This small nuclear RNA is transcribed by RNA polymerase II from individual promoters. In Leishmania tarentolae the SL RNA genes reside in two multi-copy tandem arrays designated MINA and MINB. The transcript accumulation from the SL promoter on the drug-selected, episomal SL RNA gene cassette pX-tSL is ~10% that of the genomic array in uncloned L. tarentolae transfectants. This disparity is neither sequence- nor copy-number related, and thus may be due to interference of SL promoter function by epigenetic factors. To explore these possibilities we examined the nucleoplasmic localization of the SL RNA genes as well as their nucleosomal architecture.The spliced leader (SL) RNA provides the 5' mMINA array was resistant to micrococcal nuclease digestion between the -258 and -72 positions relative to the transcription start point due to nucleosome association, leaving the promoter elements and the entire transcribed region exposed for protein interactions. A pattern of ~164-bp protected segments was observed, corresponding to the amount of DNA typically bound by a nucleosome. By contrast, nucleosomes on the pX-tSL episome were randomly distributed over the episomal SL cassette, reducing transcription factor access to the episomal promoter by approximately 74%. Cloning of the episome transfectants revealed a range of transcriptional activities, implicating a mechanism of epigenetic heredity.The genomic SL RNA genes and the episome did not co-localize within the nucleus. Each genomic repeat contains one nucleosome regularly positioned within the non-transcribed intergenic region. The 363-bp The disorganized nucleosomes on the pX episome are in a permissive conformation for transcription of the SL RNA cassette approximately 25% of the time within a given parasite. Nucleosome interference is likely the major factor in the apparent transcriptional repression of the SL RNA gene cassette. Coupled with the requirement for run-around transcription that drives expression of the selectable drug marker, transcription of the episomal SL may be reduced even further due to sub-optimal nucleoplasmic localization and initiation complex disruption. The SL provides a 5' cap to the polycistronically transcribed mRNA and has been implicated in mRNA translation [Leishmania tarentolae, a striking observation was made regarding the transcriptional activity of the SL RNA gene cassette expressed on the pX plasmid [Leptomonas seymori [Leishmania versus Leptomonas have been useful for studying SL RNA gene mutations that would otherwise be dominant negatives at competitive levels. Splicing defective mutations expressed from high copy episomes, presumably due to the relative abundance of the toxic mutated SL RNA, were not tolerated within Leptomonas and quickly lost [The spliced leader (SL) RNA gene represents the best-characterized transcriptional system in kinetoplastids. The SL RNA is a non-coding small nuclear (sn) RNA that is nslation . During  plasmid ,3. Thoug plasmid . A simil seymori . Functiokly lost .c) [L. tarentolae are organized into two separate, head-to-tail tandem arrays, MINA and MINB [MINA array contains ~60 gene copies with a 363-bp repeat length of which 105 are transcribed, resulting in a 96-nt mature transcript. The MINB array has ~40 copies, with a periodicity of 296 bp. The transcribed regions in both arrays are identical. The non-transcribed regions contain a bipartite promoter at -67/-58 (the -60 element) and -40/-31 bp (-30 element) from the transcription start site in the MINA array [MINA tagged SL (tSL) RNA gene cassette in the pX episome contains the transcribed region with an 11-bp mutation in the 28–39-nt region of the exon, 100-bp of upstream sequence including the -60 and -30 elements, and 45 bp of sequence downstream of the transcription-termination inducing T tract [L. tarentolae multimerizes the plasmid into larger circles with five or six complete copies per molecule. The parasite will amplify variably the amount of multimers in any cell, with ratios of genomic:episomal SL RNA genes ranging from 0.5 to 7.4 [MINA or MINB promoter in the episomal context. Thus the reduction in transcriptional activity is not related directly to the sequence of the SL RNA gene cassette in pX [The SL RNA gene is transcribed by an RNA polymerase (RNAP) II complex -11. As fc) ,12-16 asc) ,17,18. Tand MINB . The MIN T tract . When trte in pX .Trypanosoma brucei nucleus migrate to a perinucleolar RNAP I-containing domain upon activation, whereas the distributed rRNA loci congregate at a RNAP I domain in the nucleolus. [Trypanosoma cruzi epimastigote occurs in a single spot, in this case a perinucleolar RNAP II factory [Transcription in the nucleus tends to occur in discrete sub-nuclear domains . These dcleolus. . Transcr factory .Template access and nucleosome positioning are vital to RNAP II transcription initiation in eukaryotes . A surveL. tarentolae genomic SL RNA gene array and on the SL RNA gene cassette in the episomes. Both the nucleosomal organization and localization of the episomes are different and discrete from the genomic loci. Clonal episome lines have varying transcriptional activities, suggesting a mechanism of epigenetic heredity. These observations provide a tangible explanation for the observed differences in transcription between the episome and the genomic SL RNA gene array.To assess structural differences between the episome and the chromosomal array, we localized the SL RNA gene array and the pX episome relative to one another within the nucleoplasm and mapped the nucleosome positions in both the in situ hybridization (FISH). As the genomic SL RNA genes appear in two distinct arrays in the haploid genome, we would anticipate seeing up to four SL RNA gene signals per nucleus. For the episome, the number of discrete molecules is between 20–30, thus the range of possible distributions is between one to several dozen.Differential nucleoplasmic localization could be a contributing factor in the reduced transcription of the episomal SL RNA genes. The relative positions of the genomic SL RNA gene arrays and the pX-tSL RNA gene episomes were established by fluorescent L. tarentolae showed that MINA and MINB reside in a single spot within the nucleus  digestion of chromatin in permeabilized cells. MNase digestion mediates efficient double-stranded breaks in linker DNA and is blocked on nucleosome-associated DNA.Given the paucity of information concerning transcription initiation and chromatin organization in kinetoplastids, we sought to investigate the chromatin context of both the SL RNA gene locus and pX-tSL RNA gene episome. Nucleosome distributions on the Digestion of the parasite chromatin with a range of MNase concentrations showed a characteristic ladder of DNA fragments when separated on agarose gels Figure . The botL. tarentolae by this assay is comparable with those seen in T. brucei and T. cruzi as well as higher eukaryotes [The nucleosome configuration in karyotes ,34. The By using a selected series of oligonucleotide probes we can determine areas of DNA protection by nucleosome binding . BlottinMINA SL RNA gene array .Primer extension mapping was performed to confirm the blot results and to map precisely the locations of the high occupancy nucleosomes on the MINA nucleosomes showed four definitive stops at nucleotides -258, -251, -249, and -237 relative to the start site of transcription. The 5'-most band corresponded with the 3'-end of the poly-T tract downstream of the preceding SL RNA gene, the termination signal for the SL RNA gene transcription complex [BssHII and one for DraIII. The second band seen in the BssHII control was unexpected and may represent sequence heterogeneity within the MINA non-transcribed region. However, this unexpected pattern is likely enzyme-mediated, given that all other restriction enzymes used in this assay produced the predicted number of stops, and BssHII is known to exhibit star activity. There were four definitive stops in the 3' map with similar relative spacing to the results for the 5' map. The stops mapped to positions -92, -88, -87, and -72. Taken in pairs, the gaps measured 166 bp, 163 bp, 162 bp, and 165 bp, suggestive of a nucleosome core particle (146 bp)[Primers located in nucleosome-protected fragments were extended and separated on a high-resolution gel alongside a sequencing reaction using the same primer Figure . The arr (146 bp) plus his (146 bp) , showed no preferential protection. The probability of protection between any of the areas analyzed within the 500-bp region was approximately the same, indicative of nucleosome occupancy across the entire sequence distributed across the population of molecules. The blotting results for the pX-tSL RNA gene episome inidicated randomly distributed nucleosomes within the transfectants. Primer extension mapping was performed as on the chromosomal locus and no informative bands were produced (data not shown), as anticipated for a randomized nucleosome distribution.Leptomonas was the absence of single-cell cloning for the Leishmania transfected lines [L. tarentolae transfectants. This simple difference could account for the transcriptional disparity between the two systems, and predicts that cloned transfectants have varied transcriptional activities. Uncloned populations of cells expressing green fluorescent protein from epsiomal plasmids show heterogeneous levels of protein expression (data not shown). In an uncloned population there could either be a range of cells that express the tSL RNA gene cassette at different levels that average out to 5–10% of total SL RNA production; alternatively, each cell may express the tSL RNA at the same, relatively low rate.One difference between our transfection studies and those performed in ed lines . To explL. tarentolae population were examined. Poison-primer extension was used to quantify the ratio of endogenous to tSL RNA expressed in the clonal lines, while Southern blots reported the episome quantity normalized to the genomic copies  might affect the topology of the gene. Nucleosomal binding creates a bend in the DNA of 85° [SacI and BglII sites.Considering the bends induced within a genomic array due to nucleosome association and active transcription initiation, the SL RNA gene itself could exist in a topologically complex structure. Nucleosomal condensation and transcription-initiation complex binding could contribute to the discrete sub-nucleoplasmic localization seen A of 85° , likewisA of 85° ,32,40. WA of 85°  containiL. tarentolae nuclear extracts and their relative mobility measured. The mobility of the maximally-bent EcoRV-released DNA, with the -60 element in the middle, was 73.2% of the mobility in EMSA of the minimally-bent BamHI- and EcoRI-released fragments where the -60 element was located closer to either end  of 0.732. Using the formula illustrated in Figure The -60 element can be released from the plasmid on identical-sized (409 bp) restriction fragments at multiple positions relative to the ends of the DNA Figure . Inducedd Figure  meaning In all experiments, binding of the complex to the mutated probes was never observed Figure , thus weL. tarentolae follows a regular pattern of approximately 160-bp nucleosome-bound DNA separated by an approximately 70-bp linker region. The nucleosomes on the genomic SL RNA gene array, however, are essentially excluded from the 185-bp promoter and transcribed regions, and reside in a narrow range of positions within the non-transcribed intergenic spacer. In addition to nucleosome-induced bending, transcription factor binding at the SL RNA gene -60 promoter element may introduce a further 80° kink into each array repeat. In contrast with this transcriptionally-permissive arrangement in the genomic array, nucleosomes on the episomes are randomly distributed over the tSL RNA gene cassette, potentially obscuring the tSL RNA gene promoter up to 74% of the time. Cloning of the pX-tSL RNA gene transfectants had a notable effect on the tSL RNA gene transcript contribution of the episome, but did