Liquid-solid transition, also known as gelation, is a specific form of phase separation in which molecules cross-link to form a highly interconnected compartment with solid – like dynamical properties. Here, we utilize RNA hairpin coat-protein binding sites to form synthetic RNA based gel-like granules via liquid-solid phase transition. We show both in-vitro and in-vivo that hairpin containing synthetic long non-coding RNA (slncRNA) molecules granulate into bright localized puncta. We further demonstrate that upon introduction of the coat-proteins, less-condensed gel-like granules form with the RNA creating an outer shell with the proteins mostly present inside the granule. Moreover, by tracking puncta fluorescence signals over time, we detected addition or shedding events of slncRNA-CP nucleoprotein complexes. Consequently, our granules constitute a genetically encoded storage compartment for protein and RNA with a programmable controlled release profile that is determined by the number of hairpins encoded into the RNA. Our findings have important implications for the potential regulatory role of naturally occurring granules and for the broader biotechnology field. Condensates composed of RNA and proteins are biologically vital but generally poorly understood. Here, the authors engineer synthetic RNA-protein condensates and show that gel-like condensates form as a result of liquid-gel phase separation in a specific and selective fashion. In cells, phase separation results in the formation of membrane-less compartments containing a high-concentration mix of biomolecules , which are surrounded by a low-concentration solution. Generally, phase separations are classified by the different material states which can lead to multiple types of transitions . The forms commonly reported in cellular biology are broadly liquid-liquid and liquid-solid , however determining the exact mechanisms for phase separation in a living cellular environment is often challenging5.Phase separation, the process by which a homogeneous solution separates into multiple distinct phases, has been connected to a wide range of natural cellular processes in virtually all forms of life7. On the other hand, liquid-solid based condensates show none of the above qualities and are mainly dependent on the number of ‘cross-linkers’, which are points of contact between the molecules, rather than on the concentration of the molecules themselves10.Liquid-liquid phase transitions can be distinguished from liquid-solid by the dynamical properties of the resulting condensates. Liquid-based condensates show rapid internal rearrangement of molecules, fusions between different condensates upon contact, and dependency on the concentration of the molecules in the condensed phase11 reported on the formation of RNA granules both in vivo and in vitro, from highly repetitive RNA sequences associated with repeat expansion diseases. These RNA sequences, comprised of dozens of triplet-repeats of CAG or CUG nucleobases, form intramolecular hairpin structures12, which facilitate multivalent intermolecular interactions. The RNA granules presented features associated with liquid-solid phase transition systems: a lack of internal mobility, virtually no fusion events, and dependence on the number of repeats in the RNA sequence  rather than the concentration of the RNA. These characteristics helped establish the granules as physical solids.Recently, Jain & Vale18, and enables visualization of RNA transcripts when the CPs are co-expressed. This approach, originally introduced by Singer and others15, was devised for the purpose of probing the dynamics of transcription and other RNA-related processes, irrespective of cell-type. When co-expressed, the coat-protein-bound RNA molecules yield bright puncta, which are similar in appearance to natural biomolecular condensates. Consequently, we hypothesized that co-suspension of synthetic RNA hairpin cassettes together with their binding CPs can lead to the formation of gel-like particles via liquid-solid phase separation in vitro. In addition, by utilizing the CP binding ability of the hairpins, we expect to be able to selectively incorporate proteins of our choosing into the solid-like granules, resulting in a selective platform for the stable concentration of proteins.Hairpin forming RNA sequences are widespread in the RNA world and are not strictly associated with disease phenotypes. Such sequences are commonly used in synthetic systems for biological research. Perhaps the most ubiquitous system is composed of RNA sequences that encode for multiple hairpin motifs that can bind the phage coat proteins (CPs) of PP7 or MS2. Using this system to label the 5’ or 3’ end of a transcript has become commonplace in the last two decades21 to design and synthesize a variety of PP7 coat-protein (PCP) binding synthetic long non-coding RNA molecules (slncRNAs). Using fluorescent RNA nucleotides, we show that these slncRNAs form isolated puncta in vitro in a manner dependent on the number of hairpins encoded into the RNA. We further show that addition of fluorescent PCP to the suspension results in almost complete co-localization between protein and slncRNA. By tracking puncta fluorescence signals over time, we demonstrate that for all slncRNAs used, the various puncta emitted similar signals characterized by bursts of increasing or decreasing fluorescent intensity. We further show that signal intensities and temporal characteristics are dependent on the number of hairpins present in the RNA. Using these observations, we conclude that these “fluorescence-bursts” corresponded to addition or shedding of slncRNA-PCP nucleoprotein complexes. These events occur at rates that are consistent with the puncta being phase-separated solid-like granules. Consequently, we present these slncRNA-protein granules as a genetically encoded platform for the selective storage of proteins as well as a model system for exploration of liquid-solid phase separation.In this paper, we rely on our previous works21. We divided our slncRNAs into two groups. For the first group (class I slncRNAs), we designed three cassettes consisting of three, four, or eight hairpins that encode for PCP binding sites . In this group, hairpins were spaced by a randomized sequence that did not encode for a particular structure. For the second group (class II slncRNAs), we encoded three cassettes that consisted of three, four, and fourteen PCP binding sites that were each spaced by hairpin structures that do not bind PCP . In addition, we designed a negative control slncRNA which does not contain any hairpin binding sites. To ensure that the negative control sequence has a similar GC content as the other slncRNA molecules (45%), it was designed as a permutation of the PCP-8x sequence. The sequences encoding for the slncRNAs were cloned downstream to a pT7 promoter and transcribed in vitro to generate the corresponding RNA. To visualize the RNA, we incorporated fluorescent nucleotides in the transcription reaction such that an estimated 35% of uracil bases were tagged by Atto-488 fluorescent dye. Each slncRNA-type was separately mixed with granule forming buffer  binding-site cassettes using our binding site resourceThe images show that reactions with slncRNA molecules which contain hairpin binding sites result in the formation of a multitude of bright localized fluorescent condensates, with the exception of the PCP-3x case Fig. . InteresIn addition to the localized, small condensates, we note the formation of larger structures in the reactions prepared with the longer slncRNA molecules , consistent with a gel like solid network Fig. . We examQuantification of the area of the localized condensates shows that granule size is generally dependent on slncRNA length rather than on number of hairpins, with shorter slncRNAs resulting in smaller granules Fig. .