start codon. This observation of large distances between TSSs and their corresponding start codons agrees with high frequencies of large distances between TSSs and start codons found in D. melanogaster using tiling arrays [The mean genomic distance from TSSs to the most upstream start codon annotated in release 4.3 was 1,353 bp, with a median of 264 bp. This is 91 bp smaller than our previous estimate of 1,444 bp between TSS and start codon using chromosome 2R . This dig arrays . Due to g arrays . As a reRtnl1), CG14039 (quick-to-court), and CG11525 (CycG). Flybase listed three fewer alternative TSSs for quick-to-court, and four fewer for CycG in release 5.11 [Rtnl1 and quick-to-court, and three transcript isoforms for CycG are annotated for these genes. Whereas some of the TSSs of CycG and quick-to-court are close to each other and combined in cluster groups, all of the TSSs of Rtnl1 are well-separated peaked TSSs. Due to the stringent selection criteria we employed in the clustering strategy, genes with more than seven promoters may exist, but we found the most common range of alternative TSSs to be much lower.The maximum number of individual TSSs identified per gene was seven for the genes CG33113 , a transcriptional repressor located on chromosome 3R . While EPD and Flybase provide high quality support for the identified sites across the For more than 20 years, it has been known that some promoters are highly position-specific, while others are spread over larger regions . The anaDrosophila genome have identified a larger set of sequence motifs enriched in core promoters. Ohler et al. [et al. [et al. This knowledge allowed us to investigate whether the peaked and broad promoters were associated with specific core promoter elements, similar to the TATA box and CpG island biases found in mammals [et al. that have either been biologically validated or previously reported as building blocks for core promoter sequence modules. The eight motifs included four location-specific canonical motifs  [Compared to mammals, analyses of the r et al.  predicte [et al.  later id mammals . We focuand MTE) , and fouand MTE) ,20. Of tand MTE) . We evalFigure The greatest difference in element frequency between peaked and broad promoters was observed for the INR and DRE. This suggests that the DRE may be of equal importance to transcription for broad promoters as the INR is for the peaked promoters. All motif observations were higher than the mean number of occurrences found across the three random intergenic sets, and random occurrence rates corresponded well to the expectation based on motif score cutoffs. When motifs in peaked promoters were constrained to their functional locations , the same trends of occurrences were observed . We did not analyze restricted motif locations for the broad promoters, as multiple TSS reference points in the TSS cluster groups prevented distinct assignments within the overlapping core promoters.Next, we evaluated the presence of combinations, or modules, of known elements in the core promoters of the peaked TSSs and broad TSS cluster groups. A previous study had identified five different core promoter modules, which we evaluated here: TATA/INR, INR/MTE, INR/DPE, Ohler 6/1, and Ohler 7/DRE   and C (0.234) than broad core promoters  and the 100-bp sequences surrounding the random intergenic sites . These results confirm previous work showing that core promoters with the DPE, INR, and TATA/INR have a moderate GC content, and core promoters with the DRE, and Ohler 1/6 elements have a GC-poor profile [Drosophila genomes. We selected the promoters of individual TSSs and TSSs in TSS cluster groups that had aligned sequences in all 12 species . This led to a reduced set of 4,243 promoters for 3,175 genes: 2,886 peaked TSSs, and 1,357 TSSs in broad promoters. We compared the conservation of the eight core promoter motifs in D. melanogaster to the other eleven genomes in a pairwise fashion . In other words, we assessed whether a presumably functional motif, defined by the occurrence of a motif match in the preferred window relative to the location of a mapped TSS in D. melanogaster, was still detected in a second species in the corresponding position in the alignment. Figure melanogaster subgroup to approximately 50% for promoters in distantly related species. These levels directly correlate with the phylogenetic distances of the 12 genomes [Given the different associations of motifs with initiation patterns, we sought to examine whether there were differences in the conservation of core promoter motifs across the 12 fully sequenced  genomes . SimilarD. melanogaster promoters. After repeating this analysis on a set of similar sized random intergenic sequences, we took the ratio between promoters and random sequences as the motif enrichment score; for D. melanogaster alone, this score simply indicated the enrichment of hits in the preferred window  using Shannon entropy . As mentioned above, the cDNA library information for each of the ESTs was mapped to one of eight distinct conditions  plus a default (diverse) category. Overall, the data are more descriptive of spatial body parts than of well-resolved temporal stages of Drosophila development.Sites of transcription initiation are determined by the conditions under which transcription factors mediate the recruitment of RNA pol II to the core promoter. Associations of TSSs with conditions can give insight into the utilization and organization of TF binding sites in core promoters. For this reason, we characterized the condition associations of the set of 5,665 TSSs identified from (sub-)clusters in the hierarchical clustering of 5' ESTs in P << 0.001; Figure There were 1,997 (35%) TSSs with specific associations Figure , and 1,6P << 0.001; Additional data file 1). However, with additional conditions and ESTs, we expect to observe a larger percentage of alternative TSSs with different associations.When considering condition associations on a gene level, the numbers of specific, supported, and mixed TSSs did not significantly differ for genes with alternative TSSs compared to those having single TSSs, indicating that the presence of condition associations for more than one core promoter is a common phenomenon across