not approach genomic levels nor show significant alteration in nucleosome distribution. The combination of differential sub-nucleoplasmic localization and nucleosome arrangements between the genomic and episomal SL RNA genes indicate that altered access to the SL RNA gene promoter elements accounts in large part for the variance in SL RNA relative to tSL RNA. The SL RNA genomic nucleosome placement is consistent with RNAP II promoter architecture in other organisms, such as yeast [Here we examined the spatial and structural organization of genomic and episomal versions of SL RNA genes to assess epigenetic factors that could affect levels of gene transcription. The episome and genomic arrays do not co-localize within the parasite nucleus. The chromatin in as yeast ,42. Give6C) found in other eukaryotes [T. brucei, base J is associated with repeated sequences including the SL RNA gene array [Leishmania [L. tarentolae SL RNA genes in either the chromosomal or episomal context.Factors other than chromatin configuration can contribute to epigenetic effects on transcriptional regulation. Such factors include DNA modification  and topokaryotes ; the maikaryotes . As wellne array . Base J ishmania , howeverT. cruzi SL RNA gene array resides in a specialized RNAP II transcriptional domain [L. tarentolae SL RNA genes are likely to reside in a similar specialized domain given the chromosomal arrays localization in a single nuclear spot. In L. tarentolae, the probe used to localize the arrays did not distinguish between the MINA and MINB loci. A single spot in the nucleus argues in favor of a single specialized transcription zone for SL RNA gene expression. Likewise, the discrete localization of the episomes are consistent with the concept of transcriptional zoning. The episomes reside as a series of 20–30 concatamerized circular DNA species within the nucleus. In Leptomonas and L. major, catenated episomes have been observed, but the steady state number of these species are relatively small compared to the free circles [The l domain . The L.  circles ,49, thusL. tarentolae SL RNA gene promoter is similar to those measured for TATA-box promoter-bound TBP in humans [LtTBP or some other factor in the L. tarentolae PreIC. Bending of DNA upstream of the vertebrate U6 snRNA promoter is mediated not by TBP and SNAPc but by a precisely-positioned nucleosome [L. tarentolae -60 element is essential for transcription [T. cruzi are adjacent to the nucleolus in transcriptionally-active cells, yet dispersed in the nucleoplasm with the presence of transcription inhibitors [T. cruzi. The cumulative effects of inherent DNA bending by the nucleosome [The bend angle of 82° measured for the n humans . At prescleosome . Since tcription , alterathibitors . A regulcleosome  and by tL. tarentolae PreIC  is sign: 38.5 Å . The tra: 38.5 Å , transcr to FACT  may incrMINA array is distinct from that of the average nucleosomal array in L. tarentolae, and may reflect the dynamics of transcription factor association, active transcription, and nucleosome placement in non-transcribed regions. Because the intergenic regions in the array are not transcribed [T. brucei SL RNA gene array, which encodes a ~150-nt primary transcript and has the largest non-transcribed intergenic region characterized among the kinetoplastids, we would envisage 220-bp nucleosome-free regions spanning the promoter element and transcribed regions separated by up to five bound nucleosomes. Likewise, SL RNA gene arrays that are interspersed with 5S rRNA genes [MINA array is just sufficient to accommodate a single nucleosome, a fortuitous situation for our nucleosome mapping.We have correlated the repression of episomal transcription with nucleosome association. The specific periodicity of the nucleosomes within the nscribed , nucleosnscribed . AlternaNA genes  may limiL. tarentolae the SL RNA genomic and pX-tSL RNA gene episomes reside in discrete sub-nuclear locations. Nuclease protections indicate that a single nucleosome is positioned on the chromosomal SL RNA gene array in the intergenic region, leaving the promoter and transcribed gene region nucleosome-free. The array periodicity of one nucleosome per 363 bp differed from the standard heterochromatin arrangement in L. tarentolae of one nucleosome per 230 bp. The array is bent further by the interaction with transcription factors. By contrast, nuclease protection studies suggest that the pX-tSL RNA gene episome nucleosomes were distributed evenly. Nucleosome arrangement may be vital for efficient transcription initiation. We estimate the maximum percentage of promoter accessibility at 26% in the episomes, and other competing factors explain the observed episomal transcription levels of 10% in L. tarentolae. The presence of distinctly different transcriptional activities in cloned pX-tSL RNA gene lines argues for maintained epigenetic context for each clone.We describe two epigenetic features for episomal and genomic SL RNA genes that may result in lower expression of the episomal cassette. In L. tarentolae UC(A) strain parasites were used for all subsequent assays and transfections. Cells were grown in Brain Heart Infusion media supplemented with 100 mg/ml of hemin at 28°C. Transfections were performed as described [L. tarentolae SL RNA gene locus with a mutated region in bases +28 to +39 that served as a molecular tag, tSL. Transfectants were selected and maintained in 200 μg/ml of paromomycin (PGC Scientific). Cell lines were cloned on paromomycin/BHI agar plates following a protocol provided by A. Simpson and L. Simpson [The  Simpson .L. tarentolae cells were grown to mid log phase (3–7 × 107) and fixed in 2% formaldehyde/1× PBS for 15–30 min. Fixed cells were washed twice, resuspended in PBS, and adhered to slides coated with 0.5 mg/ml poly-L-lysine (Sigma). The cells were permeabilized with 0.1% NP-40/1× PBS for 10 min. The slides were washed three times with PBS, and incubated with 10 μg/ml proteinase K (Roche), 10 μg/ml RNase A , 1× PBS at 37°C for 10 min. The treated slides were washed three times in 1× PBS and dehydrated with sequential, 2 min washes in cold 70%, 90%, and 100% ethanol, and allowed to dry. The DNA was denatured prior to hybridization at 85°C in 70% formamide, 2× SSC for 5 min. Hybridizations and washes were the same for both oligonucleotide and PCR prepared probes. Hybridizations were performed in 50% formamide, 1× SSPE, 10% Dextran, 250 μg/ml salmon sperm DNA. PCR prepared probes were used at a concentration of 3 μg/ml, oligonucleotide probes were used at 1 μg/ml and the hybridization/probe mixture was denatured at 85°C for 10 min, spun down and plunged into an ice bath. The denaturing solution was removed from the slides and the predenatured probe/hybridization solution was applied. The slides were then incubated at 85°C for 3 min and transferred to a humid chamber prewarmed to 60°C. The chamber was equilibrated to 35°C and the slides incubated overnight. The slides were washed twice in excess 50% formamide, 2× SSC at 35°C for 15 min. The slides were then washed twice in excess 2× SSC at 50°C for 15 min. The final wash was performed in 1× SSC at room temperature for 15 min. The slides were dried and mounted with Vectashield mounting medium (Vector labs) containing 70 μg/ml 4',6-diamidino-2-phenylindole . Images were visualized using either a 100× or 63× objective on a Zeiss Axioscop2. Images were captured with a Zeiss Axiocam using the Axiovision software suite. (Carl Zeiss Inc.)The Two types of DNA probe were used: oligonucleotides synthesized with incorporated fluorophores, or PCR-amplified dsDNA fragments that had fluorophores subsequently conjugated to guanine residues. The PCR probes were labeled with the Ulysis Alexafluor 488 (green) (Invitrogen). Amplified probes were purified from the initial PCR reaction using DNA purification columns (Qiagen) and either restriction digested or DNase I digested down to fragments of ~100–200 bp (Invitrogen).L. tarentolae cells were grown to mid log phase (3–7 × 107 cells/ml) and centrifuged at 3500 g for 5 min. The cell pellet was resuspended and washed twice in chilled incomplete MNase Protection Assay (MPA) buffer . The cells were then permeabilized by treating with 500 μg/ml lysolethicin in completed MPA buffer (completed with the addition of 1 mM DTT and 10 μg/ml leupeptin) for 10 min. The cells were washed twice and resuspended at 2 × 109 cells/ml in complete MPA buffer. Microccocal nuclease (USB) was added to 200 μl aliquots of cells. The MNase was titrated over a range of 5–1000 units/ml. Cells were incubated at 37°C for 3 min, the reactions were stopped, and the cells lysed with the addition of 200 μl of 2× Stop solution ). The lysates were incubated at 55°C for 4–16 h. These digestions were then phenol/chloroform extracted, precipitated with the addition of 1/10th volume of 3 M sodium acetate pH 5.0 and 2–3 volumes of ethanol, and incubated at -20°C for a minimum of 2 h prior to centrifugation. The prepared DNA was resuspended in TE and treated with 100 μg/ml RnaseA at 37°C for 1 h prior to further analysis.Fifty milliliters of 32ATP. The hybridization conditions were as follows: Membranes were pre-incubated in a solution of 6× SSC, 1× Denhardts solution, 0.5% SDS and 10 μg/ml yeast tRNA (Sigma) at 42°C for 10 min-1 h. Twenty-five nanograms of probe were hybridized in 6× SSC, 1× Denhardts solution, 0.1% SDS, and 10 μg/ml yeast tRNA at 42°C for a minimum of 2 h. The blots were washed of excess probe in 0.1% SDS, 2× SSC at a salt adjusted Tm calculated using the Oligonucleotide Properties Calculator [The mapping protocol was adapted from Gregory and Hörz . The MNalculator . The waset al. [Taq polymerase (CLP). Four to eight μl of the sample and control DNA was added along with 10 ng of the 5'-end labeled, specific primer to a 20 μl Taq reaction. The reaction was cycled 20–30 times in a thermocycler (MJ Research) to extend the primers to the end of the MNase-digested template. After cycling, 8 μl of sequencing stop solution  was added to the reaction. The reaction was denatured at 85°C for 5 min and quickly cooled to 4°C in a thermocycler. The extension products were separated on a 1× TBE/6% polyacrylamide/8 M urea sequencing gel (Whatman/Biometra). The gel was transferred to a 0.4 mm Whatman paper, covered in plastic film, and vacuum dried. The dried gel was exposed overnight on an imager screen (GE Bioscience) and imaged on a PhospoImager 445 SI scanner (GE Bioscience).The primer extension protocol was adapted from Ryan et al. . High reL. tarentolae nuclear extracts and EMSA were performed as described [et al. showed that when a molecule (of length L1) is bent at its midpoint, as would occur during an EcoRV digest (yielding an end-to-end length of L2), the ratio of end-to-end distances .escribed . The angescribed ,57. A 34escribed . The resgh a gel . Mx was RNA from each cell line was extracted using TriZOL (Invitrogen) as described . Primer DraIII and NotI (New England Biolabs) restriction enzymes, yielding a DraIII genomic fragment of 363 bp and a 220 bp episomal DraIII/NotI fragment. The digests were separated on a 1.5% low melt agarose gel (Fisher) and blotted onto nylon membranes (GE Bioscience) by capillary transfer with 10× SSC for 4 h. Blots were probed with end labeled oligos with sequences shared by both the episomal and genomic SL RNA genes. Imaging and quantification were performed in a similar manner to the previously described Southern blot nucleosome mapping. The amount of episome was expressed as a ratio of episomal signal divided by genomic signal.Genomic DNA from the different clones and controls was isolated with DNAzol (Invitrogen) using the standard protocol. The DNA was digested with RH performed the localization and nucleosome experiments, data analysis and interpretation, and drafted the manuscript. ST performed the DNA bending analysis. DC conceived of the project and participated in data analysis and interpretation. NS participated in data analysis and interpretation, and drafted the manuscript.


