Anabaena (Nostoc) sp. strain PCC 7120 (hereafter Anabaena) is a multicellular filamentous cyanobacterium that can "fix" atmospheric nitrogen into ammonia when grown in the absence of a source of combined nitrogen. Because the nitrogenase enzyme is oxygen sensitive, Anabaena forms specialized cells called heterocysts that create a microoxic environment for nitrogen fixation. We have employed directional RNA-seq to map the Anabaena transcriptome during vegetative cell growth and in response to combined-nitrogen deprivation, which induces filaments to undergo heterocyst development. Our data provide an unprecedented view of transcriptional changes in Anabaena filaments during the induction of heterocyst development and transition to diazotrophic growth.Cyanobacteria are potential sources of renewable chemicals and biofuels and serve as model organisms for bacterial photosynthesis, nitrogen fixation, and responses to environmental changes. Using the Illumina short read platform and a directional RNA-seq protocol, we obtained deep sequencing data for RNA extracted from filaments at 0, 6, 12, and 21 hours after the removal of combined nitrogen. The RNA-seq data provided information on transcript abundance and boundaries for the entire transcriptome. From these data, we detected novel antisense transcripts within the UTRs (untranslated regions) and coding regions of key genes involved in heterocyst development, suggesting that antisense RNAs may be important regulators of the nitrogen response. In addition, many 5' UTRs were longer than anticipated, sometimes extending into upstream open reading frames (ORFs), and operons often showed complex structure and regulation. Finally, many genes that had not been previously identified as being involved in heterocyst development showed regulation, providing new candidates for future studies in this model organism.Anabaena filaments during the response to nitrogen deprivation. We have identified genes and noncoding RNAs that are transcriptionally regulated during heterocyst development. These data provide detailed information on the Anabaena transcriptome as filaments undergo heterocyst development and begin nitrogen fixation.Directional RNA-seq data were obtained that provide comprehensive mapping of transcript boundaries and abundance for all transcribed RNAs in  Cyanobacteria are photosynthetic prokaryotes that have evolved a wide array of metabolic capabilities . BecauseAnabaena (Nostoc) sp. strain PCC 7120 grows as long filaments of photosynthetic vegetative cells in the presence of combined nitrogen. In an environment lacking combined nitrogen, about 7 to 10% of the cells terminally differentiate into nitrogen-fixing heterocysts. Heterocysts provide a microoxic environment for the expression of the oxygen-sensitive nitrogenase enzyme [The cyanobacterium e enzyme ,6. Single enzyme . Vegetate enzyme , thus cr2, and increase respiration to consume O2 that enters the cell. Heterocyst differentiation requires dramatic changes in transcription and some of the key components of this regulation are known. Nitrogen limitation is sensed by accumulation of 2-oxoglutarate (2-OG), the backbone for nitrogen assimilation. 2-OG enhances the DNA-binding activity of the transcription factor ntcA [nrrA, which is partially responsible for upregulation of hetR [hgl), exopolysaccharide genes (hep), and the patS gene, which encodes a peptide involved in heterocyst pattern formation [The differentiation of a vegetative cell into a heterocyst involves substantial changes in cell morphology and physiology ,6. Hetertor ntcA , which r of hetR ,14. HetRormation .Anabaena filaments during nitrogen step-down to identify and map all transcripts during heterocyst development [Factors other than those described above are known to be involved in heterocyst development and have been identified through microarrays and genetic screens -22. Whilelopment -27.Our RNA-seq data provide information on the UTR lengths of each mRNA transcript, on the transcription of sense and antisense or noncoding RNAs, and on the changes in expression of all transcripts whether or not they carry an annotation. The data show long 5' UTRs for many genes, likely with multiple transcriptional start or processing sites. In addition, our study identifies antisense transcription in the coding region or UTR of many genes known to be involved in heterocyst development. Finally, we detected new genes that are significantly upregulated in response to nitrogen deprivation.Anabaena filaments grown with ammonium as a nitrogen source and at three times after nitrogen step-down from ammonium to dinitrogen in air. The nitrogen step-down produces relatively synchronous induction of heterocyst development. RNA-seq data were acquired from filaments at 0, 6, 12, and 21 hours after nitrogen step-down, which provides detailed transcriptome data at important stages of heterocyst development (GEO accession #GSE26633). At 0 hours, all cells in the filaments are actively growing photosynthetic vegetative cells. At 6 hours, the cells have responded to the nitrogen step-down and are expressing early heterocyst differentiation genes such as hetR, the master regulator of heterocyst development, and patS, which is involved in pattern formation. By 12 hours, proheterocysts are committed to complete differentiation and are expressing genes required for altering their morphology and physiology to become microoxic. By 21 hours, nearly all heterocysts appear fully formed, contain polar cyanophycin granules, and are actively fixing nitrogen.We obtained RNA-seq data for total RNA isolated from reads per kilobase (kb) of CDS (coding sequence) model per million mapped reads in the sample [RNA-seq expression data are presented as RPKM, or e sample , with thnifHDK and other nif operons at 0, 6, and 12 hours after nitrogen step-down (when heterocysts are not yet fully formed). The reads for all nif operons and especially for the nifHDK genes are dramatically increased in the 21 h sample, when most heterocysts are fully differentiated  were upregulated by 12 hours after nitrogen step-down (Table hgl genes) did not occur until the 21-hour sample. These data show that during heterocyst morphogenesis, the polysaccharide genes are expressed first, likely depositing the stabilizing exopolysaccharide later; subsequently, hgl genes are expressed to produce the underlying glycolipid envelope layer, which together are required to help create a microoxic environment within the heterocyst.Formation of the heterocyst envelope involves deposition of a polysaccharide outer layer followed by deposition of an inner glycolipid layer ,11. The nif operons from fdxH -nifB  -alr2524 region, which contains the cytochrome oxidase genes coxBAC, and many genes annotated as unknown or hypothetical, was strongly upregulated by 21 hours after nitrogen step-down. Genes in the region alr2816-all2838, which contains hetC, hetP, and hepA, as well as many genes annotated as encoding hypothetical, glycosyltransferases, and metabolic proteins, were upregulated by 12 hours after nitrogen step down. Finally, genes in the region alr5340-alr5370, which contains several hgl (heterocyst glycolipid) genes along with a number of hypothetical genes, were upregulated by 21 hours after nitrogen step-down. Each of these regions contains a number of genes and operons that are important for heterocyst development and nitrogen fixation.In addition to identifying single genes that respond to nitrogen deprivation, we mapped gene clusters that were upregulated in response to nitrogen step-down. As expected, the region containing the major romosome ) was str fdxH all430-nifB Anabaena heterocyst differentiation. We identified several new genes transcribed in response to nitrogen deprivation that have GO terms associated with regulation, including transcriptional regulators, two-component regulators, and kinases . These 5' ends often corresponded with published transcriptional start and/or processing sites; for example psbB, petF, nrrA, psbAI, and nifB, all of which were previously analyzed via primer extension [Unlike previous whole-transcriptome analyses in xtension -35  and rbcL (carbon fixation), the pattern of reads showed evidence for transcripts extending upstream from published 5' ends . The antisense transcripts would not have been identified with standard microarray or RNA deep sequencing methods because these methods do not normally distinguish between sense and antisense transcripts.Anabaena transcriptome (Table hetR (the master regulator of heterocyst differentiation) and hetC (a gene involved in early heterocyst development). Furthermore, we confirmed the presence of the noncoding RNA NsiR1 in the upstream region of hetF (another heterocyst regulatory gene) [hetF. Other potential noncoding RNAs identified by our directional RNA-seq data include, for example, antisense reads in the region from alr0091 to alr0094 and from alr0709 to alr0710; and abundant rightward reads between alr0249 and all0250, and leftward reads between alr1199 and alr1200 (GEO accession #GSE26633).Our directional RNA-seq data showed antisense RNAs throughout the ry gene) -43, and nblA, which is involved in degradation of phycobilisome proteins in response to nitrogen deprivation [nblA sense reads increased  sp. strain PCC 7120 cultures grown in 100 ml of liquid medium in 250-ml flasks with cotton plugs as previously described with slight modifications [750 of 0.5 in BG-11(NH4) medium, which lacked sodium nitrate and contained 2.5 mM ammonium chloride and 5 mM MOPS (pH 8.0). For the 0 hour sample, cells were collected before deprivation of combined nitrogen. For nitrogen-deprived samples, cells were collected by centrifugation and washed 3 times in BG-110, which lacks sodium nitrate, resuspended in BG-110 to an OD750 of approximately 0.05, and incubated for 6, 12, or 21 hours. These times were chosen because at 6 hours cells are beginning to establish a pattern of differentiating cells, at 12 hours proheterocysts are committed to becoming heterocysts [g for 2 minutes at 4°C. Supernatant was removed and cell pellets were flash frozen in liquid nitrogen for storage at -80°C. RNA was isolated from filaments with the Ambion RiboPure RNA isolation kit according to the manufacturer's protocol and total RNA was used for deep sequencing.For deep sequencing, total RNA was prepared from ications . Brieflyerocysts , and at Ribosomal RNA was not removed from total RNA to avoid any depletion of coding transcripts. The presence of ribosomal and transfer RNAs in our sequencing sample did result in a decreased yield of transcript information from coding RNAs (only ~10% of the sample at each time point was non-rRNA and non-tRNA transcripts); however, this protocol avoided the known biases introduced by current rRNA depletion methods . FurtherFor sequencing, the library was denatured and diluted following standard Illumina-recommended protocols to a final concentration of 9 pM before being loaded