Ribosomal RNA modifications are important in optimizing ribosome function. Sugar 2′-O-methylation performed by fibrillarin-associated box C/D antisense guide snoRNAs impacts all steps of translation, playing a role in disease etiology (cancer). As it renders adjacent phosphodiester bonds resistant to alkaline treatment, 2′-O-methylation can be monitored qualitatively and quantitatively by applying next-generation sequencing to fragments of randomly cleaved RNA. We remapped all sites of 2′-O-methylation in human rRNAs in two isogenic diploid cell lines, one producing and one not producing the antitumor protein p53. We identified sites naturally modified only partially  and sites whose 2′-O-methylation is sensitive to p53. We mapped sites particularly vulnerable to a reduced level of the methyltransferase fibrillarin. The remarkable fact that these are largely sites of natural hypomodification provides initial insights into the mechanism of partial RNA modification. Sites where methylation appeared vulnerable lie peripherally on the 3-D structure of the ribosomal subunits, whereas the numerous modifications present at the core of the subunits, where the functional centers lie, appeared robustly made. We suggest that vulnerable sites of 2′-O-methylation are highly likely to undergo specific regulation during normal and pathological processes. Ribosomal RNA is extensively modified by base isomerization and by covalent addition of chemical groups to nucleotides2. RNA modifications extend the topological repertoire of RNAs, stabilizing rRNA structural elements at the core of the ribosomal subunits3. Covalent modifications include ribose and base methylation, base acetylation, and base aminocarboxypropylation4. Base isomerization consists in the conversion of uridines into pseudouridines. With around fifty of each on yeast ribosomes and 100 of each on human ribosomes, 2′-O-methylations and pseudouridines are by far the most abundant rRNA modifications2.Ribosomes are essential nanomachines which, in all living cells, convert the information encoded in messenger RNAs into proteins. At the functional core of the ribosome is ribosomal RNA (rRNA), a ribozyme catalyzing the critical steps of decoding and amino acid polymerization5. Ribosomopathies are cancer predisposition syndromes caused by ribosome biogenesis dysfunction resulting from a mutation in either a ribosome assembly factor or a ribosomal protein6. There are ribosomes in every cell of our body, but the effects of reduced ribosome production or altered ribosome quality depend on the tissue and cell type7. Understanding how this cell/tissue specificity originates is a major challenge in the field. There is increasing evidence that cells produce heterogeneous populations of ribosomes that may differ in composition and translational capacity8. Specialized ribosomes may play important roles in normal processes such as embryonic development and in diseases such as cancer10. The best demonstration of the coexistence of distinct ribosomes in cells is partial modification, i.e. modification at specific positions on some but not all ribosomes , reading frame maintenance, and stop codon recognitionRecently, deep-sequencing-based strategies have been developed to map RNA modifications at the transcriptome-wide level. These strategies rely on the ability of RNA modifications to be detected by antibodies, to promote specific reverse transcriptase ‘drop off’, to confer specific resistance to RNase digestion, or to induce specific cleavage of the RNA chain when subjected to particular chemical treatments  and one that does not (HCT116 p53 −/−)15. Altogether, our RiboMethSeq analysis identified 106 positions on mature rRNAs: 39 sites on 18S rRNA, 65 sites on 28S rRNA, and 2 sites on 5.8S rRNA  by unassembled ribosomal components see refs  and 40. 35. Expecting this to be important in interpreting the results of systematic 2′-O-methylation site mapping after fibrillarin depletion (see below), we examined the extent and kinetics of the impact of fibrillarin depletion on the formation of mature rRNAs in the cell lines used here.Fibrillarin homologs in budding yeast  and other eukaryotes, including in HeLa cells, have been shown to be important for ribosome biogenesis, and in particular for the initial pre-rRNA processing steps leading to synthesis of the small-ribosomal-subunit rRNA (18S rRNA)Total RNA was extracted at different time points during fibrillarin depletion  from both HCT116 p53 +/+ and HCT116 p53 −/− and resolved by denaturing agarose gel electrophoresis. The large mature rRNAs (18S and 28S) were visualized by ethidium bromide staining Fig. . This reTo gain precise information on the inhibited step(s) of ribosome biogenesis, pre-rRNA processing was analyzed in detail by high-resolution quantitative northern blotting. Specific probes were used to detect all the major known pre-rRNA intermediates  involves extensive processing of long primary transcripts (47S pre-rRNA) synthesized by RNA polymerase I. In the primary transcripts, the sequences of the mature rRNAs are interspersed with the 5′ and 3′ external transcribed spacers (5′ and 3′ ETS) and the internal transcribed spacers 1 and 2 (ITS1 and 2) . All of the modified positions described above were identified, a methylation score was computed for each, and the methylation scores were clustered with the dedicated software package ‘R’ Fig.  and 4. AAt this point we can see how important it was to establish precisely the levels of the various pre-rRNA intermediates over the time course of fibrillarin depletion: it appears that the reduced methylation observed at specific sites cannot be explained solely by reduced production of the precursors harboring them. Most of the positions where methylation appeared particularly sensitive to fibrillarin depletion  were grouped in six categories . We predict that in cells, these snoRNAs compete particularly efficiently for fibrillarin binding during snoRNP assembly.Lastly, we mapped the sites of methylation vulnerability identified in this work to 3-D models of ribosomal subunits, using a specific color code for sites of putative hypomodification, sites sensitive to p53, and sites particularly sensitive to fibrillarin depletion Fig. . Sites o9. This makes it important both to establish the complete repertoire of ribosomal RNA modifications and to identify positions likely to be modified on only a subset of ribosomes, as modification is liable to undergo considerable regulation at these sites.Ribosomal RNA modifications have been shown in multiple cases to optimize ribosome function . The cell lines used in this work were obtained directly from ATCC and passaged in the laboratory for fewer than 6 months after receipt. All cell lines were diagnosed by ATCC by short tandem repeat (STR) profiling. In HCT116 p53 −/−, the endogenous alleles of p53 were disrupted sequentially by homologous recombination37.Human cells (HCT116 p53 +/+ and HCT116 p53 −/−) were grown at 37 °C under 5% COThe total number of viable cells and the percentage of viable cells in each sample analyzed were established with a Muse® cell analyser (Merck-Millipore) and the Cell Count and Viability Reagent (REF MCH100102), according to the manufacturers’ instructions.5 cells (for 72 hours), 3 × 105 (for 48 h) 6 × 105 (for 24 h) resuspended in 2.5 ml antibiotic-free medium were seeded into each well. Inactivation was carried out for 24, 48, and 72 hours. The silencers used are listed in Supplementary Table HCT116+/+ and HCT116−/− cells were reverse transfected as follows: 1.5 µl of 20 µM DsiRNA (Integrated DNA Technologies) or 20 µM siRNA (Life Technologies) and 4 µl Lipofectamine RNAiMAX (Life Technologies) were mixed with 500 µl Opti-MEM (Life Technologies) in each well of a 6-well plate. After a 20-min incubation at room temperature, 1.5 × 1046. The NGS-based method of 2′-O-methylation detection was as described for yeast in ref. Total RNA was extracted as previously described6 HCT116 cells. Cells were washed once with ice-cold 1x phosphate buffered saline (PBS) and lysed in lysis buffer  plus protease inhibitors  for 20 min on ice. Lysates were cleared by centrifugation at 20,000 g and 4 °C for 20 min. Protein concentrations were estimated by the Bradford protein assay (Biorad). 30 µg total human protein extract was loaded on a 12% SDS PAGE gel and transferred to a PVDF membrane . Antibodies against the following proteins were used at the indicated dilutions: fibrillarin ; p53 . The secondary antibody used was either a horseradish-peroxidase-conjugated anti-mouse IgG  or a horseradish-peroxidase-conjugated anti-rabbit IgG . Probed membranes were incubated for 10 min with the Super Signal West Pico Chemiluminescent Substrate (Pierce), and the luminescence signal was acquired and processed with a ChemiDoc MP (Bio-Rad).Total protein was extracted from ∼1 × 1046. The membranes were hybridized with 32P-labelled oligonucleotides and the signals acquired with a Phosphorimager .Total RNA was extracted from HCT116+/+ and HCT116−/− cells in Tri-reagent solution (Life Technologies) according to the manufacturer’s recommendations, except that the RNA pellets were washed with absolute ethanol and then with 75% v/v ethanol. The concentration and quality of the RNA were assessed with a Nano Drop 1000 spectrophotometer (Thermo Scientific). RNA electrophoresis on denaturing agarose gels and northern blotting were conducted as described previouslyThe RiboMethSeq reads were aligned to the reference rDNA sequence NR_046235. Clustering of methylation scores and snoRNA levels was performed with “R” with hclust function using Euclidean distances. To perform statistical analysis of snoRNA abundances after fibrillarin depletion, we used DESeq. 2.Supplementary InformationSupplementary Dataset Number 1