Neurospora crassa, and find that it forms a relatively compact dimeric molecule, each subunit of which comprises several domains with, at its core, a catalytic apparatus and protein fold strikingly similar to the catalytic core of the DNA-dependent RNA polymerases responsible for transcription. This evolutionary link between the two enzyme types suggests that aspects of RNA silencing in some organisms may recapitulate transcription/replication pathways functioning in the ancient RNA-based world.RNA silencing refers to a group of RNA-induced gene-silencing mechanisms that developed early in the eukaryotic lineage, probably for defence against pathogens and regulation of gene expression. In plants, protozoa, fungi, and nematodes, but apparently not insects and vertebrates, it involves a cell-encoded RNA-dependent RNA polymerase (cRdRP) that produces double-stranded RNA triggers from aberrant single-stranded RNA. We report the 2.3-Å resolution crystal structure of QDE-1, a cRdRP from  Neurospora crassa. A striking resemblance to eukaryote and bacterial DNA-dependent RNA polymerases was observed.Insights into RNA-induced gene silencing are gained from the structure of an RNAi (RNA-dependent RNA) polymerase from RNA silencing, or RNA interference (RNAi), refers to a group of RNA-induced gene silencing mechanisms that developed early in the eukaryotic lineage and play essential roles in cellular immunity, modulation of chromatin structure, and development –3. RNAi Neurospora crassa (quelling) is one of the best studied models for RNAi. Three genes products were identified by screening for quelling defective phenotype, QDE-1 (cRdRP), QDE-2 (Argonaute), and QDE-3 (RecQ-like helicase) [Transgene silencing in elicase) . Subsequelicase) . We haveelicase) .In order to understand the functionality of the QDE-1 in more detail, we have determined the high-resolution crystal structure. This reveals the molecule to be dimeric and containing at its core two subdomains responsible for catalysis. These subdomains each have the topology of double-psi β-barrels (DPBBs), and are similar to (and disposed in a similar fashion to) two separate subunits in the DNA-dependent RNA polymerases (DdRPs) that perform transcription across the domains of life. The structure not only suggests how the molecule might efficiently produce dsRNA triggers, but may also add a piece to the jigsaw that relates the RNA world to the DNA world, and provide a model for all cellular RdRPs.1,P2 and the crystallographic asymmetric unit contains two subunits, which together form a compact pyramidal object with dimensions of 90 × 70 × 127 Å3. The two constituent subunits are related by an approximate 2-fold axis and are in such intimate contact  that we would expect this to represent a functional dimer [work of 21.7% (Rfree = 26.4%), and the stereochemistry is good  analysis of a crystal of selenomethionated protein, expressed in yeast, to a resolution of 3.2 Å . The stral dimer . This wa; C2 see . In spacEach QDE-1 subunit contains 41 α-helices and 25 β-strands, creating a four domain fold previously undescribed for RdRPs A and 1B.2+ ion coordinated by these aspartic acid side chains . Overall, QDE-1 exists as a compact, but flexible, dimeric enzyme with metal binding sites confirming positions of the catalytic sites but with extensive additional structure whose biological functions are less immediately clear.The QDE-1 ΔN molecule has several distinct channels and cavities: first, there is a channel formed between the slab and head of each subunit, which is highly positively charged and leads to the active site A; we pro2+ coordination to metal A in the yeast enzyme [A search using the QDE-1 ΔN active site residues (ASSAM ) identift enzyme . Moreovet enzyme ,21, are t enzyme . IntriguOverall, the DdRP structures are much more elaborate than QDE-1 ΔN, and we can detect no significant structural similarity beyond the vicinity of the active site. Nevertheless, there may be some functional relationship at the level of protein domains. The flexible head that forms part of the proposed QDE-1 product groove might be equivalent to the clamp in yeast Rbp1 : the heaQDE-1 ΔN is active in solution , and we Helicobacter pylori also has its active site on a single chain, due to the fusion of the rpoB and rpoC genes, coding for the β and β′ subunits [Escherichia coli β-β′ protein can assemble into a functional polymerase, although there is presumably some advantage in vivo for separate β and β′ chains [From the structure of QDE-1, it appears that all cellular RdRPs as well as DdRPs are related but structurally distinct from viral RdRPs, which have the “right-hand” architecture –30. The subunits . Indeed,′ chains . Classif1P2), and two native datasets (space group 1P2 and C2) have been described previously [1P2 data to 2.3-Å resolution to yield the final model described in the main text and C2 crystal form with one molecule in the asymmetric unit was solved by molecular replacement and refined, keeping the domains as rigid bodies  and ESPript [Figures were prepared using PyMOL ( ESPript .QDE-1 ΔN size was determined by (1) gel filtration  with blue dextran , catalase (232 kDa), aldolase (158 kDa), bovine serum albumin (68 kDa), ovalbumin (43 kDa), chymotrypsin A (25 kDa), and RNase A (13.7 kDa) as molecular mass markers; and (2) by sedimentation in a linear 10% to 40% sucrose gradient in 50 mM Tris-HCl (pH 8.0), 350 mM NaCl , with catalase (232 kDa), bovine serum albumin (68 kDa), phage PM2 protein P2 (30.2 kDa), and lysozyme (14 kDa) as molecular mass markers.Figure S1Schizosaccharomyces pombe, Spo; Neurospora crassa, Ncr; and Gibberella zeae, Gze) and Basidiomycota , slime molds , dicot plants , monocot plants , protozoa , and nematodes  were aligned using standard settings of ClustalW algorithm. Local alignment was improved by manual editing. N. crassa QDE-1 protein sequence is shown on the top. N. crassa contains two additional non-allelic cRdRP genes—SAD-1  and RdRP-3—that likely function in distinct cellular pathways. Invariant residues are shaded in black; other residues with 80% or more conservation are shaded in grey. Conserved sequence motifs comprising invariant residues are outlined: motif 1, red; motif 2, orange; motif 3, dark yellow; motif 4, purple; motif 5, violet; motif 6, light pink; and motif 7, blue. QDE-1 secondary structure elements are shown on top, coloured according to domain definition . The identified double-psi β-barrels DPBB1 and DPBB2 are outlined by deep purple boxes. The flap sub-domain and the potential “bridge helices” are also represented by boxes, coloured light purple and grey, respectively.Multiple sequence alignment of a representative subset of cRdRPs. Amino acid sequences of 30 cRdRPs from fungi from the groups of Ascomycota ((914 KB DOC)Click here for additional data file.http://www.rcsb.org/pdb) as accession numbers 2J7N and 2J7O. The GenPept accession numbers for the genes and gene products mentioned in this paper are N. crassa QDE-1 protein sequence (EAA29811); dRP-3 (EAA34169); and N. crassa SAD-1 (AAK31733).Coordinates and structure factors have been deposited in the Protein Data Bank (PDB;


The glucocorticoid dexamethasone was observed to decrease urokinase plasminogen activator (uPA) RNA levels from within 1 h of treatment of MAT 13762 mammary adenocarcinoma cells. The drug did not alter the rate of uPA gene transcription in these cells, but decreased the stability of cytoplasmic uPA mRNA transcripts. Results from cycloheximide and actinomycin D experiments indicated that the dexamethasone-mediated reduction in uPA RNA required both new protein and RNA synthesis. Based on these results, we propose that dexamethasone induces a short-lived protein(s) which down-regulates uPA RNA levels post-transcriptionally in these metastatic tumour cells.