onto an Illumina single read flow-cell for massively parallel sequencing on an Illumina GAIIx. Raw sequences were obtained from GA Pipeline software using CASAVA v1.7. The reads were further processed to remove any adapter sequence using the Illumina Flicker add-on. Flicker v2.7 trims the adaptor sequence from each read and does iterative alignment to the reference genome using ELAND.One sample was sequenced per lane, yielding an average of 17 million high quality 36-bp reads per sample for the 0-, 12-, and 21-hour time points, 1.7 million of which were from non-rRNA and non-tRNA transcripts. The 6-hour sample was sequenced with longer 100-bp reads; however, these reads were trimmed to 40 bp for our analysis. RNA-seq data were aligned and analyzed with CLC Genomics Workbench 4 to create SAM files that were further analyzed with the Cufflinks software suite . CLC genAnabaena sp. strain PCC 7120 genome are included in the accession. Raw reads are .txt files and can be opened with a FASTA viewer. Aligned reads are in .BAM format and can be analyzed with free or commercial software suites.RNA-seq data are available through the NCBI Gene Expression Omnibus (GEO) database, accession number #GSE26633. The raw sequence reads as well BAM files of reads at each time point aligned to NCBI's current build of the The authors declare that they have no competing interests.BLF participated in the design of the experiments, collected RNA samples, analyzed sequence data, and drafted the manuscript. FVN constructed the cDNA library. SRH helped design the directional library construction and oversaw Illumina sequencing. JWG participated in design of the experiments and helped draft the manuscript. All authors read and approved the final manuscript.Chromosome RNA-seq data. Chromosome RNA-seq data for Anabaena PCC 7120 at 0, 6, 12, and 21 hours after nitrogen step-down.Click here for fileAlpha plasmid RNA-seq data. Alpha plasmid RNA-seq data for Anabaena PCC 7120 at 0, 6, 12, and 21 hours after nitrogen step-down.Click here for fileBeta plasmid RNA-seq data. Beta plasmid RNA-seq data for Anabaena PCC 7120 at 0, 6, 12, and 21 hours after nitrogen step-down.Click here for fileGamma plasmid RNA-seq data. Gamma plasmid RNA-seq data for Anabaena PCC 7120 at 0, 6, 12, and 21 hours after nitrogen step-down.Click here for fileDelta plasmid RNA-seq data. Delta plasmid RNA-seq data for Anabaena PCC 7120 at 0, 6, 12, and 21 hours after nitrogen step-down.Click here for fileEpsilon plasmid RNA-seq data. Epsilon plasmid RNA-seq data for Anabaena PCC 7120 at 0, 6, 12, and 21 hours after nitrogen step-down.Click here for fileZeta plasmid RNA-seq data. Zeta plasmid RNA-seq data for Anabaena PCC 7120 at 0, 6, 12, and 21 hours after nitrogen step-down.Click here for fileRPKM heat map data. Change in RPKM data for Anabaena PCC 7120 from 0 to 6, 12, and 21 hours after nitrogen step-down used to prepare heat map.Click here for file


Crassostrea virginica). Subtidal oyster reefs in coastal North Carolina, USA show distinct acoustic signatures compared to adjacent off-reef soft bottom habitats, characterized by consistently higher levels of sound in the 1.5–20 kHz range. Manipulative laboratory playback experiments found increased settlement in larval oyster cultures exposed to oyster reef sound compared to unstructured soft bottom sound or no sound treatments. In field experiments, ambient reef sound produced higher levels of oyster settlement in larval cultures than did off-reef sound treatments. The results suggest that oyster larvae have the ability to respond to sounds indicative of optimal settlement sites, and this is the first evidence that habitat-related differences in estuarine sounds influence the settlement of a mollusk. Habitat-specific sound characteristics may represent an important settlement and habitat selection cue for estuarine invertebrates and could play a role in driving settlement and recruitment patterns in marine communities.Following a planktonic dispersal period of days to months, the larvae of benthic marine organisms must locate suitable seafloor habitat in which to settle and metamorphose. For animals that are sessile or sedentary as adults, settlement onto substrates that are adequate for survival and reproduction is particularly critical, yet represents a challenge since patchily distributed settlement sites may be difficult to find along a coast or within an estuary. Recent studies have demonstrated that the underwater soundscape, the distinct sounds that emanate from habitats and contain information about their biological and physical characteristics, may serve as broad-scale environmental cue for marine larvae to find satisfactory settlement sites. Here, we contrast the acoustic characteristics of oyster reef and off-reef soft bottoms, and investigate the effect of habitat-associated estuarine sound on the settlement patterns of an economically and ecologically important reef-building bivalve, the Eastern oyster ( Most bottom-dwelling marine organisms have a biphasic life cycle, consisting of a dispersing larval phase that develops in the plankton prior to settlement into seafloor habitat and a sessile or sedentary adult phase. Successful recruitment of marine larvae, beginning with larval settlement into quality habitat, is fundamental to replenishing populations and structuring benthic communities Underwater sounds produced by physical and biological processes are increasingly recognized as a potentially effective signal for larvae of benthic organisms to locate patchily distributed—yet acoustically distinctive—settlement habitat, such as coral reefs and other subtidal habitats The majority of habitat-associated soundscape characterization has occurred in a single region in New Zealand Here, we use the oyster reef soundscape as a novel study system to examine the possibility that habitat-related sound characteristics influence larval settlement processes. Oyster reef soundscapes are of particular interest as a larval cue because reefs are patchily-distributed and productive habitats that harbor many sound-producing organisms  Crassostrea virginica, to determine if habitat-related sound affects settlement.While larvae of certain bivalves can respond to acoustic stimuli To determine whether the estuarine habitats of interest differed in their acoustic spectral characteristics, and therefore represented a potential settlement cue, field recordings of ambient sound on oyster reef and nearby soft-bottom habitats were conducted several times during the peak oyster settlement months. Using laboratory and field experimental approaches, we then examined the settlement response of oyster larvae to natural ambient sound associated with suitable (oyster reef) and unsuitable settlement habitat (unstructured soft-bottom) to test the hypothesis that oyster larval settlement would be higher in the presence of sound associated with their preferred settlement habitat compared to sounds of other habitats. In laboratory experiments, we quantified oyster larval settlement in cultures exposed to two estuarine soundscapes (oyster reef vs. unstructured soft bottom), as well as a no sound control. Because acoustic stimuli matching field conditions are particularly difficult to produce in small laboratory tanks 2) and sheltered compared to the larger (55 400 m2) and more exposed Crab Hole reef. Continuous recordings of ambient habitat sound were collected using underwater recording systems consisting of a SQ26-08 Sensor Technology omnidirectional hydrophone, with an effective sensitivity of −169±1 dB re 1V/μPa over the 0.1–28 kHz frequency range. The hydrophone was positioned 1 meter from the seafloor and connected to an M-Audio Microtrack II digital recorder (sample rate: 48 kHz) in a waterproof housing at the surface. For reef recordings, hydrophones were stationed within the reserve boundary but on unstructured bottom approximately 25 meters from reef structure.During 2010, oyster reefs and nearby soft-bottoms (∼ 2 km from oyster reefs) at two sites in Pamlico Sound, North Carolina  were acoDigital recording samples were analyzed in MATLAB using purpose-written code. Spectrograms were first inspected for anomalous transient or anthropogenic noise and acoustic power spectra for concurrent recordings were produced to make comparisons of the acoustic characteristics of the two habitat types.Crassostrea virginica pediveligers  were dry-shipped on ice overnight from the Horn Point Laboratory (HPL) oyster hatchery (University of Maryland) where broodstock was obtained from Chesapeake Bay oyster populations. Following arrival to the laboratory in North Carolina, USA , larvae were warmed in dishes of 10 µm filtered seawater at a salinity matching HPL's rearing conditions (10–15 psu), and held at room temperature (23–25°C) for the duration of the experiments. Twice in 2011, larvae were available from a local NC hatchery (Bear Creek Shellfish Hatchery), and were obtained for use in a laboratory trial and a field trial, following the same protocol as other trials.Prior to each laboratory- or field-based settlement trial, eyed in situ at oyster reef and adjacent off-reef soft bottom habitats at West Bay and Crab Hole sites. Prior to use in experiments, waveforms and spectrograms of the candidate recordings were visually inspected using Audacity™ software to ensure the absence of anthropogenic or anomalous noise.The field soundscape sampling effort described above generated a library of 4-to-5-hour-long recordings of reef and off-reef sounds from which experimental playback treatments were selected. Sound treatments used in laboratory larval settlement experiments consisted of replaying the habitat sounds recorded In the four trials comprising the first laboratory settlement experiment in September 2010, a 15-minute recording of dusk-time oyster reef sound was played continuously as the sound treatment. The 15-minute reef sound-clip was selected from a September recording of the West Bay oyster reserve on a new moon, contained no anthropogenic noise, and was typical of reef sounds recorded within Pamlico Sound reef habitats. For the second set of laboratory experiments in July and August 2011, in which both reef and off-reef sound treatments were applied, pairs of simultaneously recorded audio clips were used in each trial. The recordings used in the five trials of experiment 2a were 15-minute samples from recordings made at the West Bay oyster reef and off-reef sites at dusk in July 2010. To avoid concerns of pseudoreplication associated with the use of a single recording in experimental playback experiments Prior to the start of experimental trials, in-tank recordings using a calibrated omni-directional hydrophone (Sensor Technology SQ26-08) and digital recorder (M-Audio Microtrack II) were used to adjust the speaker levels in sound treatments to reflect typical oyster reef or off-reef sound pressure levels, and to the degree possible, match the acoustic spectrum of the original