all conditions. Because we assigned conditions to individual TSSs, it was possible for the 1,225 genes with alternative TSSs to have more than one association. We thus divided genes with alternative TSSs into two groups: genes whose TSSs had different condition associations, if at least one TSS had at least one different association from the gene's remaining TSSs; and genes with the same condition associations for all of the alternative initiation sites. In our dataset, 392 (32%) genes with alternative TSSs had the same condition association, and over two times that number of genes with alternative TSSs , had different condition associations. The number of genes with different conditions was significantly lower than expected when evaluated using random permutations of the condition association labels . Our methodology resulted in a low expected false positive rate of 0.02 to.035  and, by pooling all promoters together, we saw 58.7% transcribed in at least one of the 12 embryonic time points. The largest number of promoters  was utilized at time points 1 and 2, compared to any other developmental period Figure . These rP << 0.01; Figure P << 0.01; see Materials and methods). Here, initiation sites were deemed to have an embryo EST association if an individual TSS, or at least one of the TSSs in a TSS cluster group, had the association, resulting in 50.3% of TSSs and 74.3% of the TSS cluster groups having embryo-specific or embryo-supported associations. When comparing the condition associations of both promoter types across EST and tiling array experiments, we saw consistency in embryonic utilization of promoters  were 'all off' - that is, no utilization during any period (41%) - and 'all on' - that is, expression for the entire 24-hour duration of embryogenesis . Patterns observed for more than five promoters are listed in Additional data file 6. In particular, we explored the profiles of genes with alternative promoters in greater depth . In this analysis, we excluded broad promoters from the set of 540 genes with alternative TSSs separated by at least 100 bp, on account of their lack of precise individual TSS resolution, and divided the remaining 407 genes into four categories. The first category consisted of 143 genes (35%) with no expression from any peaked promoters at any time point. The second category comprised 170 genes (42%) with exactly one alternative promoter active during embryogenesis. In this group, 75 genes showed expression at time point 1 and their promoters were thus maternally utilized. The third category included 20 genes (5%) with more than one but not all alternative peaked promoters utilized during embryogenesis. The remaining 74 genes (18%) in the fourth category had all alternative peaked promoters utilized at some time during embryogenesis.men), and CG32473, different peaked promoters corresponded to completely non-overlapping periods of activity. Available RNA in situ images [hunchback, for which our dataset unfortunately did not contain enough ESTs to call TSSs. This analysis shows that dynamic properties of alternative promoter activity, such as onset and duration, are needed to properly characterize the regulation of transcription initiation during embryogenesis.For the 74 genes in the fourth group, we examined the onset of utilization, as defined by the first time point in which utilization lasted at least 4 hours, or 2 periods. This removed isolated and thus potentially erroneous calls. There were 30 genes with the same onset time across alternative peaked promoters, albeit with different durations of utilization. The temporal utilization of the 44 genes with different onset across alternative peaked promoters was typically a combination of both maternal and zygotic utilization. For two candidate genes in particular, CG10120 . While we saw small differences between motif frequencies in the embryo and head-specific promoters, no clear trends for condition-enriched motifs were observed . This most likely resulted from the low resolution of these conditions, as both 'head' and 'embryo' encompass numerous tissues across various developmental stages.The presence of the two types of core promoters defined by different initiation patterns in Drosophila in situ hybridization database [2 tests, the null hypothesis that initiation patterns and temporal conditions are independent of each other was rejected at (α = 0.05), indicating that maternal versus zygotic activity of core promoters and their initiation patterns are related to each other. For peaked and broad promoters with both zygotic and maternal activity, the frequencies of known elements agreed with those of the maternally utilized promoters . This relationship can be expected, as promoters with both patterns of utilization could in fact have resulted from the use of maternal promoters whose transcripts were not yet degraded within the cell. When compared to the numbers of occurrences in the random intergenic sets, the frequencies of the most common motifs were much higher overall in the promoters, although some of the less common motifs were in the range of frequencies observed for the random sites. This shows that when not in proper context, occurrences of the sequence elements are not as meaningful.We therefore examined the presence of sequence elements in the more precisely defined conditions that the tiling expression time course data allowed for, and analyzed 319 maternally inherited, 766 zygotically utilized, and 1,021 mixed maternally and zygotically active peaked promoters . We performed a concurrent analysis on 97 maternally inherited, 99 zygotically utilized, and 392 mixed broad promoters, to ensure that any identified associations of promoter elements with embryonic time points were consistent for different initiation patterns. The set of zygotically utilized peaked promoters showed a clear enrichment in the elements with strong positional bias - the TATA, INR, DPE, and MTE - and the maternally utilized sites had higher frequencies of the less location-biased elements . The results showed that the TATA/INR, INR/MTE, and INR/DPE modules had higher frequencies in the zygotically transcribed peaked promoters, and the Ohler 6/1 and Ohler 7/DRE modules had higher frequencies in