Drosophila orthologue of the PP1 Nuclear Targeting Subunit (dPNUTS) is essential for organismal development and is cell autonomously required for growth of developing tissues. The function of dPNUTS in tissue development depends on its binding to PP1, which we show is targeted by dPNUTS to RNAPII at many active sites of transcription on chromosomes. Loss of dPNUTS function or specific disruption of its ability to bind PP1 results in hyperphosphorylation of the RNAPII CTD in whole animal extracts and on chromosomes. Consistent with dPNUTS being a global transcriptional regulator, we find that loss of dPNUTS function affects the expression of the majority of genes in developing 1st instar larvae, including those that promote proliferative growth. Together, these findings shed light on the in vivo role of the PNUTS-PP1 holoenzyme and its contribution to the control of gene expression during early Drosophila development.In multicellular organisms, tight regulation of gene expression ensures appropriate tissue and organismal growth throughout development. Reversible phosphorylation of the RNA Polymerase II (RNAPII) C-terminal domain (CTD) is critical for the regulation of gene expression states, but how phosphorylation is actively modified in a developmental context remains poorly understood. Protein phosphatase 1 (PP1) is one of several enzymes that has been reported to dephosphorylate the RNAPII CTD. However, PP1's contribution to transcriptional regulation during animal development and the mechanisms by which its activity is targeted to RNAPII have not been fully elucidated. Here we show that the  During development, cells rely on appropriate patterns of gene expression to regulate metabolism in order to meet cellular demands and maintain rapid tissue growth. Conversely, dysregulation of gene expression is critical in various disease states, such as cancer, and during ageing. A key mechanism that is ubiquitously employed to control gene expression is reversible phosphorylation, a molecular switch that is used to regulate the activity of the transcriptional machinery. Here we identify an enzyme that binds to and regulates the phosphorylation state of RNA Polymerase II, a central component of the general transcription machinery. We also show that an essential role of this enzyme is to support normal patterns of gene expression that facilitate organismal growth. These findings are not only of relevance to the understanding of normal enzyme function but may also assist in the development of therapeutic strategies for the treatment of aberrant patterns of gene expression that occur during ageing and disease progression. Drosophila development, during which animals accumulate a 200-fold increase in body mass. The metabolic needs to sustain this rapid expansion are underpinned by transcriptional programmes initiated in the embryo; as maternal products become exhausted, large numbers of zygotically expressed genes, responsible for converting raw materials into cell mass, are induced to sustain developmental growth Development must be tightly coupled with cellular metabolism to ensure that necessary nutritional and energetic requirements are met and the available resources are utilised effectively to sustain appropriate levels of tissue growth. A particularly dramatic example of how development is coupled to metabolism is during the transition through the larval stages of Reversible phosphorylation plays important roles in the regulation of transcriptional networks and in coordinating spatial and temporal patterns of gene expression. Phosphorylation of RNA polymerase II (RNAPII) at multiple sites on its C-terminal domain (CTD) is critical for gene expression and its regulation Drosophila, PP1 is found at multiple sites on chromosomes where it has been postulated to play important roles in regulating developmentally controlled gene expression in vitro substrate specificity. In vivo, PP1 has been shown to associate with different targeting subunits that restrict its activity towards particular substrates Serine/threonine protein phosphatase type 1 (PP1) is one of four protein phosphatases known to contribute to the regulation of CTD phosphorylation in vitroin vivoIn mammalian cells, the PP1 Nuclear Targeting Subunit (PNUTS) is one of the two most abundant PP1-interacting proteins in the nucleus D. melanogaster orthologue of PNUTS (dPNUTS), display a larval growth defect and are larval lethal. Mutant clones show a cell autonomous growth defect and are eliminated from wild type epithelia due to cell competition. RNA-Sequencing (RNA-Seq) analysis indicates that dPNUTS affects the expression of the majority of genes in 1st instar larvae, including those that are highly expressed and are involved in cellular metabolism and larval development. The function of dPNUTS in tissue development is dependent on binding to the catalytic subunit of Protein phosphatase 1 (PP1), which is targeted by dPNUTS to RNA polymerase II in cell extracts and at many active sites of transcription on polytene chromosomes. Loss of dPNUTS function, or displacement of dPNUTS-PP1 using a non-PP1 binding mutant of dPNUTS, results in hyperphosphorylation of the C-terminal domain of RNA Polymerase II in whole animal extracts and on chromosomes. Taken together, these data suggest that dPNUTS-PP1 is a global regulator of gene expression via effects on RNAPII phosphorylation and is required in larvae to promote normal developmental growth.Here we show that null mutants in the C. elegans indicates that it has not been retained in all metazoa. D. melanogaster contains one gene encoding PNUTS: CG33526/dPNUTS. Comparison of full-length PNUTS cDNA and genomic sequences shows that all four of dPNUTS intron/exon boundaries are shared with human PNUTS . Flies carrying an inverted repeat (IR) construct under UAS control were crossed to a salivary gland GAL4 source to induce expression of intron-spliced hairpin dsRNA for dPNUTS in the progeny. In squash preparations from relatively normal looking glands expressing IRUAS-dPNUTS we found greatly reduced dPNUTS staining . Molecular analysis revealed that virtually all of the fourth coding exon of dPNUTS is deleted in 9BdPNUTS, and the entire coding region, including the translation start site, is deleted in 13BdPNUTS  in which the P element had been precisely excised ast4, a deficiency that removes the dPNUTS gene. The phenotype of 9BdPNUTS and 13BdPNUTS homozygotes was indistinguishable from that of 9BdPNUTS or 13BdPNUTS/Df(2L)ast4 hemizygotes, so we conclude that the excision alleles have little or no residual dPNUTS function. To confirm that disruption of the dPNUTS transcription unit is responsible for the larval lethality, we generated transgenic flies carrying a genomic fragment containing the entire PNUTS locus. A single copy of the transgenic construct was capable of fully rescuing the homozygous lethality of 9BdPNUTS and 13BdPNUTS mutants  larvae alongside their heterozygous (GFP marked) siblings. Homozygous 9BdPNUTS and 13BdPNUTS animals developed to 1st instar larvae but died in the ensuing 8 days without further growth and development  enzyme to induce mitotic recombination between two FRT chromatids, one of which carried a mutant dPNUTS allele and the other which expressed a GFP marker. Mitotic recombination events produce a GFP-negative cell clone that are homozygous for the mutant allele, together with a “twin-spot” marked by the presence of two copies of GFP. Surrounding heterozygous tissue is labelled with one copy of GFP. We failed to recover homozygous mutant cells when clones were induced in early 1st instar larvae, whereas wild type cells induced at the same stage proliferated to generate large clonal patches  allele of RpL27A. Notably, under conditions in which dPNUTS mutant clones in a wild-type background are normally eliminated, we recovered dPNUTS clones in M/+ discs  as the dPNUTS mutant strains. Homozygous 9BdPNUTS and 13BdPNUTS mutant 1st instar larvae had widespread changes in gene expression compared to control animals of the same stage  enrichment of terms for cell death and stress responses amongst genes overexpressed in dPNUTS mutants  terms amongst differentially expressed genes. When compared to the frequency of GO terms amongst all genes encoded by the genome, we observed significant 2.9 FPKM; data not shown). Taken together with the widespread effects on transcript abundance, these data indicate that dPNUTS globally affects gene expression and in 1st instar larvae is required to promote expression of highly expressed genes that support developmental growth.While these analyses provide biological insight into the likely processes underpinning the r larvae . Indeed,To confirm the RNA-Seq results, we selected genes representative of enriched GO categories for quantitative real-time qRT-PCR analysis. Measurements of relative mRNA expression level determined by qRT-PCR were consistent with our RNA-Seq data .dPNUTS two-hybrid clones, including the shortest interacting fragment encoding residues 608 to 1135 D. melanogaster PP1 isoforms (WT) and a mutant form in which Trp726 was replaced with Ala (dPNUTSW726A). Immunoprecipitation with antibodies against Myc-tagged dPNUTS, followed by immunoblotting with antibodies against PP1, showed that PP1 co-precipitated very efficiently with dPNUTSWT but not dPNUTSW726A , V/I/L, x, F/W that in PNUTS/p99 is necessary for binding to, and inhibition of, PP1 isoforms , consistUTSW726A , indicatin vivo, we examined the distribution of dPNUTS and PP1 on polytene chromosomes from 3rd instar larvae. We previously reported that ectopic HA-tagged PP187B, the major PP1 isoform in DrosophilaDrosophila PP1  and phosphorylated RNAPII (RNAPIIo), can be detected using an antibody (ARNA-3) that recognises a peptide mapping to central region of RNAPII. Both these forms precipitated with dPNUTS-S, but only RNAPIIA co-precipitated efficiently with dPNUTS  has not yet been fully determined, we found that dWdr82 co-precipitated with dPNUTS from Drosophila cell extracts indicating that the ability of Wdr82 to bind PNUTS is shared between fly and human orthologues (dPNUTS loss of function on the levels of RNAPII CTD Ser5-P. Using an antibody (4H8) that recognizes the Ser5-phosphorylated C-terminal domain dPNUTS mutant larval extracts by Western Blotting compared to wild type (1118w) or revertant (exKGdPNUTS/exKGdPNUTS) controls , which recognizes RNAPII Ser5-P in the context of Ser2 phosphorylation WTdPNUTS and W726AdPNUTS in embryos, and tested their