recordings. For these calibrations, the hydrophone was placed just below the water surface where the experimental jars used in trials were located. Hydrophone recording in the no sound (control) tanks also confirmed the absence of substantial noise from these treatments. Additional measurements of particle motion were made after the experiments were concluded to ensure that the total acceleration during the playbacks approximated far-field conditions. Particle acceleration measurements were made following the methods of Glade Crassostrea virginicaInitial trials to test the effect of underwater sound on oyster larval settlement occurred in September 2010. Oyster settlement  was measured for groups of larvae randomly assigned to tanks with or without playback of continuous oyster reef sound. During this preliminary experiment, a series of four trials were conducted, each lasting between 2–5 days as part of method refinement to determine the most appropriate trial length to ensure measurable settlement rates. Trials were conducted in complete darkness to remove any effect of light on settlement behavior, as experimental light conditions have been implicated in producing contradictory results in studies of oyster settlement response to physical factors At the beginning of each trial, groups of 100 actively swimming pediveliger larvae were randomly assigned to a 20-L glass experimental tank where they were housed 0.2 m off-bottom in a 100 mL plastic container  filled with 10 µm filtered seawater . Each taA second set of experiments was conducted in 2011 to expand upon the scope of the preliminary experiment by including an additional off-reef sound treatment, increasing replication, and improving the quality of laboratory sound playbacks through the use of cylindrical tanks and underwater speakers. Three experimental arenas were constructed, each consisting of a 20-L cylindrical water bath with an underwater speaker  placed on the bottom 0.2 m below larval culture containers . SpeakerFor each trial, 15 groups of 100 actively swimming pediveliger larvae were placed in 80-mL containers and randomly assigned to an experimental tank . The experimental tanks were randomly designated as reef sound, off-reef sound or no sound treatments prior to each trial, and for sound treatments a recording played continuously for the duration of the trial. As in experiment 1, oyster settlement at the conclusion of a trial was measured in each container under a dissecting microscope as the proportion of individuals attached to the substrate or container surfaces, and the mean proportional settlement for each replicate was calculated. For each of the two experiments, randomized block ANOVAs were used to test for a difference in the response variable (mean settlement) amongst sound treatments, blocked by trial. Significant differences in mean settlement among the sound treatments were identified with a Tukey's Honestly Significant Differences test.To further overcome limitations related to the reproduction of sound using speakers in small tank experiments In each of four trials, four replicate “larval housings” were placed at each site. Larval housings consisted of sample jars identical to those used in laboratory trials and each jar contained an oyster shell disc as settlement substrate. The number of larval cultures used in each replicate larval housing varied among trials (1–4 jars per replicate) based on availability of larvae and logistical constraints. As in laboratory settlement experiments, groups of 100 larvae were placed in the tightly sealed jars prior to deployment at the habitat sites, thereby exposing larvae to habitat sounds while excluding other potential habitat-associated cues such as differences in water chemistry. Larval housings were suspended 1 meter above the seabed . At the The different soundscapes of oyster reef and off-reef sites at West Bay were well-characterized prior to this field experiment, providing support for the assumption that the sites could provide distinct sound treatments for the experimental units (see soundscape measurement results below). Recording equipment to monitor the site acoustics during field experiment trials was unavailable until the final trial in August 2012, for which a long-term acoustic recorder  was deployed at each site on a recording schedule of 1 minute every 15 minutes at a sampling rate of 50 kHz. Each DSG consisted of an individually calibrated HTI-96-MIN hydrophone (Hi-Tech Inc), with the frequency-amplitude response of the system being flat (+/− 0.2 dB) over the range of ∼ 100–25,000 Hz.Alpheus heterochaelis) The spectral composition of oyster reef sound was consistently different compared to nearby soft bottom habitats for the July, August and September sampling periods at the two field sites . The difThe conventional computer speakers placed in waterproof bags and used in laboratory experiment 1 to replay oyster reef sounds produced a sound spectrum that generally matched the sound pattern of the original field recordings; however, there was a somewhat limited ability to reproduce all frequencies consistently . In partin situ recordings in their general pattern  the broadband rms sound pressure levels of the field sound recordings.For the on reef treatments, broadband rms sound pressure levels ranged between 114.4 and 128.0 dB re 1 µPa and the measured rms acceleration in the 0.1–6 kHz band varied between −45.0 and −37.8 dB re 1 m/s1,20 = 28.75, p<.0001). There was no significant interaction between trial and treatment .Oyster larval settlement was significantly higher in response to the reef sound treatment compared to no sound (Control) treatment in the 2010 laboratory experiment . Mean oyster larval settlement for the off-reef sound treatment did not significantly differ from the no sound treatment .In the second laboratory experiment, oyster larval settlement was significantly higher when exposed to the reef sound treatment (with and without preferred substrate) compared to both the off-reef sound treatment and no sound treatment . This overall treatment effect was apparently driven by the June 2011 and July 2012 trials; however, because the statistical model did not find a significant trial by treatment interaction , data were pooled across trials for the overall treatment effect test.In agreement with the laboratory results, oyster larval settlement in larval housings suspended in oyster reef habitats during the field-based experiment was significantly higher compared to larval settlement in off-reef sites  to habitat sounds, and by investigating the threshold sound levels and frequencies that elicit settlement responses. The effect of artificial rearing conditions on larval responses is an important consideration in the interpretation of experiments using hatchery animals, particularly in light of evidence that reef fish larvae are influenced by previous acoustic experiences The experiments presented here expand our understanding of underwater sound as an influence on ecological processes in marine environments, and highlight the need for a better understanding of a variety of topics related to sound-mediated larval behavior and settlement. The specific sensory mechanism for the larval response to acoustic stimuli remains unknown for this species and the other invertebrates that have shown behavioral or physiological responses to sound


Significant efforts have been applied to develop new in vivo chemical probing reagents, new library construction protocols for sequencing platforms and improved RNA prediction software based on the experimental evidence.RNAs are important catalytic machines and regulators at every level of gene expression. A new class of RNAs has emerged called long non-coding RNAs, providing new insights into evolution, development and disease. Long non-coding RNAs (lncRNAs) predominantly found in higher eukaryotes, have been implicated in the regulation of transcription factors, chromatin-remodeling, hormone receptors and many other processes. The structural versatility of RNA allows it to perform various functions, ranging from precise protein recognition to catalysis and metabolite sensing. While major housekeeping RNA molecules have long been the focus of structural studies, lncRNAs remain the least characterized class, both structurally and functionally. Here, we review common methodologies used to tackle RNA structure, emphasizing their potential application to lncRNAs. When considering the complexity of lncRNAs and lack of knowledge of their structure, chemical probing appears to be an indispensable tool, with few restrictions in terms of size, quantity and heterogeneity of the RNA molecule. Probing is not constrained to  Currently, RNA molecules are viewed as important catalytic molecular machines and important regulators of gene expression during transcription, mRNA maturation and translation –3. In rei.e., sequence specific processes). For example, mature miRNA and siRNA molecules basepair to their targets [Certain functional properties of RNA are determined by primary structure  specify the precise geometrical and topological arrangements of the helices, yielding the three-dimensional architecture, or tertiary fold . Nuclease S1, nuclease P1, RNase T1, RNase U2, and RNase A are enzymatic probes commonly used to map single stranded RNA  (N-methylisatoic anhydride), 1M7 (1-methyl-7-nitroisatoic anhydride) and BzCN (benzoyl cyanide), which vary in hydrolysis half-lives. More detailed information on advances in chemical probing can be found elsewhere [Until recently, other widely-used chemical probes included: dimethyl sulfate (DMS), kethoxal and 1-cyclohexyl-(2-morpholinoethyl)carbodiimide metho-e (CMCT) . These re (CMCT) . This islsewhere .3.3.The most powerful and reliable alternative method to determine the helical composition of RNA is comparative sequence analysis . This meThis technique has proven quite powerful in the case of ribosomal and riboswitch RNAs, where several thousand sequences are available and covariance analysis can be used to predict the presence of helices with high confidence. LncRNAs, however, are present primarily in the mammalian transcriptome, limiting the number of available sequences for use in multiple sequence alignments. In addition, many lncRNAs exhibit very low sequence conservation, making multiple sequence alignment difficult. Finally, lncRNAs often exhibit lineage-specific functions. For instance, 30% of human lncRNAs are estimated to be primate-specific . We noteIndividual 2-D methods or combinations of these methods have been applied to produce the secondary structures of many housekeeping RNA molecules ,43. Thes4.Thousands of new lncRNA molecules have been discovered in recent years. Traditional experimental investigations of RNA structure—one molecule at a time—cannot cope with this large demand. Many powerful computational methods have been developed to produce predictions of RNA secondary structures . These iMany RNA