the maternally utilized peaked promoters. Similarly, the numbers for promoters with both maternal and zygotic transcription initiation agreed with the maternally utilized module frequencies once again Figure . The samD. melanogaster that should serve as a useful resource for information regarding condition-specific transcription initiation, and for computational modeling of promoter regions. Nevertheless, the saturation of the D. melanogaster transcriptome by available ESTs is certainly incomplete, and additional TSSs will certainly exist beyond the high quality set identified in this work. While promoters of alternative TSSs that are active under different spatiotemporal conditions have been reported for several individual fly genes [D. melanogaster. Some individual designations may result from biases due to the comparatively low coverage of ESTs or, in the case of the tiling arrays, from transcript expression levels falling below the sensitivity of the microarrays; however, the overall results strongly indicate that usage of many alternative promoters is condition-dependent. In humans, previous work has shown that the aberrant use of alternative promoters is associated with various diseases, such as cancer [Drosophila may provide insight into downstream effects on transcripts and the mechanisms governing disease .The identification of 5,665 TSSs from hierarchical 5' EST clustering provides a comprehensive map of reliable TSSs in ly genes ,29, our s cancer . Genomicyellow gene has been shown to interact with a promoter in cis and a promoter in trans based on core promoter composition [in situ hybridization during different stages of fly embryogenesis [In situ images are able to capture spatial gene expression patterns at a much higher resolution than ESTs and microarrays. Our study provides promising candidates for the design of isoform-specific probes, which would link differences in the spatial and temporal expression of transcripts of the same gene to different promoters.The promoters of alternative TSSs may also be utilized under the same broad EST-derived conditions. In fact, there was a higher than expected number of genes with alternative TSSs having the same condition associations. Alternative TSSs with the same condition associations may result from a series of point mutations, or be created anew through promoter sequence duplication . In caseposition . A possiogenesis ,51. In sDrosophila core promoters distinguish themselves from other eukaryotic species investigated so far by being defined by a repertoire of well-known sequence motifs. Recent work has shown that core transcriptional complexes are remodeled in specific cell types in both mammals and flies [nd flies ,52. Herend flies . We shownd flies ,24. In and flies .Drosophila are functionally equivalent to those of the single dominant peaked TSSs in vertebrates. The peaked promoters in both D. melanogaster and vertebrates have single, well-defined sites of initiation, contain location-specific motifs, and are associated with similar functional subsets of genes. Here, we showed that peaked D. melanogaster promoters are utilized zygotically, confirming previous findings that the promoters of genes with the INR and DPE are associated with developmental regulation and that the TATA is overrepresented in terminally differentiated tissues, such as the cuticle, and endocrine glands [Drosophila, developmentally regulated genes were later shown to be associated with stalling of the RNA pol II machinery [Drosophila, the functional associations of peaked promoters with developmental regulation and terminally differentiated tissues should be explored in greater depth. Our current set of peaked TSSs may change with additional data, as more detailed information on initiation events may lead to reassignments of patterns to promoters.Our findings suggest that the core promoters of peaked TSSs in e glands ,21. In ve glands . In Drosachinery , and a cachinery . This suDrosophila are functionally equivalent to broad regions of initiation in vertebrates [Drosophila, this work supports previous studies showing that core promoter motifs without a location enrichment are utilized in the embryo, and are associated with housekeeping functions, such as DNA repair and translation, and the proteins necessary to perform them, such as the components of RNA pol II, and mitochondrial proteins [D. melanogaster [Similarly, we propose that the promoters of broad TSS cluster groups in tebrates . Both ofproteins ,21. Housnogaster , and witnogaster . Furthernogaster  and protnogaster , the relDrosophila and vertebrates, and not the actual sequence features that comprise them, as Drosophila and vertebrates have core promoter sequence features that are uniquely adapted to the transcription initiation machinery of each species. For instance, out of the eight motifs used in this study, only three motifs  have been shown to be functionally relevant for transcription initiation in vertebrates [D. melanogaster [D. melanogaster, CpG islands do not exist, and peaked promoters have higher frequencies of G and C than those of broad promoters. This may indicate that the shape of promoters may be independent of the functional properties of CpG islands. The core promoter motifs may have been decoupled from CpG islands, or the properties of CpG methylation, selectively in the evolutionary history of D. melanogaster, as many other insect taxa have CpG methylation and orthologous proteins that catalyze it in vertebrates [It is important to recognize, however, that we are comparing the functional usage of each 'type' of core promoter across tebrates . In turnnogaster . The mostebrates ,59. FurtDrosophila genomes. As we have experimental data for one species, we can only evaluate the loss of a D. melanogaster site in the corresponding location in another species. The fraction of candidates with non-conserved promoter elements in the melanogaster subgroup (approximately 10% depending on the motif and species) agrees with the turnover frequency measured by the ChIP-validated Zeste binding site [melanogaster subgroup. A larger evolutionary effect in more distal species is certainly expected, but the recently observed low performance of multiple alignment algorithms