ability to bind to RNAPII CTD Ser5-P. Immunoprecipitation with anti-Myc antibodies, followed by immunoblotting with anti-RNAPII CTD Ser5-P (4H8) antibody, revealed that RNAPII CTD Ser5-P was only recovered in Myc-W726AdPNUTS and not Myc-WTdPNUTS precipitates . Although the degree of functional conservation between mammalian and hologues . This prcontrols . Using aextracts . To testipitates , furtherW726AdPNUTS on RNAPII phosphorylation on polytene chromosome spreads. Since W726AdPNUTS shows reduced binding to PP1, we predicted that ectopic expression of this mutant form would compete with endogenous PNUTS-PP1 complexes and thereby reduce RNAPII dephosphorylation by PP1. Correspondingly, we found that levels of RNAPII CTD Ser5-P appeared modestly elevated on chromosomes from glands overexpressing W726AdPNUTS . Together, these results indicate that the dPNUTS-PP1 holoenzyme associates with RNAPII and regulates the dephosphorylation of its C-Terminal Domain.To further test the role of PP1-bound dPNUTS, we examined the effect of ectopic UTSW726A . To quannous PP1 , indicat animals . EctopicW726AdPNUTS on gene expression and the distribution of RNAPII at specific gene loci. Overexpression of W726AdPNUTS in 3rd instar larvae using da-GAL4 (W726Ada>dPNUTS) had a similar, but weaker, effect on gene expression to that of dPNUTS loss-of-function in 1st instar larvae  and/or because the regulation of some target loci is different at this later developmental stage. Amongst the genes we examined, ImpL3, nop56 and ACC were underexpressed, whereas the stress response gene Thor was overexpressed in response to ectopic W726AdPNUTS. Next, we examined the distribution of RNAPII at selected loci by Chromatin Immunoprecipitation (ChIP). For these experiments, chromatin was extracted from W726Ada>dPNUTS or control larvae and precipitated with either mouse IgG or anti-total RNAPII antibody (8WG16). We determined the abundance of precipitated chromatin by qPCR with gene specific primers. Control precipitations with mouse IgG showed a low level of non-specific background in all of these experiments  Relatively little is known about the effect of RNAPII Ser5 hyperphosphorylation on gene expression, but it has been associated with decreased elongation rate or pausing of RNAPII when it occurs on the body of genes r larvae . This mieriments –E. When Drosophila PNUTS, a regulatory subunit of PP1 that is highly conserved between flies and humans. We find that dPNUTS is essential for organismal growth, with mutant animals arresting early in larval development. Survival of the null zygotic mutants until the early larval stage is most likely due to perdurance of maternal dPNUTS gene products, raising the possibility of additional roles for dPNUTS during embryological development that we have not uncovered here. Clonal analysis indicates that dPNUTS has a cell autonomous effect on growth, with mutant clones failing to survive unless given a growth advantage. Transcriptomics characterisation of dPNUTS mutant animals indicates that the larval arrest phenotype is associated with the underexpression of many RNAPII-dependent genes, including those that normally support developmental growth. Of particular interest in this regard is the significant enrichment of genes involved in cellular metabolism. The underexpression of these genes suggests that an important role of dPNUTS during larval growth might be to ensure transcription of highly expressed metabolic pathways responsible for fuelling energy production and generating the macromolecular precursors for RNA and protein synthesis. Metabolic state is monitored in developing epithelia, ensuring that the fittest cells are selected as organ precursors Here we report the functional analysis of dPNUTS mutants. Indeed the non-identical distribution of dPNUTS and RNAPII on chromosomes suggests that dPNUTS is present in chromatin-associated complexes lacking RNAPII. Notably we do not see any detectable condensation defects in dPNUTS mutant clones but we cannot exclude the possibility that dPNUTS may also contribute to other processes that underlie tissue growth, such as transcription-independent cell cycle control, as has been reported for other enzymes that regulate CTD phosphorylation, such as FCP1 dPNUTS  and the relative amounts of the two proteins vary widely amongst these sites. This suggests that the association of dPNUTS with RNAPII, or with associated factors, which may affect the availability of the dPNUTS epitope for detection by our antibody, may be differentially regulated. PNUTS contains a number of conserved macromolecular-interaction domains, which have led to the suggestion it might serve as a multivalent adapter protein. However, it has not yet been established to what extent the known interactors, Tox4 and Wdr82 aid in the recruitment of PNUTS to chromosomal loci. These issues will require investigation of the genome-wide sites of dPNUTS binding, as well as identification and comprehensive characterisation of dPNUTS-interacting proteins and their role in dPNUTS recruitment.Like its mammalian counterpart, we have shown that dPNUTS is a nuclear protein that localises to chromatin during interphase. By utilising larval polytene chromosomes, which are readily visible by light microscopy, we have been able to extend this analysis by determining the distribution of dPNUTS on interphase chromosomes dPNUTS mutant larval extracts and tissues; iii) dPNUTS colocalises with PP1 and RNAPII on chromosomes; iv) ectopic expression of a mutant version of dPNUTS that displaces PP1 from polytene chromosomes results in elevated RNAPII CTD Ser5-P levels on chromosomes. dPNUTS-PP1 appears to preferentially target Ser5-P of the CTD as we observed only a modest effect on Ser2-P levels and no effect on phosphorylation of other RNAPII-CTD residues in dPNUTS mutant larval extracts by Western blotting  dPNUTS is complexed with RNAPII in nuclear extracts and regulates RNAPII CTD phosphorylation in a PP1-dependent manner; ii) RNAPII CTD Ser5-P levels are elevated in blotting . HoweverdPNUTS mutant animals are correlated with the normal expression level of the affected transcripts; these changes may also reflect the spatial distribution of dPNUTS expression during development. During embryogenesis we observed that the levels of dPNUTS expression in the gut and the ventral nerve cord correlates with stages in which these tissues are undergoing periods of rapid expansion and development. In an analogous fashion to SCP1, which restricts RNAPII dephosphorylation of neuronal genes to non-neuronal cells by virtue of its expression pattern dPNUTS in proliferating tissues may function to promote expression of highly expressed transcripts, such as those involved in cellular metabolism, in these tissues, to support their development. In mammals, the gradual decrease from a high level of PNUTS during embryogenesis to a relatively low level in adults has been taken to imply that PNUTS could play a role in cortical development C.elegans, where strictly controlled cell lineage determines tissue architecture. An evolved function of PNUTS might therefore be to support proliferative states in organisms where compensatory mechanisms such as cell competition are at play.Changes in the pattern of gene expression that we have observed in How do dPNUTS and RNAPII hyperphosphorylation regulate gene expression? Studies of other enzymes that control CTD phosphorylation state indicate that maintaining correct levels of CTD phosphorylation is critical for normal levels of transcription and that hyperphosphorylation of RNAPII can increase or reduce gene expression depending on what stage of the transcriptional cycle phosphorylation is affected. For instance, FCP1 targets Ser2-P in vivoW726AdPNUTS suggest that displacement of PP1 binding to dPNUTS does not result in accumulation of RNAPII on the coding region of affected loci. The precise mechanisms of how loss of dPNUTS function and RNAPII hyperphosphorylation disrupt gene expression require further investigation. However, we might expect processes dependent on normal CTD phosphorylation, including RNA processing, transcription-coupled chromatin modification and transcription-associated homologous recombination per sedPNUTS described here reveals an important function for this evolutionarily conserved chromatin-associated protein, via association with PP1, in the regulation of RNAPII phosphorylation and the appropriate expression of genes during larval development, which support organismal growth. These findings provide insight into the role of PNUTS and RNAPII phosphorylation during normal development, and may also be of relevance to the understanding of aberrant gene expression patterns observed in disease processes and ageing.In summary, the analysis of Drosophila melanogaster stocks were kept at 18°C or 25°C on standard agar-cornmeal-yeast medium. Genotypes are provided in Text S1.dPNUTS by P element excision from KGdPNUTS was carried out by crossing w; KGdPNUTS/CyO, P(Delta2-3) males to y, w; Tft/CyO females. From each cross, a single w revertant male in which the P element was excised, was individually crossed back to w; Tft/CyO females. To determine the molecular lesion in excisions, genomic DNA surrounding the original KGdPNUTS insertion site was amplified from heterozygous mutants by PCR using flanking primers (see Text S1) and sequenced. For genetic complementation tests, a 9.1 kb BamHI restriction fragment from P1 clone DS02684, which contains all of the transcribed dPNUTS sequence, was subcloned into the BamHI site in pW8 and injected into flies. Details of the growth arrest experiment can be found in Text S1.Isolation of a null allele of rd instar larval library (see Text S1). W726AdPNUTS was generated by PCR-based site-directed mutagenesis. For ectopic expression in flies, full-length dWTPNUTS and W726AdPNUTS were subcloned into pUAS-HM, a modified of pUAST that contains an N-terminal 3× His 6× Myc (HM) tag. UAS-HM-PNUTS flies were made by P element-mediated germline transformation into a 1118w stain by Genetic Services Inc. . Tagged WTdPNUTS and W726AdPNUTS were ectopically expressed ubiquitously using da-GAL4 or in salivary glands using AB1-GAL4.Full-length cDNAs for dPNUTS-S and PNUTS-L cloned into pNB40 were isolated from a 3in situ hybridisation was essentially performed as previously described pNB40-dPNUTS clones were used to generate Digoxigenin (DIG)-labelled RNA probes. RNA Text S1. All samples were normalized to 18S RNA. The ΔΔTC method was