λ = 0). For PCP-3x/MCP-3x, and PCP-4x/MCP-4x, a Poisson distribution of λ~1 seems to be the best fit. Finally, for PCP-8x, and PCP-14x/MCP-15x, a Poisson distribution of λ~2-3 fit best. These results are consistent with the formation of condensates that are characterized by an increasing number of slncRNA molecules that are cross-linked to form a gel-like “granule”, where the number of hairpins encoded into the slncRNA determines the average number of molecules or cross-links within the observed field of granules. Moreover, the interpretation suggested by the shape of the distribution is contrasted by the counter-intuitive observation of decreasing value of the of the fitting parameter K0 as a function of an increasing number of hairpins  to the granule formation reaction in large excess  to saturate the slncRNA molecules while accounting for the multiple binding sites present on one slncRNA molecule Fig. . The tdPges Fig.  show colges Fig. . FinallyTo check that the observed colocalization is due to affinity between the coat protein and the corresponding binding sites, we repeated the granule formation reactions with a tandem dimer MS2 coat protein fused to mCherry (tdMCP-mCherry) protein. In this case, granules formed with class I slncRNAs showed no colocalization with the protein, while those formed with class II slncRNAs (which contain MCP binding sites) were colocalized . This behavior indicates at the existence of an optimum point for slncRNA design in terms of number of binding sites and complexity of the design. Fig. . Togethe5 to ~103) in a step-like function as the RNA concentration is reduced from 100 to 1 nM, providing further indication that RNA is essential for granule formation. Likewise, the intensity distribution of the puncta declines in a more gradual fashion as the protein concentration is reduced, but overall, a similar disappearance of puncta is observed.Finally, we explored the phase space of SRNP granule formation. To do so, we characterized formation of the PCP-14x/MCP-15x SRNP granules as a function of both slncRNA and protein concentration. For this we produced non-fluorescent RNA molecules (for higher concentrations) and mixed different titers of slncRNA and tdPCP-mCherry protein, each varied over two orders of magnitude. Puncta like structures were detected only for slncRNA and proteins concentrations of 10 nM and 100 nM respectively, or above Fig. . The ima11, albeit at a significantly slower rate as compared with a high density liquid phase. These exchange events are predicted to occur independently of one another, at a rate which depends on multiple parameters: the probability of cross linking within the gel network , the transient concentration of the molecules in the surrounding solution, and the average diffusion rate of the monomers. The movement of molecules  between the different phases should be reflected by changes in granule fluorescence intensity.A hallmark of liquid-liquid phase separation is the exchange of molecules between the dilute phase and the dense phase. This is also true for gels with non-permanent intermolecular interactions, wherein random breaks and rearrangement of the connections which form the inner network allow macromolecules  to diffuse in and out of the gel phasep-value<1e-3) , and the 585 nm channel (for protein), of each granule in a given field-of-view for 60 min. We analyzed the brightness of each granule at every time point using a customized analysis algorithm . The resulting signals are either decreasing or increasing in overall intensity, and dispersed within them are sharp variations in brightness, that are also either increasing or decreasing. Next, we employed a statistical threshold which flagged these signal variation events, whose amplitude was determined to not be part of the underlying signal distribution p-value<e-3 . Together, this indicates that slncRNA degradation occurs outside of the granules, while inside the structure they seem to be protected from degradation, consistent with a gel-like phase.To confirm that we are observing entry and shedding events of what are likely single slncRNA molecules into and out of the fluorescent granules vis-a-vis the signal bursts, we tracked the intensity of PCP-14x/MCP-15x RNA-only granules with and without the presence of RNase A. We first found that at enzyme concentrations above 35 nM, no granules were observed whatsoever, indicating correct activity of the enzyme. At a concentration of 35 nM we were able to track identified granules for at least 60 min. Figure We then proceeded to gather statistical tracking data for granules produced from all previously described slncRNA designs (including the PP7-3x which does not phase separate on its own at our working concentration). Comparison of the amplitude distributions per design (class I vs. II), Fig.  reveals 24, but is in line with the measurements performed on RNA gels by Vale et. al.11, providing additional confirmation that the SRNP granules are gel-like particles  is two orders of magnitude above the typical rate observed in liquid phase separated condensatesles Fig. . Examinales Fig. -top. Entles Fig. -bottom. We next carried out protein exchange or competition experiments on PCP-14x/MCP-15x granules and measured the dynamics and time-scales associated with protein replacement. To do so we initially prepared PCP-14x/MCP-15x granules with tdPCP-mcherry and allowed the system to equilibrate. Then, immediately prior to imaging, we added tdPCP-mCerulean and observed the granule dynamics in all three channels . Altogether, we tracked 39 co-labeled granules in multiple experiments. Tracking of the formed granules in both channels  reveals a variety of signals, indicating various types of mixing of the two labels. For instance, we observed events of apparent displacement where one signal increases as the other decreases Fig. -right inComparing the total number of events in both channels during the first 20’ reveals that while the number of entry events is similar Fig. . This anWe next examined the burst amplitudes as a function of tracking duration intervals Fig.  in the mTo provide a measure for the number of slncRNA molecules within the granules, we computed the ratio between the mean granule fluorescence and the mean burst amplitude, assuming the average burst corresponds to one slncRNA molecule bound by proteins. The results Fig.  show thaTo further characterize the “capacitor-like” behavior of the type II granules, we performed a titration experiment with PCP-14x/MCP-15x slncRNAs. We formed granules with a constant slncRNA concentration (120 nM) and different protein concentrations, resulting in a 1:1, 10:1 and 100:1 protein to RNA ratio. We collected shedding