on distal non-coding regions is likely to be a strong contributor to this observation [Drosophila genomes. This provides initial evidence of an average lower negative selective pressure on alternative and broad promoters, linked to the presence of functional motifs. A possible explanation for this effect was given in a recent TSS study on human and mouse, by using high-throughput CAGE sequence tags [Our study provided a high-quality data set to assess the conservation of core promoter elements across the recently published 12 ing site . The observation ,62. Promnce tags . This stnce tags .D. melanogaster genome, we expect the number of genes with alternative TSSs to scale accordingly. The first sets of 5' capped high-throughput transcript data have become available concurrently with our study, and such data will provide the necessary scale to follow up on our observations [The presence of canonical core promoter elements has shown that TSSs may be more dynamic than previously thought . In addirvations .Drosophila TSSs and the distinct spatiotemporal conditions under which their promoters are utilized. Long underestimated in importance, differences in the motif composition of peaked and broad alternative core promoters have now been shown to be part of the complex spatiotemporal regulatory code of the eukaryotic transcriptome.Our study provides a genome-wide mapping of Drosophila release 4.3 to identify TSSs, which enabled us to directly map our results to other available data sources . We filtered the ESTs in a four-step process by first eliminating ESTs that did not cover an intron splice junction. This reassured us that the remaining ESTs were produced from mature transcripts. Second, we removed ESTs having aligned fragments longer than 1,500 nucleotides, or a distance greater than 100 kb between any two fragments. This was done to exclude dubious ESTs that may incorrectly map to the genome. The parameter range of 50 to 100 kb corresponded to an upper bound of the genomic span of fly genes and was previously used as a natural cutoff for the determination of promoter co-regulation [We used EST alignments from gulation . Third, We implemented a hierarchical clustering strategy to define individual TSSs Figure . We firsWe next computed the standard deviation of EST locations, and iteratively divided windows into smaller clusters until each had a standard deviation of less than 10. We refer to all of the clusters and sub-clusters having a standard deviation less than 10 by the term (sub-)cluster. This was done to discriminate regions of high localized EST frequency from broad regions with low EST frequency. It also served to separate singleton EST outliers into separate (sub-)clusters. The choice of 10 as standard deviation parameter corresponds to a variance of 100 bp and, thus, the size of a core promoter, as defined above.We identified TSSs from the (sub-)clusters using four criteria. First, we found the location with the highest frequency of ESTs in each (sub-)cluster, and removed (sub-)clusters with a maximum frequency at a single site of less than 2. This criterion selected only those (sub-)clusters with consistently and reproducibly utilized TSSs. If two or more sites were tied for having the highest frequency of ESTs, the upstream site was chosen.Second, to ensure that predicted locations coincided with the beginning of full-length transcripts, we selected sites that had to be supported by either at least three ESTs from a 5' capped library sequenced by RIKEN [Third, if a cluster contained several TSSs identified for more than one (sub-)cluster, we placed a new window starting at one TSS and ending at the second TSS. If the standard deviation of this new window was less than the cutoff of 10, we kept the site with the higher frequency of ESTs as the TSS and removed the second location from the dataset. If the standard deviation of the new window was greater than 10, we kept both locations as TSS candidates. This eliminated closely spaced TSSs from adjacent (sub-)clusters.Fourth, we required sites to be upstream of a start codon annotated for the gene in release 4.3. Because ESTs do not span the entire length of a transcript, we generally do not know what downstream isoforms correspond to the TSSs. For this reason, we conservatively required TSSs to be upstream of the most downstream start codon. If any of these criteria were not satisfied, we declared the (sub-)cluster to not have any conclusive TSSs and removed it from further analysis.We applied the program PATSER  to the pet al. [P-value of 10-3 for the expected false positive hit per nucleotide. As seen in Figure et al. [We used relative frequency matrices for eight core promoter motifs reported by Ohler et al.  and thatet al. . We estie et al. , with onD. melanogaster TSS set . These windows overlapped the most enriched motif locations as identified in the Flybase-defined promoter analysis of Fitzgerald et al. [Preferred motif positions were defined differently for location-specific and non-location-specific core motifs. For TATA, INR, DPE and MTE, we used the ten-nucleotide window with the highest number of motif matches in our d et al. . For theD. melanogaster sequences within the 10-nucleotide preferred windows as defined above; for the other four motifs, we used the most-enriched 20-nucleotide windows [D. melanogaster were located at corresponding positions in any of the other 11 genomes. Following the example of [For the conservation analysis, we first obtained orthologous regions across the other 11 species  using al windows . Then, wample of , we alloWe assessed the condition association of TSSs by computing the Shannon entropy of the ESTs of each (sub-)cluster from which they were identified, using a protocol following previous methods . First, tss, condition i, where N = the number of ESTs in each (sub-)cluster tss and condition i, xi = the number of ESTs for one condition across all (sub-)clusters, and 5,665 = the total number of (sub-)clusters in the analysis. In other words, w represents the normalized expression counts of the ESTs by condition and the overall size of the dataset. Next, we obtained the probability of observing an EST for each condition in a (sub-)cluster:for (sub-)cluster Ntss = the total number of ESTs in the (sub-)cluster across all conditions. To avoid arbitrarily low entropy values, we smoothed the data for conditions with no ESTs by setting P (i | tss) = 0.001. We calculated the entropy:for i for each tss. Then, we penalized entropy values to account for the disparity in sampling depth across conditions:by summing across all conditions Qi,tss. Only (sub-)clusters having at least three ESTs from a condition were evaluated further to prevent potential false assignments due to a low frequency of ESTs. The entropy values for Htss ranged from 0 to log2(c), for c = the number of conditions. In our analysis, c = 9 (eight distinct conditions and one diverse condition), and values for Qi,tss ranged from 0 to log2(9) - log2(0.0001), or 16.458.Lastly, we characterized the condition utilization of each (sub-)cluster by using an EST frequency threshold and the penalized entropy values, Q values naturally segregated into three clearly distinct groups . Entropy values close to zero signified (sub-)clusters with ESTs mainly from one condition. Larger entropy values characterized (sub-)clusters with ESTs that were more broadly distributed across libraries, but still mainly concentrated in one or two conditions. The greatest entropies denoted (sub-)clusters with ESTs spread across many of the eight conditions. On account of these groups, we classified the TSS associations into three categories  based on chosen cutoffs of Qi,tss. TSSs were declared condition-specific if 0 ≤ Qi,tss ≤ 1, and there were less than two ESTs from other conditions, and condition-supported if 0 ≤ Qi,tss ≤ 1, and more than two ESTs were generated from other conditions. We also classified TSSs as condition-supported if 1 ≤ Qi,tss < 10. TSSs with Qi,tss ≥ 10, and those that were classified as specific or supported by more than two of the eight distinct conditions, were deemed to have mixed association. Finally, TSSs that were specific or supported by the diverse condition were assigned mixed association by default.Our analysis is based on a published embryonic time course, and we evaluated promoter activity by using reported normalized intensity values of 25-bp long probes . The spaDue to the differing levels of total transcription across the 12 2-hour periods, cutoffs were determined independently for each time point. A mixture model of two Gaussians was fit to the differences of each time point using expectation maximization. The point of intersection of the two Gaussians was rounded up to the nearest.5 and declared the threshold . All promoters having differences greater than the threshold were deemed transcribed (T) for that time point. Promoters having differences in median fluorescence intensity less than the time point-specific threshold were declared non-transcribed (N). To determine the expected fraction of false predictions at these cutoffs, we randomly selected 4,664 random intergenic sites as a control dataset. For each of these sites, we evaluated the difference in fluorescence intensity by using the same methodology and threshold values, and assuming the sites had positive orientation.t-test was applied to the fractions of transcribed peaked versus broad promoters to evaluate statistical significance. The same strategy was used to compare the fraction of peaked versus broad promoters with embryo EST associations over all 12 time points, and to compare the total number of initiation sites with embryo EST associations to those without. For the evaluation of the association of both types of promoters with embryo and non-embryo ESTs associations, without the tiling array data, a χ2 test with Yates' continuity correction was applied. A Bonferroni correction was used in all tests, reducing the effective significance level to 0.01.The fraction of promoters transcribed at each time point was determined by dividing the number of transcribed promoters at each 2-hour period by the total number of promoters. A paired 2 test on both 2 × 2 contingency tables.In the core promoter analysis, maternally inherited sites were defined as having utilization during time points 1 and/or 2 in the tiling array. Sites with zygotic transcription were required to have utilization during at least one 2-hour period from time points 4 through 12, and sites with both maternal and zygotic utilization needed to satisfy both requirements. The promoter element matches previously identified were summed up separately for these three sets. As the initiation pattern does not play a role with regard to random intergenic sites, the mean numbers of elements identified in the 1,299 random sites served as a baseline. To test the relationship between initiation pattern and condition, we summed the normalized frequencies of the location-specific motifs  and non-location bias motifs  in peaked promoters with maternal (respectively zygotic) utilization, and in broad promoters with maternal (respectively zygotic) utilization, and performed a χDrosophila Genome Collection; CAGE: capped analysis of gene expression; ChIP: chromatin immunoprecipitation; DPE: downstream core promoter element; DRE: DNA replication element; EPD: Eukaryotic Promoter Database; EST: expressed sequence tag; GO: Gene Ontology; INR: initiator; MTE: motif ten element; RNA pol II: RNA polymerase II; TAF: TBP-associated factor; TBP: TATA-box binding protein; TF: transcription factor; TRF2: TBP-related factor 2; TSS: transcription start site; ttk: tramtrack.BDGC: Berkeley UO, PT and EAR conceived, designed, and coordinated the study. EAR clustered the ESTs, identified the TSSs, assigned EST condition associations, evaluated promoter utilization from the tiling arrays, and compared the presence of motifs in promoters with different patterns of initiation and spatiotemporal utilization. UO and HY evaluated the conservation of motifs across species. WHM performed the GO analysis. EAR and UO wrote the manuscript.The following additional data are available with the online version of this paper: Tables S1 to S4 and Figures S1 to S4, including detailed information on the comparison of the identified TSS locations to other genomic promoter resources and on the condition-specific activity of TSSs as determined by ESTs and tiling arrays  [Drosophila chromosomes, and