Penicillium digitatum. In this study, 41 over-expressed and 84 repressed proteins in P. digitatum after 1.0 μL/mL of citral exposure for 30 min were identified by the iTRAQ technique. The proteins were closely related with oxidative phosphorylation, the TCA cycle and RNA transport. The mitochondrial complex I, complex II, complex III, complex IV and complex V, which are involved in oxidative phosphorylation were drastically affected. Among of them, the activities of mitochondrial complex I and complex IV were apparently suppressed, whereas those of mitochondrial complex II, complex III and complex V were significantly induced. Meanwhile, citral apparently triggered a reduction in the intracellular ATP, the mitochondrial membrane potential (MMP) and glutathione content, in contrast to an increase in the glutathione S-transferase activity and the accumulation of reactive oxygen species (ROS). Addition of exogenous cysteine decreased the antifungal activity. In addition, cysteine maintained the basal ROS level, deferred the decrease of MMP and the membrane damage. These results indicate that citral inhibited the growth of P. digitatum by damaging oxidative phosphorylation and cell membranes through the massive accumulation of ROS.Citral exhibits strong antifungal activity against  Penicillium digitatum is a damaging disease in citrus fruits  of 2.0 μL/mL and a minimum antifungal concentration (MFC) of 4.0 μL/mL, and the wax + citral (10 × MFC) treatment significantly decreased the incidence of green mold in Ponkan mandarin fruit after 6 days of storage at 25 ± 2°C, but did not influence the external and internal fruit qualities of citrus fruit  is mixture of two isomers, namely, geranial and neral, and is extracted from several lemon-scented herbal plants, most notably lemons, verbena, and lemongrass. Because of its particular aroma, substantial antibacterial, antifungal and insecticidal effects, as well as its low toxicity and low carcinogenicity, citral is classified as a substance that is “Generally Recognized as Safe” (GRAS) and has been widely used as a food additive and fragrance material in cosmetics. In recent years, citral has been illustrated to exhibit strong antifungal activities against Trichophyton mentagrophytes were irreversibly damaged by 0.2 mg/ml citral. Rajput and Karuppayil  in P. digitatum upon exposure to citral by iTRAQ, in an effort to elucidate the antifungal mechanism of citral on P. digitatum.It is well known that proteins serve an indispensable role in mediating the adaptability of pathogens to different stresses  were added to the 40-mL potato dextrose broth (PDB) and incubated in a moist chamber at 25 ± 2°C. The mycelia of P. digitatum grown for 48 h were collected and re-suspended in phosphate buffered saline (pH 7.0). The suspensions were then treated with 1/2MIC (1.0 μL/mL) of citral and incubated at 25 ± 2°C under agitation in an environmental incubator shaker for 30 min  to a concentration of 0.5 μg/μL, 5 μL samples were analyzed on an LC-20AD nano-LC-ESI-MS/MS system , and data acquisition was performed with a TripleTOF 5600 System  fitted with a Nanospray III source  and a pulled quartz tip as the emitter   was permitted for intact peptide masses and 0.1 Da for fragmented ions, allowing for one missed cleavage in the trypsin digests. Gln- > pyro-Glu (N-term Q), oxidation (M), deamidated (NQ) were treated as potential variable modifications, and carbamidomethyl (C), iTRAQ8plex (N-term), iTRAQ8plex (K) as fixed modifications. The charge states of the peptides were set to +2 and +3. Specifically, an automatic decoy database search was performed in Mascot by choosing the decoy checkbox in which a random sequence database is generated and tested for raw spectra as well as the real database. To reduce the probability of false peptide identification, only peptides with significance scores (≥20) at the 99% confidence interval by a Mascot probability analysis greater than the “identity” were counted as identified. Each confident protein identification involves at least one unique peptide.p < 0.05, and only fold changes of > 1.5 were considered significant.For protein quantization, it was required that a protein contains at least two unique peptides. The quantitative protein ratios were weighted and normalized by the median ratio in Mascot. We only used ratios with http://www.genome.jp/kegg/) and the COG database (http://www.ncbi.nlm.nih.gov/COG/) were used to classify and group these identified proteins, and then, the proteins were assigned to 108 known biological pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (www.genome.jp/kegg/).Functional annotations of the proteins was conducted using the Blast2GO program against the non-redundant protein database . The KEGG database , Shanghai, China] using the commercially available kits  following the manufacturer's instructions. Three independent replicates were performed for each treatment.The enzymatic activities of the mitochondrial complex I, complex II, complex III, complex IV, and complex V of the P. digitatum cells with or without 1/2MIC of citral for 0, 30, 60, and 120 min were determined by a UV2450 UV/Vis spectrophotometer using a commercially available kit  following the manufacturer's instructions. Three independent replicates were performed for each treatment.The GST activities and GSH contents of P. digitatum cells treated with 1/2MIC of citral or not were determined according to our previous method . The treated cells were stained with JC-10 and analyzed with an ECLIPSE TS100 microscope . The fluorescence values were measured by a F97 PRO fluorescence spectrophotometer . Three replications for each treatment were performed. These experiments were also performed in samples supplied with antioxidant cysteine (Cys) at a concentration of 10 μM.P. digitatum cells treated with citral at 1/2MIC or not for 0, 30, 60, and 120 min were determined by a redox-sensitive fluorescent probe dichloro-dihydro-fluorescein diacetate (DCFH-DA), according to the ROS assay kit  instructions. The fluorescence values were measured by a F97 PRO fluorescence spectrophotometer . Three independent replicates were performed for each treatment. The mycelia were observed with an ECLIPSE TS100 microscope . These experiments were also conducted in samples supplied with the antioxidant Cys at a concentration of 10 μM.The ROS levels in P. digitatum cultures supplied citral at the concentrations 0.0 μL/mL, 1.0 μL/mL (1/2MIC), and 2.0 μL/mL (MIC). The antifungal activity was measured by the agar dilution method  were analyzed by propidium iodide (PI) staining coupled with fluorescence microscopy .All data were expressed as the mean ± SD (standard deviation) by measuring three independent replicates and analyzed by one-way analysis of variance (ANOVA) followed by Duncan's multiple range test. A value of Based on the iTRAQ-labeled peptides, a total of 3,251 proteins were isolated or identified. These proteins were further categorized into three GO ontologies, including biological processes, cellular components, and molecular functions. The most favored biological process was the “metabolic process” (29.34%), mainly consisting of the “cellular process” (27.35%) and “single-organism process” (10.70%) subcategories. A greater number of proteins were assigned to the cellular component category. The largest subclasses of proteins within this group were “cell” (24.69%) and “cell part” (24.69%). Categorization of the identified proteins on the basis of molecular function indicated that the most abundant proteins belonged to “catalytic activity” (47.28%) and “binding” classes (41.09%) Table .These proteins were further classified into 24 COG functional subcategories Table . Most ofThe difference in the protein expressions between CK30 and T30 was further analyzed. As a result, 125 proteins, including 41 up-regulated and 84 down-regulated proteins, were identified as DEPs. Among them, 82 DEPs were mapped to the KEGG database and assigned to 42 specific pathways, such as oxidative phosphorylation, endocytosis, ribosome, spliceosome, RNA degradation, ribosome biogenesis in eukaryotes, peroxisome, MAPK signaling pathway, glutathione metabolism, and cell cycle Table .Nineteen proteins related with the ribosome, RNA degradation, ribosome biogenesis in eukaryotes, spliceosome, basal transcription factors, RNA transport and mRNA surveillance pathway were affected by citral Table , S6. IntThe expression pattern of the proteins related to energy and reactive oxygen species (ROS) were greatly influenced by the addition of citral Table , S6. AppP < 0.05; Figure P. digitatum cells treated with 1/2MIC of citral was notably increased to 27.4 ± 1.8 U/g and no obvious difference between the treated and untreated cells was observed. The mitochondrial complex II and complex V activities in the citral treated samples were quite different from those of mitochondrial complex I. The mitochondrial complex II and complex V activities increased to peak values  at 60 and 30 min of exposure, respectively, which were significantly higher than the control . At 120 min, mitochondrial complex II and complex V activities in 1/2MIC of citral treated groups dropped to 29.9 ± 2.8 U/g and 19.3 ± 0.4 U/g, respectively, which were still higher than the control sample . In the case of the mitochondrial complex III, no difference in the activities between the 1/2MIC-treated samples and the control samples was observed before 60 min of exposure. After 120 min of exposure, the mitochondrial complex III activity in the control groups remained at a comparable level with the initial exposure, whereas its activity in 1/2MIC citral treated samples was induced and reached 261.0 ± 3.1 U/g. The mitochondrial complex IV activity was impaired by the addition of citral. Compared with the control samples, the mitochondrial complex IV activities in the 1/2MIC citral-treated samples decreased from 47.8 to 84.0% during citral exposure.The enzymatic activities of the mitochondrial respiration complexes were found to be consistent with those of the iTRAQ analysis. The mitochondrial complex I activity in the control samples remained relatively stable during the entire period. In contrast, the mitochondrial complex I activity in the samples treated with 1/2MIC of citral was sharply decreased at 60 min of exposure, with the values reaching 18.3 ± 0.0 U/g, which was significantly lower than that of the control sample . However, the activity of GST in P. digitatum cells with 1/2MIC of citral was suddenly decreased over the remaining period and remained at a lower level compared to that of the control samples (P < 0.05).The activity of GST was induced by the addition of citral during the initial 30 min Figure . At 30 mP. digitatum was significantly decreased (P < 0.05) from 12.3 ± 1.2 μmol/g at the initial exposure to 3.2 ± 0.4 μmol/g at 30 min of exposure, which was significantly lower than that in the control samples. After 30 min of exposure, the GSH contents in the 1/2MIC-treated P. digitatum cells maintained a relatively low level throughout the whole period.The GSH content in the control samples was significantly higher than those of the citral treated samples Figure . In contP. digitatum cells treated with citral continuously decreased during the entire period, whereas those in the untreated cells remained stable .Citral exhibited an opposite effect on the extracellular ATP content Figure . After 3P < 0.05). In untreated cells, the red/green fluorescence ratio was 0.534 ± 0.011 at 30 min. However, the addition of citral caused an immediate loss of MMP, blocking JC-10 entry to the mitochondria, leaving the JC-10 monomers to fluoresce green within the cytoplasm. This finding was reflected in the red/green fluorescence ratio, which decreased to 0.214 ± 0.019 following citral treatment for 30 min and was significantly lower than that of the control sample (P < 0.05). Moreover, the addition of cysteine (Cys) could delay the reduction of MMP to a certain degree, with a red/green fluorescence ratio of 0.270 ± 0.017 at 30 min, which