used for the calculation of the relative abundances RNA was extracted using the Qiagen RNeasy Mini kit and was reverse transcribed using the High Capacity cDNA Reverse Transcription kit (Applied Biosystems). Quantitative PCR was performed following the incorporation of SYBRGreen . Primers are described in st instar larvae/genotype was extracted using the Qiagen RNeasy Mini kit following the manufacturer's instructions. Total RNA quality and quantity was verified on a NanoDrop1000 spectrophotometer (Thermofisher) and Bioanalyzer 2100. mRNA was polyA selected using Dynabeads mRNA Purification Kit for mRNA Purification from Total RNA Preps (Invitrogen). The libraries were prepared according to the SOLiD Total RNA-Seq Kit protocol . RNA samples were sequenced on an AB SOLiD sequencing platform with v4 chemistry, generating single-end 50 bp colour-space reads. More than 93M reads were generated for each sample. Reads were filtered for quality and mapped onto the dm3 D. melanogaster reference genome dPNUTS mutants were defined as genes with <0.67 or >1.5 fold change relative to controls. A significance threshold of 1 FPKM dPNUTS mutants were further analysed by Database for Annotation, Visualization and Integrated Discovery (DAVID) (http://david.abcc.ncifcrf.gov/) against the D. melanogaster database. To increase the reproducibility, enrichment of gene function was identified with EASE score ≤0.001, which is a conservative adjustment to Fisher exact probability, and a fold change enrichment (FE)≥1.5 in all samples. The GO terms were hierarchically classified using AMIGO. Human orthologues of differentially expressed genes were identified by BioMart (www.biomart.org) and used to reconstruct functional networks and predict upstream regulators using Ingenuity IPA (Ingenuity Systems Inc.), see Text S1 for details.RNA from approximately 5000 1Oregon R Drosophila embryonic nuclear extracts was performed as in Text S1), using the following primary antibodies: rabbit anti-Myc ; mouse anti-Myc ; guinea pig anti-dPNUTS and anti-dPNUTS-S (1∶10). The following primary antibodies were used for Western Blotting: mouse anti-RNAPII , which recognizes both phosphorylated and unphosphorylated forms of RNAPII; mouse anti-RNAPII Ser5-P ; purified rabbit anti-PP1 (1∶500); rabbit anti-Myc ; mouse anti-Actin . For quantitation, X-ray film was digitized with an ImageQuant biomolecular imager  and quantified using ImageJ (http://rsbweb.nih.gov/ij/).Immunoprecipitation from 2–18 hr old Text S1) with the following primary antibodies: rabbit anti-Cleaved Caspase-3 ; mouse anti-Discs large ; rabbit anti-Myc ; mouse anti-phospho-Histone H3 . TO-PRO-3  was used to visualise DNA.Tissues were fixed and stained using standard approaches (see Text S1) and stained with the following primary antibodies: guinea pig anti-dPNUTS (1∶30); rabbit anti-PP1 (1∶50); mouse anti-RNAPII Ser2-P ; mouse anti-RNAPII Ser5-P ; rabbit anti-Myc . For DNA staining, slides were incubated with either DAPI or TO-PRO-3.Polytene chromosome squashes were prepared as reported previously Images were captured on Zeiss 510 and 710 Confocal Microscopes equipped with 405 nm, 488 nm, 561 nm and 633 nm lasers using a Plan Apochromat 40x/1.3NA oil immersion objective. Images were imported to Adobe Photoshop and adjusted for brightness and contrast uniformly across entire fields. Projected images of wing discs in XY were generated using ImageJ. XZ projections were generated using the Cut function in Zen 2011 (Zeiss). Line scans of polytene chromosomes were generated using ImageJ. For this analysis, we imaged a region at end of the X chromosome that could be reliably identified on chromosomes from multiple squashes. Images were taken with identical microscope and laser settings, with signal intensities below the level of saturation. The mean intensity of RNAPII Ser5-P and PP1 fluorescence was determined for each genotype by calculating the average fluorescence intensity through the center of unprocessed images of the same chromosomal region from 6 samples, parallel to the long axis of the structure.dPNUTS and dPNUTS-S nucleotide sequences reported in this paper are AJ580979 and AJ580980, respectively.The accession numbers for the Figure S1Sequence comparison of dPNUTS and related proteins. A) Schematic representation of domains in human PNUTS (hPNUTS) and dPNUTS: Region similar to Domain 1 of TFIIS (and the corresponding domain in Elongin A); Ser-rich region; Central region, highly conserved in hPNUTS and dPNUTS containing a canonical PP1 binding motif; CCCH zinc-finger typical of NUP/Tis11 proteins. The positions of introns (arrowheads) in the coding regions are indicated. Identical intron-exon boundaries are shown with connecting arrows. B) Table of % identity and similarity of hPNUTS, Elongin A and Tis11 in the different domains relative to dPNUTS. NA, not applicable. Pairwise comparisons were performed using ALIGN (TIF)Click here for additional data file.Figure S2histone H2B-YFP (in green) or dPNUTS RNAi stained on the same slide for dPNUTS (in red) and DNA (in magenta). Levels of dPNUTS were greatly reduced on chromosomes from dPNUTS RNAi glands.Specificity of the dPNUTS antibody for immunofluorescent staining of polytene chromosomes. Chromosome squashes from salivary glands expressing either (TIF)Click here for additional data file.Figure S3dPNUTS mutant clone, which shows normal distribution of nuclei compared to neighbouring heterozygous (GFP positive) cells. In contrast, a rare M, GFP/M, GFP twinspot is located at the basal face of the epithelium and is being extruded.A) Expanded images of clones in panels K–P of (TIF)Click here for additional data file.Figure S4dPNUTS mutants.Venn diagram showing overlap between differentially expressed up- and down-regulated genes in (TIF)Click here for additional data file.Figure S59BdPNUTS/9BdPNUTS and 13BdPNUTS/13BdPNUTS mutant larvae relative to abundance of GO terms for all genes in the genome as determined by DAVID. The top GO categories for each gene set are grouped according to their hierarchical relationships along with the number of genes affected in that category, the total number of genes in that category (in parentheses), and the statistical significance of the match.Gene ontology (GO) term enrichment of the genes under-expressed (A) and over-expressed (B) in (TIF)Click here for additional data file.Figure S6exKGdPNUTS/exKGdPNUTS (exKG/exKG) and homozygous null mutant 9BdPNUTS/9BdPNUTS (9B/9B) 1st instar larvae. mAb identity is indicated in parenthesis. Relative levels in the two conditions, as derived from densitometry measurements of the respective bands, are shown below the blots. C) Published conditions of recognition of phospho-CTD by mAbs, reproduced from A) dPNUTS binds dWdr82 in S2 cell extracts. Cells were transfected with constructs expressing Flag-Myc-dWdr82 or GFP-dPNUTS-Myc or both. Ectopic dPNUTS was precipitated using GFP-Trap beads. Western Blotting with anti-Myc antibodies revealed the presence of ectopic GFP-dPNUTS-Myc in precipitates. Flag-Myc-dWdr82 co-precipitated with GFP-dPNUTS-Myc, but not from cells lacking ectopic dPNUTS. IN = Input , NB = Non-bound, and IP = immuno-precipitated. B) Western Blot showing levels of RNAPII CTD Ser2-P, Thr4-P, Ser5-P, or Ser7-P in extracts from homozygous revertant (TIF)Click here for additional data file.Figure S7Polytene chromosomes from salivary gland squashes stained with dPNUTS and RNAPII Ser5-P (H14) antibodies. Merging of the green signal representing RNAPII Ser5-P with the red signal representing dPNUTS identifies sites where these two proteins co-localize. Insets, boxes 1–4, show enlarged view of chromosome regions. The relative signals of dPNUTS and RNAPII Ser5-P vary between sites, but only a minority of dPNUTS loci colocalize with RNAPII Ser5-P staining (indicated with arrows).(TIF)Click here for additional data file.Figure S8W726AdPNUTS under the control of da-GAL4 relative to control larvae, as determined by qRT-PCR. Error bars represent the SE . B–E) Chromatin immunoprecipitation (ChIP) analyses of the indicated genes from 3rd instar larval extracts using anti-total RNAPII (8WG16) antibody and mouse IgG antibody. Immunoprecipitated DNA was amplified by qPCR. The distribution at four loci  was evaluated using primers positioned at the start (S) and middle (M), of the transcribed sequences. Percent input is the amount of precipitated DNA relative to input DNA. Error bars represent the SE of the mean .A) Expression levels of the indicated genes in larvae expressing (TIF)Click here for additional data file.Table S1dPNUTS mutant lethality by genomic transgene. Expected and observed genotype frequencies of adult progeny from complementation crosses with two independent insertions of a dPNUTS wild type trangene (n≥350 progeny/cross).Rescue of (DOCX)Click here for additional data file.Table S2dPNUTS mutants. Only the categories with a minimum of 4 genes per category and an EASE score ≤0.001 were considered.Gene Ontology (GO) classification determined by DAVID. Biological process categories from GO analysis that are significantly overrepresented among the genes for which the expression was either decreased (downregulated worksheet) or increased (upregulated worksheet) in the (XLSX)Click here for additional data file.Table S3dPNUTS mutants when compared against all genes in the genome (DAVID) or against genes expressed in matched 1118w controls (EASE). GO categories returned by the two approaches were not always identical because the programs used different versions of the D. melanogaster genome annotation for comparison .Comparison of Gene Ontology (GO) outputs from DAVID and EASE. Shown are GO categories that were enriched amongst genes that are differentially expressed (DE) in (XLS)Click here for additional data file.Table S4Ingenuity transcription factor analysis. The table shows the IPA predicted ‘upstream regulators’ for up- and down-regulated differentially expressed genes, ranked by an application of a z-score algorithm. Genes from each predicted regulator ‘pool’ present in the analyzed dataset are listed in a ‘Target molecules’ column.(XLSX)Click here for additional data file.Table S52 fold change in expression of the indicated loci in dPNUTS mutants relative to control.Comparison of RNA-Seq and qRT-PCR data, showing log(DOCX)Click here for additional data file.Text S1Additional information including detailed genotypes and primer sequences as well as methodology for supplementary figures.(DOCX)Click here for additional data file.