Gene expression profiling by microarray analysis of cells enriched by laser capture microdissection (LCM) faces several technical challenges. Frozen sections yield higher quality RNA than paraffin-imbedded sections, but even with frozen sections, the staining methods used for histological identification of cells of interest could still damage the mRNA in the cells. To study the contribution of staining methods to degradation of results from gene expression profiling of LCM samples, we subjected pellets of the mouse plasma cell tumor cell line TEPC 1165 to direct RNA extraction and to parallel frozen sectioning for LCM and subsequent RNA extraction. We used microarray hybridization analysis to compare gene expression profiles of RNA from cell pellets with gene expression profiles of RNA from frozen sections that had been stained with hematoxylin and eosin (H&E), Nissl Stain (NS), and for immunofluorescence (IF) as well as with the plasma cell-revealing methyl green pyronin (MGP) stain. All RNAs were amplified with two rounds of T7-based in vitro transcription and analyzed by two-color expression analysis on 10-K cDNA microarrays.The MGP-stained samples showed the least introduction of mRNA loss, followed by H&E and immunofluorescence. Nissl staining was significantly more detrimental to gene expression profiles, presumably owing to an aqueous step in which RNA may have been damaged by endogenous or exogenous RNAases.RNA damage can occur during the staining steps preparatory to laser capture microdissection, with the consequence of loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts. Microarray hybridization has been used to study the global gene expression from many different kinds of tissues and cell lines -4. When in vitro transcription is thought to introduce the least bias to gene expression profiling [Usually, a minimum of 5–50 μg total RNA is required for indirect or direct labeling of cDNA, respectively, with fluorochromes such as Cy3 and Cy5 to perform hybridization on one microarray chip to analyze gene expression . RNA yierofiling -17, althIt has not been determined to what extent each of the steps in LCM sample processing damages the RNA, potentially leading to loss of representation of certain genes when amplified, reverse transcribed, labeled and hybridized to a microarray containing a wide spectrum of cDNA targets on a glass slide. The purpose of the present study was to assess how much the choice of histological staining before LCM would contribute to gene loss, recognized as dropout of hybridized spots, when compared with unstained samples. To render our analysis statistically significant we performed four biological replicates for each staining protocol, starting with 16 individual LCM-derived tissue samples. Each of these 16 was compared with a pool of RNA from an identical pellet of cells. We found that the MGP staining method, which included RNAase inhibitor, was the least detrimental to the RNA, while the Nissl method, which had no RNAase inhibitor, inflicted the most damage to the RNA.RNA was extracted from pellets of cultured TEPC 1165 murine plasma cell tumor cells, which had been flash frozen immediately after harvest. LCM-derived RNA was isolated from samples of microdissected frozen sections of an identical cell pellet, which had been treated with different staining methods. To obtain a sufficient amount of total RNA from LCM-captured cells, we procured cells with 2000–2500 hits of laser . All LCM-captured samples yielded sufficient total RNA (10 – 20 μg) that could be quantitated by the low-range Ribogreen RNA Quantitation Kit (Molecular Probes). Each RNA sample was evaluated for suitability for use by electrophoresis using Agilent RNA Pico chips. RNA that was not degraded should have two clear bands representing the 28S and 18S rRNA, with ratios of 28S/18S absorbance exceeding 1.5. In addition, the RNA sample should be low in genomic DNA contamination, which would appear as bands larger than 28S rRNA. RNA from the unprocessed cell pellet had an acceptable 28S/18S rRNA ratio of about 1.5. The four LCM samples also showed clear 28 rRNA and 18 rRNA bands, but the 28S/18S ratios were different: 1.75 for the unprocessed cell pellet (A), 1.84 for MGP, 4.76 for H&E, 0.71 for NISSL, 2.05 for IF, indicating that a small amount of degradation appeared in the Nissl RNAs . One-sample t-tests identified 74, 76, 108, and 77 genes differently expressed at the 0.001 significance level between the unprocessed cell pellet and MGP, H&E, NS and IF, respectively. Testing 8,534 probes at this significance level, we expected that the average number of spuriously significant  results would be nine or less. Thus, the expression profiles in the staining groups are significantly different from those of the unprocessed cell pellet. Among these genes, 21, 44, 70, and 44 had at least 2-fold mean expression difference for MGP, H&E, NS and IF, respectively  may be a rough measure of this effect in each subgroup. Thus, we subtracted this value form the number of spots with lower intensities in the stained samples to yield a value that can be used for inter-group comparison.The cDNA microarray hybridization method is now widely used to analyze simultaneously the expression of thousands of genes in cancer tissues ,21, but To positively identify the specific cells desired for the microdissection, a staining protocol must be used, which permits identification of plasma cells in desiccated cryosections. Such sections, without cover slips, are required for microdissection and may pose a critical problem, since desiccate cryosections are not optically ideal for histological examination  to the standard MGP staining method has made it suitable for use with LCM. Sections treated as described here can be used to prepare total RNA of good quality. Though pyronin is a fluorescent molecule that can bind to RNA, we detected only 21 changes when compared with unstained LCM samples. This amounted to less than 0.3% of the analyzed microarray elements, and less than one half of the number changed due to the other staining methods tested.It appears that inclusion of RNAase inhibitor in staining solutions can prevent RNA from damage by endogenous and exogenous RNAase. The Nissl-stained group was the only staining protocol that did not include RNAase inhibitor. The number of genes in this group with 2-fold changes, 70 spots, was the highest among all four groups, indicating that this staining procedure damaged the most mRNAs.In summary, we performed a statistical analysis of 16 cDNA microarray chips comparing fluorescent-labeled cDNA generated from amplified RNA from 16 independently isolated and processed, LCM-procured, stained frozen sections with amplified RNA from an identical pellet of plasma cell tumor cells. This showed that a variable amount of spot fall-out was seen after staining of the frozen sections, depending on the staining method, indicating that the choice of staining method can be important in minimizing loss of mRNAs from microarray analysis of LCM-derived RNA. Happily, the degree of mRNA damage was small with the commonly used H&E method, so long as RNAase inhibitor was included in the aqueous hematoxylin solution. Nissl staining solution, which may not be compatible with RNAase inhibitor addition, introduced the greatest degree of damage. Fortunately, for our ongoing study of plasma cell tumor development, the MGP stain, chosen for its unique ability to flag plasma cells in tissue sections, was the least destructive of all. Our analysis suggests that maximizing the use of non-aqueous staining solutions is recommended for other specialty stains that might be advantageous for identification of other cell types in studies that require use of LCM. The inclusion of RNAase inhibitor in aqueous solutions appears to be important in rendering histological staining procedures suitable to extraction of intact RNA.RNA damage can occur during the staining steps preparatory to laser capture microdissection, resulting in loss of representation of certain genes in microarray hybridization analysis. Inclusion of RNAase inhibitor in aqueous staining solutions appears to be important in protecting RNA from loss of gene transcripts.The murine plasma cell tumor cell line TEPC 1165  was usedThe cell pellets were frozen in a dry ice-ethanol bath, embedded with OCT frozen tissue embedding medium, and stored at -80°C. Six-micrometer serial frozen sections were cut on a cryostat at -20°C and mounted on chilled, pre-cleaned, uncoated microscope glass slides that had been heated at 200°C overnight to eliminate RNAase. Slides were kept on dry ice or at -80°C until LCM was completed. Sections were stained individually with four different methods before LCM. RNAase-free (treated with diethylpyrocarbonate) water was used for all solutions. All procedures were carried out at room temperature, unless otherwise stated, and usually on the same day as the frozen sectioning.After fixation in 70% ethanol (10 sec), each slide was rinsed in DEPC-treated water (5 sec). Then, 50 μl of MGP staining solution (Sigma/Aldrich) to which RNAase inhibitor  had been added to a final concentration of 500 U/ml, was applied to the section and incubated 2 min, followed by a quick dip in diethylpyrocarbonate-treated water, dehydration in 100% ethanol in 2 steps , and xylenes in 2 steps (2 min then 3 min). It is important to note that MGP, like all histological stains, yields significantly less detail on frozen sections than on paraffin-embedded tissue, in part, owing to lack of a cover slip. MGP did enable identification of plasma cells in oil granulomas under these conditions. To be used in this way, however, one must include RNAase inhibitor if RNA extraction is desired after LCM.A modification was incorporated into the manufacturer's (Sigma/Aldrich) protocol; namely, RNAase inhibitor  was added to the aqueous hematoxylin solution to a final concentration of 500 U/ml. Briefly, slides were stained as follows: 70% EtOH for 10 sec, DEPC-treated water for 5 sec, hematoxylin with RNAase inhibitor for 20 sec, 70% EtOH for 30 sec, eosin Y in 100% EtOH for 20 sec, followed by dehydration with a series of alcohol for 30 sec each, and xylenes for 2 min.The frozen sections were fixed with 70% ethanol (30 sec), rinsed in DEPC-treated water (30 sec), immersed in NS staining solution (Arcturus Corp.) for 30 sec, dehydrated with graded alcohols (30 sec each) and xylenes (2 min and 3 min).Sections were fixed in ice-cold acetone for 2 min, rinsed in DEPC-treated PBS for 10 sec, incubated with a 1:250 dilution of goat anti-mouse Igκ conjugated with TXRD  to which RNAase inhibitor  had been added to a final concentration of 500 U/ml, for 2 min in the dark, dehydrated with 100% ethanol and xylenes (11).Cells were lifted from the slide onto CapSure LCM plastic caps (Arcturus Corp.) using a 30-μm spot size of laser at the power of 50 μv using PixCell II LCM system (Arcturus Corp.).Total RNA from the unprocessed cell pellet was extracted using TriZol reagent (Sigma), treated with RNAase-free DNAase I , followed by RNA purification with Qiagen RNeasy kit according to the manufacturer's protocol. RNA concentration was measured spectrophotometrically.RNA extraction of 16 LCM-derived samples (4 from each staining group) was performed with the PicoPure RNA extraction kit (Arcturus Corp.), simultaneously treated with RNAase-free DNAase I  according to the manufacturer's protocol. Briefly, 50 μl of extraction buffer was pipetted onto the tissue fragments that had been collected in the cap of a sterile plastic 1.5-micro-centrifuge tube , and they were incubated together in a hot-air oven at 42°C for 30 min. Cells and buffer were collected by centrifugation at 800 × g for 2 min. RNA was DNAase-treated and purified on a preconditioned RNA-purification spin column according to the manufacturer's recommendations. LCM-derived total RNA was quantitated with Ribogreen  using Victor 2 1420 multilabel counter . To assess the RNA quality and confirm the absence of genomic DNA contamination, the Agilent 2100 Bioanalyzer (Pico RNA chip) was used to perform electrophoresis on picogram amounts of total RNA. Only samples with intact 18S and 28S rRNA peaks were used for gene expression analysis.in vitro transcription of cDNA synthesized by reverse transcription primed by oligo-dT attached to the T7 RNA polymerase promoter [We performed antisense RNA amplification of each RNA sample with RiboAmp™ RNA Amplification kit  based on T7 RNA polymerase promoter . To avoi2O. In each staining group 3 of the 4 reference RNA samples were labeled with Cy5, while 1 of the 4 was labeled with Cy3. Three of each group of 4 experimental samples were labeled with Cy3, and 1 of 4 was labeled with Cy5 to test for bias from labeling. Probes were mixed and hybridized overnight at 42°C in hybridization solution (New England Nuclear) to microarray chips with a total of 9998 cDNA elements (InCyte) printed by the NCI microarray facility.Probes were synthesized and labeled from 4 μg of amplified RNA (aRNA) by the method of Xiang et al . In brieFour arrays were hybridized for each of the 4 groups . In each group 3 arrays had cDNA derived from the reference, unsectioned pellet of cells labeled with Cy5 and the LCM-derived test sample labeled with Cy3, and one array had the labeling reversed. We were interested in evaluating the possibility of gene-specific dye bias that was not removed by the normalization process. To evaluate this possibility, we computed the average difference in log2 ratio between normalized forward- and reverse-label experiments for each array element as an estimate of the residual dye bias for the associated gene. Of the 8534 array elements, none had an average difference of log2 ratio in absolute value greater than 1 . Thus, we concluded that after normalization there was no systematic bias favoring either dye.Arrays were scanned at 10-μm resolution using a GenePix 4000 (Axon Inc.) array scanner. PMT voltages were varied to gain optimum intensity of the spots. Four duplicate hybridizations/slides were used in each experiment. LCM-derived RNAs were regarded as "experimental" samples, and 3 of the 4 cDNA probes derived from them were labeled with Cy3, whereas the "reference" samples, derived from RNA from unprocessed cell pellets were usually labeled with Cy5. To rule out color bias produced by the labeling process itself, the fluorochromes were reversed once in each group of four repeats. Quantification files were obtained by using the GenePixPro 4.0 software (Axon Inc.). The fluorescence signal intensity was determined as the volume in a fixed-size circle, and background was estimated as the median pixel value in a diamond-shaped region between each adjacent four-spot region.Log-ratios of local median background-subtracted intensity levels were analyzed. For each array element, if the intensity was less than 75 in one channel but greater than 75 in the other channel, the intensity <75 was set at 75. Array elements that were flagged as poor quality during image analysis or that had intensities less than 75 in both channels were not reliable and treated as missing . Six perAverage linkage hierarchical analysis of differentially expressed genes was performed by using 1-Pearson correlation as the distance metric to group genes based on their patterns of variation across the staining groups. The clusters and associated heat maps were implemented in R.Identification of array elements that were differentially expressed between each subgroup and the reference sample and among subgroups was done using one-sample t-tests and two-sample t-tests, respectively. Differentially expressed genes were identified as those genes that were significant at the 0.001 level (p < 0.001) and which were at least 2-fold different in the geometric mean of the expression measurements. A treated subgroup was considered to have weaker expression than another treated subgroup if, among the genes that were differentially expressed between these two subgroups, it had more lower-expressed genes than higher-expressed genes. A global permutation test was used as a global test to assess if one subgroup had statistically significant weaker expression than the other subgroup. Specifically, two-sample t-tests were performed by randomly permuting the group labels. In each permutation, the difference between the number of lower-expressed genes and the number of higher-expressed genes was recorded. The p-value of the permutation test was the proportion of permutations with the same or larger difference as those observed in the original data. Two subgroups would be defined as having globally significant different expression profiles if the p-value from the permutation test is less than 0.05.LCM (Laser Capture Microdissection), MGP (Methyl Green Pyronin), H&E (Hematoxylin and Eosin), NS (Nissl Stain), IF (Immunofluorescence).HW, RFB and JFM conceived the idea for the project. HW and RFB performed the laser capture microdissection. JDO prepared and quality controlled some of the RNAs. HW performed the microarray hybridizations and scans. JHS and M-CL performed the statistical analysis and interpretation.