was significantly higher (P < 0.05) than that in the citral treatment . After 120 min of exposure, the ROS levels in the P. digitatum mycelia treated with 1/2MIC of citral were 3.55-fold higher than that of the control  by the addition of Cys. These results were consistent with the results of the fluorescence microscopy . Before treatment with 1/2MIC of citral + Cys for 30 min, hyphae exhibited relatively slight red fluorescence, indicating that the exposure to citral + Cys induced the permeation of PI in fewer cells  staining intensity than that of the control group  (Chaban et al., P. digitatum hyphae (Zheng et al., Mitochondrial oxidative phosphorylation constitutes the major cellular ATP-producing mechanism under aerobic conditions and hence plays an important role in maintaining the ATP levels in the cell. The function of oxidative phosphorylation is to synthesize ATP by generating a proton gradient within the inner mitochondrial membrane. Blocking or restraining oxidative phosphorylation can effectively decrease the ATP concentrations in the cell (Wang et al., Curcuma longa oil and thymol, were positively related with the accumulation of ROS (Tian et al., 2O2 in P. digitatum and lead to lipid peroxidation via oxidation burst (OuYang et al., In fact, the mitochondrial respiratory chain is a major source of ROS (Tian et al., P. digitatum (OuYang et al., P < 0.05; Figure P < 0.05; Figure P. digitatum hyphae.Normally, the balance between ROS production and antioxidant defenses determines the degree of oxidative stress. Our previous study found that the addition of citral resulted in oxidative stress by stimulating the activities of lipoxygenase and peroxidase in It is generally accepted that the accumulation of ROS will result in the breakdown of the normal cellular, membrane and reproductive functions by oxidizing lipids, proteins, nucleic acids, and carbohydrates (Qin et al., S. cerevisiae. To further confirm the oxidative damage of P. digitatum hyphae, Cys was added to the culture media. Cys is the rate-limiting precursor for the synthesis of GSH and is also the preeminent antioxidant of the cell (Tian et al., P. digitatum. In addition, Cys maintained the basal ROS level (Figure P. digitatum.Application of exogenous antioxidants could maintain ROS at the basal level and repair cellular damage caused by ROS (Lai et al., l Figure , and defl Figure  and the l Figure . These rP. digitatum is caused by damaged oxidative phosphorylation through massive ROS accumulation. These findings not only provide a better understanding of antifungal mechanism of plant essential oils but also provide important theoretical guidance for the development of novel fungicides, reducing the postharvest decay of fruits in the future.Taken together, our present study suggests that the antifungal activity of citral against NT designed research; QO performed research; NT and QO analyzed data; QO, NT and MZ wrote the paper. All authors contributed to study design and provided input on the manuscript preparation. All authors have given approval to the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


E. coli where FRET is observed, demonstrating that the apta-FRET system is genetically encodable and that the RNA nanostructures fold correctly in bacteria. We anticipate that the RNA apta-FRET system could have applications as ratiometric sensors for real-time studies in cell and synthetic biology.Fluorescent RNA aptamers are useful as markers for tracking RNA molecules inside cells and for creating biosensor devices. Förster resonance energy transfer (FRET) based on fluorescent proteins has been used to detect conformational changes, however, such FRET devices have not yet been produced using fluorescent RNA aptamers. Here we develop an RNA aptamer-based FRET (apta-FRET) system using single-stranded RNA origami scaffolds. To obtain FRET, the fluorescent aptamers Spinach and Mango are placed in close proximity on the RNA scaffolds and a new fluorophore is synthesized to increase spectral overlap. RNA devices that respond to conformational changes are developed, and finally, apta-FRET constructs are expressed in  FRET has been used to study protein conformational changes but has never been applied to RNA aptamers. Here the authors develop a genetically encodable RNA aptamer-based FRET system on single-stranded RNA origami scaffolds, and demonstrate it can be used to study RNA conformational changes. Analogously to fluorescent proteins (FPs), tracking of RNA in cells has been achieved using fluorescent RNA aptamers, which are structured RNA molecules that bind and enhance the fluorescence of small-molecule fluorophores3. The first demonstration of a fluorescent RNA aptamer was the malachite green aptamer4, which upon binding of malachite green increased its fluorescence more than 2000-fold. Malachite green is however toxic to yeast and mammalian cells5 a problem that has later been addressed by the development of the fluorescent RNA aptamers Spinach6, Broccoli7, and Mango8 that bind to non-toxic fluorophores. Spinach and Broccoli bind to the fluorophore 3,5-difluoro-4-hydroxybenzylidene imidazolinone (DFHBI), which mimics the fluorescence of GFP, whereas Mango binds the higher-wavelength fluorophore thiazole orange (TO) and derivatives hereof. Förster resonance energy transfer (FRET) is used experimentally to report on the conformation of biomolecules as it is especially sensitive towards changes in distance and orientation between a donor and acceptor fluorophore. FRET between FPs have been used to examine protein-protein interactions, where one of the first examples was a demonstration of the dimerization of the transcription factor Pit-1 by making fusion proteins of blue or green FPs with Pit-19. In another study, a FP-based FRET system was used for creating a Ca2+-sensor by linking the FPs with a Ca2+-binding domain that changed conformation upon ligand-binding, thereby changing FRET10. Using similar strategies, other FP-based FRET sensors have been developed for both ions and small molecules11, and these all share the advantages of being genetically encodable and providing ratiometric readouts that are not affected by fluctuations in sensor concentration.Green fluorescent protein (GFP)S-adenosylmethionine (SAM)12. In this sensor, the presence of SAM was directly coupled to the detection of fluorescence from DFHBI bound in Spinach, and the sensor was shown to work both in vitro and in vivo. Similar sensors based on riboswitches have also been produced for cyclic di-GMP13, cyclic di-AMP14, and thiamine 5′-pyrophosphate15. The folding of such riboswitches has been studied using FRET, where regions of interest on the RNA were chemically labeled with small-molecule fluorophores making it possible to follow changes in conformation due to ligand-binding18, however such labeled riboswitches are not expressible inside cells. In 2014, a reporter system for imaging gene expression in live cells, called IMAGEtag, was published. In this method, gene expression under different promotors were quantified by expressing two different RNA aptamers that bound externally added Cy3- or Cy5-modified ligands, providing an expressible system for real-time assessment of promotor activity19. Although this system was genetically encodable, it lacked structural control of the transcribed aptamers needed to make a system that could change conformation upon binding of a molecule of interest.FRET has not been used for RNA aptamer-based sensors, but in 2012, the Spinach aptamer was developed into an intensiometric riboswitch-type sensor by coupling the aptamer to an aptamer against a small molecule, namely 20, and provides a tool for creating scaffolds that can spatially organize attached molecular components with high precision for application in, e.g., medicine22 and synthetic biology23. For example, multi-stranded RNA nanostructures have been used as isothermally self-assembled arrays to scaffold two proteins of the hydrogen biosynthesis pathway in E. coli and showed a 48-fold increase in hydrogen production23. Recently, the single-stranded RNA origami method, that allows rationally designing RNA nanostructures to fold cotranscriptionally as they are being produced by the RNA polymerase, was introduced25. The method was demonstrated in vitro, but compared to many other thermodynamically designed structures should be compatible with folding in the cell.The research field of RNA nanotechnology aims at rationally designing RNA molecules that fold into well-defined shapesE. coli.Here we demonstrate FRET between fluorescent RNA aptamers by positioning Spinach and Mango in close proximity on single-stranded RNA origami scaffolds. We use the aptamer-based FRET (apta-FRET) system for producing a dynamic and reversible RNA nanodevice and for making a SAM-sensor by also incorporating the SAM riboswitch in the structure. Finally, we demonstrate that the apta-FRET constructs are genetically encodable by observing FRET when expressing the constructs in 6 28 derivative, YO3-biotin  of the fluorophores in the two aptamers (Supplementary Table 50 in Spinach than YO3-biotin (~340 nM compared to ~4 µM). Furthermore, we performed a competition assay demonstrating that DFHBI-1T outcompetes YO3-biotin bound in Spinach, whereas YO3-biotin is unable to outcompete DFHBI-1T bound in Spinach  construct the Spinach and Mango aptamers were placed in close proximity in a single-stranded RNA origami 2H-AE construct Fig. . The apt7. However, when testing the aptamers inserted in our RNA origami structures in vitro, Spinach performed as well as Broccoli for fluorescence enhancement  to point the dipole moment either towards or away from the helix axis of Mango , such that the dipole moment of DFHBI-1T pointed away from the helix axis of Mango . A SAM riboswitch37 was integrated into the S6-M19 construct to create the S6-M19-SAM sensor -M30 and an unmodified 2H-AE structures -M30 displayed almost no FRET. These results are comparable to the in vitro results using the same constructs -M30 constructs were visualized in a confocal microscope and cells that had taken up both fluorophores were selected for single cell analysis  was added to a stirred solution of 4-[(E)-2-(acetylphenylamino)ethenyl]-1-methylquinolinium iodide28  and 2-(2-methylbenz[d]oxazole-3-ium-3-yl) acetate42  in DCM. The solution was left to stir for 20 h followed by in vacuo concentration. The solid was then re-suspended in DCM (150 mL), filtered and washed with acetone (3 × 10 mL). The solid was dried in vacuo to yield  YO3-acetate as an amorphous purple solid. 