burst data for each condition and calculated the previously reported observables. Comparison of the shedding burst amplitudes Fig.  reveals 19. The first slncRNA is of a class II design, PCP-4x/ QCP-5x, consisting of four native PCP binding sites and five native Qβ coat protein (QCP) hairpins used as spacers in an interlaced manner. The second slncRNA is the ubiquitous PCP-24x cassette25, which from the perspective of this work can be regarded as a class I design slncRNA.Given the capacitor analogy, we hypothesized that in vivo the granules can be used as devices that store granule-bound proteins indefinitely. This is due to the steady state production of slncRNAs and proteins via the cellular transcriptional and translational machinery, that ensures a constant flux of proteins into the granules. To show this, we first proceeded to test whether the granule material characteristics that are measured in vivo match the in vitro measurements. To do so, we decided to utilize two previously reported slncRNA designs which were shown to yield bright localized puncta in vivo in earlier workE. coli cells. Examination of cells expressing the slncRNA and protein following overnight induction of all components revealed the formation of bright puncta at the cell poles  expression vector which is maintained at a single copy level in cells. We found that cells containing the multicopy plasmid frequently present puncta in at least one of the poles, while cells containing the single copy generally show between zero and one punctum Fig. . Given t26  in terms of the spot per cell fraction. Much like in the in vitro experiments, we found a dependence on the number of binding sites in accordance with the in vitro results and the cross linking model of gel phase formation26 Fig. . FinallyTo investigate the dynamic properties of granules formed in vivo, we utilized the same analysis approach as was used in the in vitro experiments, with minor differences. Normalizing the fluorescence of the granule by that of the cell  for every time point results in a signal vs. time trace largely independent from the effects of photobleaching and cellular background noise, allowing us to search for and measure burst events, as was done previously. In Fig. Next, we measured the amplitudes of the bursts for both slncRNAs and found that positive and negative amplitudes are proportional to the number of binding sites within the encoded cassette Fig. . In addiNext, to ascertain whether the granules facilitate increased protein titers in vivo in accordance with the capacitor model predictions, we measured for each bright granule the mean fluorescence intensity Fig. , and theIn this study, we show that synthetic gel-like RNA—protein granules can be designed and assembled using phage coat proteins and RNA molecules that encode multiple CP hairpin binding sites, both in suspension and in vivo. Using fluorescently labeled RNA, we show that granule formation is nucleated by RNA-RNA interactions that are proportional to the number of hairpins encoded into the RNA. In addition, the binding of the proteins seems to further enhance and assist the granule formation process. Using fluorescent single molecule signal analysis, we reveal entry and shedding events of molecules into and out of the granules. By investigating their size and rate of occurrence, we show that these events correspond to entry and shedding of protein-bound slncRNA molecules, and that they are dependent on the number of hairpins available for protein binding. Transitioning of macro-molecules across a phase boundary is frequently observed in phase-separated condensates, particularly in liquld-liquid based system. In particular, the frequency of these transitions reflects the underlying order, internal interactions, and density of the condensed phase. While in liquid-liquid phase separation systems such transitions occur on the scale of seconds or less, here we observe shedding and insertion events on a much longer time scale of minutes or longer, that is more consistent with a solid or gel-like condensed phase. We provide additional evidence for the liquid-gel phase transition underlying the granulation process, by taking the system out of equilibrium and observing the different equilibration times of the dilute solution and dense granule phases. To do so, we used a binding competitor in one experiment and RNAse in the other. For those experiments, the liquid phase showed rapid mixing in the former and substantial catalysis in the latter, while the granule phase showed slow mixing and undetectable amount of catalysis, respectively. The out-of-equilibrium experiments allowed us to differentiate between the liquid-gel transition from the other options which include liquid-liquid, liquid-glass, and liquid-solid transition. As a result, we believe that equilibrium characterizations should be considered a standard tool in similar biomolecular phase separation studies.We further characterized two options for slncRNA design: a homogeneous design which is comprised of multiple CP hairpin binding site and non-structured spacing regions (class I), and a hybrid design which is comprised of hairpin binding sites and additional hairpins in the spacing regions (class II). We show that the design choice has implications for the granule’s protein-carrying capacity and dynamics. In particular, class II granules formed particles with increased cross-linking capability in the RNA-only granule, which in turn led to an increased ability to insulate the protein cargo in the SRNP granule phase. On the flip side, class I granules were characterized by decreased cross-linking in the RNA-only phase and increased permeability of the protein cargo in the SRNP-granule phase. In addition, class I granules displayed a faster shedding or dissolution rate, which in turn lead to a smaller protein cargo on average. The slow release and strong internal interactions which keep the granules intact for long durations within a gel-like phase, combined with the selectivity of our system due to the RNA binding component, could be utilized as a programmable controlled release mechanism in suitable biological settings. Hence, our granules can be thought as protein and RNA storage modules akin to a capacitor, with ‘capacitance’ that is dependent on protein concentration, and a monophasic release profile that can be tuned based on slncRNA design. This two-dimensional phase space of capacity vs. rigidity offers substantial flexibility and tunability when designing SRNP granules for a variety of applications.11. Further studies will be required to explore the biological relevance of SRNP granules to the survivability of cells and organisms under various forms of stress, and to potential underlying mechanisms for various diseases.The capacitor- or storage-like behavior displayed by the SRNP granules implies that in vivo, the granules together with the gene-expression machinery form a biochemical analog of an RC-circuit. In a conventional RC-circuit, energy is stored within the capacitor for release at a later time. Such circuits are often used to protect electrical devices against sudden surges or stoppages of power. Here, the protein and slncRNA flux into the cytosol correspond to the current, which results in the formation of fully “charged” SRNP granules. This genetically encoded slncRNA and protein storage facility, which is constantly maintained, effectively increases the protein and slncRNA content of the cell beyond the steady-state levels facilitated by standard transcription, translation, RNA degradation, and proteolysis. This storage capacity is precisely the function that is carried out by capacitors in RC-circuits, allowing electrical devices to function even after “power” is cut-off. In the case here, the granules can be used not only to increase levels of a protein of choice by nearly an order of magnitude  was used for cloning procedures.http://n2t.net/addgene:31864; RRID: Addgene_31864).pCR4-24XPP7SL was a gift from Robert Singer .pBAC-lacZ was a gift from Keith Joung , as part of a puc57 plasmid, flanked by EcoRI and HindIII  restriction sites. pBAC-lacZ backbone plasmid was obtained from Addgene (plasmid #13422). Both insert and vector were digested using the said restriction enzymes and ligated to form a circular plasmid using T4 DNA ligase . Sequence was verified by sanger sequencing.21. Briefly, RBP sequences lacking a stop codon were amplified via PCR off either Addgene or custom-ordered templates. Both RBPs presented (PCP and QCP) were cloned into the RBP plasmid between restriction sites KpnI and AgeI , immediately upstream of an mCherry gene lacking a start codon, under the so-called RhlR promoter containing the rhlAB las box31 and induced by N-butyryl-L-homoserine lactone (C4-HSL) . The backbone contained either an Ampicillin (Amp) or Kanamycin (Kan) resistance gene, depending on experiment.Fusion-RBP plasmids were constructed as previously reportedA vector containing the slncRNA DNA sequence, flanked by two EcoRI restriction sites, was digested with EcoRI-HF per the manufacturer’s instructions to form a linear fragment encoding the slncRNA sequence. The enzyme was then heat-inactivated by incubating the restriction reaction at 65 °C for 20 min. For fluorescently labeled RNA, 1 µg of the restriction product was used as template for in vitro transcription using HighYield T7 Atto488 RNA labeling kit , according to the manufacturer’s instructions. Non-fluorescent RNA was transcribed using the HiScribe™ T7 High Yield RNA Synthesis Kit . Following in vitro transcription by either kit, the reaction was diluted to 90 µl and was supplemented with 10 µl DNAse I buffer and 2 µl DNAse I enzyme (NEB #M0303S) and incubated for 15 min at 37 °C to degrade the DNA template. RNA products were purified using Monarch RNA Cleanup Kit  and stored in −80°.E. coli cells expressing fusion proteins (tdPCP-mCherry / tdPCP-cerulean / tdMCP-mCherry) were grown overnight in 10 ml LB with appropriate antibiotics at 37 °C with 250 rpm shaking. Following overnight growth, cultures were diluted 1/100 into two vials of 500 ml Terrific Broth , with appropriate antibiotics and induction (500 μl C4-HSL) and grown in 37 °C and 250 rpm shaking to optical density (OD) > 10. Cells were harvested, resuspended in 30 ml resuspension buffer , disrupted by four passages through an EmulsiFlex-C3 homogenizer , and centrifuged  to obtain a soluble extract. Fusion protein was purified using HisLink Protein purification resin  #V8821) according to the manufacturer’s instructions. Buffer was changed to 1xPBS  using multiple washes on Amicon ultra-2 columns .In vitro experiments were performed in granule buffer . Reactions were set up at the appropriate concentrations and allowed to rest at room temperature for 1 h. 3–5 µl from the reaction was then deposited on a glass slide prior to microcopy.For the RNase experiment, granules were first formed as described and allowed to rest at room temperature for 1 h. Following this, RNase A enzyme  was added at 35 nM final concentration. The reaction was then immediately deposited on a glass slide and proceeded to imaging.For the competition experiment, granules were first formed with tdPCP-mCherry at a final concentration of 40 nM and allowed to rest at room temperature for 1 h. Following this, tdPCP-mCerulean was added to the reaction at 80 nM final concentration prior to imaging.32. 1.5 μl cell culture was deposited on a gel slide and allowed to settle for an additional 30 min before imaging.BL21-DE3 cells expressing the two plasmid system  were grown overnight in 5 ml Luria Broth (LB), at 37° with appropriate antibiotics , and in the presence of two inducers – 1.6 µl Isopropyl β-D-1-thiogalactopyranoside (IPTG) , and 2.5 µl C4-HSL  to induce expression of T7 RNA polymerase and the RBP-FP, respectively. Overnight culture was diluted 1:50 into 3 ml semi-poor medium consisting of 95% bioassay buffer  and 5% LB with appropriate antibiotics and induced with 1 μl IPTG  and 1.5 μl C4-HSL . For stationary phase tests, cells were diluted into 3 ml Dulbecco’s phosphate-buffered saline (PBS) with similar concentrations of inducers and antibiotics. Culture was shaken for 3 h at 37° before being applied to a gel slide Granules were imaged in a Nikon Eclipse Ti-E epifluorescent microscope  with a 100×1.45 NA oil immersion objective. Excitation was performed by a CooLED  PE excitation system at 488 nm (Atto 488) for experiments containing fluorescent RNA, 585 nm for mCherry protein, and 405 nm for cerulean protein. Images were captured using the Andor iXon Ultra EMCCD camera with a 250 msec exposure time for 488 nm, 250 msec exposure time for 585 nm, and 2 seconds for 405 nm. Microscopy control and data acquisition was performed using Nikon NIS-Elements version 4.20.02 (build 988) 64 bit.Fluorescence quenching for the granules was estimated by first placing each slncRNA sequence on a two-dimensional space, with the x-axis being the estimated number of fluorescent uracil nucleotides (assuming 35% labeling efficiency), and the y-axis being the normalized RNA-only granule fluorescence values as depicted in Fig. Gel slide was kept at 37° inside an Okolab microscope incubator . A time lapse experiment was carried out by tracking a field of view for 60 min on Nikon Eclipse Ti-E epifluorescent microscope  using an Andor iXon Ultra EMCCD camera at 6 frames-per-minute with a 250 msec exposure time per frame. Excitation was performed at 585 nm (mCherry) wavelength by a CooLED  PE excitation system. Microscopy control and data acquisition was performed using Nikon NIS-Elements version 4.20.02 (build 988) 64 bit.Quantification of the fraction of cells presenting puncta was done by taking 10–15 snapshots of different fields of view (FOV) containing cells. The number of cells showing puncta and the total number of fluorescent cells in the FOV were counted manually.Super resolution images were captured using the Elyra 7 eLS lattice SIM super resolution microscope  with an sCMOS camera, a 63×1.46 NA water immersion objective, with a 1.6x further optical magnification. 405 nm, 488 nm and 585 nm lasers were used for excitation of the cerulean, Atto-488, and mCherry respectively. Microscope control and data acquisition was performed using ZEN Black version 3.3.89. 