Arabidopsis thaliana. Genetic, cellular, and physiological experiments show that miR159- and miR319-regulated MYB and TCP transcription factors pattern the expression of miR167 family members and their ARF6/8 targets. Coordinated action of these miRNA-TF pairs is crucial for the execution of consecutive hormone-dependent transitions during flower maturation. Cross-regulation includes both cis- and trans-regulatory interactions between these miRNAs and their targets. Our observations reveal how different miRNA-TF pairs can be organized into modules that coordinate successive steps in the plant life cycle.The development of multicellular organisms relies on interconnected genetic programs that control progression through their life cycle. MicroRNAs (miRNAs) and transcription factors (TFs) play key roles in such regulatory circuits. Here, we describe how three evolutionary conserved miRNA-TF pairs interact to form multiple checkpoints during reproductive development of  Development of multicellular organisms relies on properly timed execution of different genetic programs. An example is provided by developmental progression of flowers, which begins with the initiation of individual organs, followed by differentiation, growth, and finally production of the gametes. This article investigates the contribution of three microRNAs (miRNAs) and the transcription factors (TFs) that are regulated by these miRNAs to this process. Two of the miRNA-TF pairs act early to control in parallel the activity of the third miRNA-TF pair, which in turn modulates hormone programs that drive organ maturation and reproduction. Importantly, the two upstream TFs directly interact to regulate expression of the downstream miRNA. The results described here demonstrate how miRNA-TF pairs can be organized into regulatory circuits, with independent miRNA-TF pairs converging on common downstream genes. ARF6 and ARF8 (“ARF6/8”) of Arabidopsis thaliana are fine-tuned in specific floral organs by miR167 ARF6/8 activity is also sufficient for driving growth of floral organs, as shown with plants in which miR167 function is blocked ARF6/8 levels resemble symptoms of auxin, GA and JA deficiency and cytokinin overproduction In mammals, reproductive organs are already formed in the embryo, with gametogenesis being completed after birth. By contrast, plant reproductive development is initiated only after the transition from the juvenile to the adult phase, with the production of flowers that harbor the reproductive organs. Despite these differences, both kingdoms tightly control the progression from initiation to maturation of reproductive organs and the acquisition of reproductive competence. The progression relies on successive genetic programs that govern a delicate balance of cell division and differentiation, organ growth and maturation, as well as cell death. Coordination of these events in plants makes use of a host of interacting hormones, including cytokinins, auxin, gibberellins (GAs), jasmonate (JA), ethylene and brassinosteroids. Hormone action is often mediated by dedicated transcription factors (TFs) such as the auxin response factors (ARFs), several of which are microRNA (miRNA) regulated. As an example, expression of the paralogous master regulators arf6/8 mutant flowers are reminiscent of ones observed when the function of two other miRNAs, miR159 and miR319, is compromised. Such flowers suffer from retarded development of organs in the three outer whorls, the sepals, petals and anthers. The targets of these miRNAs are MYB and TCP transcription factors A. thaliana. Transcription of MIR319A coincides with MIR319C at the base of all floral organs, in stamen filaments and petals, while MIR319B is restricted to stamens and the abscission zone of sepals Defects seen in MIR167 family members during this process. Restriction of MIR167A expression allows the progression from meristematic, cytokinin-dependent programs to auxin-dependent organogenesis, culminating in GA- and JA-dependent maturation. We propose that the convergence of unrelated miRNA targets onto common downstream targets is an important feature of miRNA networks in plant development.Here, we report how these three evolutionary conserved miRNA-TF pairs (miRNA-TF nodes hereafter) are organized into a regulatory network that is responsible for several checkpoints in floral organ maturation. MiR159 and miR319 regulate directly interacting targets, which in turn control the expression of Pro35S:MIM159 and Pro35S:MIM319 transgenic plants, in which miR159 and miR319 activities are impaired by constitutive expression of target mimics , the maturation of sepals, petals and anthers was delayed to various degrees in Pro35S:MIM159 and Pro35S:MIM319 plants. In addition, the flower stems, or pedicels, were shorter, and the angles of flowers relative to the main stem were more acute  under the control of the petal- and stamen-specific APETALA3 (AP3) promoter MIM159 and MIM319 decoys under the same AP3 promoter for comparison  and BREVIPEDICELLUS (BP) STM and BP activity in Pro35S:MIM159 and Pro35S:MIM319 inflorescences, and in MIR167C overexpressors, which have reduced ARF6/8 expression. In all three backgrounds, STM and BP expression were increased  using anti-GFP antibodies and extracts from ProTCP4:TCP4-GFP Pro35S:MIM319 inflorescences. Quantitative PCR revealed specific enrichment overlapping one of the two potential TCP binding motifs  to self-fertilization (autogamy), which is found in up to half of all flowering plants, including many domesticated species ProMIR167A:GUS, ProMIR167B:GUS, ProMIR167c:GUS ProARF8:ARF8-GUS, ProARF8:mARF8-GUS and afr6-2 arf8-3 ProLOX2:GUS and ProTCP4:TCP4-GFPbp-1 mutants Plants were grown on soil in long days (16 h light/8 hours dark) under a mixture of cool and warm white fluorescent light at 23°C and 65% humidity. MIR167A and MIR167C fragments were PCR amplified from Col-0 genomic DNA, and placed behind the constitutive CaMV 35S promoter (Pro35S) MYB33 and TCP4 coding sequences AP3 promoter ProMIR319B:GUS reporter included a 2,662 bp genomic DNA fragment that begins 182 bp upstream of the first nucleotide of pre-miR319b. The MIR167A promoter was according to Agrobacterium tumefaciens-mediated transformation ARF6/8, we used sections of inflorescences from 30-day old plants, with sense and antisense probes as described Total RNA was extracted from 30-day old inflorescences of T1 or F1 plants using TRIzol Reagent (Invitrogen) with two biological replicates using tissue pooled from 10 to 15 plants each. After reverse transcription with the RevertAid First Strand cDNA Synthesis Kit (Fermentas) of 1 µg of total RNA that had been treated with DNase I (Fermentas). PCR was carried out in presence of SYBR Green (Invitrogen) and monitored in real time with the Opticon Continuous Fluorescence Detection System (MJR/BioRad). For in situ hybridization ARF8-GUS reporters, ten-fold lower concentrations of ferri- and ferrocyanate were used to increase sensitivity. Gus pictures are representative of three different experiments that included at least 10 samples each. Petals were sequentially cleared with chloral hydrate and ethanol/glycerol/lactic acid (3∶1∶1).Inflorescences were fixed in 90% acetone, and GUS activity was assayed as described Hsf1 gene (at4g17750) and lacking any putative TCP binding site as negative control.About 150 inflorescences were collected and fixed in two biological replicates, and immunoprecipitation was performed as described −, Trp−, His−) supplemented with 60 mM 3-amino 1,2,4-triazole (3-AT). The assay was repeated four times. For the luciferase complementation assay Agrobacterium tumefaciens cultures with the different constructs at OD600 = 0.3 each were mixed in equal ratios with a P19 silencing suppressor culture at OD600 = 0.1. Leaves were imaged three days after inoculation. Details for the constructs can be found in Interaction in the yeast two-hybrid system was assayed on selective medium  Expression of miR159-MYB targets in Pro35S:MIM159 inflorescences. Expression was monitored by real-time RT-PCR. Error bars indicate range of two biological and two technical replicates. Expression values of the different genes in the mutant plants were normalized to their expression in wild type inflorescences (dashed lines).Expression levels of representative miR159 and miR319 targets in plants with specific miRNA attenuated function. (A) Expression of three representative miR319-TCP targets in (PDF)Click here for additional data file.Figure S2arf6 arf8 mutants. Scale bar indicates 2 mm.Flowers and inflorescences of mutant and transgenic plants. (A) Scanning electron micrographs of flowers from transgenic plants. MIMXXX and MIRXXX lines express the target mimics and miRNAs from the 35S promoter. MIM159, MIM319 and MIR167C plants were 30 days, MIM167 plants 38 days old. Scale bar indicates 700 µm. (B) Entire inflorescences. Note that flowers grow more upwards, that is, at a smaller angle relative to the main stem, in MIM159 and MIM319 plants, or in (PDF)Click here for additional data file.Figure S3ProMYB33:GUS is broadly express in every flower organ. (B) ProTCP4:GUS is expressed in the vasculature of sepals and anther filaments (procambium), petals and female reproductive