1H NMR  δ 10.17 , 8.47–8.38 , 8.34–8.28 , 8.24–8.18 , 8.18–8.13 , 7.94–7.87 , 7.68–7.59 , 7.52–7.46 , 7.41–7.28 , 7.01–6.94 , 5.91–5.82 , 4.47 , 4.05 . HRMS (ESI)  requires m/z 359.1390, found 359.1395.EtN-biotinyl-3,6,9-trioxaundecane-1,11-diamine43  was added and the solution was stirred for 18 h. The solvent was lyophilized and the residue was redissolved in 1:1 MeCN/50 mM NH4OAc(aq). The solution was then purified by RP-HPLC (25–50% MeCN against 50 mM NH4OAc over 30 min). RP-HPLC Rt = 14.9 min. HRMS (ESI)  requires m/z 759.3534, found 759.3531.HBTU  and DIPEA (30 eq) was added to YO3-acetate  in DMF (250 µL). The solution was allowed to stir for 10 min where after 44. Briefly, using the 3D modeling programs Swiss-PdbViewer45 and UCSF Chimera46 two standard A-form RNA double helices were aligned in parallel and rotated to create optimal spacing for an anti-parallel even (AE) double crossover (DX). An internal 180° kissing-loop  was positioned between the crossovers and UUCG tetraloops (extracted from PDB id: 1F7Y) were positioned at the ends of the double helices. The 3D design of the apta-FRET constructs was based on the 2H-AE RNA origami structure. The minimal core of the Spinach aptamer (PDB id: 4Q9R), previously used to create Bunch of Baby Spinach47, was positioned on one of the outer double helix domains flanking the DXs. The Spinach motif was rotated to point the dipole moment of DFHBI-1T either directly towards or away from the adjacent parallel-aligned double helix domain, where the Mango aptamer was to be positioned. The core in the original Spinach aptamer is flanked by two double helix domains called P1.2 and P2.1 by Huang et al.31 This allows two different versions of incorporation; the “normal” version where the P1.2 domain was used to connect Spinach to the RNA origami, and the “flipped” version (annotated with *) where the P2.1 domain was used to connect Spinach to the RNA origami. A stem-loop built from a standard A-form double helix and a UUCG tetraloop was attached to the other end of the Spinach core. Due to steric clashes only two of the possible four versions were viable; the normal version with the dipole pointing towards the adjacent double helix, and the flipped version with the dipole pointing away from the adjacent double helix. The recently published co-crystal structure of the Mango aptamer revealed a three tier G-quadruplex connected to a double helix domain through a GAAA tetraloop-like motif, and does not allow Mango to be “flipped” like Spinach. The linkage between the tetraloop and G-quadruplex is not structurally defined and is expected to be flexible, and TO3-biotin (very similar to YO3-biotin) could not be modeled into the binding pocket without steric clashes. Therefore, we could not model the precise position of the dipole of the YO3-biotin fluorophore. To find the optimal position of Mango the length of the double helix domain between Mango and the nearest DX was varied in steps of two base pairs. Some of the positions were found to have steric clashes. After initial modeling 3D structures were ligated with a Perl script  and refined using a recursive geometric refinement function in Assemble248. 3D models in this work were rendered in UCSF Chimera.The three-dimensional (3D) design of the basic 2H-AE RNA origami structure has previously been described in great detailhttp://www.chemaxon.com/). The chemical structure of DFHBI-1T was drawn in MarvinSketch, and the protonation state of the molecule was determined at pH 7.8 by using the pKa Calculator Plugin. The dipole moment of the most abundant DFHBI-1T microspecies (70.4% at pH 7.8) was calculated by using the Dipole Moment Calculator Plugin. The total dipole moment of DFHBI-1T was visualized as a vector expressed in the principal axis frame. The resulting file indicating both the chemical structure and dipole moment vector of DFHBI-1T was exported as pdb file and imported in Swiss-PdbViewer45 to align the fluorophore molecule with the 3D coordinates of DFHBI from the crystal structure of Spinach (PDB id: 4Q9R).The dipole moment of DFHBI-1T was calculated using the Marvin software suite (version 15.10.19) and the Calculator Plugin developed by ChemAxon  was retained and the remaining sequence was denoted with Ns. Each sequence was further constricted by “locking” the crossovers with G-C base pairs, incorporating a GU wobble pair per every eight continuous base pairs, and constraining the 5′-end to 5′-GGGAGA-3′, an optimal initiation sequence for T7 RNA polymerase. The 2D blueprints were read by a Perl script  that outputs the dot-bracket notation and sequence constraints appropriate for sequence design in NUPACK49. Sequences designed in NUPACK were folded and evaluated using mFold50.The sequence design process has previously been described in detailTaq DNA polymerase (Invitrogen). Amplifications were performed in 1× Taq buffer, 200 µM dNTP (invitrogen), 1.5 mM MgCl2, 1 µM Fwd and Rev primers, 4 ng ultramer, and 2.5 U Taq DNA polymerase. Fwd and Rev primers were designed for each template . The amplified DNA was purified using GFX PCR DNA purification kit (illustra) and stored in TE buffer.DNA templates of the apta-FRET constructs were produced by standard PCR amplification of gBlocks gene fragments from IDT using Phusion High-Fidelity DNA Polymerase (ThermoFischer Scientific). Amplifications were performed in 1× Phusion HF buffer (provided by the manufacturer), 200 µM dNTP (invitrogen), 1 µM forward (Fwd) and reverse (Rev) primers (ordered from IDT), 4 ng gBlock and 1 U Phusion polymerase. DNA templates of the simple aptamers were produced by standard PCR amplification of DNA ultramers (IDT) using 2, 50 mM Tris-Acetate pH 7.8, 40 mM NaCl, 0.1% Tween20), 1 mM DTT, and NTPs (2.5 mM each). T7 RNA polymerase (made in-house) was added, and the samples were incubated at 37 °C for at least 4 h. The reaction was stopped by adding DNase I (ThermoFischer Scientific) to a concentration of 1 U/100 µL and incubating at 37 °C for 15 min. The transcribed RNA was purified on 6% polyacrylamide gels after mixing 1:1 with denaturing load buffer  and heating to 95 °C for 5 min. Gel bands were visualized using UV shadowing, cut out of the gel, and eluted overnight in nuclease free H2O (Ambion). Gel pieces were separated from the liquid using Freeze‘n’Squeeze DNA gel extraction Spin columns (Bio-Rad), and the RNA was finally ethanol precipitated, re-suspended in nuclease free H2O and stored at −20 °C.In vitro transcription was performed by mixing DNA template, transcription buffer (15 mM Mg(OAc)2O was heated to 95 °C for 5 min, and then quickly cooled at −20 °C for 3 min. 5× assembly buffer  was then added to a final concentration of 1×, and the samples were left at 37 °C for 30 min.The transcribed RNA was heat annealed prior to usage to ensure correct folding of the RNA origami structures. First, the RNA in nuclease free HIDY is the emission at YO3-biotin wavelength after DFHBI-1T excitation and IDY is the emission at DFHBI-1T wavelength after DFHBI-1T excitation. Both were measured with DFHBI-1T and YO3-biotin present.Fluorescence measurements were performed on a FluoroMax 4 from Horiba, Jobin Yvon. Excitation of DFHBI-1T and YO3-biotin were performed at 450 nm and 580 nm, respectively. Emission of DFHBI-1T and YO3-biotin were recorded at 503 nm and 620 nm, respectively. Monochromator slits were set to 5 nm, and integration time was 0.2 s. Measurements were performed on sample volumes between 65 and 100 µL, and fluorophore concentrations of 1 µM DFHBI-1T and 1.7 µM YO3-biotin were used if nothing else is stated. Relative FRET values were calculated using the equation Fluorophore activation and competition assays were performed on RNA origami structures containing only Spinach or only Mango, or with an empty 2H-AE structure  vs. response (three parameters)” of a dose–response curve.The binding affinities towards different fluorophores of the aptamers integrated into RNA origami structures were measured. The constructs were heat annealed prior to use according to the protocol above, and samples prepared in 1× assembly buffer. Measurements were performed using serial diluted fluorophores of concentrations between 1 nM and 2 µM. All samples were prepared in triplicates both with and without 20 nM RNA, and fluorescence was measured on a VarioSkan Flash Reader (Thermo Scientific) by exciting the samples containing DFHBI-1T or YO3-biotin at 450 nm or 580 nm, respectively. Background fluorescence from each concentration of fluorophore in the absence of RNA was subtracted from the recorded intensities before calculating ECIF+R is the fluorescence intensity of the fluorophore in the presence of RNA and IF is the fluorescence intensity of the fluorophore alone (off-state fluorescence).Enhancement of fluorescence was calculated for the fluorophores in the minimal version of the aptamers and in the aptamers integrated into RNA origami structures. Overall, 1 µM RNA in 1× assembly buffer was incubated with 100 nM of the relevant fluorophore. Fluorescence enhancement was calculated using the equation Visualization of conformational changes as a response to invader RNAs was performed by time-resolved measurements of the apta-FRET system containing a branched KL. Fluorescence both from DFHBI-1T and YO3-biotin was recorded every 30 s, and the shutters were closed between measurements to avoid bleaching. Reversible invasion was obtained by first adding invader RNA with a toehold to a final concentration of 200 nM to a mixture of 100 nM apta-FRET structure, 1 µM DFHBI-1T, and 1.7 µM YO3-biotin, and subsequently adding “anti-invader” to a final concentration of 400 nM. FRET outputs were calculated as described previously.Invader 1: UAGCUUAUCAGACUGAUGUUGAUAUAAAAG;Anti-invader 1: CUUUUAUAUCAACAUCAGUCUGAUAAGCUA.Invader 2: CUAGACUGAAGCUCCUUGAGGGAAGUUAG;Anti-invader 2: CUAACUUCCCUCAAGGAG CUUCAGUCUAG.50 were calculated as described previously.The binding affinity of SAM in the S6-M19-SAM sensor was performed by incubation with serial diluted SAM of concentrations between 1 µM and 2.5 mM. The measurements were performed in triplicates with 50 nM RNA in assembly buffer containing 1 µM DFHBI-1T and 1.7 µM YO3-biotin. Measurements were performed in a VarioSkan Flash Reader by exciting the samples at 450 nm and recording fluorescence spectra from 470 nm to 700 nm. FRET outputs and ECBglII and EcoRI) onto the ends of the DNA templates were performed by PCR amplification using Phusion DNA polymerase as described above (see Supplementary Note BglII and EcoRI (ThermoFischer scientific—Fastdigest) for 30 min at 37 °C, the DNA was purified using GFX PCR purification kit (illustra). pET28c-F30–2xdBroccoli was received as a gift from Samie Jaffrey (Addgene plasmid # 66843). A plasmid prepared in-house based on the pET28c plasmid was digested with BglII and EcoRI, and purified on a 1% 0.5× TBE agarose gel. The linearized pET28c plasmid was extracted from gel using GFX gel extraction kit (illustra) and the insert was ligated into the plasmid in a 1:3 ratio by incubation with T4 DNA ligase at 16 °C overnight. The ligation reaction mixture was used directly to transform the plasmid into DH5-alfa E. coli (NEB) using standard heat-shock procedure. The transformed bacteria were plated onto LB-agar with Kanamycin , and incubated overnight at 37 °C. Single colonies were selected and inoculated in LB-Kan (50 µg/mL) overnight at 37 °C with vigorous shaking. The plasmids were isolated using GeneJET plasmid miniprep kit (ThermoFischer Scientific) before verified by sequencing at GATC-Biotech. Sequence positive plasmids (~1 µg) were transformed into chemically competent HT115(DE3) E. coli made in-house, and the positive transform clones were selected using LB-agar plates with Kan (50 µg/mL) and Tetracyclin  as described in Hull and Timmons51.Standard molecular cloning steps were performed. First, amplification and encoding of restrictions sites (600 ~0.25–35 (~3 h). Then IPTG (1 mM) was added to half of the sample, and the cultures incubated for ~6–9 h. DFHBI-1T (50 µM) and YO3-biotin (85 µM) were added and the cultures incubated for 30 min.The different cultures were pelleted by centrifugation at 4000×g for 5 min before re-suspended in fresh 1× M9 salt (Sigma#M6030) and analyzed by spectrofluorometry, flow cytometry or confocal microscopy.An overnight (ON) culture was made by inoculating single HT115(DE3)-pET28c-FRET colonies in 3 mL LB with Kan (50 µg/mL) and Tet (12.5 µg/mL) and allowed to grow aerobically at 37 °C with vigorous shaking overnight. The culture was diluted 1:100 in LB-Kan and incubated using the same conditions until ODIY is the emission at YO3-biotin wavelength after YO3-biotin excitation with only YO3-biotin present. Hereafter, the emission intensity arising from the DFHBI-1T tail at YO3-biotin wavelength was found; it was calculated to be 7.4%  is the emission at DFHBI-1T wavelength after DFHBI-1T excitation with only DFHBI-1T present, and ID is the emission at YO3-biotin wavelength after DFHBI-1T excitation with only DFHBI-1T present. FRET outputs were hereafter calculated by subtracting both Adir and Dleak using the equation: The cells prepared as described above were analyzed by spectrofluorometric measurements in a volume of 50 µL Samples containing both DFHBI-1T and YO3-biotin as well as controls containing only DFHBI-1T or YO3-biotin were prepared. Excitation of DFHBI-1T and YO3-biotin were performed at 450 and 580 nm, respectively. FRET outputs were calculated by first calculating the direct acceptor excitation, which was found to be 1.5%  were diluted in 950 µL 1× M9 salt before measured on a Beckmann Coulter Gallios Flow Cytometer with a 488 nm laser and the FL1(575/30) and FL3(620/30) detector filters. Kaluza Analysis software was used to process the data. Fluorescence emission was measured on 50,000 ungated cells either containing both DFHBI-1T and YO3-biotin or containing only DFHBI-1T or YO3-biotin. The geometric mean intensities of gated 2H-AE cells were used as a background and subtracted from the geometric mean intensity measured on gated cells containing apta-FRET structures. The intensity arising from DFHBI-1T in the FL3 channel was found using 2O and dried. 50 µl culture prepared as described above in 1X M9 salts containing 100 µM DFHBI-1T and 17 µM YO3-biotin was added to the wells. DFHBI-1T was excited using the 488 nm laser and recorded using EGPF filter, and YO3-biotin was excited using the 555 nm laser and recorded using Texas Red filter. FRET signal was obtained by exciting using the 488 nm laser and recording using the Texas red filter. The recorded images were processed in MatLab (the code is available from our webpage www.andersen-lab.dk), where the DFHBI-1T channel was used to locate individual cells and define their boundaries. The average intensity per pixel within each cell was calculated for all three channels. Cells were selected using the directly excited YO3-biotin fluorescence and cells with the bottom 5% intensity, which corresponds to cells showing no or very low YO3-biotin fluorescence were discarded. The values from the FRET and DFHBI-1T channels of the remaining cells were used to calculate the relative FRET outputs using the equation Fluorescence microscopy images were acquired using a Zeiss LSM 800 using the 100X oil objective. The bacteria were immobilized on poly-L-lysine (PLL) coated 96 well plates . 200 µl PLL (10 mg/ml) was applied to the wells for 30 min at 37 °C before washed with nuclease free HThe authors declare that the main data supporting the findings of this study are available within the article and its Supplementary Information file. Extra data are available from the corresponding author upon request.Supplementary InformationPeer Review File


Xenopus laevis were sequenced to identify microRNAs (miRs) expressed in each tissue. Argonaute-associated mRNAs were isolated and sequenced to identify genes that are regulated by microRNAs in these tissues. Interactions between these ectodermal miRs and selected miR-regulated mRNAs were predicted using the PITA algorithm; PITA predictions for over 600 mRNAs are presented. All sequencing data are available at NCBI (NCBI Bioproject Accession number: PRJNA325834). This article accompanies the manuscript “MicroRNAs and ectodermal specification I. Identification of miRs and miR-targeted mRNAs in early anterior neural and epidermal ectoderm”  Small RNAs from early neural  and epidermal  ectoderm in  Specifications TableValue of the data•Xenopus laevis.Sequence data and target predictions provide a foundation for subsequent functional analyses of miR-mRNA interactions. Large-scale microRNA target predictions have not previously been generated for •These datasets can support future studies on microRNA-dependent translational control in embryonic systems, and they can be used to establish the extent of conservation of microRNA-targeted mRNA interactions.•These datasets can be used to investigate the roles of microRNAs in the establishment of neural vs epidermal ectoderm, the transition from the early neural gene regulatory network to the neural proliferative and neurogenic networks, and the restriction of pluripotency in embryonic ectoderm.11)Xenopus laevis embryos. Sequence reads for 3 biological replicates, as well as the accompanying DESeq analysis, are provided. Xenopus laevis embryos (The identification of RNAs in the Argonaute Ribonucleoprotein complex (Ago–RNP) from in early neural and epidermal ectoderm from  embryos . Total R embryos .3)Predicted miR-mRNA interactions for “High Confidence” miR-targeted ectodermal mRNAs from the Ago–RNP pools for early neural and epidermal ectoderm .4)Gene Ontology (GO) categories and associated genes among the “High Confidence” miR-targeted ectodermal mRNAs .5)Conserved targets of pou5f3 among the miR-targeted mRNAs for NOG and CABR Ago-associated mRNAs and predictions of miR –mRNA interactions for the genes .These data include:2For microRNAs: Small RNA sequencing was carried out on paired NOG and CABR ectodermal samples in 3 biological replicates.For Ago-RNP RNAs: RNA sequencing was carried out on RNAs immunoprecipitated from paired NOG and CABR ectodermal samples in 3 biological replicates.2.12.1.1Detailed methods for the preparation of embryonic tissue samples are presented in Shah et al. 2.1.2™ Picogreen dsDNA reagent (Thermofisher). Sequencing of these libraries was carried out at the M. D. Anderson Sequencing and Microarray Facility.After lysing the midgastrula animal caps in Trizol, the Direct-zol RNA mini-prep kit (Zymo) was used to purify the RNA. Libraries were generated from these DNAseI-treated RNA samples using the NEBNext Multiplex Small RNA Library Prep Set for Illumina kit. Library yields were quantified using the Quant-iT2.1.3Detailed methods for co-immunoprecipitation of Ago–RNP complexes and isolation of RNP-associated RNA are presented in Shah et al. 2.1.4™ Complete Gold Kit – Low Input (Epicentre Technologies); these samples were not subjected to rRNA depletion before library preparation. Sequencing was carried out at the M. D. Anderson Cancer Center Sequencing and Microarray Facility.RNA isolated from the immunoprecipitated Ago–RNP samples was used to generate sequencing libraries via the ScriptSeq2.1.5™ Complete Kit – Low Input from Epicentre (Cat.No. SCL6H). Sequencing was carried out by the Sequencing Core Facility at the University of Houston. Sequence reads for all sequencing studies reported here are publicly available through NCBI (NCBI Bioproject Accession number: PRJNA325834).The Ribo-ZeroTM rRNA kit was used to deplete the total RNA or “input RNA”) samples of ribosomal RNA, prior to subsequent purification using the RNeasy MinElute Cleanup Kit. Sequencing libraries were then generated using the ScriptSeq2.1.6A)Mapping of small RNA sequence readsXenopus laevis genome assembly 9.1 served as the basis for the genome reference index, which was constructed using Bowtie 1.1.1  and trimmed with Cutadapt . The B)Analysis of small RNA expressionX. tropicalis miR datasets. We used DeSeq Anders and Huber P values.A non-redundant set of miRs was generated by comparisons of reads aligned to human vs C)Mapping and analysis of sequences from Ago–RNP RNA and Total RNA samplesXenopus laevis transcriptome dataset . Bowtie2 was used to align paired-end sequences to the transcriptome index using the following options: --local for local alignments, −p 8 to run parallel 8 search threads and −S for output in sam format). Sam output files were converted to Bam files using Samtools; express Roberts and Pachter Libraries prepared from the ago–RNA samples were subjected to paired-end sequencing. Cutadapt was used to trim adapter sequences using the following options: −b for both 3′ and 5′ adapter trimming because of the variable sequence length. The reference index was prepared from D)Identification of differentially represented Ago–mRNAsp value of <0.01.We omitted all transcripts with representation below threshold (<5 read counts) in all libraries. DESeq was used to normalize the levels of specific Ago–RNAs for non-specific binding, and to determine which transcripts showed a difference in representation between neural and epidermal tissues. Transcripts were normalized individually to total numbers of transcripts in each library. DESeq was used to determine the ratio of log2FoldChange (log2FC) in neural/epidermal ectoderm for each transcript using a negative binomial distribution. The thresholds for significant differential representation were (1) a log2FC of >2 and (2) a E)Sequence analysis of total RNAsBowtie2 was used to align reads from total RNA samples against the transcriptome-based index, using the following options:.−q for fastq input file format, --sensitive-local as a default mode in local alignments, −I 200 and −X 300 to set minimum and maximum fragment length valid for paired end alignments, −p 12 to run 12 parallel search threads. The resulting output was evaluated with eXpress to annotate transcripts represented in the “total RNA” pools for both neural and epidermal samples, yielding annotations, read counts, and FPKM values.2.1.7The PITA algorithm (Probability of Interaction by Target Site Accessibility (PITA), Kertesz et al.