had an elevated percentage of genes with alternative TSSs  and alternative promoters (34%), possibly due to the small sample size. Figure S2: evaluation of TSS quality. The quality of the TSS calls was evaluated by comparing the locations of initiation sites across databases and the frequencies of elements in the core promoter sequences surrounding them. (a) EPD location differences. Each of the 1,840 EPD TSSs was compared to the set of identified TSSs that were on the same chromosome. The difference in location of the closest identified TSS was taken from each EPD TSS, with the identified TSS as reference position (0). Differences ranged from 0 to greater than 1,000 bp. The plot covers a region of ± 20 nucleotides, which covers 76%  of EPD start sites. (b) Flybase location differences. All TSSs in Flybase that were upstream of the most downstream start codon, and did not map to a start codon location, were selected for comparison. Each of the TSSs identified by the hierarchical clustering strategy was compared to all of the Flybase TSSs listed for the same gene. The smallest difference in location between the Flybase TSS and the selected TSS was calculated at 1-bp resolution using the selected TSS as a reference point (0). The orientation of transcription of each gene was used to determine the orientation of the differences. A negative difference corresponded to a Flybase TSS being located upstream of the selected TSS, and a positive value signified that the Flybase TSS was downstream of the selected TSS. The plot covers a region of ± 300 nucleotides, which covered 79%  of TSSs matching to Flybase start sites. Compared to EPD, differences in start site locations are thus one order of magnitude larger at roughly the same coverage. (c) Presence of core promoter elements. For 2,725 genes with exactly one TSS in our set and an annotated initiation site in Flybase, motif matches were identified in the preferred windows in their core promoter sequences using separate zero order Markov models as background. There is a consistently higher number of motif matches in the promoters of the TSSs identified here, compared to those of the TSSs from the Flybase 5' end annotations. Figure S3: sequence elements in preferred windows of peaked promoters preserve trends of motif associations. (a) Associations of element occurrences. Motif matches were constrained to their preferred windows in peaked core promoters and normalized to the number of occurrences per 100 kb . The mean number of occurrences across the three random intergenic sets is shown. (b) Correspondence of elements to embryonic utilization. The set of peaked core promoters was divided into three groups according to the their pattern of embryonic utilization . The numbers of elements in the preferred windows of each group are shown. Figure S4: Shannon entropy values segregate into three groups. The distributions of ESTs in the (sub-)clusters used to call TSSs were evaluated using Shannon entropy. As an example, the figure shows the entropy histogram for the embryonic condition with bins of size 0.5. The QEmbryo,tss values naturally separate into three groups: those less than 1, those between 1 and 10, and those greater than 10. The large frequency of QEmbryo,tss values between 13 and 13.5 is an artifact resulting from using 0.0001 to smooth P(i | tss) for (sub-)clusters containing ESTs mainly from one non-embryo library.Table S1: false positive estimates of TSS assignments by condition. To assess the validity of the TSS condition assignments, we performed 100 random permutations of condition labels from the (sub-)clusters and evaluated their associations using the same methodology as for the identified TSSs. The numbers of false positives (column 3) were empirically estimated as the mean number of sites having a specific association with each condition (column 1) across all 100 random permutations. The false positive rate (column 4) was calculated by dividing the number of false positives by the number of identified TSSs that were observed to have the condition association (column 2). Table S2: GO enrichments for genes with different condition associations for alternative TSSs. The table lists all significant GO categories for genes with alternative TSSs associated with specific conditions, at a false discovery rate cutoff of 0.1, and present in more than five genes. Table S3: embryo associations confirm utilization patterns of known genes. We compared the embryonic utilization patterns previously observed for known genes to those identified using EST and Affymetrix tiling array data. Analysis of genes with at least one TSS having an EST embryo association (column 3), and promoter utilization in at least one tiling array time period (column 4) agree with previously reported expression patterns from olumn 5) , and pubClick here for fileGenomic locations and the frequencies of ESTs from each library are given for the initial groupings of ESTs, the (sub-)clusters created after clustering, and the TSSs chosen from each (sub-)cluster.Click here for fileAll motif matches in the peaked and broad promoters are included, regardless of preferred windows. Promoters without at least one motif match are excluded from the file.Click here for fileGene, chromosome, orientation, and condition association as determined by Shannon entropy for each individual TSS.Click here for fileGene, chromosome, orientation, and temporal pattern of utilization determined by the tiling arrays for peaked and broad promoters.Click here for filePatterns of utilization across the 12 development periods that occur at least 5 times in the set of peaked and broad promoters.Click here for file