organs.MYB33 and TCP4 expression patterns in flowers. (A) (PDF)Click here for additional data file.Figure S4MIR167A promoter activity, and comparison of MIR167A and MIR319B promoter activities. (A) Activity of ProMIR167A:GUS in different backgrounds. Note particularly strong ectopic activity in sepals, petals, and at the base of flowers and pedicels of MIM319 expressers. (B) Close-up of mature petals. Note ectopic activity in vasculature. (C) ProMIR319B:GUS expression in wild-type inflorescence. Activity is notable at the base of petioles and floral organs, and in anthers. Scale bars indicate 2 mm (A), 500 µm (B). See also Effect of miR159, miR167 and miR319 on (PDF)Click here for additional data file.Figure S5MIR167A promoter by TCP transcription factors. (A) Reporter gene assay with MIR167A promoter. Mutations in either of the two TCP binding motifs suppress ectopic activity in response to MIM319 overexpression. Scale bar indicates 2 mm. (B) Heterodimerization of TCP2 and TCP4 assayed by firefly luciferase complementation assay in N. benthamiana leaves. Luciferase activity is shown in false color, with highest levels red and lowest levels blue. See also Regulation of (PDF)Click here for additional data file.Table S1MIR167A and LOX2 promoters.Potential R2R3MYB and TCP binding motifs in (DOC)Click here for additional data file.Table S2Oligonucleotide primer sequences.(DOC)Click here for additional data file.Table S3List of plasmids.(DOC)Click here for additional data file.


Escherichia coli we found 78 regions with an extremely large number of potential transcription start points . It was shown that all PIs interact with RNA polymerase in vivo and are able to form transcriptionally competent open complexes both in vitro and in vivo but their transcriptional activity measured by oligonucleotide microarrays was very low, if any. Here we confirmed transcriptional defectiveness of PIs by analyzing the 5′-end specific RNA-seq data, but showed their ability to produce short oligos (9–14 bases). This combination of functional properties indicated a deliberate suppression of transcriptional activity within PIs. According to our data this suppression may be due to a specific conformation of the DNA double helix, which provides an ideal platform for interaction with both RNA polymerase and the histone-like nucleoid protein H-NS. The genomic DNA of E.coli contains therefore several dozen sites optimized by evolution for staying in a heterochromatin-like state. Since almost all promoter islands are associated with horizontally acquired genes, we offer them as specific components of bacterial evolution involved in acquisition of foreign genetic material by turning off the expression of toxic or useless aliens or by providing optimal promoter for beneficial genes. The putative molecular mechanism underlying the appearance of promoter islands within recipient genomes is discussed.Expression of bacterial genes takes place under the control of RNA polymerase with exchangeable σ-subunits and multiple transcription factors. A typical promoter region contains one or several overlapping promoters. In the latter case promoters have the same or different σ-specificity and are often subjected to different regulatory stimuli. Genes, transcribed from multiple promoters, have on average higher expression levels. However, recently in the genome of  E.coli encodes seven σ-subunits FecI, σF and σN), and/or to survive in a variety of stress conditions  D, which activates several thousand of promoters with certain correspondence to the consensus motifs TTGACA and TG-TATAAT, located about 35 and 15 bp upstream of the transcription start point (TSP), respectively. Sequence motifs recognized by RNAPs with alternative σ-factors differ from those of σDS). That is why many σS promoters can be activated by the σD-RNAP and vice versaH and σE promoters (heat shock response) the difference is much more pronounced D-RNAP S- and σH-RNAP H (rpoH) is regulated by five transcription factors and can be transcribed from five closely spaced promoters, of which one combines σD- and σS-specificity, while others are activated by σN-, σE- and σD–RNAP E.coli genes have two or more documented promoters, thus indicating a tendency to express genes from a single promoter.Bacterial transcription is carried out by a single enzyme DNA-dependent RNA polymerase (RNAP), which utilizes exchangeable σ-subunits to recognize and activate different promoter types. The genome of E.coli, one by one, using classical biochemical approaches. Since the distance between the TSP and the −10 element in promoters varies from 2 to 11 bp, and RNA synthesis can be primed by 2–4 bases long primers The transcription start points of most known promoters have been mapped in external score”, which took into account the position of the predicted TSPs relative to the initiating codon, and the “cover function” that allowed to ignore weak promoters in the vicinity of a stronger one in silico should not be considered as merely false positives Clusters of potential promoters in bacterial genomes for the first time were discussed by Huerta and Collado-Vides D-promoters either exactly fits to the experimentally mapped start or is located in a neighboring position (±2). However, some genomic loci not obey this rule and have extremely high density of potential TSPs. We named them promoter islandsE.coli we found 78 such islands with length varying in the range 300–1101 bp and made sure that the high density of TSPs can not be an artifact of our software, since another promoter finder also revealed the same bunching (Our promoter finder PlatProm bunching .genomic islands (GI) containing alien DNA, and a new sliding window method GIST  has been developed to find these regions E.coli MG1655 GIST predicted 59 GIs, with the length of 4–15 kb and the average density of TSPs in the 4 kb sliding window at least 5 fold higher than in genome. Forty of them contained PIs, which have on average 7 fold higher promoter densities than genomic islands. It was proposed genomic islands were emerged by accelerated evolution so as to integrate foreign genes into the host cells regulatory networks but according to the expression analysis performed on microarrays promoter islands are transcriptionally inactive promoter islands with normal promoters in terms of structural and functional properties in order to understand their biological role.Previously it has been observed that the high frequency of PlatProm predicted TSPs may be used as a marker of long Escherichia coli K12 MG1655 (GenBank accession number U00096.2), where 78 PIs were identified by PlatProm DNA fragments were taken from the chromosome of control set was composed of genomic regions with minimal PlatProm scores, which were taken from the previously used compilation of non-promoter DNAs CS1 The single (within 300 bp) promoters was collected using information of RegulonDB The set of multiple promoters included at least 3 experimentally mapped TSPs within 300 bp.Samples with Virtual Footprint (http://prodoric.tu-bs.de/vfp/vfp_promoter.php) Virtual Footprint scores were chosen for structural analysis.To compose the set of H-NS binding sites, we first used the chip-on-chip data published by Kahramanoglou et al. alien genes were selected from within the “genomic islands” identified in the E.coli DNA genomic islands” found by IslandViewer included PIs, so they were ignored. The remaining 19 “islands” contained only 18 experimentally mapped TSPs, but 3 of them have already been selected for other promoter sets. The missing 63 promoters were added using RegulonDB information on the E.coli transcription units. The centers of selected fragments were placed in PlatProm-predicted TSPs. Twelve of them were later mapped in RegulonDB with a 0–3 bp shift and in 7 cases the predicted starts deviate from the novel experimental TSPs for 8–16 bp. Functionality of 34 alien promoters was therefore confirmed experimentally.Normal promoters of promoter islands and normal promoters was assessed using chip-on-chip data 2 of the ratio of hybridization signals obtained with DNA co-immunoprecipitated with the enzyme by σ70-specific antibodies and the control DNA recovered from the complexes without specific immunoprecipitation (experiment B in ref. 34). An ability of PIs and normal promoters to form complexes with nucleoid proteins H-NS, Fis, IHF and with the transcription factor FNR was investigated using data processed by authors. In the case of PIs the binding sites of different proteins were looking for within their boundaries , we assumed that all they gave equal contribution to the registered number of sequence reads. This number, thus, was divided by the number of matching sites, and the resulting quotient was ascribed to each of them. The sequence reads remained after the first selection, were subjected to the next round of search for samples having 43 bases perfectly matching the genome at the 5′-end, and so on. The next nucleotide within a sample collected at each step can be either mismatch or the first nucleotide of the adapter sequence. In the former case the sample may represent a normal transcript, while in the later one – short oligonucleotide. Efficiency of productive transcription