Saccharomyces cerevisiae generation of export-competent mRNPs terminates the nuclear phase of the gene expression pathway and facilitates transport to the cytoplasm for translation. Nab2 functions in this process to control both mRNP compaction that facilitates movement through nuclear pore complexes and the length of transcript poly(A) tails. Nab2 has a modular structure that includes seven CCCH Zn fingers that bind to A-rich RNAs and fingers 5–7 are critical for these functions. Here, we demonstrate, using both biophysical and structural methods, that binding A11G RNA induces dimerization of Zn fingers 5–7 mediated by the novel spatial arrangement of the fingers promoting each RNA chain binding two protein chains. The dimerization of Nab2 induced by RNA binding provides a basis for understanding its function in both poly(A) tail length regulation and in the compaction of mature transcripts to facilitate nuclear export.In  Saccharomyces cerevisiae, the nuclear export of mature transcripts is mediated primarily by the export factor Mex67:Mtr2 that binds to the mRNPs and, through interactions with NPC proteins that contain multiple phenylalanine–glycine motifs (FG-nucleoporins), facilitates their passage though the pores  in the nucleus to generate mature mRNAs. The generation of export-competent mRNPs (messenger ribonucleoprotein complexes) represents the final step in the nuclear portion of the gene expression pathway and facilitates the transport of mature transcripts through nuclear pore complexes (NPCs) to the cytoplasm for translation. During nuclear processing a broad spectrum of proteins bind to the transcripts. Although some facilitate particular functions and are generally then released, other RNA-binding proteins function to compact mature transcripts to facilitate movement through NPCs (reviewed by ). In Saciewed by ). Althounab2 mutants frequently generate hyperadenylation, defects in surveillance, and reduced mRNA nuclear export resulting in nuclear accumulation of poly(A)-mRNA, but the impact on each of these functions often varies between mutants, consistent with the Nab2 protein having several functions in the gene expression pathway . Nab2 aiewed by ,9 and, aiewed by ,11. Nab2iewed by ,9.S. cerevisiae Nab2 protein contains four domains  tail length control, and also functions as a checkpoint for proper 3΄ processing . The Zniewed by . Althougiewed by . Thus, Ss per kb , whereass per kb . Transcrs per kb  and ChIPs per kb  also inds per kb  and comps per kb  have ideChaetomium thermophilum Nab2 bound to short (2–3 nt) adenosine oligomers  induces formation of a heterotetramer containing two protein and two RNA chains, whereas ZnF567 alone is monomeric in solution. The crystal structure of ZnF567 bound to A11G RNA indicated that there are few direct interactions between the protein chains in the heterotetramer and that each RNA chain binding to two protein chains mediates the generation of a ZnF567 dimer. Dimerization of the Zn fingers generated by RNA binding provides a basis for understanding the function of Nab2 in both compacting and packaging mature transcripts for nuclear export as well as controlling 3΄ poly(A) tail length.Here, we demonstrate that binding either Aby SELEX  to S. ceS. cerevisiae Nab2 corresponding to ZnF567 (residues 409–485) and the corresponding F450A mutant were expressed in Escherichia coli and purified as described (12 and A11G) were purchased from Integrated DNA Technologies (Belgium). The full-length mRNA open reading frame of the S. cerevisiae GAL1 gene was produced by in vitro transcription. The gene was amplified by PCR and sub-cloned into a pUCIDT (amp) vector containing an upstream T7 promoter and a downstream Xho1 site for effective linearization of the vector. The run-off transcription reaction contained 0.04 mg/ml T7 RNA polymerase mixed with 100 ng/μl DNA template, 7.5 mM NTPs, 50 mM MgCl2, 1 mM spermidine and 80 mM Na–HEPES buffer, pH 7.5, and incubated at 37°C for 4 h. The RNA was purified by phenol/chloroform extraction at pH 4.5 followed by ethanol precipitation and was stored at −20°C.A fragment of escribed . SynthetSize exclusion chromatography-multiangle light scattering (SEC-MALS) employed a Superdex 200 10/30 column coupled to a Wyatt Heleos II 18 angle light scattering instrument coupled to a Wyatt Optilab rEX online refractive index detector  as described  and Nab2 fingers 5–7  were mixed in 25 mM HEPES buffer, pH 8 and then separated on a 10–30% (w/v) sucrose density gradient in which 0.25% (v/v) of glutaraldehyde had been added to the 30% sucrose solution used to make the gradient. Samples were centrifuged in a Ti60 rotor  for 18 h at 4°C and seven-drop fractions collected and examined following negative staining with 2% (w/v) uranyl acetate. Micrographs were recorded at 23 000× using Techni Spirit or T12 electron microscopes operated at 120 kV and equipped with Gatan Orius and Ultrascan 1000 CCD cameras, respectively.Samples for electron microscopy were prepared using the GraFix procedure  in which12 and A11G RNAs bound to Nab2 Zn fingers 5–7 (ZnF567) with an ∼1:1 stoichiometry and comparable affinity, although A11G RNA bound with a marginally higher affinity than A12 RNA  and A11G RNA  were 4.8 and 4.6 kDa, respectively, consistent with their being monomeric in solution , indicating that binding either A11G and A12RNA induced ZnF567 dimerization leading to the formation of a heterotetramer that contained two protein and two RNA chains.ITC indicated that both A1P2 symmetry that diffracted to 1.55 Å resolution were obtained for the complex of A11G RNA with ZnF567. Initial phases were obtained using the Zn anomalous signal and iterative cycles of refinement using PHENIX (R-factor of 13.1% (Rfree = 15.2%), excellent geometry (Table B-factor 29.22 Å2) and 685 water molecules (average B-factor 39.34 Å2). Residues 409–479 were clear in all chains with density corresponding to the N-terminal Gly-Ser from TEV cleavage and residues 480–481 sometimes present. Electron density corresponding to residues 482–485  was nottructure— as outlitructure— is not tfinement  was cons12 RNA and ZnF567F450A was 14.4 kDa  tail length in vivo when many of the key residues identified in the crystal structure  were mutated, but did not identify the importance of Cys421, Cys437, Cys464 (mutation of which would have impacted on the structure of the finger), Asp447 and Glu456, or the main chain interactions involving Thr422, Arg438, Asp447, Leu449 and Arg459. The interactions of the adenine bases with ZnF567 were generally similar to those observed in crystals in which A8 RNA was bound to C. thermophilum Nab2 fingers 3–5 that have sequence similarities to Nab2 ZnF567  binding residues in ZnF567 using NMR  were fru2 ZnF567 . With thproteins –32, the proteins , whereasproteins ,35.11G RNA demonstrated how reciprocal interactions between A-rich sequences have the capacity to generate Nab2 dimers in a way that does not depend on interactions between the proteins themselves but depends critically on the unique spatial arrangement of the Zn fingers.In summary, the crystal structure of the complex formed between Nab2 Zn fingers 5–7 and A11G RNA, might link them together and thereby facilitate compaction. As a proof-of concept, a transcript generated in vitro corresponding to the coding sequence of GAL1 was used as a model system and binding was assessed using gel electrophoresis, exploiting the difference in charge between the RNA (negative) and the protein (positive). Thus, when mixed with ZnF567 the density of the GAL1 RNA band decreased, coupled with formation of a heterogeneous mixture of different species species that migrated more slowly towards the positive electrode . A similar depletion of the ZnF567 protein band on SDS PAGE was observed on the addition of increasing amounts of GAL1 transcript  tails ,9,14, wee Figure , consistt Figure .GAL1 RNA generated compacted complexes. Thus, when GAL1 RNA and ZnF567 were mixed and then fractionated using the Grafix procedure (n = 53), consistent with ZnF567 alone mediating some compaction the GAL1 transcript. Although there was considerable heterogeneity both in the size and shape of these particles, this was probably a result of the Nab2 Zn fingers linking different regions of the RNA chain in different particles and perhaps, at times, also crosslinking two transcripts together to form a larger particle. RNA alone binds uranyl acetate strongly and so appears dark in electron micrographs  tails are typically ∼60 nt long. However, a large number of Nab2 mutants show increased poly(A) tail length in vivo  RNA binding provides a rationale for the function of Nab2 in controlling poly(A) tail length Figure . Polyadeiewed by ). Viphak  and so only an A-rich region, possibly terminating in G, as suggested by SELEX  and alse et al. . Althoug of NPCs ,40.11G RNA induces dimerization of ZnF567 that is mediated by each RNA chain binding to two protein chains. The dimerization of Nab2 induced by RNA binding provides a basis for understanding its function in both poly(A) tail length regulation and in the compaction of mature transcripts to facilitate nuclear export.In summary, biophysical and structural methods demonstrate that binding A11G RNA have been deposited with the protein data bank with accession code 5L2L.Coordinates and structure factors for the complex of Nab2 Zn fingers 5–7 with ASupplementary DataClick here for additional data file.