prediction programs incorporate sequence homology to improve their structure prediction accuracies. These programs include RNAalifold, Construct, CM-finder and others ,60–62. I5.Methods used to gain information about RNA tertiary contacts include UV/chemical crosslinking and hydroxyl radical probing –70. X-ra6.Until recently, only low-throughput structural studies of RNA molecules—one molecule at a time—have been published and accessed. Structural investigations of entire transcriptomes have been realized with high-throughput sequencing platforms . Two indin vitro refolded RNAs.The second paper introduced FragSeq approach, utilizing RNase P1 (a single-stranded RNA nuclease) to analyze the structural content of nuclear ncRNA in mouse cell lines . In bothin vivo.While the above protocols rely on RNase digestion to generate smaller RNA fragments, other RNA chemical probing protocols, which modify RNA, can be adapted to deep-sequencing platforms (SHAPE-seq) . The dev7.in vitro applications, only the base-specific DMS reagent was applicable to study intact cells and has been used for decades [in vivo environments by developing two new SHAPE reagents [Ideally, we need to study RNA structure in its natural environment: living cells. Because RNA folds while being transcribed, the rate of transcription is an important parameter for consideration . In cell decades ,85. Chanreagents . These t8.in vitro analysis. This is the only method that can provide an experimental structural output for any given RNA sequence in vitro and in vivo at the nucleotide level of detail [in vivo chemical probing reagents, new library construction protocols for sequencing platforms and improved RNA prediction software based on experimental data. Significant advances have been made in the past two years.Chemical probing is the only available technology for RNA structure determination that has no restrictions in terms of the size of RNA molecules, their quantity and heterogeneity. Most importantly, chemical probing is not constrained to f detail . Moreovein vivo RNA analysis tools is likely to produce an explosion of RNA structural information in the near future. The next step will be to determine the particular structural elements that are functional. One approach is to analyze lncRNA sequence conservation in the context of experimentally-determined secondary structures. This route can uncover common motifs and regulatory trends conserved at the structural level, which were previously overlooked. In light of the large amount of data, this task will be an interesting challenge for bioinformatics investigators.The advancement of in vivo reagents with deep-sequencing platforms offers new research directions in studying entire structurome not only under normal conditions, but under stress, changes in temperature and other variations of environment [Without doubt, coupling chemical ironment ,75,77,86


The essential herpesvirus adaptor protein HVS ORF57, which has homologs in all other herpesviruses, promotes viral mRNA export by utilizing the cellular mRNA export machinery. ORF57 protein specifically recognizes viral mRNA transcripts, and binds to proteins of the cellular transcription-export (TREX) complex, in particular ALYREF. This interaction introduces viral mRNA to the NXF1 pathway, subsequently directing it to the nuclear pore for export to the cytoplasm. Here we have used a range of techniques to reveal the sites for direct contact between RNA and ORF57 in the absence and presence of ALYREF. A binding site within ORF57 was characterized which recognizes specific viral mRNA motifs. When ALYREF is present, part of this ORF57 RNA binding site, composed of an α-helix, binds preferentially to ALYREF. This competitively displaces viral RNA from the α-helix, but contact with RNA is still maintained by a flanking region. At the same time, the flexible N-terminal domain of ALYREF comes into contact with the viral RNA, which becomes engaged in an extensive network of synergistic interactions with both ALYREF and ORF57. Transfer of RNA to ALYREF in the ternary complex, and involvement of individual ORF57 residues in RNA recognition, were confirmed by UV cross-linking and mutagenesis. The atomic-resolution structure of the ORF57-ALYREF interface was determined, which noticeably differed from the homologous ICP27-ALYREF structure. Together, the data provides the first site-specific description of how viral mRNA is locked by a herpes viral adaptor protein in complex with cellular ALYREF, giving herpesvirus access to the cellular mRNA export machinery. The NMR strategy used may be more generally applicable to the study of fuzzy protein-protein-RNA complexes which involve flexible polypeptide regions. Herpes viruses invade cells, hijacking cellular components to sustain their lifecycle and replicate. A critical step of infection is the export of viral mRNA from the nucleus to the cytoplasm, where the molecular machinery to produce proteins is located. To provide a link between their mRNA and cellular components of the mRNA export pathway, all herpesviruses use special adaptor proteins. These adaptor proteins specifically select viral mRNAs from the mixture present in the nucleus, and introduce them to cellular mRNA export factors, such as ALYREF. How these viral adaptors manage to trick ALYREF to accept foreign genetic material has not been understood on a molecular level. In this study we reveal how a typical viral adaptor protein ORF57 recognizes specific viral RNA motifs, and also how it binds to the cellular protein ALYREF. We uncover details of how ORF57 transfers the viral RNA to ALYREF, locking it in the cooperative ternary complex. We also describe the atomic-resolution structure of ORF57-ALYREF interaction interface. Together the data provides the first molecular insight of how viral mRNA is transferred between viral and cellular proteins, thus helping virus to hijack a cell. Mammalian gene expression is coupled with mRNA maturation, where nascent transcripts undergo a continuous series of splicing and processing events finally leading to nuclear export to the cytoplasm Herpesviridae possess an intriguing ability to circumvent the sophisticated cellular controls which ensure that only mature spliced mRNA can be exported from the nucleus. Viral mRNA is generally unspliced, therefore it cannot acquire the normal protein markers during splicing, which would signal that mRNA is ready for export to the cytoplasm. However, all herpesviruses express an essential multi-functional adaptor protein which specifically recognizes viral mRNA, and bridges its interaction with TREX complex via binding to cellular mRNA export factors such as ALYREF and UIF Recently, the structure of the interaction interface between HSV-1 adaptor protein ICP27 and cellular mRNA export factor ALYREF was determined In this study we used solution state NMR to reveal molecular details of the ternary complex assembly of functional fragments of HVS ORF57, HVS RNA and ALYREF, and suggest a model for the mechanism of RNA transfer between protein molecules in this system. The mapping experiments show a clear difference between binding of non-specific random-sequence RNA oligos, and RNA oligos containing HVS-specific sequence motifs, to a flexible arginine-rich region of ORF57. We reveal that for the ORF57 protein, its ALYREF binding site also forms part of the specific viral RNA recognition region, with adjacent arginine-rich sequences also contributing to RNA binding. We present the atomic-resolution structure of the ORF57-ALYREF binding interface, which somewhat differs from that of ICP27-ALYREF identified earlier 8–120, and study specific vs non-specific binding, we used NMR spectroscopy. Sequence specific signal assignments of all amides of ORF578–120 allowed the mapping of interaction sites to a residue-level resolution. The unlabelled RNA oligonucleotides were added to 15N-labelled protein samples and residue-specific signal changes were monitored. The effect of non-specific RNAs of different lengths  on signal position and shape were compared with ORF57-specific RNA oligos (7merS and 14merS) containing the previously identified HVS motif GAAGAG 8–120 were small and scattered across the entire sequence  were observed even with a 3-fold excess of RNA . We could not observe intermolecular NOEs between RNA and protein for the definitive binding epitope mapping, therefore, to separate possible indirect effects of conformational changes on signal shifts brought about by RNA binding and identify direct points of contact, we used RNA→ORF57 cross saturation transfer (ST) experiments 15N-labelled ORF578–120 : RNA 7merS in a ratio of 1∶0.5 was prepared . Selective saturation of RNA signals with a series of radiofrequency pulses resulted in a significant decrease in signal intensity of the backbone amides in 1H-15N correlation spectra (relative to the reference spectrum with off-resonance saturation) of mainly aa107–120 and aa81–92, and to a lesser extent, aa94–105, and even less, aa64–79  with ORF578–120 could not be determined due to an unfavorable chemical exchange regime, causing signal broadening for the interacting residues 103–120 construct, which displayed much improved spectra and less exchange behavior  was previously mapped to RGG motifs situated within its unstructured N-terminus and also to loops L1 and L5 of the RRM domain 15N]-REF1–155 using equimolar 7merS or 14merS , however signals from other regions of both proteins are clearly observable, and their pattern is characteristic of ORF57-ALYREF complex formation. Having been assigned to particular amino acid residues, they were able to report site-specific changes in the protein-protein interactions in response to ligand binding  and remained broad. IDIS-TROSY spectra of both ALYREF and ORF57 confirmed formation of the protein-protein complex as the fingerprint pattern of observable ORF57 signals was consistent with ORF57 bound to ALYREF, but not RNA. These direct experiments demonstrate that virus-specific RNA is displaced from ORF57 aa106–120 by the competitive binding of ALYREF to this region, and not by the preferential binding of RNA to ALYREF.In an initial experiment, a stoichiometric equivalent of a shorter specific RNA 7merS was added to the differentially-labeled ORF57-ALYREF complex. In contrast to the substantial broadening of aa64–120 observed on addition of 7merS to free ORF57 present . This ingo 7merS . The ALY1–155 and ORF578–120 in the ternary complex . Protein deuteration was used to improve the quality of spectra and reduce possible artifacts due to spin diffusion effects 5.85/I21.0 obtained with on-resonance ribose proton (5.85 ppm) and off-resonance (21.0 ppm) saturation, we noticed a significant amount of non-specific saturation transfer to virtually all serine residues in ORF57. We explained that by the inadvertent saturation of serine hydroxyl groups. To compensate for this effect, we have used two different saturation schemes. In the first