was assessed by the number of samples with perfect compliance with the genome (44 bases); while the number of short oligos was estimated using samples containing adapter sequence GATCGTGACTG.Transcriptional activity of PIs was addressed using 5′-end-specific RNA-seq data (supplement in ref. DNA tools (http://hydra.icgeb.trieste.it/dna/model_it.html) using electrophoretically estimated structural parameters of dinucleotides. These models were analyzed by the software aSHAPE conformational chains  were obtained in pdb-format by software l chains . We empl purines . In the ase pair . The oriReal Length (RL), Straightened Length (SL) and cumulative twist angle (Ω), while the local conformation was defined by the bending angle θ and the torsion angle φ  The thermodynamic stability of DNA samples was characterized by stacking energy, which was calculated for fragments of different lengths by using the values computed for dinucleotides . Ideally they mark both ends of initial transcripts, which minimal length expected to be 44n. As a result, 8,967,903 forty-four nucleotides long sequence reads were published by Dornenburg et al. Our attention to A in E.coli genome. This part contains 25 out of 78 PIs, but only one of them, located in the promoter region of divergently transcribed genes yhiL and yhiM , gave 10 products to the set. In the whole genome there are only 7 PIs that gave 88 sequence reads, if only internal regions of PIs were analyzed , and detected samples were derived from 35 single or 51 multiple promoters. Thus, PIs are defective in productive transcription, supporting our previous observation made on the basis of microarray data Samples that have no adapter sequences and perfectly match to the genomic DNA, we considered as products of full-fledged transcription. The section analyzed , or 10 Panalyzed . In the Then we removed perfectly matching samples from the data set and looked for reads that have 43 bases long sequences at the 5′-end ideally matching to the genome and repeated this procedure for sequences of length 42, 41 … 9 bases. The relative amount of reads derived from PIs remained almost constant for samples corresponding to 44–15 nucleotides long RNAs and started to grow when this length decreased to 14 bases and less . That is why; we reanalyzed the data using the samples with unique matching to the genome. Mismatches near the 5′-ends of long RNAs also increased the number of products erroneously considered as short RNAs. Though their contribution to the transcriptional output of islands should be much less than to the set of RNAs derived from normal promoters, we reduced this source of errors collecting 9–27 nucleotides long products from the subset of reads with adapter sequence at the 3′-end. As a result we observed the same dependence (single and multiple promoters was much higher (blue curves) showing no increase in the range of abortive RNAs.However, the number of short products ascribed to pendence  and S1. single promoters  multiple promoters  representing local bends  using the mode of sliding window. multiple promoters and control samples are shown in For comparison 300 bp 3D models were transformed into a set of short fragments of a given size (multiple promoters (blue curves) differ from non-promoter DNA (dashed gray curves) in all parameters tested except twist angles   . Howevertwo sets . Moreove for PIs , which a for PIs . Decreas for PIs , measuremultiple promoters is simply due to the larger number of potential RNAP binding sites, curves reflecting structural features of single promoters should be shifted towards curves of control samples. This was really the case for RL-SL, the bending angle Θ and the torsion angle φ, while other metrics remained almost unchanged , in addition to RNAP binding.If the greater difference from control samples observed for PIs than for nchanged  excludinpromoter islands suggested their existence in heterochromatin-like state, which is usually mediated by the specific proteins of bacterial nucleoid. Thus, we compared occupancy of PIs and normal promoters by nucleoid proteins H-NS, Fis and IHF using available chip-on-chip data multiple promoters were used for normalization . Their interaction with PIs  was variable (magenta bars) but an average portions of PIs recruiting H-NS were comparable with single promoters. So we had no reason to consider these proteins as specific silencers of PIs. We did not notice essential difference in the ability of PIs to bind transcriptional regulators CRP, FNR, LexA or RutR (for FNR exemplified in H). According to the data published by Kahramanoglou et al. promoter islands in different growth conditions varied in the range 24729–30026 bp (expected by chance 4661–6784 bp), i.e. up to 90% of the total length of PIs (33397 bp) may be covered by H-NS. 3D models of H-NS binding sites, taken from independent genomic loci, were therefore analyzed. Black curves in panels D and F of φ are close to those of PIs, which is not typical for normal promoters. Deletion of hns increased transcription output from at least 4 investigated PIs (manuscript in preparation). Thus we concluded that H-NS is involved in interaction with PIs, and structural properties of its binding sites contribute to the specific characteristics of promoter islands.Analyzed data sets testified almost equal interaction of Fis and IHF with Genomic islands” identified by IslandViewer promoter islands. Except GIST, the largest overlap was observed with genes, whose foreign origin was predicted on the basis of comprehensive sequence comparison or codon usage profiles Genomic islands” found by IslandViewer because foreign origin of long DNA fragments is predicted with a higher reliability than of single genes and IslandViewer makes predictions without relying on transcription signals.The histone-like protein H-NS acts as a global repressor of transcription and preferentially suppresses the expression of horizontally-acquired genes multiple promoters , the average number of TSPs was 1.3-fold higher but 5-fold lower than in PIs. Nineteen promoters of “Genomic islands” gave perfectly matching samples in the analyzed data set of sequence reads multiple promoters, but ∼2-fold greater than contribution given by PIs. Finally, 65.4% of alien promoters interacted with H-NS, which is also an intermediary between multiple promoters (46.9%) and PIs (100%). Thus, promoters of alien genes are more similar to PIs than promoters of two other groups.Though A/T content of the selected promoters was almost the same as in the set of alien promoters were intermediate between multiple promoters and PIs  and within three genomes of Enterobacter cloacae. S. enterica thus may be considered as a putative donor. We used PlatPromS version of our software previously adapted to the context of Salmonella promoters folD - fimA region in many strains of S. enterica and found that all of them contain normal promoters  with alien gene and sfmA . Therefopromoter islands with regulatory regions of potential donors revealed certain symptomatic features, which are exemplified in folD-sfmA(fimA) intergenic sequences from the genomes of S.enterica and E.coli by T-Coffee promoter island (underlined). Thirty-four substitutions decreased the AT content in this region, 47 were neutral, and 54 mutations increased it. Thus the total AT-content in the region flanking sfmA gene became higher than in the promoter area of fimA , which is typical for alien DNA and PIs. Thirty-five of 54 substitutions (64.8%) that increased AT content can appear as a result of cytidine deamination (shaded nucleotides in E.coli cytidine deaminase (gene cdd) is to produce uridine. So far it is not clear, whether this enzyme can modify cytidines within the DNA or RNA molecules, though in 3D structure it is related to the human cytidine deaminase specifically editing ApoB RNA (APOBEC-1) The ability to receive and assimilate foreign genes is a feature of bacterial evolution review: . MoleculE.coliTCGATAAATTsfmA at least two H-NS binding sites were evolved . To increase the resolution in the bottom part of the figure we changed the scale of the Y-axis at the level 0.54.(TIF)Click here for additional data file.Figure S2Histograms representing results of structural analysis for multiple promoters and promoters of alien genes. Metric parameters (specified under the X-axes) were obtained using the carbon  or phosphorus  chains. Studied genomic regions and the colors used are indicated in the panel A. The number of fragments that have similar values of the measured parameters were combined in the intervals “i”, which are indicated in panels. Parameters RL-SL, Ω and stacking energy were measured for fragments of different lengths in the range 20–200 bp. Observed dependences were exemplified for fragments of indicated length (S). The numeric values obtained for 58 promoters of horizontally acquired genes were normalized to the size of other sets. Molecular models of single and alien promoters were created for sequences lying around the transcription start points (between positions −150 and +149).(TIF)Click here for additional data file.Table S1promoter islands and other selected genomic regions.Genomic coordinates of (XLS)Click here for additional data file.