Chromatin immunoprecipitation combined with genome tile path microarrays or deep sequencing can be used to study genome-wide epigenetic profiles and the transcription factor binding repertoire. Although well studied in a variety of cell lines, these genome-wide profiles have so far been little explored in vertebrate embryos.Xenopus tropicalis genome. In particular, a whole-genome microarray design was used to identify active promoters by close proximity to histone H3 lysine 4 trimethylation. A second microarray design features these experimentally derived promoter regions in addition to currently annotated 5′ ends of genes. These regions truly represent promoters as shown by binding of TBP, a key transcription initiation factor.Here we report on two genome tile path ChIP-chip designs for interrogating the Xenopus embryos.A whole-genome and a promoter tile path microarray design was developed. Both designs can be used to study epigenetic phenomena and transcription factor binding in developing  Drosophila embryos at promoter regions Xenopus and to analyze spatial regulation of gene expression during gastrulation Chromatin immunoprecipitation combined with either microarray hybridization (ChIP-chip) or sequencing (ChIP-seq) allows to determine genomic association of DNA binding proteins and to analyze epigenetic regulation X. tropicalis design and a promoter microarray design based on chromatin decorated with H3K4me3. The data show that both microarray designs are suitable for studies of histone modifications and transcription factor binding events in early Xenopus embryogenesis.The challenge in the near future is to elucidate epigenetic transitions and transcription networks that underlie early vertebrate development, the analysis of which will be facilitated by genome binding site analyses using either ChIP-chip or ChIP-seq. Genome tiling arrays are most cost-efficient if a dedicated design covering the relevant regulatory regions is used. Such a design can be made on the basis of annotation, or alternatively using experimental data of histone modifications like H3K4me3 that identify these regulatory regions. Here we present results obtained using a five array whole-genome tiling Xenopus tropicalis embryos, chromatin was harvested (Nieuwkoop-Faber stage 11–12) and immunoprecipitated using H3K4me3 antibodies. The purified DNA of H3K4me3-ChIP was amplified using a T7 amplification protocol X. tropicalis genome (Joint Genome Institute v4.1). The microarrays used each consist of 2.1M isothermal (76°C) probes of 50–75bp in length that are spaced by an average of 100 bp in the genome, with the exclusion of repeat-masked regions . The correlation between the promoter microarray experiments was r = 0.94 (p<2.2 * 10−16). This shows that ChIP-chip experiments based on genome-wide tiling or a promoter microarray design are highly reproducible and that the biological variance between different batches of embryos is relatively low.Two new H3K4me3 gastrula ChIP-chip samples were generated, amplified using the T7 method and hybridized to the new promoter microarray design. The two biological replicate samples are quite similar in terms of location and shape of the enriched regions as is shown for part of scaffold 1 . We deteX. tropicalis experimentally validated genes .To examine the application value of our promoter microarray design for transcription factors we studied TATA-binding protein (TBP), a key initiation factor that is known to bind to promoter regions. T7 amplified TBP ChIP and input DNA was hybridized to the promoter microarray. Many TBP-enriched regions colocalize with H3K4me3 enriched regions as is seen for example for tubulin alpha 1c . AlthougX. tropicalis. So far gene regulatory networks and epigenetic regulation during vertebrate embryogenesis have not extensively been studied using genome-wide binding analysis. By contrast, many epigenetic profiles have been established for human cells in culture Our results present ChIP microarray designs for Xenopus gastrula embryos based on ChIP-chip or ChIP-seq Xenopus, a promoter microarray design based on current Joint Genome Institute gene annotation would lose valuable information regarding the TSS, since a large number of H3K4me3-enriched regions do not overlap with current JGI gene annotation within 1 kb . An experimental approach to the design of a promoter microarray, based on H3K4me3-enriched regions, is therefore highly favored. Although many promoters featured on this microarray design are expected to be active in multiple tissues and stages of development, it should be noted that most comprehensive results will be obtained with this design when analyzing promoter binding events in gastrula stage embryos.The number of H3K4me3-enriched regions in Xenopus gastrula embryos. We also performed TBP ChIP-chip and find TBP peaks overlapping with H3K4me3 peaks, as expected for active promoters. The correlation between H3K4me3 and TBP, though highly significant, is not as strong as that observed between biological replicates of H3K4me3 enrichment. However, it should be noted that TBP paralogs have been identified that are required for transcription initiation during embryogenesis Xenopus development.The biological variation of the H3K4me3 modification is quite low in Xenopus embryogenesis using ChIP-chip. For the analysis of promoter binding the promoter microarray design for X. tropicalis can be used. For a genome-wide analysis of DNA binding or epigenetic regulation the five microarray set can be used. These types of genomic studies will enhance our understanding of transcriptional networks and developmental pathways and identify novel targets genes important for vertebrate development.This work describes microarray designs which are made available to the community, thereby facilitating future studies in Xenopus tropicalis embryos were obtained from a natural mating procedure after human chorionic gonadotropin injection, dejellied in 2% cysteine and collected at the indicated stage. Chromatin harvesting from 300 gastrula X. tropicalis embryos and ChIP  was performed as described Animal work has been conducted according to relevant national and international guidelines and following approval of the institutional review board for animal experimentation (Dierexperimenten commissie). X. tropicalis embryos using TRIzol reagent (Invitrogen). 