scheme, we selectively saturated two RNA resonances (moieties) with similar chemical shifts (5.75 and 5.85 ppm), and calculated the ratio of signal intensities I5.75/I5.85 , suggesting that RNA is retained by ALYREF within the ternary complex more efficiently than by ALYREF alone.As the short RNA 7merS cannot be bound efficiently by the ORF57-ALYREF complex, subsequent experiments were performed using a longer specific RNA 14merS. Importantly, as evidenced by the presence of a large number of relatively sharp signals from amide groups of both proteins , Fig. S6 complex . A sampl75/I5.85 . If one lculated . The RNAlculated ,H. The mlculated . The reged by ST ,H is exped by ST . In the The NMR experiments therefore all indicate that ALYREF partially displaces the viral RNA initially bound specifically to ORF57, but retains it within the complex. In the ternary complex ORF57 aa106–120 directly interacts with the ALYREF RRM, whereas flexible flanking regions of ALYREF (aa24–48) and ORF57 (aa81–92), and to lesser extent, parts of helix 2 of the ALYREF RRM, jointly keep hold of the viral RNA molecule. Interestingly, amide signals from flexible protein regions which become involved in direct contacts with RNA (as evidenced by RNA-protein saturation transfer), are only partially broadened in the complex. They had intensities higher than signals from the folded regions, but lower than signals from the unfolded non-interacting regions  forms part of their binding interface, and is buried upon protein complex formation. Control experiments showed that ALYREF1–155 and ORF578–120 both have a fluorescence intensity maximum at 355 nm which is not shifted by 14merS RNA addition . The formation of equimolar ALYREF1–155 - ORF578–120 complex leads to a blue shift of the emission maxima of the sample , the assembly shows clear-cut cooperative behavior dK>50 µM, see above) is taken into account , compared to the background level of non-specific ALYREF-RNA complex , for the concentrations used in this example the amount of virus-specific RNA in complex with ALYREF increases more than 3.6 times.Fluorescence measurements were used to quantify the overall strength of the ALYREFe sample , in agre±0.20 µM . Additio account , and twoInterestingly, adding a large excess of RNA to the 2.5 µM ALYREF-ORF57 mixture displayed a more complex behavior of signal shift : the bluThe experimental fluorescence equilibrium binding data thus reveal the overall cooperativity in the ternary complex formation when the components are present at or near stoichiometric amounts, and support a role of ORF57 as an adaptor introducing RNA to ALYREF. The fluorescence data are also consistent with a local competitiveness of ORF57-ALYREF and ORF57-RNA interactions: this competitiveness becomes apparent at macroscopic  level only if RNA is in significant excess. These observations fit well with the NMR experiments which show the ability of ALYREF to partially displace RNA from R-b helix of ORF57, while forming ternary complex.8–120 were confirmed by UV cross-linking using purified protein and radio-labeled RNA oligonucleotide, performed as previously described The results of NMR mapping of RNA binding regions of ORF578–120, ALYREF1–155 and their complex, we performed in vitro reconstitution assays followed by UV cross-linking experiments. ORF578–120 showed a strong RNA-binding activity for 7merS and 14merS in sharp contrast to GST-ALYREF which bound weakly with both RNAs  level concurs fully with the NMR data obtained at a residue-specific level of detail. Interestingly, the increase in ALYREF-RNA cross-linking efficiency observed experimentally in the presence of ORF57 fits well with the numerical estimates using COPASI simulations shown on To independently confirm the NMR observations in regard to RNA oligonucleotide binding with ORF57oth RNAs . When ORThe combination of structural and interaction data allows us to suggest a model that explains how the adaptor protein ORF57 from HVS introduces viral mRNA to cellular mRNA export factor ALYREF, functioning as a molecular “hijacker”. As previously noted, ALYREF itself binds mRNA weakly and non-specifically, and cannot discriminate between cellular and viral transcripts, needing other proteins to recruit mRNA and strengthen this binding to a functionally significant level. This non-specific binding can be observed and mapped here by weak saturation transfer from RNA to protein . In its The functional role of the viral protein ORF57, to introduce specific viral RNA to the cellular protein ALYREF, thereby facilitating the export from the nucleus of unspliced viral mRNA via the NXF1-dependent cellular pathway, is fulfilled via several critical properties. First, ORF57 must recognize a specific viral mRNA, which contains characteristic sequence motifs, and ignore cellular mRNA. Second, it should interact with cellular ALYREF, and induce binding of a specific viral mRNA to ALYREF, allowing ALYREF then to pass it over to NXF1 at the next stage of the pathway. Therefore, the ability to recognize and reversibly bind RNA is crucial for correct and efficient functioning of viral ORF57 as a “molecular highjacker” of the host cell pathway. Here, we have reconstituted in vitro and studied in detail the function of the core responsible for the recruitment of viral RNA to ALYREF, using the essential protein fragments of ORF57(aa8–120) and ALYREF(aa1–155) which interact with each other and with viral RNA. A range of experimental approaches was used to reveal the molecular mechanism of viral RNA recognition and following transfer from ORF57 to ALYREF with atomic-to-residue-level resolution.8–120 regions in direct contact with RNA, aa107–120 and aa81–92, with residues from aa94–105 and aa64–79 also contributing. Although the general “polyelectrostatic effect” 8–120 cross-linking, confirming their involvement in mediating RNA binding  is lower than to ALYREF1–155 (>50 µM) or ORF578–120 (7.57 µM) individually. The inferred Kd of ALYREF binding to ORF57-RNA complex . For NMR studies, murine ALYREF  isoform constructs aa1–155 (ALYREF1–155), aa54–155 (ALYREF54–155), as well as ORF5756–140 and ORF578–120, were produced as described previously 103–120 peptide was produced as a GST-fusion construct as described for ICP27103–138103–120 was obtained from Peptide Protein Research Ltd (UK). For UV cross-linking, hexa-histidine ORF578–120, hexa-histidine GB1 and GST-ALYREF fusions were purified by affinity chromatography and dialyzed against RB100 buffer .All proteins were expressed in 103–120 in free form and with a 3-fold excess of unlabelled ALYREF54–155 added, ORF5756–140 in the free form, and ALYREF54–155 with a 3-fold excess of ORF57103–120 synthetic peptide added. ALYREF54–155, ALYREF1–155 and ORF578–120 were assigned previously Bruker) and analyzed using Sparky . Distance restraints obtained from 3D 15N- and 13C- edited NOESY-HSQC experiments (τm 130 ms) and dihedral restraints from TALOS+ 13C-edited, 12C-filtered NOESY-HSQC (τm 150 ms) spectra acquired on a Varian Inova 800 MHz spectrometer. In this experiment only NOE crosspeaks between 1H-13C moieties of 13C,15N-labelled ALYREF and 1H(12C) of unlabelled ORF57 were observed DeLano Scientific). Chemical shift assignments were submitted to the BioMagResBank for free ORF57103–120 (bmr17664), free ORF5756–140 (bmr17663) and the ALYREF-ORF57 complex (bmr17693). Structure coordinates and experimental constraints for ALYREF-ORF57 complex were deposited into the Protein Data Bank (2yka). Ramachandran plot statistics for residues in most favored regions, additional allowed regions, generously allowed regions, disallowed regions calculated for structured ALYREF74–152+ORF57106–120 are: 79.8%, 20.2%, 0%, 0%.All experiments were carried out at 30°C on Bruker DRX600, DRX700 and Varian Inova 800 MHz spectrometers equipped with cryoprobes, and a Bruker DRX800 with a room temperature probe. Standard triple-resonance experiments were used to assign spectra: ORF5713C,15N-labelled ORF578–120 and 15N-labelled ALYREF1–155 or ALYREF54–155, followed by additions of RNA. RNA oligonucleotides were obtained from Sigma. Two oligos contained the ORF57-specific motif GAAGAGG (7merS) and CAGUCGCGAAGAGG (14merS), and two were non-specific CAGUCGC (7merN) and CAGUCGCAUAGUGCA . The saturation pulse train was tagged at the end of relaxation delay of 2.3 s, immediately prior to the first hard proton pulse. RNA peaks were selectively irradiated by centering the pulse train at 5.85, 5.75 or 12.00 ppm frequencies, with off-resonance irradiation at 21 ppm. Ratios of amide signal intensities in equivalent spectra, obtained with saturation at two different frequencies freq1 and freq2 (as indicated) were obtained. Residues were highlighted as close to RNA in space if the ratio of signal intensities Ifreq1/Ifreq2 differed significantly from unity (by more than three standard deviations (SD), calculated from the Ifreq1/Ifreq2 variability observed within non-interacting regions).IDIS-TROSY spectra 32P]-ATP using Polynucleotide Kinase (Fermentas). UV cross-linking with proteins was performed as previously described in vitro reconstitution assay, 10 or 100 µg ORF578–120 was incubated with 5 µg radiolabelled and cold RNA (7merS or 14merS) at room temperature for 10 minutes. The mixture was added to 20 µg of GST-tagged full length ALYREF (aa1–218) immobilized onto Glutathione-coated beads  in RB100 buffer. Beads were washed and complexes were eluted in native conditions  before being subjected to UV-irradiation or not. Proteins were resolved on 15% SDS-PAGE stained with Coomassie blue and analyzed by PhosphoImaging.RNA oligonucleotides were end-labelled with  NOE, are highlighted by solid and broken bars mark, respectively. Similarly, large and moderate changes in chemical shifts (δCS) of amide signals are shown as solid and broken bars, respectively. Red or orange bars mark residues forming direct inter-molecular NOE contacts in ALYREF-ORF57 or ICP27 complexes, respectively. The position of secondary structure elements  is shown. Data for ORF578–120 and ICP27103–138 marked with asterisks was previously released  and is included here for comparison.