The path from DNA to RNA to protein sounds straightforward enough, but few processes in the life of a cell could be called simple. Gene expression is a complex, highly regulated affair that involves the activity of discrete teams of molecular manipulators at key steps in the protein production pathway. As soon as transcription begins, RNA processing machinery sets to work on messenger RNA (mRNA) precursors in the nucleus, proofreading the RNA copy, stabilizing the elongating transcripts, and making sure mRNAs reach the translation machinery in the cytoplasm.A key step in RNA processing involves the addition of a string of adenine nucleotides to the 3′ end of the growing transcript, a modification called polyadenylation.  In eukaryotes like yeast and humans, polyadenylation helps to stabilize the mRNA transcript and to ensure its export from the nucleus. Once in the cytoplasm, the mRNAs' poly(A) tails interact with components of the translation apparatus and facilitate protein synthesis. Polyadenylation is mediated by a class of enzymes called poly(A) polymerases (PAPs), which typically act in concert with other proteins in the cell's nucleus.Saccharomyces cerevisiae, and find evidence that Trf4p-mediated polyadenylation plays a role in RNA quality control in eukaryotes.Just three years ago, a new class of PAPs was discovered that belong to the Trf4/5 family of yeast proteins and are found in the cytoplasm, rather than the nucleus, of the cell. Unlike the nuclear PAPs, in which one protein contains both catalytic activity and an RNA-binding domain, the new class relies on two or more protein subunits to carry out these tasks. It's been suggested that these enzymes stabilize specific mRNAs in the cytoplasm by extending their poly(A) tails. It's long been known that adding poly(A) tails to RNAs in prokaryotic bacteria promotes the degradation of defective RNAs, but the existence of a similar mechanism in yeast has just recently come to light. Previous genetic experiments on live yeast cells by James Anderson and collaborators suggested that when the protein Trf4p polyadenylated a particular type of abnormal transfer RNA (tRNA)—the intermediary that translates the nucleotide code into the amino acid code—the tRNA was destroyed. In a new study, Walter Keller and colleagues investigate the biochemistry, composition, and function of Trf4p in the brewer's yeast After showing that mutating two amino acid residues in the predicted catalytic center of Trf4p eliminates its activity, Keller and coworkers determined that the enzyme forms a PAP complex with three other proteins . They also showed that the Trf4p complex selectively targets and successfully polyadenylated only tRNA molecules that were either lacking the chemical modifications required for normal folding or that were misfolded by mutation. Polyadenylation appears to tag the aberrant RNA as damaged goods, signaling the cell's nuclear molecule-degradation complex, the exosome, to initiate destruction.Keller and colleagues propose that the Trf4p complex recognizes structural defects in RNA, prompting the Trf4p subunit to add poly(A) tails to the RNA, which initiates RNA degradation. In this model, Trf4p, along with either Air1p or Air2p, interacts with the RNA enzyme Mtr4p, which physically connects the tRNA-Trf4-PAP complex to the exosome. These results suggest that Trf4-PAP monitors the quality of tRNAs by detecting misfolded RNAs and engineering their destruction before they can gum up the works of protein assembly.That the polyadenylation pathway for discarding defective tRNA appears in both bacteria and yeast suggests that this quality-control mechanism represents the ancient role for polyadenylation, the authors propose; the stabilization function of adding poly(A) tails may have arisen as eukaryotes evolved a nucleus and other organelles. Whether this notion or the model described here proves correct remains to be seen, and the authors outline a number of avenues for further study. Determining the structure of RNA–protein complexes, for example, and their binding properties and interactions, the authors argue, should elucidate the mechanism by which this RNA surveillance complex operates and what features of its RNA substrates it recognizes.


Poliovirus consists of little more than a few genes encased in a protein coat, yet once this RNA virus enters the nervous system, it can induce paralysis within hours. Polio crippled thousands of children a year in industrialized countries during the first half of the 20th century, until the Salk and Sabin vaccines brought the virus under control in the late 1950s and early 1960s. Although five cases of polio were reported in an Amish community in Minnesota in 2005, the disease, which still has no cure, remains endemic in just four countries: Nigeria, India, Pakistan, and Afghanistan.Like all viruses, the poliovirus’s genetic material sits inside a protective protein-laden “capsid” shell. In most animal viruses, the capsid receives additional protection from a protein-studded viral envelope that facilitates infection by recognizing and binding to receptors on the cell surface. The poliovirus, however, has just the capsid to mediate protection and infection.Scientists have long debated how the poliovirus manages to get its genome inside the cell. Does it simply inject its RNA through a channel in the plasma membrane or does it commandeer an endocytic pathway, which the cell uses to internalize extracellular molecules? The details of viral entry have long remained obscure, in part because visualizing the process has proven technically difficult and partly because animal viruses produce so many noninfectious particles that confound observations.In a new study, Boerries Brandenburg, Lily Y. Lee, and colleagues describe a novel approach that circumvents these technical hurdles to track individual virus particles as they infect living cells. Working with the poliovirus as a model for nonenveloped viruses, the researchers used fluorescence microscopy to examine not only how the virus enters the cell, but also where and when it releases its genetic material.To investigate the poliovirus’s mode of entry, Brandenburg et al. labeled the viral capsid and RNA with distinctly colored fluorescent tags. Getting dyes to bind to viral RNA inside the capsid without inactivating the RNA, however, is no easy feat. The researchers had to screen 20 dyes before they found one that would bind to the RNA as the virus reproduced without compromising the infectivity of the virus. After infecting human cells with the dual-labeled virus, they observed virions releasing their RNA, which the virions did with surprising efficiency: most had been released an hour after infection.The researchers determined where the RNA was released by analyzing images of the labeled virus at different points after infection. Five minutes after infection, nearly all the virus particles, aglow with both capsid and RNA labels, stayed near the cell surface. By 20–50 minutes after infection, particles gravitated toward the cell interior, most glowing with just the capsid dye. RNA release appeared to occur either near the cell surface or just after entry, and either at the top or bottom surface of the cell.To find out whether genome release proceeds from the plasma membrane or from discrete compartments  near the membrane, the researchers tagged capsids with a dye that loses fluorescence when exposed to high pH. Capsids outside the cell would be sensitive to pH changes while those internalized would be protected by the cell’s own pH-buffering mechanisms. The percentage of virus particles displaying pH sensitivity decreased over time, suggesting that the particles had entered the cell. And because the dynamics of this process mirrored those of RNA release, and no RNA was released from particles that remained on the cell surface, Brandenburg et al. concluded that RNA release happened after internalization.By using inhibitors designed to disrupt cell processes that might play a role in infection, the researchers revealed that RNA release is not a passive process, but requires energy, just as endocytosis does. Genome release also depends on actin, a structural protein involved in endocytosis. Although infection does not depend on well-known components of the endocytosis pathway, it does require a class of enzymes that interact with the actin network beneath the cell membrane. The dependence of RNA release on various cellular factors determined by this imaging method correlates with the dependence obtained using an infectivity assay, demonstrating that the pathway monitored by imaging is the relevant pathway leading to infection. By testing inhibitors known to target specific enzymes, future studies can determine which one poliovirus hijacks to infect cells.Altogether, these results suggest that the poliovirus enters the cell after binding to the cell surface, then rapidly releases it genome from vesicles near the membrane. Researchers can now investigate how these vesicles trigger RNA release and how the invasive RNA reaches the cell’s replication machinery. And since nonenveloped viruses often tailor their entry mechanisms to the cell they target, the innovative imaging technique described in this study should provide researchers with a valuable tool to deconstruct, and eventually, prevent their path to infection.