A pool of small RNA fragments (RFs) derived from diverse cellular RNAs has recently emerged as a rich source of functionally relevant molecules. Although their formation and accumulation has been connected to various stress conditions, the knowledge on RFs produced upon viral infections is very limited. Here, we applied the next generation sequencing (NGS) to characterize RFs generated in the hepatitis C virus (HCV) cell culture model (HCV-permissive Huh-7.5 cell line).We found that both infected and non-infected cells contained a wide spectrum of RFs derived from virtually all RNA classes. A significant fraction of identified RFs accumulated to similar levels as miRNAs. Our analysis, focused on RFs originating from constitutively expressed non-coding RNAs, revealed three major patterns of parental RNA cleavage. We found that HCV infection induced significant changes in the accumulation of low copy number RFs, while subtly altered the levels of high copy number ones. Finally, the candidate RFs potentially relevant for host-virus interactions were identified.Our results indicate that RFs should be considered an important component of the Huh-7.5 transcriptome and suggest that the main factors influencing the RF biogenesis are the RNA structure and RNA protection by interacting proteins. The data presented here significantly complement the existing transcriptomic, miRnomic, proteomic and metabolomic characteristics of the HCV cell culture model.The online version of this article (doi:10.1186/s12864-017-3891-3) contains supplementary material, which is available to authorized users. In recent years, the spectrum of known small non-coding RNAs has significantly expanded along with the discovery that virtually all RNA classes reproducibly give rise to a broad repertoire of stable, well-defined fragments –4. TheirSince the discovery of RFs, it has been observed that they are formed in response to various pathological processes. There are a number of reports showing a prominent accumulation of RFs under different stress conditions as well as in cancer , 27–30. Globally, the hepatitis C virus (HCV) is a leading cause of persistent liver infections that can result in cirrhosis and hepatocellular carcinoma. HCV has a single-stranded (+)RNA genome, in which a single open reading frame is flanked by regulatory 5′ and 3′ untranslated regions (5′ and 3′ UTRs) . The RNAFor the long time our knowledge on factors shaping the early stages of HCV infection had been very limited. The situation changed after the development of the Huh-7.5 cell line-based HCV cell culture (HCVcc) model. Its application has allowed to elucidate key aspects of viral infections and host-virus interactions . Our undConsidering the recent evidence demonstrating the importance of RFs in various cellular processes, we characterized the pool of small RNAs (15–82 nt long) that accumulate in the Huh-7.5 HCVcc model. We found that Huh-7.5 cells contained a broad spectrum of RFs derived from multiple RNA classes. The vast majority of these fragments had well-fixed lengths and were repeatedly generated from the same regions of their parental molecules. This observation strongly suggested that specific cellular mechanisms control the process of RF formation. Consequently, we identified several patterns according to which particular RNAs were cleaved into fragments. The fact that a number of RFs accumulated to levels that were similar to those of the miRNAs suggested that RFs could not be neutral to the cell. We observed HCV infection-induced remodeling of the RF pool in Huh-7.5 cells. The levels of low copy number RFs significantly increased in infected cells and the accumulation of high copy number RFs displayed only subtle changes. Accordingly, one can assume that RFs constitute a considerable component of the cellular landscape in which HCV infection occurs. Altogether, our data provide new insight into the widely used HCV infection model and open a novel perspective for future studies of host-HCV interactions.To identify and characterize RFs that form during HCV infection we used the HCVcc model. We inoculated Huh-7.5 cells with HCV JFH-1 and collected samples from cultures grown for either 72 h or 96 h post inoculation (hpi). Under the conditions we used, at least 80% of cells were infected at the time of harvest, as shown by immunofluorescence analysis  retained either the 5′ or 3′ ends of the mature tRNA Fig. . They weIn contrast to tRFs, most of snoRNA fragments (snoRFs) (74%) lacked the original 5′ and 3′ ends of their parental molecules Fig. . BecauseThe majority of snRNA fragments (snRFs) (67%) were generated by a cleavage from both ends of their parental molecules Fig. , whereasApproximately one-third of Y RNA fragments (YRFs) retained the 5’ end of mature Y RNA Fig. . They weTo determine the patterns of the cleavage of parental RNA into fragments, we aligned the sequences of all identified RNA species to the sequences of their parental molecules. As a result, we identified three major cleavage patterns.The first pattern, called a single-set single-region pattern, was observed when all RFs were of similar length and overlapped a single region of parental RNA Fig. . There wThe second pattern, called a single-set many-regions pattern, was observed when RFs were excised from more than one region of parental RNA and constituted separate sets of RFs, each overlapping another portion of the full-length molecule Fig. . Each seThe third pattern, called a many-sets single-region pattern, was observed when one region of parental RNA gave rise to at least two sets of RFs of substantially different lengths Fig. . In someRFs, miRNA) were selected as described in A detailed examination of the composition of the sets revealed that they comprised one or more clusters of very similar species. For example, the species differed only by a few nucleotides in length or had single nucleotide substitutions. The latter were detected mainly in the case of tRFs and could be attributed to the base modifications of mature tRNA. It is known that RNA modifications can decrease the fidelity of cDNA synthesis during the preparation of sequencing libraries . We assumiRNA and RFs in all samples was established as a value relative to the amount of liver-specific miR-122  .Next, the abundance of tRFs was assigned to the range 0.1%–1%. Further, 23%–32% of tRFs displayed relative abundance of 1%–10%, whereas for 2%–7%, their relative abundances were in the range 10%–100%. Several tRFs accumulated to higher levels than miR-122. The relative abundance of tRFs in cultured cells increased over time and was higher upon HCV infection. Similar results were obtained for snoRFs and YRFs. A lower relative abundance was observed for snRFs. In non-infected cells, over half of snRFs were assigned to the range below 0.1%, and the other half was split between the 0.1%–1% and 1%–10% ranges. However, HCV infection triggered a substantial increase in snRNA fragmentation, which was most evident at 96 hpi. Taken together, the distribution of the relative abundance values in the analyzed classes of RFs greatly resembled the one obtained for miRNA. This observation indicates that RNA fragments are as abundant as miRNA in the HCV cell culture model.More than a half of RFs were assigned to a relative abundance range of at least 1%–10% across the samples, and the majority were assigned to the 10%–100% range . Y RNA generated 2 plentiful fragments, both containing an Ro60 binding region. We also identified 1 abundant fragment of HIST2H2AA3 mRNA, 1 tRNAseZL-interacting RNA and 5 fragments classified as derivatives of putative conserved non-coding RNA. The length of the highly accumulated RFs spanned a range from 15 to 69 nt. Two of them, derived from Y RNA and putative conserved non-coding RNA, had sizes similar to those of mi/siRNA .All of the 25 most abundant RFs, we compared RF accumulation levels in infected and non-infected Huh-7.5 cells. The analysis revealed that the accumulation of a vast majority of RFs was not affected. The molecules that did display statistically significant differential accumulation between infected and control cells were the RFs of low abundance. Among 827 representative species, 62 and 96 were found to be differentially accumulated at 72 hpi and 96 hpi, respectively, with 52 in common for both time points. Table RFs. The relative abundances of all of them were in the ranges 0.1%–1% and 1%–10% in infected cells at 72 hpi and 96 hpi, respectively. The most prominent differentially accumulated RF originated from Y RNA. It demonstrated an increased abundance upon HCV infection at 72 hpi and 96 hpi, but this change reached statistical significance only at the latter time point . This Y RNA-derived RF, mentioned above as one of the most abundant fragments (Table RFs derived from tRNA (9), snoRNA (5), snRNA (5), piRNA (1) and 3 molecules that could not be unambiguously classified. The predominant tRFs were tRF-5A, which originated from tRNA-Glu, tRNA-Leu and tRNA-Tyr. tRNA-Glu and tRNA-Leu were also the source of tRF-5D, and tRNA-Glu was the source of tRF-Δ5A-Δ3AA. The remaining 2 most abundant differentially accumulated tRFs were tRF-Δ5D-Δ3A and tRF->5T, derived from tRNA-Gln and tRNA-Lys, respectively. The snoRNAs whose fragmentation was significantly elevated upon HCV infection included SNORD82, SNORD26, SNORD45, SNORA7 and small Cajal body-associated HBII-382. Nearly all of them yielded fragments that contained functionally relevant regions such as box C, D, and ACA and/or a guide sequence. HCV infection was also associated with an increased production of fragments originating from snRNA, in particular from U1, which gave rise to 4 snRFs of considerable abundance, 3 of which contained an Sm binding site. One U2-derived RF was also among the 25 most abundant differentially accumulated RFs. The lengths of all RFs classified in this group ranged between 15 and 55 nt, with 4 representative species (derived from Y RNA and snoRNA) displaying miRNA-like lengths of 21 to 24 nt.To investigate whether HCV infection induces changes in the pool of RFs with the highest fold change upon HCV infection. Their relative abundance in non-infected cells was extremely low and did not reach 0.1% of the amount of miR-122. However, HCV infection dramatically raised their accumulation levels – in some cases the change was several orders of magnitude. RFs with log2FC ≥ 5, at least at 96 hpi, are presented in Table RFs, 10 were generated from U1 snRNA and 1 from U2 snRNA. This indicates that spliceosomal RNAs are predominant targets of the RNA cleavage that occurs in cells upon HCV infection. Other RFs were derived from snoRNA (6), tRNA (2), putative conserved noncoding regions (2) and piRNA (2). In addition, this group included derivatives of 3 parental molecules that otherwise did not yield any other fragments: fibroblast growth factor-2 (FGF-2) internal ribosome entry site (IRES), signal recognition particle RNA (7S RNA) and nuclear RNase P RNA.In the next stage