(EPS)Click here for additional data file.Figure S454–155 : ORF57103–120 complex.NOE-derived distance constraints used in the structure calculation of the ALYREF The position of short and medium range NOE connectivities are shown in (A) for ALYREF and (B) for ORF57. The sequences colored blue highlight tags introduced in cloning. (C) The distribution of all NOEs on a per residue basis. White, light grey, dark grey and black shading of bars indicates the number of meaningful intra-residue, sequential (i+1), medium (2≤i≤4) and long (5≤i) range constraints. Two samples were used for structure determination of the ORF57103–120: ALYREF54–155 complex, these contained one protein 13C,15N uniformly labeled at 1 mM plus the binding partner in unlabelled form at 3 mM. Over-titration of the labeled component was necessary to observe the signals otherwise broadened in the equimolar complex. (D) Intermolecular NOE restraints used in structure calculations are shown schematically between the individual residues of ALYREF and ORF57. Positions of two α-helices of ALYREF are marked. Each line corresponds to a non-redundant NOE restraint. Dark green continuous lines represent NOEs obtained unambiguously from 13C edited, 12C-filtered NOESY-HSQC spectra. Additional NOEs represented by light green dashed were obtained from more sensitive standard 3D 13C-resolved NOESY-HSQC spectra. (E) Example sections of 3D 13C edited, 12C-filtered NOESY-HSQC spectra showing intermolecular NOEs. Positive signals are colored green and negative red. ORF57 1H signal assignments are shown in blue and ALYREF 1H assignments shown as vertical orange dashed lines. The experiment selects NOE cross peaks between 1H(12C) of unlabelled ORF57103–120 and 1H-13C moieties of - ALYREF54–155, therefore providing exclusively inter-molecular restraints.(EPS)Click here for additional data file.Figure S51H-15N correlation spectra of ALYREF1–155 (i8–120  and ORF57ii) in different binding states illustrate that the presence of ALYREF partially shields ORF57 from binding specific RNA 14merS. Where indicated with arrows, the spectra of differentially-labeled proteins were acquired simultaneously in the same sample using IDIS-TROSY experiment. (A) TROSY spectra of proteins in free form (red) are overlaid with IDIS-TROSY of a 1∶1 complex (blue). The signals from residues at the protein-protein interface are exchange broadened, but signal shifts from other residues nearby are characteristic to complex formation. (B) An equimolar amount of HVS-specific RNA oligo 14merS was added to this ALYREF:ORF57 complex (grey), which induced signal changes mostly in ALYREF and to small extent in ORF57. (C) For comparison, addition of the same RNA oligo to ALYREF in the absence of ORF57 causes identifiable signal shifts on ALYREF, as revealed by comparison of HSQC spectra. Addition of the same RNA oligo to ORF57 in the absence of ALYREF causes very extensive peak broadening in the whole C-terminal half of ORF578–120. The examples of IDIS-TROSY spectra shown in (A) and (B) illustrate the ability to monitor in both proteins the individual signal changes caused by inter-protein complex formation, and further changes on both proteins caused by the addition of RNA.(EPS)Click here for additional data file.Figure S6The local ORF57-ALYREF interaction is stronger than the ORF57-RNA. Same type of experiments are presented as shown on 54–155 (i) , ORF578–120 (ii) and a shorter specific RNA 7merS. (A) TROSY spectra of protein in free form (red) are overlaid with IDIS-TROSY of a 1∶1 complex (blue); signals from residues at the protein-protein interface are exchange broadened, while movements of signals from residues close to the interface are characteristic to protein-protein complex formation. (B) An equimolar amount of HVS-specific RNA oligo 7merS was added to this complex (grey), which induced very limited signal changes in ALYREF and even less in ORF57. (C) For comparison, addition of the same RNA oligo to ORF57 in the absence of ALYREF causes very extensive peak broadening in the whole C-terminal half of ORF578–120.(EPS)Click here for additional data file.Figure S7Estimates of binding affinities using fluorescence. ORF578–120 (13 µM) was titrated with RNA oligos 14merS (A) and 7merN (B), and change in integral fluorescence emission intensity ΔI was monitored. The values of Kd shown were obtained using DynaFit software (BioKin Ltd) 8–120: ALYREF1–155, ) causes blue shift of fluorescence emission peak, as measured by a change in λbcm. The upper panel shows fluorescence spectra normalized by protein concentration, with concentration for each sample in µM units marked on the right. The bottom panel shows non-linear best-fit of Kd for ORF57-ALYREF binding is 2.56 µM. (D) Addition of specific RNA oligo to equimolar mixture of ORF578–120: ALYREF1–155 (OA) first further enhances blue shift of fluorescence which is consistent with the ternary complex formation, however overtitrating this complex with excess RNA (above 5-fold) causes fluorescence maximum shift in the opposite direction, consistent with dissociation of protein-protein complex formed earlier. The inset illustrates typical behavior of the fluorescence signal in response to addition of RNA to 2.5 µM protein-protein complex. Experimentally measured values for 10 and 2.5 µM complexes are represented with diamonds and triangles, respectively. The solid lines represent typical theoretical binding curves calculated using equilibrium models shown on (TIF)Click here for additional data file.


With continuing identification of novel structured noncoding RNAs, there is an increasing need to create schematic diagrams showing the consensus features of these molecules. RNA structural diagrams are typically made either with general-purpose drawing programs like Adobe Illustrator, or with automated or interactive programs specific to RNA. Unfortunately, the use of applications like Illustrator is extremely time consuming, while existing RNA-specific programs produce figures that are useful, but usually not of the same aesthetic quality as those produced at great cost in Illustrator. Additionally, most existing RNA-specific applications are designed for drawing single RNA molecules, not consensus diagrams.We created R2R, a computer program that facilitates the generation of aesthetic and readable drawings of RNA consensus diagrams in a fraction of the time required with general-purpose drawing programs. Since the inference of a consensus RNA structure typically requires a multiple-sequence alignment, the R2R user annotates the alignment with commands directing the layout and annotation of the RNA. R2R creates SVG or PDF output that can be imported into Adobe Illustrator, Inkscape or CorelDRAW. R2R can be used to create consensus sequence and secondary structure models for novel RNA structures or to revise models when new representatives for known RNA classes become available. Although R2R does not currently have a graphical user interface, it has proven useful in our efforts to create 100 schematic models of distinct noncoding RNA classes.http://breaker.research.yale.edu/R2R and as an Additional file.R2R makes it possible to obtain high-quality drawings of the consensus sequence and structural models of many diverse RNA structures with a more practical amount of effort. R2R software is available at  Numerous structured RNAs have been identified in the last decade that are involved in a variety of biological processes -3. ReseaSeveral programs have been created to draw individual RNA molecules, and thus inherently address many of the issues associated with drawing a consensus diagram. Some programs implement algorithms that automatically determine a feasible layout of the RNA molecule -11, and The goal of R2R is to facilitate the creation of RNA consensus diagrams by bioinformaticians that are comparable in quality to those produced using Adobe Illustrator, but take less time to create. Because consensus diagrams are generally derived from multiple-sequence alignments, R2R takes as input a multiple-sequence alignment in Stockholm format  with addR2R source code is freely available and is distributed with over 100 example input and output files in both PDF and SVG format . To shocrcB RNAs from Acidothermus cellulolyticus and Roseburia intestinalis that suggest a model for gene regulation. We also previously used R2R to display structural probing data obtained by in-line probing experiments on a SAM-IV riboswitch [Although the primary goal during the design of R2R was to produce software to assist in drawing consensus diagrams, R2R can also be used to draw the sequences and structures of individual representatives of a noncoding RNA class. For example, Figure boswitch .R2R facilitates the application of the following design principles for RNA secondary structure diagrams. Although little research has investigated practical benefits of different RNA drawing styles , the priThe principles are as follows. First, nucleotides or other symbols should not overlap. Second, nucleotides within bulges and loops should ideally be drawn along circles. Such a layout leads to symmetry  in the lConsensus diagrams merit annotation to highlight the extent of nucleotide conservation and to feature evidence supporting the proposed structure. This information, which is included in Figure Some annotations specific to consensus diagrams are automatically computed by R2R, using approaches described previously . R2R graR2R does not indicate other patterns of conservation. For example, the nucleotide immediately 5' to the hammerhead ribozyme cleavage site must be A, C or U , but thiR2R marks each predicted base pair to indicate covariation .r, the angle between nucleotides along the circle is calculated based on the isosceles triangle with sides r, r and d, where d is the fixed distance between consecutive nucleotides or between base-paired nucleotides. Suppose r* is the radius of a suitable circle for a given loop. If nucleotides are drawn with radius r <r*, the sum of angles will exceed 360 degrees, while r >r* will result in fewer than 360 degrees. R2R uses binary search to solve for r*. A similar approach was also developed for VARNA [By default, all nucleotides in a loop are positioned along a common circle. R2R keeps the distance between consecutive nucleotides strictly constant. Previous solutions to this problem assumed that distance between base-paired nucleotides is equal to the distance between consecutive nucleotides , but theor VARNA . For bulIn many RNA structures, it is desirable to arrange the nucleotides within a multistem junction on a circle, while constraining the stems on the junction to be oriented in specific directions , consisting of a non-linear objective function that is minimized subject to non-linear constraints. The NLP is solved by CFSQP . GradienR2R provides three different mathematical formulations to express the notion that the junction should approximate a circle. All methods use highly non-linear functions, and the optimizer can get stuck in local minima. Therefore, it is sometimes useful to try multiple formulations, although the second formulation usually produces an acceptable layout , the lengths of these regions are variables in the NLP, allowing some additional flexibility , and the distance da between c and the nucleotide adjacent to n , only one variable is used: the angle of the vector from one base-paired nucleotide to the adjacent one. For each junction of unpaired nucleotides between two stems, these nucleotides are drawn along a circle, but each junction's circle has its own independent center and radius , and also allows aligning the centroids of multiple nucleotides : Platform independent. Note: R2R is only tested using the GNU C++ Compiler.• Programming language: C/C++ and Perl.• Other requirements: CFSQP is needed for some methods of automated layout of multistem junctions. Other aspects of R2R will function with or without CFSQP. CFSQP is free for research and development purposes.• License: GNU General Public License.• Any restrictions to use by non-academics: None.• ZW created the software and drew consensus diagrams based on design principles initially articulated by RRB. ZW and RRB wrote the manuscript, and both authors read and approved its final version.Source code and example input and output files. C++ and Perl source code is provided. Installation and usage instructions are given in the user manual (Additional file Click here for fileR2R user manual. User manual explaining R2R installation and usage (also available within Additional file Click here for fileGeneric annotations for use in drawings, PDF format. This file contains a generic legend for R2R drawings and some annotations we frequently use, in PDF format. It can be imported into Adobe Illustrator or CorelDRAW.Click here for fileGeneric annotations for use in drawings, SVG format. The same content as Additional file Click here for file