Compartmentalization is a key feature of eukaryotic cells, but its evolution remains poorly understood. GTPases are the oldest enzymes that use nucleotides as substrates and they participate in a wide range of cellular processes. Therefore, they are ideal tools for comparative genomic studies aimed at understanding how aspects of biological complexity such as cellular compartmentalization evolved.YlqF Related GTPase (YRG) family, which are present in Eukarya, Bacteria and Archea and include the stem cell regulator Nucleostemin. To extend the computational analysis, we showed that hLsg1 is an essential GTPase predominantly located in the endoplasmic reticulum and, in some cells, in Cajal bodies in the nucleus. Comparison of localization and siRNA datasets suggests that all members of the family are essential GTPases that have increased in number as the compartmentalization of the eukaryotic cell and the ribosome biogenesis pathway have evolved.We describe the identification and characterization of a unique family of circularly permuted GTPases represented by the human orthologue of yeast Lsg1p. We placed the members of this family in the phylogenetic context of the We propose a scenario, consistent with our data, for the evolution of this family: cytoplasmic components were first acquired, followed by nuclear components, and finally the mitochondrial and chloroplast elements were derived from different bacterial species, in parallel with the formation of the nucleolus and the specialization of nuclear components. S. cerevisiae, C. elegans, D. melanogaster or B. subtilis) and are therefore mainly used by the small part of the scientific community working with this organism and able to handle the outcome and limitations. Attempts have been made to correlate large datasets across species, for example in the case of protein-protein interactions  and in Deuterostomia  .E. coli  GTP to purified His tagged-hLsg1 using as control a His-tagged Sar1p, a well characterized GTPase regulating the vesicular coat complex COPII [32P] GTP, although more weakly than Sar1p. However, hLsg1 did not bind GDP under those experimental conditions (data not shown), which may reflect weak binding. To determine the GTPase activity of hLsg1, we performed a GTPase assay using an HPLC system as previously described [in vitro purified recombinant hLsg1 and GDP was the only final product   Figure . Since lAccording to our results, hLsg1 is essential, like its yeast counterpart, and this characteristic seems to be common to the YRG family members. This implies that each YRG protein fulfils essential functions.Compartmentalization of the human cell allows better control of function and reactions steps in many pathways, including ribosome assembly. Cellular localization is a key to defining protein function. Using large-scale localization screens, we previously identified hLsg1 as an endoplasmic reticulum localized protein , in contWe decided to confirm our preliminary data on hLsg1 localization in humans using GFP-fused constructs as well as specific polyclonal antibodies. When expressed as a C-terminally tagged YFP fusion protein, hLsg1 localized to the ER in most cells Figure , 1. In 1(Clontech ER marker)  Figure , top rowThese data demonstrate that in contrast to its yeast counterpart, hLsg1 localizes to the ER and to Cajal bodies in the nucleus.The dual localization of hLsg1 in the cytosol and nucleus suggests nucleocytoplasmic trafficking of the protein, possibly in relation to rRNA maturation. We constructed hLsg1 deletion mutants containing or excluding the putative the C-terminal NLS (YFP-hLsg1-1-600 and YFP-hLsg1-480-658) and transfected them into Hela cells Figure . While YTo determine whether hLsg1 shuttled between nucleus and cytosol via a CRM1-dependent nuclear export pathway, we transfected Vero cells with either hLsg1-YFP or hLsg1 deletion mutants and compared the localization of the fusion proteins after treatment with the CRM-1 nuclear export inhibitor Leptomycin B (LMB) Figure . Full-leThese data suggest that hLsg1 shuttles between the cytosol and Cajal bodies via a CRM1-dependent export mechanism.YlqF Related GTPases [see Additional files Using database sequence similarity searches coupled with phylogenetic analysis, we were able to unite the circularly permuted GTPases into a family that we have named YRG for Phylogenetic analysis defines ten GTPase subfamilies with a global phyletic distribution compatible with their presence in the last universal common ancestor (LUCA) of extant life forms . An emerThe YRG family was originally defined as a particular class of GTPases showing a circularly permuted structure, with the four GTPase motifs reorganized as G4 followed by G1, G2 and G3 Figure . This ciA. thaliana . The cytosol contains huge numbers of ribosomes freely diffusing or bound to the endoplasmic reticulum, and is the main transit pathway for rRNA pression ,44. ConsUsing comparative genomics, we defined the YRG family as a unique group of circularly permuted GTPases. We suggest a potential function for this family, as well as a potential pathway by which the family members may act sequentially, following an evolutionary process linked to compartimentalization Figure . A futurHomo sapiens gene FLJ11301 (GenBank accession no. NP_060855) was used to search the non-redundant protein database at the National Center for Biotechnology Information using the PSI-BLASTP program (15). Homologues were identified in Homo sapiens (GenBank accession identifier BAA92116), Mus musculus (XP_148574), Danio rerio (AAH66695), Caenorhabditis elegans (NP_490904), Caenorhabditis briggsae (CAE74467), Drosophila melanogaster (NP_569915), Anopheles gambiae (EAA13064), Saccharomyces cerevisiae (NP_011416), Schizosaccaromyces pombe (NP_593948), Arabidopsis thaliana (NP_172317), Zea mays (AAD41267), Encephalitozoon cuniculi (CAD26329), Eremothecium gossypii (NP_985506) and Plasmodium falciparum (NP_702181). The sequence corresponding to Rattus norvegicus had to be reconstructed using an insertion from Mus musculus, probably owing to an incorrect gene prediction (XP_213604).The translated sequence of the The 14 orthologous sequences were aligned using the ClustalW program . PSI-BLA2. Cells were seeded on to glass coverslips, Nunc plates or LabTek dishes and were transfected using Fugene6 (Roche) according to the manufacturer's protocols. For immunocytochemistry, transiently transfected HeLa cells were grown on coverslips and fixed in ice-cold methanol for 5 min at -20°C. The cells were then washed again and incubated in PBS for 20 min. Primary and secondary antibodies were diluted in PBS. The cells were incubated with primary antibodies followed by secondary antibodies for intervals of 30 min with three washing steps in between. The coverslips were then mounted in Mowiol on glass slides. Images of the stained cells were acquired using either a Zeiss Cell Observer System or a Leica AOBS confocal laser-scanning microscope.HeLa (ATCC CCL-2) and Vero (ATCC CCL-81) cells were cultured in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% FCS and penicillin/streptomycin at 37°C in an atmosphere of 5% CO2, 10 mM EDTA, 0.5 g/l bovine serum albumin, (3H)GTP or (3H)GDP  and cold 30 μM GTP or GDP. After incubation at 30°C for the indicated times, samples were diluted in 500 μl of ice-cold washing buffer  and applied to a nitrocellulose filter . The filters were rinsed with 4 × 4ml ice-cold washing buffer and the radioactivity retained on the filters was determined by scintillation counting.Nucleotide binding was measured by the filtration method. Recombinant proteins were incubated in 20 mM Tris-HCl pH 7.5, 1 mM DTT, 5 mM MgClGTPase activity measurement by HPLC was described by Ahmadian et al. 1999 .siRNA sequences were BLAST searched against the human genome to ensure that they were specific for hLsg1. The hLsg1 siRNA sequence showed no exact or near exact matches to any other sequence in the human genome and are therefore hLsg1-specific. siRNAs were synthesized by EUROGENTEC. hLsg1 siRNA (5'-UGGAGAGAAACUGCAAGACTT-3') targets nucleotides 506–524 of human hLsg1 relative to the first nucleotide of the start codon.Cells were seeded into 12-well plates. Twenty-four hours later, they were transfected with 1.68 μg of siRNA per well (unless otherwise noted). Transfections were as described  with theReynaud E.G. carried out the molecular biology experiments, in collaboration with Ly T.B.N, the localization studies, the immunofluorescence and the cell biology studies. Andrade M.A. carried the complete phylogenetic studies of the YRG family and drafted part of the manuscript. Bonneau F. and Scheffzek K participated in the characterization of the Lsg1 GTPase activity. Knop M. participated in the design of, and performed part of, the yeast experiments. Pepperkok R. conceived the study and participated in its design and coordination. All authors read and approved the final manuscript.Complete Phylogenetic Tree of the YRG family. A multiple alignment of sequences of the YqeH, YjeQ, EngA, and YlqF families. The alignment was produced using ClustalW followed by manual editing [ editing . The tre editing  (The rooClick here for fileThe YRG family members. The table compiles all the data collected from several datasets available for all the YRG members known so far.Click here for file


Non-coding RNAs (ncRNAs) are an emerging focus for both computational analysis and experimental research, resulting in a growing number of novel, non-protein coding transcripts with often unknown functions. Whole genome screens in higher eukaryotes, for example, provided evidence for a surprisingly large number of ncRNAs. To supplement these searches, we performed a computational analysis of seven yeast species and searched for new ncRNAs and RNA motifs.A comparative analysis of the genomes of seven yeast species yielded roughly 2800 genomic loci that showed the hallmarks of evolutionary conserved RNA secondary structures. A total of 74% of these regions overlapped with annotated non-coding or coding genes in yeast. Coding sequences that carry predicted structured RNA elements belong to a limited number of groups with common functions, suggesting that these RNA elements are involved in post-transcriptional regulation and/or cellular localization. About 700 conserved RNA structures were found outside annotated coding sequences and known ncRNA genes. Many of these predicted elements overlapped with UTR regions of particular classes of protein coding genes. In addition, a number of RNA elements overlapped with previously characterized antisense transcripts. Transcription of about 120 predicted elements located in promoter regions and other, previously un-annotated, intergenic regions was supported by tiling array experiments, ESTs, or SAGE data.Our computational predictions strongly suggest that yeasts harbor a substantial pool of several hundred novel ncRNAs. In addition, we describe a large number of RNA structures in coding sequences and also within antisense transcripts that were previously characterized using tiling arrays. Neurospora crassa, as well as many other multicellular fungi, have up to 10 times larger genomes [The genomic structure of yeast is much simpler than the genomic organization of multicellular species. With a size of about 12 million bases, the yeast genome is shorter than the genomes of most other currently known fungi; S. cerevisiae genome. A substantial number of these sequences have no apparent orthologs in other species. Nevertheless, Havilio et al demonstrated abundant transcription of many of these orphan transcripts. A plausible working hypothesis is that most of these sequences are in fact non-coding RNAs (ncRNAs) similar to mRNA-like ncRNAs [Recent reports highlighted very different aspects of alternate regulative modes of gene expression in yeast. Several of them emphasize non-protein coding RNA molecules: the data in Steigele and Nieselt  showed ae ncRNAs ,6 that wRecent tiling array experiments -9 revealde novo identification of structured RNAs. Structured RNAs are defined