16-bit 2D image sets were collected with 13 phases and analyzed using the SIM^2 image processing tool by Zeiss.E. coli BL21 cells were grown overnight, diluted 1:100 the next day and grown until OD of 0.3. Cells were diluted 1:10 in 1xPBS in a 1.5 ml tube and vortexed. Samples and appropriate controls were loaded onto a 96-wells plate  in triplicates, each well containing 100 μl of the diluted bacterial cells. The cells were then measured using flowcytometry , with the 561 nm excitation laser and the Y2 detector channel (a 615/20 nm filter). The flowcytometer was calibrated using MacsQuant calibration beads (Miltenyi Biotec) before measurement. Running buffer, washing solution, and storage solution were all purchased from the manufacturer . Voltages for the SSC, FSC, and mCherry (Y2) channel were 467, 313, and 333 volts, respectively.IPTG / C4HSL-induced or non-induced Events were defined using an FSC-height trigger of 3. An FSC-area over SSC-area gate (gate-1) was created around the densest population in the negative control (non-induced cells), and events falling inside this gate were considered live bacteria. From the gate-1-positive cells, an SSC-height over SSC-area gate (gate-2) was created along the main diagonal, and events falling inside this gate were considered single bacterium. Finally, from the gate-2-positive cells, a histogram of mCherry distribution was created, with the threshold for mCherry-positive cells set by leaving around 0.1% positive events in the negative control.35. A typical field of view usually contained dozens of granules (in-vitro) or cells containing puncta (in vivo)  in the field of view were tracked over time and space via the imageJ MosaicSuite pluginx,y,t coordinates of the bright spots centroids), together with the raw microscopy images were fed to a custom built Matlab  script designed to normalize the relevant spot data. Normalization was carried out as follows: for each bright spot, a 14-pixel wide sub-frame was extracted from the field of view, with the spot at its center. Each pixel in the sub-frame was classified to one of three categories according to its intensity value. The brightest pixels were classified as ‘spot region’ and would usually appear in a cluster, corresponding to the spot itself. The dimmest pixels were classified as ‘dark background’, corresponding to an empty region in the field of view. Lastly, values in between were classified as ‘cell background’  not relating to the spot itself, and photobleaching. This can be described as follows:Where To find This leads to:rd degree polynomial . This is done to capture the general trend of the signal while completely eliminating fluctuations due to random noise.To get We assume the total fluorescence is comprised of three distinct signal processes: RNP granule fluorescence, background fluorescence and noise. We further assume that background fluorescence is slowly changing, as compared with granule fluorescence which depends on the dynamic and frequent insertion and shedding events occurring in the droplet. Finally, we consider noise to be a symmetric, memory-less process. Based on these assumptions, we define a “signal-burst” event as a change or shift in the level of signal intensity leading to either a higher or lower new sustainable signal intensity level. To identify such shifts in the base-line fluorescence intensity, we use a moving-average filter of 13 points  to smooth the data. The effect of such an operation is to bias the fluctuations of the smoothed noisy signal in the immediate vicinity of the bursts towards either a gradual increase or decrease in the signal  and Ntot correspond to the number of increasing instantaneous events and total number of events in a trace respectively. Likewise, the number of decreasing instantaneous events is defined as:To translate this probability to a computational threshold, we first compute the intensity difference distribution for every trace separately. This distribution is computed by collecting all the instantaneous differences in signal m) to satisfy our 1 in 1000 threshold for a significant signal increase burst event m as follows:This in turn allows us to compute the number of consecutive instantaneous signal increase events . Furthermore, since the moving average filter itself can induce correlations in the signal, we determined that the minimum allowed threshold is the moving average window span. This means that any calculated threshold lower than the moving average size is increased to this bare minimum.We mark each trace with the number of events whose duration exceeds the threshold and define those as bursts. Segments within the signal that are not classified as either a negative or positive burst event are considered unclassified. Unclassified segments are typically signal elements whose noise profile does not allow us to make a classification into one or the other event-type. For each identified segment we record the amplitude , and K0 is a fitting parameter whose value corresponds to the amplitude associated with a single RBP-bound slncRNA molecule within the burst. For each rate we chose the fit to K0 that minimizes the deviation (MSE) from the experimental data. Fits were validated by observing the resulting QQ-plots.Given the fact that we cannot directly infer the fluorescence intensity associated with a single RNA-RBP complex, we fitted the distributions with a modified Poisson function of the form:Each granule formation reaction and subsequent microscopy experiment was successfully repeated in duplicate on multiple days as follows: PCP-3x – 4 days; PCP-4x – 3 days; PCP-8x – 3 days; PCP-3x/MCP-3x – 2 days; PCP-4x/MCP-4x – 2 days; PCP-14x/MCP-15x – 4 days.RNase A degradation experiments were repeated in duplicate on 2 separate days. Titration experiments were repeated in triplicate on 2 separate days. Super resolution microscopy was repeated on 3 separate days. In-vivo experiments were repeated in triplicate over 5 separate days. Flow cytometry measurements were performed in triplicate.Further information on research design is available in the supplementary informationPeer Review FileDescription of additional Supplementary Filesupplementary data 1Reporting Summary


Long non-coding RNAs (lncRNAs) belong to a class of non-protein-coding RNAs with their lengths longer than 200 nucleotides. Most of the mammalian genome is transcribed as RNA, yet only a small percent of the transcribed RNA corresponds to exons of protein-coding genes. Thus, the number of lncRNAs is predicted to be several times higher than that of protein-coding genes. Because of sheer number of lncRNAs, it is often difficult to elucidate the functions of all lncRNAs, especially those arising from their relationship to their binding partners, such as DNA, RNA, and proteins. Due to their binding to other macromolecules, it has become evident that the structures of lncRNAs influence their functions. In this regard, the recent development of epitranscriptomics (the field of study to investigate RNA modifications) has become important to further elucidate the structures and functions of lncRNAs. In this review, the current status of lncRNA structures and functions influenced by epitranscriptomic marks is discussed. By definition, long non-coding RNAs (lncRNAs) are any ncRNAs that are longer than 200 nucleotides (nt). With the advancement of high-throughput techniques , many lncRNAs have been discovered . To date6-methyladenosine (m6A), which is a methylation of nitrogen-6 position of adenosine (A) found in messenger RNAs (mRNAs) and non-protein-coding RNAs (ncRNAs). Other epitranscriptomics marks in mammals include the A-to-I RNA editing, 2′-O-methylation (2′-O-Me), N1-methyladenosine (m1A), 3-methylcytidine (m3C), 5-methylcytosine (m5C), N7-methylguanosine (m7G), pseudouridylation (Ψ) to name a few , recognize dsRNAs to catalyze adenosine to inosine (A-to-I) conversion, mostly at ALU repeats and introns [ADAR1 gene result in the autoimmune disease, Aicardi-Goutières syndrome, while the whole-body knockout mice of Adar1 results in embryonic death due to massive apoptosis and aberrant interferon induction, which can be rescued to live birth by ablating the RLRs, Mavs or Mda5 (melanoma differentiation-associated protein 5) [ADAR1 in the human hepatocellular carcinoma cell line, HepG2, resulted in shifting of dsRNAs to ssRNAs at the transcriptome-wide level [6A, if not edited [6A, could competitively affect the secondary structures of lncRNAs, thereby, influencing the binding of other macromolecules.A-to-I RNA editing is a type of epitranscriptomic mark that involves the RNA editing enzymes, ADARs [adenosine deaminases acting on RNA, consisting of three genes:  introns . ALU rep introns . Two tra introns . I is re introns . Mutatiootein 5) ,70,71. Botein 5) ,73  bind ssRNAs or dsRNAs to modulate their stability and translation . RBPs altability ,80,81. Ctability ,83,84. Itability ,86. Indetability , POSTAR2tability , and statability . Thus, itability .ELAVL1 gene) [LINC02381, that stabilizes the 3′-untranslated region (UTR) of the HOXC10 mRNA via HuR [https://darned.ucc.ie, accessed on 2 February 2022), nor m6A site  in the 3′-UTR of HOXC10 gene, an 5-methylcytosine (m5C) site  is present in the 3′-UTR of HOXC10 gene, which calls for further investigation of this region to understand the causal relationship between lncRNA, RBP, and epitranscriptomic marks.RBPs can either stabilize or degrade the bound RNA  Figure . Given tL1 gene) . This stL1 gene) ,94. Furt via HuR . Interes via HuR ,97, httpdatabase , http://database , http://6A readers: YTHDF1-3, YTHDC1, YTHDC2, HNRNPC, RBMX (HNRNPG), IGF2BP1-3 [6A sites, a convenient tool called, m6Adecom, was introduced recently [Given that many epitranscriptomic readers are RBPs , itrecently . HoweverAPOLO [HOTTIP [TERRA [R-loops (RNA loops) are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA, leading to a displaced single-stranded DNA (ssDNA). These structures typically result from nascent transcription at regions of high GC-skew, such as CpG islands in gene promoters . When imAPOLO , HOTTIP  [HOTTIP , and TERP [TERRA ,118,119,P [TERRA   forms an R-loop, leading to chromatin remodeling and expression of the sense vimentin (VIM) gene [TARID  forms an R-loop which leads to GADD45A recruitment, demethylation, and expression of TCF21 mRNA [GATA3-AS1 (GATA3 antisense RNA 1) forms an R-loop which promotes permissive chromatin marks and expression of GATA3 mRNA [ANRASSF1 (RASSF1 antisense RNA 1) forms an R-loop that recruits PRC2 to repress the RASSF1 gene [COOLAIR forms a cis R-loop to repress transcription at the FLC locus in Arabidopsis [R-loops form readily both from protein-coding and non-coding RNA species, particularly lncRNAs ,128. HowIM) gene . In a siF21 mRNA . FinallyTA3 mRNA . ConversSF1 gene . Additiobidopsis . These ebidopsis . A propobidopsis . HoweverTERRA (telomeric-repeat-containing RNA) forms R-loops in trans at telomeres, also in a RAD51 (DNA repair protein)-dependent manner [GAL forms R-loops which promote rapid adaptation to changing nutrient availability [APOLO lncRNA forms an R-loop which regulates the PID gene in cis and multiple auxin-responsive target genes in trans to promote lateral root development [lncRNA forms an R-loop in trans via the invasion of duplex DNA distal to the site of lncRNA transcription. Wahba et al. first described this phenomenon in a 2013 study, which found that lncRNAs form trans R-loops via the action of Rad51p in yeast . Subsequt manner . Howeverlability . Curiouslability , suggestelopment .Myogenin locus [HOTTIP  forms trans R-loops and promotes cohesin binding and long-range enhancer interactions [Recent work suggests lncRNA formation of trans R-loops may also play a role in supporting long-range chromatin interactions and enhancer formation via the cohesin complex. The cohesin complex is a multiunit complex comprising the SMC1/3, RAD21, and STAG1/2 proteins. It forms a ring structure responsible for establishing and maintaining 3D chromatin architecture . Previouin locus . Moreovein locus . Finallyractions . Taken t6A marks are highly studied. As it is evident that lncRNAs are modified by various epitranscriptomic enzymes, it is still difficult to understand what these epitranscriptomic marks mean for the functions of lncRNAs with largely unknown functions. Furthermore, a recent study about epitranscriptomic marks on tRNAs show that epitranscriptomic marks affect tertiary structures of tRNAs [While functional characterizations of lncRNAs have intensified in the past decade, the identification and characterization of various epitranscriptomic marks are still at their infancy as only mof tRNAs , suggest


In addition, GC content and plastomic size were positively correlated with the number of chloroplast RNA editing sites in gymnosperms, suggesting that the increase in GC content could provide more materials for RNA editing and facilitate the evolution of RNA editing in land plants or vice versa. Interestingly, novel G-to-A RNA editing events were commonly found in all sampled gymnosperm species, and G-to-A RNA editing exhibits many different characteristics from C-to-U RNA editing in gymnosperms. This study revealed a comprehensive evolutionary scenario for chloroplast RNA editing sites in gymnosperms, and reported that a novel type of G-to-A RNA editing is prevalent in gymnosperms.Although more than 9100 plant plastomes have been sequenced, RNA editing sites of the whole plastome have been experimentally verified in only approximately 21 species, which seriously hampers the comprehensive evolutionary study of chloroplast RNA editing. We investigated the evolutionary pattern of chloroplast RNA editing sites in 19 species from all 13 families of gymnosperms based on a combination of genomic and transcriptomic data. We found that the chloroplast C-to-U RNA editing sites of gymnosperms shared many common characteristics with those of other land plants, but also exhibited many unique characteristics. In contrast to that noted in angiosperms, the density of RNA editing sites in  HoweveSelaginella uncinata, whereas fewer than 200 editing sites were found in angiosperm chloroplasts [Arabidopsis, Nicotiana, or Oryza [The number of chloroplast C-to-U RNA editing sites varies greatly in different plants; however, the monophyletic origin of RNA editing has been proposed . Many orroplasts ,19,20. Iroplasts , and chlor Oryza ,19. Receor Oryza . Plant cor Oryza ,23,24,25or Oryza . In addior Oryza . In theiKeteleeria davidiana and five species from five genera of Conifer II [As the sister group of angiosperms, gymnosperms represent five of the six lineages of seed plants, i.e., Cycadales, Ginkgoales, Gnetales, Pinaceae, and Conifer II (non-Pinaceae conifers or Cupressophyta), which diverged before the Jurassic ,27. Prevnifer II . Recentlnifer II . HoweverIn this study, the evolutionary