Schizosaccharomyces pombe. Under both normal and heat shock conditions, we found that polyadenylated antisense transcripts are broadly expressed while distinct expression patterns were observed for protein-coding and non-coding loci. Dominant antisense expression is enriched in protein-coding genes involved in meiosis or stress response pathways. Detailed analyses further suggest that antisense transcripts are independently regulated with respect to their sense transcripts, and diverse mechanisms might be potentially involved in the biogenesis and degradation of antisense RNAs. Taken together, antisense transcription may have profound impacts on global gene regulation in S. pombe.A strand-specific transcriptome sequencing strategy, directional ligation sequencing or DeLi-seq, was employed to profile antisense transcriptome of  Emerging evidence has suggested that both strands of eukaryotic genomes are transcribed Several antisense RNAs have been functionally characterized to date, including those involved in X-inactivation, genomic imprinting and clonal gene expression ArabidopsisTo monitor global antisense expression, several high-throughput strategies have been developed. Pioneering studies relied on microarrays consisting of both strands of the targeted genomic regions Schizosaccharomyces pombe with a Directional Ligation sequencing (DeLi-seq) strategy. Initial mapping results showed that nearly one third of protein-coding regions have high-confidence antisense expression, and antisense transcripts are dominate in meiotic and stress-response genes. Detailed analyses further revealed that antisense transcripts are regulated independently of their respective sense transcripts, and multiple distinct mechanisms might be broadly involved in the regulation of antisense expression. Our findings support the notion that gene expression and regulation are more complicated than previously appreciated even in single-cellular organism.Herein, we profile antisense transcriptome of To monitor sense and antisense transcriptomes simultaneously by high-throughput sequencing, we have developed a directional ligation sequencing strategy or DeLi-seq . Its oveS. pombe grown under both normal (NM) and heat shock (HS) conditions. We obtained ∼32 million 36-mer raw reads for the four libraries, two biological replicates for each condition. Of them, 96.9% (∼31.3 M reads) were mapped back to the reference genome with 74.8% (∼24.2 M reads) mapped to a unique genomic location  have antisense expression under normal and/or heat shock conditions  Stand-specific RNA-seq is expected to facilitate more quantitative transcriptome analysis by avoiding assignment of short sequence reads to the wrong strand , for which potential antisense transcription would be more prominently reflected by Pol II. These loci were further divided into two groups based on the relative ratio of antisense/sense transcripts (AS/S). The results showed that Pol II occupancy is significantly higher in loci with high-level antisense transcripts than those with lower AS/S ratio . We thus compared the DeLi-seq results with Pol II occupancy S. pombe as exemplified at the Guf1/Wis2 locus , suggesting that bidirectional promoters might be involved in antisense transcription in at least a subset of tandem gene loci.Independent regulation of sense and antisense transcripts implies that antisense transcripts are autonomously expressed, either with their own promoters or through other mechanisms. Emerging evidence suggests that bidirectional promoters are likely a major contributor for antisense expression in budding yeast S. pombe gene pair encoding the GRIP- and LEA domain-containing proteins, respectively. Using strand-specific RT-PCR, we detected the read-through transcript originated from the LEA gene . Taken together, these results suggest that transcriptional read-through, similar to bidirectional promoter, might partially explain antisense expression at the convergent loci in S. pombe.Transcriptional read-through is another mechanism underlying antisense expression p<1E-22; H2A.Z, a widely-conserved histone variant, is often found in the nucleosome free regions (NFRs) of eukaryotic promoters and involved in transcriptional gene regulationPol II occupancy was then examined with respect to the presence of antisense expression. We focused on convergent loci because antisense transcript, if there is any, is presumably the result of transcriptional read-through rather than driven by its own promoter. Therefore, the difference in Pol II occupancy (the above H2A.Z occupancy as well) can be interpreted without the complication of extra promoter activity. Strikingly, we found that the Pol II occupancy tends to be higher in the transcribed region of genes with antisense expression than those without , similarS. pombe transcriptome.Two possibilities might be plausible for increased Pol II occupancy at transcribed regions: (1) elongating Pol II associated with antisense transcription; or (2) stalling of Pol II due to antisense expression. We favor the second model in that the relative contribution of antisense transcription (compared to sense transcription) to Pol II occupancy is expected to be small. More importantly, H2A.Z occupancy is also higher at these antisense-containing regions, suggesting co-existence of H2A.Z and stalled Pol II . AlthougS. pombe transcriptome. For 302 (or 5.9%) protein-coding genes, the abundance of antisense transcripts is higher than their respective sense transcripts. Because antisense expression is condition-specific  and elongating Pol II (38). Our results, which showed elevated H2A.Z level tends to coincide with increased Pol II occupancy in the presence of antisense transcripts, suggest that H2A.Z might signal Pol II-associated exosome to degrade antisense transcripts at the convergent loci. In addition, a number of studies showed that promoter-associated short RNA (PASR) is a widespread phenomenon of active lociLastly, this study is focused on long polyadenylated antisense transcripts. Our results showed that they might play a role in gene regulation distinct from those antisense RNAs without polyA tails 2) and heated at 94°C for 3 min. RNA fragments were precipitated with GlycoBlue (Ambion) as a carrier. Reverse transcription (RT) of the recovered RNA was performed with SuperScript II reverse transcriptase (Invitrogen) in a 50 µl reaction, containing 2.5 pmol random primer (5′-AGA CAT TAC CCT GTT ATC CCT ANN NNN N-3′), 0.25 pmol oligo(dT) primer (5′-AGA CAT TAC CCT GTT ATC CCT ATT TTT TTT-3′), 100 units of RNasin (Promega) and 6 ng/µl freshly-made actinomycin D (which inhibits DNA-dependent DNA polymerase activity of reverse transcriptaseMethods S1). Ligation products were then gel purified to select the DNA fragments in the 200–300 bp range. 12-cycle PCR was then performed with Phusion Hot Start High-Fidelity DNA Polymerase (Finnzymes) to generate the final sequencing library, which was sequenced using Illumina/Solexa Genome Analyzer II.Fission yeast was cultured in rich medium with or without heat shock  was used to remove potential genomic DNA contamination; and a DNase I digestion step was also included. 250 ng of DNA-free RNA was used to perform reverse transcription (RT) with gene-specific primers. Since antisense and sense transcripts are unlikely to share same introns, we only use primer pairs span single exon to perform the validation. 30 cycles of PCR was performed in 20 µl reaction, which contains 1 µl of RT reaction, 1x AmpliTaq Gold buffer (ABI), 1.5 mM MgCl2, 0.2 mM dNTP, 3 pmol of forward primer, 3 pmol of reverse primer and 1.5 unit AmpliTaq DNA polymerase. We preferred to use AmpliTaq Gold DNA polymerase (ABI) to perform qPCR because the hot start performance of the enzyme provides higher specificity of amplicons. To monitor the amplification curve, 0.15 µl 10x SYBR Green I (Molecular Probe) was added to the 15 µl PCR reaction described in strand-specific RT-PCR. Each sample was prepared in duplicate to get more reliable Ct value.Total RNA was isolated from S. pombe was downloaded from GeneDB (ftp://ftp.sanger.ac.uk/pub/yeast/pombe/GFF/). A three-step procedure was then used to map raw sequence data to the reference pombe genome. Step 1: Short tags were mapped to the genome sequence using SOAP programS. pombe) using SOAP; Step 3, Unmapped reads in steps 1 and 2 were mapped to the S. pombe genome using BLAT with the parameters of ≥95% identity and gap size ≤2000 bp . Only uniquely mapped reads were used in the following analysis, and the definition of sense and antisense transcripts are based on known genome annotation. For 43 coding-coding pairs that are annotated to have partial 5′-5′ or 3′-3′ overlaps, approximately 0.04% of the all reads mapped to these regions. These ambiguous reads were eliminated to avoid double counting. To visualize the reads along the fission yeast genome, wiggle files were generated from uniquely mapped reads based on their location and counts.The genomic sequence (Sep. 2008 version) and genome annotation  of The coverage of each individual base in the genome was determined by normalizing to the total number of uniquely mapped reads for each condition and the results were stored in wiggle format. The data were then visualized by two methods: (a) we constructed a local gff2 database that integrates the reference genome sequence, known annotations and wiggle files generated from our dataset. The results can be visualized by GBrowse (GMOD project) and a local gff2 database; (b) Using a modified plotAlongChrom function in the BioConductor “tilingarray” package, base counts were plotted along genome annotation in a given region. A 16-bp window was used to perform data smoothing. S. pombe were downloaded from GeneDB (version 7/16/08). For each given protein-coding gene or noncoding RNA, the normalized count of reads uniquely mapped to the region was first computed. To determine the relative expression level, the read count was further normalized by the transcript length and mappability . Overall, 5079 protein-coding genes and 491 previously reported ncRNAsThe genome annotations of q value. A stringent criterion (q<0.05 and fold changes >2) was used to identify transcripts whose expression levels were significantly changed.Gene expression values were normalized based on the total number of uniquely mapped reads of each library. In order to increase the overall accuracy, the results of four additional libraries were included, which are technical replicates of the 4 libraries shown in the main text. These four libraries have fewer reads ; however, their gene expression profiles are well correlated with their respective technical replicates. To define differentially expressed transcripts between wide type and heat shock conditions, SAM  was employed to compute the S. pombe genes was download from GeneDBp value for the enrichment of a given functional category.GO enrichment analysis was performed with the topGO package (BioConductor), and GO annotations for S. pombe genome (Sep. 2008 version) in GeneDB. Genes with CDS less than 200 bp were excluded from the analyses. Probes fell in gene body, 1000 bp upstream of ORF start site and 1000 bp downstream of ORF end site were used to analyze the pattern of Pol II and H2A.Z. Gaussian filter (sd  = 40 bp) was used to smooth the data points. In the generated graphs, the height and the thickness of each curve represents the mean value and standard deviation of the local data points.ChIP-chip datasets of Pol II and H2A.Z were downloaded from GEO with accession ID GSE17271. Both Pol II and H2A.Z intensity was normalized by whole-cell genomic DNA. The localization of the probe was lifted to match the updated Detailed DeLi-seq library construction protocols and computational analyses are available in the Supplementary information file, Text S1Strand information facilitates more quantitative transcriptome analysis.