here to be either an ncRNA gene, or a conserved RNA structure embedded within coding sequences or UTRs. A detailed comparison of the predicted RNAs is provided, with experimental evidence from recent high-throughput experiments.Previously, only one computational study has been conducted to discover new ncRNAs in yeast . This woS. cerevisiae, S. paradoxus, S. mikatae, S. kudriavzeii, S. bayanus, S. castelli and S. kluyveri for structured RNAs. The coverage of the multiz multiple sequence alignments (MSAs) was almost complete, covering 96.7% of the 12 Mb yeast genome. This input data set consisted of 27031 individual alignment blocks longer than 20 bp that were processed in overlapping windows. Altogether, 239313 windows were analyzed, as described in the Methods section.We screened the genomes of the seven yeast species PSVM) larger than 0.5 presents a plausible trade-off between specificity and sensitivity for most classes of non-coding RNAs. Thus, we used this PSVM value as the lower cutoff value. In addition, we report the data for a more conservative PSVM cutoff of 0.9. With a PSVM value larger than 0.5, 4567 windows with an RNA structure were found. Of these, 1821 windows have a PSVM value larger than 0.9. To remove false positives, we shuffled the alignments of all windows with a structured RNA and recalculated the probability of the shuffled alignment to contain a structured RNA. To be conservative, we removed predictions for which the shuffled alignments were also classified as structured RNAs with an above-cutoff classification confidence. This filtering step, indicated by a * in the following, retained 4395 candidates at Washietl et al  showed tSaccharomyces Genome Database (SGD), which provides an almost complete annotation of the yeast genome. We analyzed all features of the yeast genome that are related to the transcriptional output of the yeast genome and further subdivided these into several classes, including ncRNA  and several types of features that are related to proteins or more generally to mRNAs . A total of 2089 of 2811 (74%) and 789 of 1136 (69%) 'predicted RNA elements' from the 0.5 and 0.9 In order to assess the sensitivity of our screen, we compared our predictions with the PSVM value cutoff-level, however. We almost completely recovered the ribosomal RNAs, which are encoded by the RDN1 and RDN2 loci.We found the majority of all known ncRNAs overlapped with 'predicted RNA elements' Figure , 4. ConsIn contrast to the strong and stable RNAz signals of the known ncRNA genes, the signals of predictions in the coding sequences are systematically weaker and are less likely to be destroyed by the shuffling procedure: only 2.4% of shuffled windows were again classified as 'structured RNA' compared to 3.8% of the entire screen. However, the majority of the predicted signals within the coding sequence vanished when they were filtered at the more restrictive 0.9 SE = TP/T. The sensitivity of the genome-wide screen is the composite of two effects, namely the sensitivity of the RNAz classificator and the quality of the input alignments. In order to assess the latter contribution, we counted the total number of all known RNA genes that are represented in the input alignments. Almost all ncRNA genes reported in S. cerevisiae are present in the other yeast genomes and are also present in the multiple alignments. We concluded that the sensitivity of our screen is thus dominated by RNAz. For rRNAs and tRNAs we found SE(rRNA) = 0.78 and SE(tRNA) = 0.72, respectively, while we detected essentially all the transposable elements. Altogether, we predicted 257 out of 375 known ncRNAs, yielding a sensitivity of 69%.To evaluate the sensitivity of the screen, we defined the sensitivity as the proportion of correctly predicted RNA genes (TP) divided by the number of known RNA genes (T), i.e. S. cerevisiae that contained at least one structured RNA predicted by RNAz . To ensure that highly similar sequences were not dominating the alignments, we always chose the four most diverged sequences. This is especially useful in sequence-based comparisons of coding-sequences that mutate much more slowly than sequences of ncRNAs and are therefore much more similar. Also, to achieve a high sequence diversity we used additional yeast species for the analysis that are more distant to S. cerevisiae proteins. Of 1309 CDS, 318 have no ortholog or are duplicated in S. cerevisiae and were disregarded. The remaining 991 CDS were then re-screened using the 'shuffled-CDS method' with the following result: at the cutoff level of 0.5, 286 of 991 CDS were found to contain a predicted conserved RNA structure. At the nucleotide level, the average mean percent identity of the RNA structure positive alignments was 61.7% compared to 67.8% overall , regulation of cellular physiological processes , response to stress , a larger group of genes involved in the transport and localization of other proteins  and a group of genes involved in the cell cycle . A much large number of CDS with 5' structures are annotated constituents of non-membrane-bound organelle . Here, the biggest subgroup consists of mitochondrial proteins. Around a quarter of all CDS with structured 5'-UTRs are related to mitochondrial function, homeostasis or integrity of mitochondria .GO terms are available for 65 of the 80 CDS that have a predicted RNA element in their 5'-UTR. Here, we report selected significant groups larger than five CDS only. The most significant functional classes are development  or are constituents of the ribosome . Similar to CDS with RNA structures in their 5'-UTR, proteins were found that are constituents of non-membrane-bound organelles are again significantly overrepresented .Specific functional groupings are also found for the predicted 3'-UTR structures. GO terms are provided for 70 of the 87 CDS in question. Significant gene groups are involved in amino acid metabolism .A possible explanation for this is that many of these RNAz hits are associated with promoter regions. In order to investigate this possibility, we used the data on transcription factor binding sites in yeast that were compiled by Harbison et al Figure 3. In addiInterestingly, we found several transcription factor binding-sites that are frequently covered by predicted RNA structures Table . With thNeurospora crassa, Cryptococcus neoformans, Aspergillus nidulans, Gibberella zeae and Ustilago maydis. Only one significant hit was found, which is a short (and as yet unannotated) duplication of the 26S-RNA in vicinity to the original rRNA-cluster on chromosome 12 of S. cerevisiae. All other predicted elements seem to be restricted to the hemiascomycetes phylum.A total of 572 unannotated predicted RNA elements (at the 0.5 g blastn  with the-6) in the NONCODE database [snR161 that was recently identified by Schattner et al [Saccharomyces Genome Database used in this work. The other element is 100% identical over a length of 80 nucleotides to an RNA from mice annotated as U5 RNA. However, intensive searches in mammalian genomes convinced us that this sequence is most likely a contamination and misclassified in NONCODE (NONCODE accession number u4120). Searches of the Rfam database [We also searched specialized ncRNA databases to see if some of the 572 RNAz hits can be annotated by homology with a known functional ncRNA. A blast search  of the predicted intergenic RNA elements is verified by tiling array data, for additional 49 elements there is evidence from ESTs and/or SAGE data . Samanta et al further provided a sub-classification of intergenic transcripts into real intergenic transcripts and transcripts that are associated with known promoter regions. Interestingly, 13 of 15 RNA elements overlap with promoter-based transcripts . HoweveA similar number of the intergenic RNA structures were also verified by EST sequences. From the 154 ESTs that unambiguously map mainly to intergenic regions of the yeast genome, 33 ESTs overlap with 17 predicted (novel) ncRNAs. To check for typical signals of POL-II transcripts, we searched for poly-(A) tails using the program Trimest   have predicted structures in their overlap region. In addition, 27 intergenic RNA elements form large duplex regions, which potentially act as pure non-coding antisense transcripts , butand Eddy  used QRNand Eddy  and was and Eddy  are contSurprisingly, the largest single class of predicted RNA structures was found in protein coding sequences. By contrast, it is widely believed that RNA structures in CDS can interfere both with translation and with the evolution of the protein coding sequence . FurtherThe relevance of the observation of a large number of structured RNA elements in coding regions is supported by an unexpected clustering of functional GO annotation terms of the affected protein coding genes. This significant clustering into a small number of functional classes strongly supports the interpretation that these RNAz hits are functional on a posttranscriptional level. The most prominent groups is related to cellular metabolism. Another large group of proteins is found to function within the ribosomal complex or within the mitochondria. ASH1 also belongs to the latter group. Many mitochondrial proteins are among the 55 organelle-specific proteins that have RNAz signals. This list includes in particular ATP2 and TIM44, both of which are known to be actively transported to the mitochondria ,39. It icis-acting elements) often bind trans-acting factors and control important aspects of gene expression, such as translational efficiency, mRNA stability and subcellular localization. Known examples are iron response elements (IRE), the translation control elements (TCE), internal ribosome entry sites (IRES) and AU-rich elements [Structured RNA elements in UTR regions  were downloaded from the Genome Browser at UCSC, California [S. cerevisiae as a reference, which is used for annotation of the alignments via known genetic elements from the genome of S. cerevisiae.Multiple alignments, calculated by the multiple alignment program multiz  of sevenlifornia . Each alGenomic alignments were processed using the following protocol. In alignments with only two sequences, all gapped positions were deleted. In alignments with more than two sequences, all columns with more than 50% gap characters were removed. If the number of sequences in an alignment was larger than six sequences, one of the two most closely related sequences was removed. This is necessary as the machine-learning approach implemented in the RNAz program is not able to process alignments with more than six sequences. Final alignment sizes larger than 200 bp were processed by a sliding-window approach with a windows size of 120 bp and a stepsize of 40 bp.PSVM value that the input alignment has a significant evolutionary conserved secondary structure based on the thermodynamic stability of predicted structure and on sequence covariations consistent with a common structure. For details we refer to [PSVM value of 1 defines the most reliably predicted RNA. Signals with a PSVM value smaller than 0.5 were discarded.We used RNAz v1.01 to predict structured RNAs. Both the forward and backward strand of the alignments were screened separately. The RNAz classifier is based on a support vector machine (SVM). This classifier computes a probability refer to . An RNA PSVM value higher than 0.5 (0.9) were shuffled once and re-screened with RNAz. All alignments that had a PSVM value higher than 0.5 (0.9) after shuffling were discarded. RNAz also computes a z-score, which could be interpreted to quantify the thermodynamic stability of the predicted RNA structure versus the folding energy relative to a set of shuffled sequences.As the sensitivity of RNAz is dependent on base composition and sequence identity, we used a shuffling algorithm developed for ncRNAs  to removFinally, all results of the RNAz screen and the corresponding alignments were stored in a relational database for further processing and analysis of the structured RNAs.S. cerevisiae genome. We used BLAT [All multiz alignments were