5 µg of RNA was subjected to a reverse transcription reaction in the presence (cDNA) or absence (RT-) of SuperScriptIII (Invitrogen).Total RNA was isolated from 20 gastrula 5 µl of ChIP material  or 10 times diluted cDNA or RT- was used for quantitative PCR. PCR reactions were performed on a MyIQ single color real-time PCR detection system (BioRad) using iQ SYBR Green Supermix (BioRad). Primer sequences are available in In vitro transcription coupled to 1st and 2nd strand synthesis was done to acquire dsDNA.T7 amplification procedure was essentially identical as described by ChIP-chip samples were prepared according to the manufacturers protocol (Roche Nimblegen). In short, DNA yielded by 4 ChIP reactions  was pooled and amplified using the T7 strategy. DNA purified from de-crosslinked chromatin  was also amplified. Per labeling reaction 4 µg DNA was required (post-amplification). ChIP experimental samples were labeled with Cy3 and genomic control samples with Cy5. Samples were hybridized to the NimbleGen ChIP-chip microarrays by Research and Development at Roche NimbleGen .H3K4me3-positive regions to include on the promoter microarray design were selected based on relaxed criteria, to include as many putative positive regions while still keeping to the practical size limit of one HD2 Nimblegen microarray (∼2.1 million probes). A relatively simple procedure was chosen in order to retrieve an inclusive peak set. This peak selection was only used to design the promoter microarray, not for any further comparisons. Peak detection was performed using a sliding window operation, with three different thresholds for three window lengths . These different windows were used to select relatively small high peaks, as well as somewhat broader, lower peaks. As a control, all probes were randomized per microarray and sliding window detection on the randomized probes was performed. On both real and randomized data the sliding window detection was repeated with an increasing threshold. A definitive threshold was chosen such that the number of peaks in the randomized set divided by the number of peaks in the real data, the theoretical FDR, was <10%. All overlapping positive regions were merged and each region was extended both up- and downstream by 2 kb. In total this resulted in 27,019 putative promoter regions, the same order of magnitude as the annotated genes . The design was extended by the addition of several  datasets. All 5′ gene ends of JGI FilteredModels genes were added, as well a set of putative transcription start sites based on EST evidence , both extended by 2 kb up- and downstream. Finally, the complete tile path of scaffold_1, scaffold_73, scaffold_130, scaffold_185, scaffold_432, scaffold_654 and scaffold_2758 was included. These regions can be used to assess genomic background in peak calling applications. The complete design consists of 1,951,339 probes, which fits on a single 2.1M Nimblegen microarray, covering a total of 46,302 contiguous sequences with a median length of ∼4 kb.X. tropicalis genome (JGI 4.1) were removed. The following Tilemap parameters were set: method HMM, posterior probability 0.01, expected hybridization length 10. All other parameters were left to default settings. All resulting peaks of only one probe were removed, and all peaks within 1.5 kb were merged. The peaks for TBP  were called using Tilemap with default parameters. The files containing the H3K4me3 peaks, the TBP peaks, the number of matches for each probe to X. tropicalis JGI 4.1, as well as the Tilemap parameter files are available as supplementary information through GEO Series GSE19413.To call H3K4me3 peaks based on the three biological replicates (one genome-wide and two replicates on the promoter microarray design), TileMap X. tropicalis ESTs were downloaded from the UCSC Genome Browser . ESTs were filtered based on two criteria: 1) mapping to exactly two scaffolds and 2) a H3K4me3 peak within 1 kb of the EST on one of the scaffolds. All unique combinations of two scaffolds with evidence of more than one filtered EST were kept and are summarized in All mapped http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14025] were intersected with the peaks determined by ChIP-chip in this study. All ChIP-seq peaks overlapping with at least 1bp were counted as detected by both methods.To calculate the correlation of the genome-wide replicate to the two replicates on the promoter microarray the mean per-peak log2 ChIP/input signal was calculated per replicate for all the 10,179 peaks. The correlation coefficient between these replicate per-peak signals was calculated using the Pearson's correlation. To calculate the overlap between H3K4me3 determined by ChIP-chip and ChIP-seq, the H3K4me3 ChIP-seq peaks determined previously  [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19413). Improved versions (v2) of the X. tropicalis genome-wide microarray design and the promoter microarray design are available at the authors' web site (http://www.ncmls.nl/gertjanveenstra). These updated designs include extra control probes . The Arabidopsis sequences can be used as spike-in controls. In addition, all scaffolds of the whole-genome tiling microarray design were randomly distributed over the 5 microarrays of the array set to prevent that any single microarray features all the small scaffolds. The small (high number) scaffolds contain significantly fewer genes and distributing these scaffolds evenly over the 5-array set may prevent signal normalization issues. Arrays featuring these designs can be purchased from Roche Nimblegen.The data and the microarray designs used to generate the data have been deposited in NCBI's Gene Expression Omnibus Table S1H3K4me3-enriched regions and annotation. List of all H3K4me3-enriched regions and associated annotation (within 1 kb) for Xtev, JGI FilteredModel and RefSeq genes.(1.36 MB XLS)Click here for additional data file.Table S2Orphan H3K4me3 peaks: 991 regions are enriched for H3K4me3 and have EST annotation on two scaffolds.(0.11 MB XLS)Click here for additional data file.Table S3Primer sequences.(0.02 MB XLS)Click here for additional data file.Figure S1Distribution of H3K4me3 enrichment at JGI FilteredModels genes.(0.20 MB TIF)Click here for additional data file.Figure S2ChIP-qPCR validation of randomly selected H3K4me3-enriched regions. (A) Average enrichment (three experiments) determined for a genomic locus on scaffold 1 (scaffold_1:6458583-6458633). Asterisk indicates enrichment less than 2.5. (B) Average enrichment relative to a genomic locus on scaffold 919 (scaffold_919:126357-126407). Error bars represent the SEM of three biological replicates.(0.61 MB TIF)Click here for additional data file.