pattern of chloroplast RNA editing sites was investigated in 19 species from all 13 families of gymnosperms based on a combination of genomic and transcriptomic data, and a novel type of RNA editing sites, G-to-A was found to be widespread in gymnosperms. In addition, the characteristics of chloroplast C-to-U RNA editing sites in gymnosperms were compared with those in other land plants. Finally, the correlations between the abundance of RNA editing sites and some important factors, such as plastomic size, GC content, and nucleotide substitution rate, were assessed. This study will shed new light on the evolution of chloroplast RNA editing in gymnosperms, even in land plants.Ephedra przewalskii) to 164,957 bp (Zamia furfuracea) and 34.7% to 39.7%, respectively. In addition, the number of chloroplast genes ranged from 111 (Pinus armandii) to 134 (Zamia furfuracea), including 65–88 protein coding genes, 4–8 rRNA genes, and 28–41 tRNA genes.The plastomic size, GC content, and gene number  of 19 gymnosperms are shown in rrn23, one in the intergenic region, and one in the CDS region of the ycf1 gene   . Generalctively) . Second,ctively) . Third, nifer II . Finallynifer II a. Fourthnifer II . Finallynifer II .rpl20-296) was shared in all gymnosperm lineages. In addition, Cycadales and Ginkgoaceae shared 37 sites, whereas Conifer II and Cycadales only had 6 common editing sites , GC and C content , but insignificantly negatively correlated with Nd (nonsynonymous substitution rates), Sd (synonymous substitution rates), NR (absolute nonsynonymous substitution rates per branch), and SR (absolute synonymous substitution rates per branch) (The Pearson correlation coefficient showed that the number of RNA editing sites was significantly positively correlated with plastomic size ( branch) .Betula platyphylla [Vigna species [Betula platyphylla and Vigna species from Leguminosae [Vigna, supporting the idea that RNA editing is a mechanism to correct mutations in the genomic coding sequences [In this study, we found that G-to-A, a novel type of RNA editing site, is common in our sampled gymnosperm species. Although the number of G-to-A editing sites is small (only 71) and the editing efficiency is low, the reliability of the G-to-A RNA editing sites was confirmed . So far,typhylla  and Vign species . Based ouminosae ,37, the uminosae ,40,41,42equences ,43. In aequences , a smallequences , such asBetula platyphylla and Vigna species, the number of chloroplast G-to-A RNA editing events in gymnosperms is very low, and the editing efficiency of most edited sites is relatively low. However, G-to-A RNA editing was present not only in protein-coding genes but also in rRNA genes and intergenic regions and rarely in tRNA genes, which was different from that noted in angiosperms , rrn23 (Similar to iosperms . The G-t), rrn23 , implyinGinkgo biloba. More sites in Pinaceae and Gnetales appeared in the third codon position, whereas the G-to-A RNA editing sites in Conifer II mainly occurred in the first and third codon positions  was shared by all gymnosperm lineages and there were more RNA editing sites shared by the close-related taxa , similar to angiosperms [Arabidopsis growth to maturity but have significant selective advantages for individuals in which environmental conditions are less than optimal, which could be the reason why few RNA editing sites were shared in gymnosperms and angiosperms . In addn et al. . Therefondh genes encoding subunits of the NADH degydrogenase-like (NDH) complex and the rpo genes encoding subunits of the DNA-dependent RNA polymerase, which is similar to that noted in angiosperms [rpo, psb, or pet genes in Pinaceae and Gnetales due to the absence of all ndh genes [ndh genes was not the highest in sampled gymnosperms , especially C content , was positively correlated with the number of chloroplast RNA editing sites in gymnosperms   a. Differng sites d–g. In fThe correlation between the frequency of RNA editing sites and the diversity of PPR proteins has been frequently reported in plants. Particularly, the evolutionary distribution of organelle RNA editing and the DYW domains seemed to correlate well along land plant phylogeny ,75,76. HThe evolutionary pattern of chloroplast RNA editing sites was investigated in 19 species from all 13 families of gymnosperms based on a combination of genomic and transcriptomic data. In total, 1435 chloroplast RNA editing sites were identified from 19 gymnosperms, including 1364 C-to-U and 71 G-to-A RNA editing sites. Interestingly, G-to-A RNA editing events are common in gymnosperms but have many different characteristics from C-to-U RNA editing sites. It still remains a mystery why G-to-A RNA editing appears in plants. Multiple proteins are required for C-to-U RNA editing in plants, but there is no evidence that these proteins can be involved in G-to-A RNA editing because direct modification of G to A requires amination at the C6 position and concomitant deamination at the C2 position, which is quite different from the process of C-to-U RNA editing. We speculated that G-to-A RNA editing sites could have been neglected due to that chloroplast RNA editing has only been studied in detail in a few species, leading to the fact that they were currently only found in a small number of taxa outside gymnosperms. This type of RNA editing sites will be found in more species and the molecular mechanisms behind G-to-A RNA editing will be gradually unraveled with chloroplast RNA editing being studied in an increasing number of land plants in the future. In addition, the chloroplast C-to-U RNA editing sites of gymnosperms share many common characteristics with other land plants, supporting the monophyletic origin of RNA editing sites. However, they also have many unique characteristics, such as the distribution patterns and loss and gain histories in protein-coding genes. Finally, GC content and plastomic size were positively correlated with the number of chloroplast RNA editing sites in gymnosperms, but further research is needed to test whether this correlation exists widely in land plants.https://www.bioinformatics.babraham.ac.uk/projects/fastqc/, accessed on 5 January 2022). Then, the low-quality reads were filtered and the adaptor sequences were trimmed using Trimmomatic (ILLUMINACLIP:TruSeq3-PE-1.fa:2:30:10 LEADING:20 TRAILING:20 MINLEN:36) [In total, 19 species from all 13 families of gymnosperms were sampled . The DNANLEN:36) . Detailek-mer values set to 21, 33, 55, 77, 99, and 127  [To ensure assembly reliability, the plastomes of 19 species were assembled using the following approach. First, we applied Bowtie2 v 2.2.9   to buildcareful) . Finallycareful) . Based oA BLASTN search was performed to annotate protein-coding genes and ribosomal RNAs (rRNAs) using a local database of extracted gene sequences from published gymnosperm plastomes with evalue and identify sets of 1e-5 and 0.85, respectively, and tRNAscan-SE v.2.0.3   was used to annotate the transfer RNAs (tRNAs) . The annGnetum montanum) with few RNA editing sites to visualize its bam files (Binary Alignment/Map file: a compressed binary format of Sequence Alignment/Map (SAM) file (.sam), which is used for storing the sequence alignment information) of aligned RNA reads from RES-Scanner using Integrative Genomics Viewer (IGV) v. 2.4.10  [RNA editing sites of all plastomes were identified using RES-Scanner , which cge, USA) . Second,Amborella trichopoda [Nymphaea ”Joey Tomocik” and Liriodendron tulipifera [Intersections among edited sites of coding regions in five lineages and 19 species were evaluated using UpSetR v.1.4.0  . The anclipifera  were selSd and Nd), and absolute rates of substitutions per branch (SR and NR), were related to the abundance of RNA editing sites. The substitution rates were calculated following the study of Kan et al. [https://www.python.org/ (accessed on 12 March 2022). The scatter diagram and regression line between the number of RNA editing sites and each factor were drawn using the “geom_point” and “geom_smooth” functions in the ggplot2 package of R 4.0.2 .Pearson correlation coefficient analysis was employed to test whether some factors, such as plastomic size, chloroplast GC and C content, synonymous and nonsynonymous rates (n et al. . The Pean et al.  of Pytho