(DOC)Click here for additional data file.Methods S1Supplementary Methods.(DOC)Click here for additional data file.Figure S1Overall coverage of sense transcripts.S. pombe, the coverage at the nucleotide level was computed based on the DeLi-seq reads uniquely mapped to the locus in the sense orientation. Cumulative plot is used to show the percentage of genes that passes each respective coverage threshold. Four DeLi-seq libraries were analyzed separately and the results showed that they have comparable coverage depth.For each annotated protein-coding gene in (TIF)Click here for additional data file.Figure S2Validation of novel introns.SPBP35G2.04c, two novel introns were identified by DeLi-seq, and one of them was randomly selected for validation.10 candidate novel introns were selected for validation. For each candidate, a pair of gene-specific primers was designed upstream and downstream of the putative intron. RT-PCR was performed with the RNA samples obtained from normal or heat shock condition. Genomic DNA was used as a negative control, which gives rise to unspliced products. For 8 out the 10 cases, spliced products with an expected size were observed. In the case of (TIF)Click here for additional data file.Figure S3Reproducibility of the DeLi-seq method.The count of uniquely mapped reads for each annotated locus was determined and normalized to the total number of reads of each library. Sense and antisense transcripts of each locus were treated as separated data points. Correlation coefficient was then computed between the two biological replicates of either normal (A) or heat shock (B) condition.(TIF)Click here for additional data file.Figure S4Reproducibility of sense or antisense read counts.Pairwise comparison of the normalized expression level of sense (A) or antisense (B) transcripts among four DeLi-seq libraries. The histograms on the main diagonal represent the expression distribution of individual libraries. Each scatter plot was generated based on the normalized gene expression levels obtained from the two corresponding libraries. Pearson correlation coefficients are shown for all possible library pairs.(TIF)Click here for additional data file.Figure S5Identification of gene loci with high-confidence antisense expression.2(S/AS) follows a negative binomial distribution Click here for additional data file.Figure S6Visualization of DeLi-seq results.A 30 kb genomic region is shown with known annotations (upper panel), including protein-coding genes (light blue) and ncRNAs (green). In the lower panel, read counts from the top strand (orange) and bottom strand (dark blue) are shown separately. For SPAC10F6.15 locus, the level of antisense transcripts is much higher than that of sense transcripts (open box).(TIF)Click here for additional data file.Figure S7spo6 locus.Dominant antisense expression at the Spo6 gene is encoded on the Watson strand based on genome annotation. However, majority of the reads were mapped to the Crick strand in this locus under both normal and heat shock conditions.(TIF)Click here for additional data file.Figure S8Comparison between DeLi-seq and HybMap results.http://bioserver.hci.utah.edu/SupplementalPaperInfo/2008/Dutrow_NatGen_PombeTranscriptome/. The data set contains the expression values that were computed based on the probe intensity subtracted against the background (intergenic regions). Pearson correlation coefficient (R) was computed for both sense (A) and antisense (B) transcripts.For DeLi-seq method, the relative expression level of each transcript was computed based on normalized read count. HybMap data was downloaded from (TIF)Click here for additional data file.Figure S9Validation of antisense expression by strand-specific RT-PCR.PP: S≥ AS in both NM and HS; PN: S≥ AS in NM and S< AS in HS; NP: S< AS in NM and S≥ AS in HS; NN: S< AS in both NM and HS). To carry out strand-specific RT-PCR, either the forward or reverse primer was added at the RT step, which specifically amplifies the antisense or sense transcripts, respectively. As a positive control, both primers were added at the RT step (T). In addition, RT reaction was also performed without any primer to serve as a negative control (−). The final PCR products were resolved by agarose gel electrophoresis, and each of the primer pairs gave rise to a specific band with expected size.16 genes were randomly selected to examine antisense expression. These genes are broadly divided into four different categories based on the ratio of sense (S) and antisense (AS) transcripts ((TIF)Click here for additional data file.Figure S10Comparison of antisense expression level in differentially expressed genes.Differentially expressed genes were divided into two groups based on sense-antisense expression correlation. The correlated group (Cor) contains sense-antisense pairs with correlated or anti-correlated expression patterns. The non-correlated group (Non-Cor) group consists gene loci for which sense and antisense transcripts are independently regulated. The absolute antisense expression level (A) or relative antisense/sense ratio (B) was then compared between the two groups by one-way ANOVA test. No significant difference can be detected between the two subcategories in terms of antisense expression level (p = 0.125) or antisense/sense ratio (p = 0.776).(TIF)Click here for additional data file.Figure S11Bidirectional promoter leads to antisense transcription in tandem gene pair.Wis2-Guf1 locus. The sense transcripts of these two genes (solid boxes) are encoded on the negative strand of chromosome 1, and organized in a tandem orientation. Based on the DeLi-seq results, the expression of Guf1 antisense transcripts (dashed box) are increased under the heat shock condition and the increase is coordinated with Wis2 sense transcript. Wis2 encodes a peptidyl-prolyl isomerase required for protein unfolding, transport and assembly. The Guf1 sense transcript encodes a mitochondrial matrix GTPase associated with mitochondrial ribosome, and is known to be down-regulated by heat shock. (B) Validation of DeLi-seq results for the Wis2-Guf1 locus by strand-specific RT-PCR. T, combined level of sense and antisense transcripts; A: antisense transcripts; S: sense transcripts; -, negative control, for which no primer was added during reverse transcription. (C) A conventional heat shock element (HSE) with multiple GAA blocks is identified in the candidate bidirectional promoter region. Both sense transcript of Wis2 and antisense transcript of Guf1 have their own TATA-box (black block).(A) A Schematic diagram of the (TIF)Click here for additional data file.Figure S12Antisense transcripts derived from transcriptional read-though at a convergent locus.SPBC365.11 and SPBC365.12c loci. The two sense transcripts (solid box) are coded on different strands and organized in a convergent orientation (tail-to-tail). The expression level of both SPBC365.12c and the antisense transcripts to SPBC265.11 (dashed box) are induced by heat shock. In contrast, the sense transcript of SPBC365.11 is transiently down-regulated under the heat shock condition. (B) Heat shock induced transcriptional readthrough is confirmed by strand-specific RT-PCR. T, Total level of sense and antisense transcripts; AS, expression level of antisense transcripts; S, expression level of sense transcripts; -, negative control, which contained no primer during reverse transcription. In order to detect readthrough transcripts, a primer pair was used which spans the two annotated genes; the relative locations of these two primers are shown. At the RT step, only left (L) or right (R) primer was added to detect readthrough transcript of right (SPBC365.12c) or left (SPBC365.11) gene. The readthrough transcript of SPBC365.12c gene was apparent under the heat shock condition.(A) Schematic diagram of the (TIF)Click here for additional data file.Figure S13Differentially expressed sense and antisense transcripts identified by DeLi-seq.q<0.05 and >2-fold change) are shown as colored dots in a MA plot. Up-regulated (red and blue) and down-regulated (green and magenta) are shown. False negative (blue and magenta) and false positive (black) genes were determined assuming strand information is not provided. (B) The number of false positives and false negatives obtained in (A) are color coded and shown in a Venn diagram.(A) Differentially expressed sense transcripts ((TIF)Click here for additional data file.Table S1Mapping efficiency of sequencing reads.(DOC)Click here for additional data file.Table S2The reads mapped to the exon-exon junctions in sense and antisense transcripts.(DOC)Click here for additional data file.Table S3Uniquely mapped reads in protein-coding region and ncRNAs.(DOC)Click here for additional data file.Table S4GO analysis of genes with AS ≥S in both NM and HS.(DOC)Click here for additional data file.Table S5GO analysis of genes with AS ≥S in NM but not HS condition.(DOC)Click here for additional data file.Table S6Primers used for strand-specific RT-PCR and qPCR.(DOC)Click here for additional data file.