However, current methods typically employ hybridization times on the order of 2–16 hours, limiting its potential in applications like rapid diagnostics. We present here a set of conditions for RNA FISH (dubbed Turbo RNA FISH) that allow us to make accurate measurements with no more than 5 minutes of hybridization time and 3 minutes of washing, and show that hybridization times can go as low as 30 seconds while still producing quantifiable images. We further show that rapid hybridization is compatible with our recently developed iceFISH and SNP FISH variants of RNA FISH that enable chromosome and single base discrimination, respectively. Our method is simple and cost effective, and has the potential to dramatically increase the throughput and realm of applicability of RNA FISH.Advances in RNA fluorescence  In its latest incarnation, it offers the ability to detect individual RNA molecules via fluorescence microscopy, in which each RNA molecule appears in the cell as a bright, diffraction limited spot RNA FISH does, however, suffer from some important drawbacks compared to other methods in its current incarnation. One is that it is typically a low-throughput method in the sense that, like RT-qPCR, one can usually only analyze around 5 or so genes at a time, although barcoding schemes can increase this number to many dozens and potentially hundreds We here describe a protocol that enables one to obtain quantifiable single molecule RNA FISH signals in under 5 minutes. We optimized both fixation conditions and hybridization conditions to achieve these results, showing there is a tradeoff between hybridization speed and probe concentration. We showed that these conditions apply across a variety of probes and cell types, and show that the technique is also compatible with our recently developed SNP FISH TBCB mRNA in The method we employ for RNA FISH involves the use of several 20-base long single-stranded DNA oligonucleotides, each individually labeled Traditionally, we have performed our hybridizations overnight in order to obtain strong signals. In order to perform rapid RNA FISH, we initially reasoned that one could speed the hybridization kinetics by increasing the concentration of probe included in the hybridization. Thus, we initially attempted to speed hybridization by simply increasing the amount of probe in our hybridization solution. We found, however, that despite increasing the concentration 20 fold, the signals were greatly diminished at hybridization times of 5 minutes . Our norWe then quantified the number of mRNA detected in all conditions using software similar in principle to that we have applied previously We then explored the degree to which there is a tradeoff between increasing the concentration of the probe and the hybridization time for rapid hybridization in methanol-fixed cells. In order to do so, we needed a means to assess and compare the quality of the signal in these various conditions. Ultimately, we settled on a metric based on the sensitivity of the threshold between signal and background . BrieflyWe here present data from A549 cells, a common cancer cell type that we have found overall to be more difficult to perform rapid hybridizations in (hence providing a stringent test of our method). We performed RNA FISH (targeting TOP2A mRNA) over a range of hybridization times from 30 seconds to 10 minutes and probe concentrations ranging from our conventional probe concentration to 100 fold greater (approximately 4.4 µM to 400 µM). Throughout, we compared also to our traditional overnight hybridization protocol . We founFor comparison, we also performed the same analysis by using the concentrations and wash protocol we used for our conventional overnight RNA FISH, except performing the hybridization for various amounts of time. We found that we obtained poorly quantifiable signals (as indicated by the sensitivity metric) once the hybridization time went below 2 hours, which is 24-fold as much time as our rapid hybridization assay .In our lab, we have recently developed two variants of single molecule RNA FISH: 1. a method based on targeting introns that reveals chromosome structure and transcriptional activity . However, we note that because of the decreased time for drying, our protocol uses roughly 10 fold less hybridization solution for the hybridization itself, greatly mitigating such concerns. We believe that the ultimate choice of how much probe to use and how fast to drive the reaction will depend on the specifics of the application at hand. In some cases, getting a hybridization time of 5–10 minutes may be perfectly fine, in which case one may not need to use large concentrations of probe. However, in some situations, such as during a surgical procedure, the decreased hybridization times may be a benefit that outweighs the cost of increased probe usage.Of course, even with rapid hybridizations, we have not addressed the issue of the imaging time itself. Typically, image acquisition may require taking image stacks from multiple positions on the slide to obtain enough cells’ worth of image data to make statistically significant claims about differences in gene expression. Currently, doing so could take on the order of 10–20 minutes per condition. However, we believe that technical advances can reduce the time required for both image acquisition and analysis by at least an order of magnitude. In such a case, one could envision comparing gene expression in two samples in well under 30 minutes from living cells to quantified data.It may be useful here to make a comparison to other methods such as RT-qPCR. RT-qPCR is the current gold standard for gene expression analysis, widely considered to be the most accurate method for quantifying gene expression to date. It has many benefits, including high dynamic range, low cost per reaction, and the ability to parallelize in 96-well plate format. The qPCR itself usually takes on the order of 1–2 hours to complete, but if one includes both RNA extraction and setup time, the total time required is probably closer to around 3–4 hours.  We believe that with rapid hybridization, RNA FISH competes favorably with RT-qPCR on most counts. With respect to quantification, our method provides accurate, absolute counts of gene expression of 3 to 5 genes in individual cells without the explicit need for normalization. Since RNA FISH is a direct detection scheme without any amplification, we are able to detect even small fold-changes with high precision, differences that would be hard to measure accurately with RT-qPCR, at least not without a large number of replicates. The cost per reaction is probably dominated by the cost of the probe, which is currently around $300–$600 per probe set for 10,000 hybridizations ($0.06 per reaction) and is thus comparable to a molecular beacon or Taq-man RT-qPCR probe. Of course, costs of labor, equipment and other reagents are variables that are hard to predict, but will be of the same order of magnitude, although we note that the labor required for RNA FISH is probably lower, whereas the cost of an automated microscope is admittedly higher than most qPCR machines. Both the accuracy and cost comparisons to RT-qPCR were valid even with overnight RNA FISH.The time required for previous iterations of RNA FISH, however, was considerably longer than for RT-qPCR, and our new method alleviates that discrepancy. If one is just comparing the expression of a few genes in a few conditions, then we believe our method is unequivocally several times faster than RT-qPCR, especially when one factors in RNA extraction and setup time. For analyzing larger numbers of genes in parallel, though, the imaging time will become a factor. If one assumes 5–10 minutes per condition and triplex RNA detection, then analyzing, say, 20–30 genes could require up to 2 hours. With advances in high throughput imaging, we anticipate that one could reduce this time by an order of magnitude, thus further increasing the speed advantages.Another major advantage of RNA FISH is that it also provides single cell information, something that is much more difficult to obtain with single cell RT-qPCR approaches. This enables one to measure variability in gene expression from cell to cell. Since the measurements yield absolute numbers of RNA, the measurements do not necessarily require normalization to an internal control (such as GAPDH), although one could perform such an analysis if one wished through multiplexing. Normalization can be difficult to perform with RT-qPCR approaches, since one typically uses all the material for a single qPCR reaction, leaving none for further normalization.Furthermore, RNA FISH also provides spatial information on the localization of RNA. Such information is important both for examining differences from cell to cell within a tissue and even subcellular spatial localization. In tissues, one can easily identify particular cells by labeled RNA specific to those cells with one color and then looking at the gene of interest in another color. Subcellular information can be of particular importance for RNA that localize to particular regions of the cell, such as many non-coding RNA, in which case RNA FISH can reveal much about its behavior.We have also shown that one can perform iceFISH and SNP FISH to visualize chromosomes and single base changes, respectively, with rapid hybridization. Such techniques could be useful for rapidly diagnosing chromosomal abnormalities and for rapid genotyping of particular single nucleotide variants.In summary, our method for rapid hybridization results in orders of magnitude improvements in hybridization time for single molecule RNA FISH, enabling a new set of high throughput and rapid diagnostic applications.2, and penicillin/streptomyocin.We cultured A549 cells (ATCC CCL-185), HeLa cells We fixed cells for 10 minutes in 