fragmented during the RNAz screen. As we did not track all column removals, we needed to remap the positively classified alignment windows onto the sed BLAT  for thispredicted RNA elements' and thus regarded as single entities. However, a 'predicted RNA element' is a dynamic entity, which is dependent on construction rules: only windows above a certain treshold for the PSVM value are allowed. In fact, two different PSVM values for the filtering process were used. The first measurement is the PSVM value for the original alignment and the second measurement is the PSVM value for the shuffled windows, which is denoted as PSVM values lower than 0.5 and 0.9 and Overlapping windows and windows that are at most 60 bp apart were combined to 'Saccharomyces Genome Database [Saccharomyces Genome Database, SGDlite, which has been implemented using the Generic Model Organism Database Construction Set as part of the GMOD project [Most of the annotation was performed using precalculated annotations from the Database . We used project .The genomic loci with RNAz predictions were compared with the SGD annotation. A 'predicted RNA element' was defined to overlap with an SGD annotation element if its sequence length overlaps at least 20% with the respective length of the SGD element.To align protein coding sequences (CDS) at the level of nucleotide sequence, we aligned sequences in protein space and project the aligned positions back to the nucleotide coordinates. The resulting alignments have some characteristics that are different from pure nucleotide alignments, such as any gap position is a multiple of three (one codon). The background signal within coding regions thus has to be estimated from a random model that takes the protein coding nature of the sequence into account.The first step of the shuffled-CDS method is the determination of a set of orthologous proteins. Orthology is determined by best-reciprocal FASTA  hits in x or more out of n genes having a given annotation, given that X of N  have that annotation in the genome in general.All common Gene Ontology (GO) terms shared by CDS were detected using the GO-TermFinder perl modules . These pA web-site featuring an interface for interactive data exploration and a Predicted RNA Yeast Genome Browser is available .SS co-developed the project idea, designed and implemented the software, performed the research and data analysis and wrote the manuscript. WH assisted in statistical analysis and participated in discussions. CS performed the reanalysis of the strand specificity of predicted RNAs. PFS developed the project idea, participated in discussions and revised the manuscript. KN developed the project idea, revised the manuscript, participated in discussions and supervised the overall project.Predicted RNA structures in fasta file format. The element_id is decomposed as follows: StartCoord_Length_Chr_strand. First part of the file contains RNA structure elements found on the PSVM0.5 and the second part RNA structure elements found on the PSVM0.9 cutoff level.Click here for fileDistribution of z-scores of predicted structured RNA for each annotation class as reported by RNAz. (A) Click here for fileKnown RNA genes in the yeast genome, covered by predicted RNA structures. The annotation was taken from the Saccharomyces Genome Database. Structured elements with reported SE denotes the sensitivity to detect functional classes of known RNAs, ali refers to the number of elements in the input alignments, mpi is the mean percent identity of the windows.Click here for filePredicted RNA structures annotation file. The element_id is decomposed as follows: StartCoord_Length_Chr_strand. The first part of the file contains RNA structure elements found on the Click here for fileCDS with conserved RNA structure. RNA structure found within CDS . RNA elements that were positively predicted by both, the 1 and 2 stem scanner mode of snoGPS are given in bold type.Click here for filePredicted RNA structures in intergenic regions. The element_id is decomposed as follows: StartCoord_Length_Chr_strand. The file contains all RNA structure elements found on the Click here for fileAnalysis of potential duplexes formed by predicted intergenic ncRNA transcripts. First, we filtered potential duplexes by fast searches for overlap regions with wublast  with parameters that also allow for G-U basepairs, as described in Steigele et al [le et al . Second,Click here for file


RNA silencing — also known as RNA interference — is an intriguing phenomenon in which short, double-stranded RNA “triggers” can prevent the expression of specific genes. First discovered in plants, RNA interference is now recognized as a widespread, if not ubiquitous, phenomenon, and it is causing great excitement as an experimental technique for selectively blocking gene expression.The mechanisms of RNA silencing have been intensively studied. One important step is the formation of single-stranded RNA pieces  from the double-stranded triggers. In “lower” organisms—including plants, protozoa, fungi, and nematode worms—it also involves an enzyme—called RNA-dependent RNA polymerase—that can generate a strand of RNA using existing RNA as a template. This means that it can create double-stranded RNA from single-stranded pieces of RNA. By doing this, it generates more triggers and so amplifies the effect of RNA silencing. Paula Salgado and her colleagues have studied the structure of one such polymerase, called QDE-1, and found that it provides clues to the earliest stages of evolution.When a gene is transcribed and translated to generate a protein, the process begins with a DNA-dependent RNA polymerase. Like QDE-1, DNA-dependent RNA polymerases generate strands of RNA—the difference is that they use a DNA template to do it. The RNA they generate is called messenger RNA and is in turn used as the template for building a protein out of amino acids. The structures of DNA-dependent RNA polymerases have been described previously, so that the authors of this study could compare them with their new structure of QDE-1.What they found was a remarkable similarity. Both DNA-dependent RNA polymerases and QDE-1 have an active catalytic site—the working core of the enzyme—that is formed by two distinctive structural domains called double-psi β-barrels. This strong structural resemblance between QDE-1 and the DNA-dependent RNA polymerases points towards an evolutionary link between the two types of RNA polymerase.An influential theory on the origin of life proposes that RNA molecules were the first self-replicating molecules, forming a kind of precellular life in an “RNA world.” Initially, RNA molecules would have had to act as enzymes as well as genetic information so that they could replicate, but it is likely that an RNA-dependent RNA polymerase would have been one of the earliest protein-based enzymes to evolve.The similarity between QDE-1 and the DNA-dependent RNA polymerases suggests that both evolved from one ancestor, because otherwise, the resemblance between their active sites would be highly unlikely. This common ancestor might have been a primordial RNA polymerase in an RNA world. The authors suggest that this ancestor would have had just one double-psi β-barrel, and that gene duplication led to an enzyme with two barrels. From this early polymerase evolved both QDE-1–like RNA-dependent RNA polymerases and a diverse array of specialized DNA-dependent RNA polymerases. The diversification of DNA-dependent RNA polymerases would have been facilitated by the splitting of the two double-psi β-barrels onto separate subunits, rather than being borne on the same subunit as in QDE-1, so that different subunits could combine to create specialized polymerases.These findings provide a link between RNA silencing and the earliest mechanisms of RNA transcription—perhaps shedding light on both the origins of RNA replication (and therefore life) and the evolution of RNA silencing. They also provide insights into the mechanism of action of QDE-1 that might apply across the board to RNA-dependent RNA polymerases, and that will be built upon by further work.


Owing to the rapid expansion of RNA structure databases in recent years, efficient methods for structure comparison are in demand for function prediction and evolutionary analysis. Usually, the similarity of RNA secondary structures is evaluated based on tree models and dynamic programming algorithms. We present here a new method for the similarity analysis of RNA secondary structures.5S rRNAs. Set II includes the secondary  structures from RNase P and RNase MRP. Set III includes the structures from 16S rRNAs. Reasonable phylogenetic trees are derived for these three sets of data by using our method. Moreover, our program runs faster as compared to some existing ones.Three sets of real data have been used as input for the example applications. Set I includes the  structures from The famous Lempel-Ziv algorithm can efficiently extract the information on repeated patterns encoded in RNA secondary structures and makes our method an alternative to analyze the similarity of RNA secondary structures. This method will also be useful to researchers who are interested in evolutionary analysis. RNA secondary structures play an important role in determining the functions of RNA molecules. Some of them have been accepted as good data for evolutionary analysis. With the completion of the sequencing of the genomes of human and other species, major structural biology resources have been harnessed to predict functions. More and more RNA structures are accumulated and we know little about their functions. This calls for the development of cost-effective computational methods to predict RNA functions, which will provide preliminary information for biologists and guide biological experiments. Earlier studies usually adopt dynamic programming algorithms and tree models. Shapiro et al  proposedIn this paper we propose a novel method for the similarity analysis of RNA secondary structures, where pseudoknots are also taken into account. In our approach, each secondary structure is transformed into a linear sequence. The linear sequence not only contains the information on the corresponding RNA primary structure, but also contains the information on the base pairing.Furthermore, standard and famous Lempel-Ziv algorithm  is emploRNase P and RNase MRP. They are distantly related and there is little sequence homology between them. These secondary structures are used to test distant RNA secondary structures. They are mainly obtained from the RNase P Database /2, which leads to the fact that the distance calculated by the formula proposed in [Rd also satisfies the conditions required by a distance metric.The denominator in  is equivposed in  will alwposed in  has beenc(L(S)L(Q))-c(L(S)) and c(L(Q)L(S))-c(L(Q)) are, and then the smaller Rd is.It's obvious that the more similar S is to Q, the smaller n RNA secondary structures S1, S2,......, Sn, we can obtain their linear characteristic sequences by the above-mentioned rule, which are L(S1), L(S2),......, L(Sn). They are linear sequences defined over alphabet {A, C, G, U, a, c, g, u,} and carry the information on RNA secondary structures. Then, by using Lempel-Ziv algorithm, the distance between any pair of structures, Rd, may be rapidly computed. By arranging them into a matrix, a pair-wise distance matrix is obtained, denoted by RD. RD =) contains the information on the similarity/dissimilarity between any pair of RNA secondary structures.Generally, given Based on what Otu et al have proven, we can easily conclude that our distance metric is also valid for inferring phylogeny of species because it satisfies all the conditions for phylogeny analysis. Hence our pair-wise distance matrix may be input the programmes for phylogeny inference to study the phylogeny for RNA molecules based on their secondary structures.NL conceived of the study and drafted the manuscript. NL participated in the design of the algorithm. NL and TMW performed the comparison of RNA secondary structures and tested the algorithm.