of our analysis, we focused on the Collectively, our analyses reveal that HCV infection triggers an overall increase in the accumulation of RFs. The infection, however, mostly impacts the fraction of low copy number fragments. Therefore, even upon up-regulation, most of these differentially accumulated RNAs remained less abundant than the fragments that were reproducibly generated in high amounts, both in infected and non-infected cells.RFs are an emerging group of non-coding RNAs with functional potential. Although they have been increasingly well characterized in a variety of organisms under both pathological and physiological conditions –30, 61, Our analyses demonstrated that virtually all classes of cellular RNA reproducibly generated stable RFs in Huh-7.5 cells. In accordance with findings from earlier reports , 65, 66,Our analyses also revealed that some regions of parental RNAs preferentially give rise to RFs. Among the tRFs, those with retained 5′ ends, especially tRF-5A, were the most numerous in the HCVcc model. However, another class of tRNA-derivatives, termed tRFΔ, was likewise considerable. Thus far, only a few reports have described internal tRFs , 67, 68,In view of the fact that the vast majority of tRNAs are complexed with proteins , 70, it We also found that a number of snoRNA-, snRNA- and Y RNA-derived RFs included regions relevant for the function of their parental molecules. Most snoRFs carried the conserved boxes , which is consistent with previously published data , 72. TheIn contrast to earlier reports , 72, we The results presented here suggest that RNA structure and the RNA-protein interactome are the major factors shaping RF structure and composition. Interestingly, small non-coding RNAs detected in chloroplasts have been proposed to be footprints of pentatricopeptide repeat proteins . In additRF species instead of only comparing the proportions of reads that map to particular RNA classes. In this way we were able to observe that most miRNAs accumulate to levels several orders of magnitude lower than that of miR-122. Similar patterns of relative accumulation were revealed for tRFs, snoRFs, YRFs and, to some extent, for snRFs as well. Based on the estimation that miR-122 is present at approximately 15,000 copies per cultured hepatoma cell [RFs to have functional impacts. Importantly, we discovered that not only tRFs but also the derivatives of other RNAs accumulated to levels comparable with the abundance of individual miRNAs. Selitsky and coworkers showed that derivatives of tRNA-Val and tRNA-Gly were the 2 most abundant tRFs in livers of patients with chronic hepatitis C (CHC). Their levels were increased upon infection compared to non-infected livers  but became reduced again in cancerous tissues [tRFs as being among the most abundant in Huh-7.5 cells; however, their levels were not higher than that of miR-122 and were not elevated upon HCV infection. These discrepancies can be attributed to the fact that Huh-7.5 cells are hepatoma cells and thus display the characteristics of cancerous tissue. In addition, it is plausible that the RF levels differ between the beginning of the infection (observed in the HCVcc model) and a prolonged exposure to HCV during CHC. Nevertheless, the existence of the same tRFs in Huh-7.5 cells and in liver tissues of CHC patients supports the physiological relevance of the HCVcc model for studies of non-coding RNA. This model could be applied to investigate the potential impact of tRNA-Val and tRNA-Gly fragments on the course of HCV infection.Recently Selitsky and coworkers have characterized the tRF abundance in the human liver . To thisoma cell  and thatoma cell , one can tissues . We idenRFs, we identified an 18-mer derived from a short RNA previously found to interact with tRNAseZL [L used other fragments of tRNA and rRNA as guide molecules to target mRNA of, respectively, PPM1F (protein phosphatase Mg2+/Mn2+ dependent 1F) and DYNC1H1 (dynein cytoplasmic 1 heavy chain 1). Furthermore, tRNAseZL was demonstrated to be ubiquitous in diverse cell types, including HepG2 hepatoma cells, and to be involved in the regulation of apoptosis [RFs identified in Huh-7.5 cells included also several derivatives of snoRNA. The fragments originating from SNORD44 and SNORD78 overlapped with the species recently shown to be up-regulated in malignant prostate tissue . Interestingly, a derivative of SNORD78 highly similar to the one identified in Huh-7.5 cells has been proposed as a novel prognostic biomarker of metastatic disease in prostate cancer [RFs in Huh-7.5 cells, which was also significantly up-regulated upon HCV infection at 96 hpi, was a derivative of hY4. A small RNA of the same sequence (termed ASR2) was discovered in cells infected with Eppstein-Barr virus (EBV), where it was up-regulated during the lytic phase of the viral replication cycle [Interestingly, among the 25 most abundant tRNAseZL . Althougpoptosis . In thise cancer . The lason cycle . Furtheron cycle . Our resRFs but instead elevated the accumulation of the low copy number fragments. It remains to be established to what extent this minor influence of HCV on the global RF pool is conditioned by the background of Huh-7.5 cells, which are already rich in RFs before the onset of an infection. Although increased amounts of RFs have been generally associated with cancer [Our analyses revealed that HCV infection in a cell culture model generally did not impact the highly abundant h cancer , 64, 81,h cancer . In addih cancer , 34; howh cancer .RFs, we identified several candidates that reached considerable levels and whose role in HCV infection is worth experimental evaluation  was kindly provided by T. Wakita and was used to generate high-titer stocks of cell culture-produced virus (HCVcc) according to a previously published procedure . The hummirVana miRNA Isolation Kit (Ambion) according to manufacturer’s instructions. For each of the two biological replicates, the four following RNA samples were obtained: from infected cells collected at 72 h post inoculation (hpi) (72I), from infected cells collected at 96 hpi (96I) and from the corresponding controls . A two-step isolation method was used, where the first step was the extraction of total RNA, and the second the fractionation of the total RNA into short (< 200 nt) and long (> 200 nt) RNA. Next, the integrity and purity of the RNA samples were assessed using a NanoDrop 2000 spectrophotometer (Thermo Scientific) and Bioanalyzer 2100 (Agilent) according to the manufacturers’ instructions. The samples were analyzed with a RNA 6000 Nano Assay. The representative electropherograms obtained for the sequenced samples  are shown in Additional file RNA was isolated from infected and control Huh-7.5 cells using a Each short RNA sample from one biological replicate  was used to obtain the NGS library. For this purpose, the TruSeq Small RNA kit (Illumina) was used according to the manufacturer’s instructions. Briefly, 0.5 μg of the short RNA fraction was subjected to indexed adapter ligation and reverse transcription, followed by library amplification (11 cycles). The amplified cDNA was quantified on a NanoDrop 2000 spectrophotometer (Thermo Scientific), and the product length was analyzed with a Bioanalyzer 2100 and a High Sensitivity DNA Assay (Agilent). The four samples had similar DNA concentrations (222–264 ng/μl) and DNA peak profiles. To ensure uniform size fractionation, the indexed libraries were combined and size-separated in 6% denaturing polyacrylamide gel (Novex). The fraction located between the tRNA band and adapter dimer band was collected and recovered from the gel. The effectiveness of the size selection procedure was confirmed via a High Sensitivity DNA Assay (Agilent). The entire procedure was then repeated for the second set of 72I, 72C 96I, and 96C short RNA samples. Each of the gel-eluted mixtures of the four libraries (without DNA precipitation) was sequenced independently on an Illumina Genetic Analyzer IIx for 100 cycles.The raw sequencing reads were assigned to the appropriate libraries  based on their indexes and checked for quality with Prinseq , and the2 fold change (log2FC) ≥ 2 or ≤ −2 and a false discovery rate (FDR) < 0.05 as being significantly differentially accumulated.A differential accumulation analysis was performed for representative RNA species, which were selected according to the following procedure. The sequences of all RFs derived from the same parental full-length RNA were aligned and compared. Next, in each of the obtained alignments, the RF with the highest mean abundance across all samples  was selected to initiate a cluster. Subsequently, all RFs that mapped within the same region of parental RNA and differed in length from the first one by +/− 10% were added to the cluster. If not all RFs were clustered, the next RF with the highest mean abundance among the remaining RNA species was selected to initiate the second cluster, to which suitable RFs were subsequently added. The procedure was repeated until no RFs remained ungrouped. To ensure appropriate clustering, the initial segregation results were checked. It was revealed that some RFs, because of their alignment position and length, could fit into more than one cluster. In such cases, for each of the considered clusters to which a particular RF could fit, the mean length of the remaining cluster members was calculated. The RF was assigned to the cluster for which the difference between mean length and RF length was the smallest. Finally, the representative RF for each cluster was determined. For this, we first added the mean abundances of all cluster members to obtain a total value for a cluster. Then, we calculated the summarized mean abundance for each nucleotide covered by cluster members in the parental RNA sequence. The representative RF was the one with a summarized mean abundance for each nucleotide that was not less than 40% of the total value for the cluster. In this way, we ensured that clusters were represented by the most distinctive RFs. The clustering operation reduced the initial library of RNA species. Consequently, from this stage on, the initially obtained normalized read counts could not be further considered. Therefore, the abundance of each representative RF was calculated again by adding its raw read count to the raw read counts of other RFs belonging to the same cluster. These values were then normalized by the reduced library size. Sequences of individual RNAs that mapped to a certain miRNA were assigned to one cluster. The reference sequences from miRbase were taken as representative sequences, and their abundance was calculated as described for representative RFs. In total, 1001 clusters were obtained (827 for RFs and 174 for miRNA), each represented by one RNA species and a newly calculated abundance. Subsequently, a differential accumulation analysis was performed for the representatives using edgeR and comparing infected cells to controls. We considered representative RNAs with log