4% formaldehyde/10% formalin in 1X phosphate buffered saline solution at room temperature. Following fixation, we washed cells twice with 1X phosphate buffer solution and then permeabilized the cells with 70% ethanol and stored them at 4°C for at least overnight.We fixed cells in pre-chilled ethanol or methanol (−20°C) for 10 minutes. Following fixation, we proceeded immediately to RNA FISH or Turbo RNA FISH.To perform RNA FISH, we followed the protocol in Raj et al. Nat Meth 2008 For Turbo RNA FISH, we removed the alcohol from previously fixed samples and performed hybridization with 5 uL of hybridization buffer containing 71 µM TOP2A probe and 98 µM TBCB probe (unless otherwise specified), 10% formamide, 2X SSC, and 10% dextran sulfate (w/v). We hybridized the samples for 5 minutes (unless otherwise specified) on a covered hot plate at 37°C. Following hybridization, we washed the samples three times for one minute at 37°C with prewarmed wash buffer. We then imaged the samples in 2X SSC.For Turbo iceFISH, we followed the protocol of Levesque and Raj Nat Meth 2013 For Turbo SNP FISH, we followed the protocol of Levesque et al. Nat Meth 2013 We imaged all samples on a Nikon Ti-E inverted fluorescence microscope using a 100X Plan-Apo objective  and a cooled CCD camera (Andor iKon 934). We sequentially acquired three-dimensional stacks of fluorescence images in four different fluorescence channels using filter sets for DAPI, Cy3, Alexa 594, and Atto 647 N. Our exposure times ranged from 2–3 s for most of the dyes except for DAPI, for which we used ∼50 ms exposures. The spacing between consecutive planes in our stacks was 0.3 µm.The filter sets we used were 31000v2 (Chroma), 41028 (Chroma), SP102v1 (Chroma), a custom set from Omega as described previously After imaging, we then put our data through an image analysis pipeline for semi-automated spot recognition. We implemented the analysis pipeline in MATLAB. Briefly, our method for analysis involves running the images through a linear filter designed to enhance spots around the size of those we observe, then finding all regional maxima within the filtered image, and then counting the number of regional maxima below a variety of thresholds


Enterovirus genus of the Picornaviridae family and it is a major etiological agent of hand, foot, and mouth disease (HFMD), which is a common illness affecting children. CVA16 possesses a single-stranded positive-sense RNA genome containing approximately 7410 bases. Current understanding of the replication, structure and virulence determinants of CVA16 is very limited, partly due to difficulties in directly manipulating its RNA genome.Coxsackievirus A16 (CVA16) is a member of the via a native XbaI site to yield a full-length cDNA. A T7 promoter and poly(A) tail were added to the 5' and 3' ends, respectively, forming a full CVA16 cDNA clone. Transfection of RD cells in vitro with RNA transcribed directly from the cDNA clone allowed the recovery of infectious virus in culture. The CVA16 virus recovered from these cultures was functionally and genetically identical to its parent strain.Two overlapping cDNA fragments were amplified by RT-PCR from the genome of the shzh05-1 strain of CVA16, encompassing the nucleotide regions 1-4392 and 4381-7410, respectively. These two fragments were then joined We report the first construction and characterization of an infectious cDNA clone of CVA16. The availability of this infectious clone will greatly enhance future virological investigations and vaccine development for CVA16. Coxsackievirus A16 (CVA16) and enterovirus 71 (EV71) are major etiological agents of hand, foot, and mouth disease (HFMD), which is a common illness in children ,5-8. TheEnterovirus genus of the Picornaviridae family and they possess a single-stranded positive-sense RNA genome containing approximately 7400 bases. The CVA16 genome can be divided into 5'-non-coding, protein coding, and 3'-non-coding regions [Both CVA16 and EV71 are members of the  regions . The 5'- regions . Recent  regions . HoweverFor many RNA viruses, cDNA clones of the entire viral genome can serve as a template for the generation of infectious RNA. These infectious cDNA clones provide a platform for the manipulation of viral genomes and they provide a valuable tool for studying the molecular biology of virus replication, virus structure, virulence determinants, and vaccine development. Infectious cDNA clones have been successfully developed for a number of enteroviruses, including poliovirus , coxsackEU262658) is an RNA molecule containing 7410 nucleotides. Viral RNA was extracted and subjected to reverse transcription using oligo(dT) primers. Two overlapping cDNA fragments were amplified from the first strand cDNA, encompassing nucleotides 1-4392 and 4381-7410 of the CVA16 genome, designated as CV(1-4392) and CV(4381-7410), respectively . CV(6087-7410-pA), which contains nucleotides 6087-7410 and a poly(A) tail, was also amplified . All three mutations resulted in amino acid changes. The entire cDNA cloning process was repeated, starting from RNA isolation from the same batch of virus. Three clones from two independent cloning events were fully sequenced and the identical mutations were found in all three clones. Thus, these three mutations were not introduced during the cloning process. Instead, they were likely to have been acquired during multiple passage of the virus in cell culture since the original report [The genome of the CVA16 strain shzh05-1  by PCR amplification with primers P6 and P7  of RNA transfected cells were observed as an indicator of productive virus infection. As shown in Figure Recovered CVA16 was characterized by immunofluorescence. As shown in Figure The capsid composition of the R1 virus was analyzed by western blotting using the same polyclonal antibodies against VP0, VP1 and VP3 of CVA16. As shown in Figure The biological characteristics of the wild-type and recovered viruses were also compared. The R1 virus was found to generate the same negative-strand viral RNA as the wild-type virus, as demonstrated by the amplification of a ~0.9 Kb RT-PCR product from the R1 virus (data not shown) and the wild-type virus-infected cells Figure . R1 viruXbaI site, to yield CV(1-7410). The first strategy is successful for the construction of infectious clones of a number of enteroviruses [The aim of this study was to construct an infectious clone of CVA16. The genome of CVA16 is an RNA molecule measuring 7410 bases in length. In our study, viral RNA was reverse transcribed to yield first-strand cDNA, which was then used subsequently as a template for the PCR amplification of CVA16-specific fragments. Two strategies were adopted to obtain a full-length cDNA clone of CVA16. The first was to directly amplify the full-length CV(1-7410) from the reversely transcribed cDNA, while the other was to amplify two fragments, i.e., CV(1-4392) and CV(4381-7410), and subsequently rejoin them via an oviruses ,24,29, ioviruses , but it In vitro generated RNA transcripts were transfected into RD cells via electroporation to regenerate CVA16. The data demonstrates that these RNA transcripts were capable of directing viral protein expression and processing  supplemented with 10% FBS, 100 U/ml penicillin, and 100 μg/ml streptomycin at 37°C with 5% COribed in , was proribed in .RNA was extracted from CVA16/shzh05-1 infected RD cells using Trizol reagent . The extracted RNA was reverse transcribed using oligo(dT) primers and M-MLV reverse transcriptase to produce cDNA , according to the manufacturer's instructions. The resultant first strand cDNA was used as a template for subsequent PCR amplification of CVA16 genome fragments.EU262658) , and it contained engineered XbaI and NotI restriction enzyme sites. Primers P5 and P6 were designed to amplify a cDNA fragment encompassing nucleotides 6087-7410 with an added poly(A) tail, which was designated CV(6087-7410-pA). Primer P7 contained a HindIII site, a T7 promoter sequence, and 20 nucleotides of the 5' UTR of CVA16 cDNA. It was used to introduce the T7 promoter upstream of the full-length cDNA for efficient in vitro transcription and to prime the synthesis of first strand cDNA from negative-strand viral RNA. Primer P8 anchored to the nucleotides 2447-2470 of positive-sense CVA16 full-length cDNA while P9 was complementary to the nucleotides 3304-3328 of positive-sense cDNA. Both P8 and P9 were used to detect negative-strand RNA by RT-PCR amplification of a ~0.9 KB fragment (nucleotides 2447-3328).Primers were designed based on the published sequence of CVA16 strain shzh05-1 . CV(6087-7410-pA) was digested with XhoI/NotI and then used to replace the corresponding sequence within pcDNA3.1-CV(1-7410), resulting in pcDNA3.1-CV(1-7410-pA). The primer pair P6/P7 (Table in vitro transcription. The resultant PCR product containing an engineered T7 promoter sequence upstream of the CV(1-7410-pA) was cloned into the pMD19-T Simple vector , yielding pMD19-CV.CV1-4392) was amplified from the reverse transcribed first strand cDNA using primers P1 and P2 , according to the manufacturer's instructions.PMD19-CV was digested with 6 cells) of the cell suspension was mixed with 10 μg of in vitro synthesized RNA transcripts. These mixtures were incubated for 3 min at room temperature, transferred into an electroporation cuvette, and then subjected to electroporation at 220 V using the GenePulser Xcell™ electroporation system . Immediately after electroporation, the mixtures were resuspended in 5 ml of DMEM supplemented with 10% FBS, transferred to a T25 flask, and incubated at 37°C with 5% CO2 for 72 h.RD cells were grown in T75 flasks to 90% confluency, harvested by centrifugation, then resuspended in OPTI-MEM medium . Next, 400 μL  agarose  was added to each well, before incubating at 37°C. The medium was discarded after several days and cells were fixed in 10% formaldehyde solution then stained with 0.1% crystal violet .CVA16: Coxsackievirus A16; HFMD: Hand, Foot, and Mouth Disease; EV71: Enterovirus 71; CPE: CytoPathic Effect; DMEM: Dulbecco's Modified Eagle's mediumThe authors declare that they have no competing interests.FL, QL and YC performed the experiments. ZH conceived the study and wrote the manuscript. QL participated in the study design and data analyses. All authors read and approved the final manuscript.We thank Drs Bing Sun and Qi Jin for providing the CVA16 virus. We also thank Dr. Andy Tsun and the International Science Editing for their excellent editorial contribution. This work was supported by a grant (#KSCX2-YW-BR-2) from the Chinese Academy of Sciences "100 Talents" program and a grant (#2010KF-07) from the Biochemical Engineering National Key Laboratory of China. Z.H. gratefully acknowledges the support of SA-SIBS scholarship program.


There was an error in the first affiliation. The correct affiliation is:"Department of Gynecology and Obstetrics, Ren Ji Hospital, School of medicine, Shanghai Jiao Tong University, Shanghai, P.R. China"