NORAD, an intronless cytoplasmic long noncoding RNA (lncRNA), and found an RNA binding protein, RBM33, that directs the nuclear export of NORAD and numerous other transcripts. These results provide a broadly applicable strategy for the genetic dissection of nuclear export mechanisms and reveal a long-sought nuclear export pathway for transcripts with GC-rich sequences.In this study, Thomas et al. developed a genome-wide screening strategy to investigate the mechanism of export of  NORAD, an intronless cytoplasmic long noncoding RNA (lncRNA). This screen revealed an RNA binding protein, RBM33, that directs the nuclear export of NORAD and numerous other transcripts. RBM33 directly binds substrate transcripts and recruits components of the TREX–NXF1/NXT1 RNA export pathway. Interestingly, high GC content emerged as the feature that specifies RBM33-dependent nuclear export. Accordingly, RBM33 directly binds GC-rich elements in target transcripts. These results provide a broadly applicable strategy for the genetic dissection of nuclear export mechanisms and reveal a long-sought nuclear export pathway for transcripts with GC-rich sequences.Although splicing is a major driver of RNA nuclear export, many intronless RNAs are efficiently exported to the cytoplasm through poorly characterized mechanisms. For example, GC-rich sequences promote nuclear export in a splicing-independent manner, but how GC content is recognized and coupled to nuclear export is unknown. Here, we developed a genome-wide screening strategy to investigate the mechanism of export of  Nuclear export of RNA is a highly coordinated process that facilitates the selective transport of processed transcripts to the cytoplasm while retaining partially processed or misprocessed transcripts in the nucleus. This selectivity is achieved through the controlled deposition of specific proteins on an export-competent RNA following the completion of processing events such as capping, splicing, and polyadenylation . The cancis-element called the REV response element (RRE) in incompletely spliced viral RNAs, routing them through the CRM1-dependent protein export pathway (cis-element in unspliced mRNAs encoded by the Mason–Pfizer monkey virus (MPMV), termed the constitutive transport element (CTE), directly recruits NXF1, obviating the need for additional trans-acting factors to promote nuclear export , that mediate RNA export via the NXF1 pathway  are a class of non-protein-coding transcripts >200 nt in length with diverse functions . Owing tNoncoding RNA activated by DNA damage (NORAD) is a prominent example of a lncRNA whose precise subcellular localization is essential for its function. This 5.3-kb unspliced lncRNA is efficiently exported to the cytoplasm, where it binds and sequesters Pumilio (PUM) RNA binding proteins in condensates termed NORAD-Pumilio (NP) bodies  bodies . PUM pro) bodies . Becausee models . Efficierom NXF1 . GC-richanscript . NeverthNORAD and potentially other intronless transcripts, we carried out a genome-wide CRISPR–Cas9 loss-of-function screen using a reporter cell line in which a green fluorescent protein (GFP) open reading frame, inserted into the endogenous NORAD locus, is translated only when NORAD is exported to the cytoplasm. In addition to known RNA export factors, this screen revealed a poorly characterized RNA binding protein, RBM33, that promotes the nuclear export of NORAD, thereby preventing its degradation by the nuclear exosome. RBM33 directs NORAD nuclear export by directly binding to this lncRNA and recruiting UAP56 and NFX1. RNA-seq of RBM33-deficient cell lines identified hundreds of additional transcripts whose efficient nuclear export requires RBM33. Surprisingly, RBM33 substrates were not enriched for intronless RNAs. Rather, high GC content emerged as the most prevalent feature of transcripts that depend on RBM33 for nuclear export. Accordingly, transcriptome-wide mapping of RBM33 binding sites using enhanced cross-linking immunoprecipitation (eCLIP) demonstrated binding to GC-rich elements. These results introduce a flexible screening approach for the genetic interrogation of nuclear RNA export mechanisms and uncover an RBM33-dependent RNA export route that promotes the cytoplasmic localization and enhanced expression of GC-rich RNAs.To identify factors required for the nuclear export of NORAD. Using homologous recombination, we first inserted an internal ribosome entry site coupled to a GFP open reading frame (IRES-GFP) into the endogenous NORAD locus, near the 3′ end of the transcript, in the stably diploid cell line HCT116 . Northern blotting confirmed that the full-length NORAD transcript exhibited the expected increase in size in NORAD-IRES-GFP reporter clones , while flow cytometry demonstrated that reporter cells displayed ∼10-fold higher GFP fluorescence compared with parental HCT116 cells . Moreover, short interfering RNA (siRNA)-mediated knockdown of NORAD confirmed that fluorescence intensity was coupled to NORAD abundance in reporter cells . Importantly, insertion of the IRES-GFP cassette did not affect NORAD expression or cytoplasmic localization, suggesting that this reporter system could be used as a reliable readout for NORAD trafficking   yielded a large number of potential regulators of the NORAD-IRES-GFP reporter .an genes . Twelve g (FACS) F. sgRNA UTP3, UTP14A, and UTP23) . It is probable that the loss of these genes resulted in decreased fluorescence of the NORAD reporter through their effect on IRES-driven translation, rather than by influencing NORAD localization or abundance. IRES-dependent translation is generally less efficient than canonical cap-dependent translation and is therefore likely to be highly sensitive to depletion of ribosomal subunits. Genes that encode epigenetic regulators and components of the cleavage and polyadenylation machinery were also identified as hits, presumably due to their impact on NORAD transcription and 3′ end processing. Reassuringly, several RNA export factors, including TPR, which is known to be required for cytoplasmic trafficking of NORAD   and seveof NORAD , were reRBM33, CELF1, DDX10, YTHDC1, NOL7, SRP14, and SRSF11), raising the possibility that one or more of these factors may play a direct role in NORAD expression or trafficking. We assessed the effect of knocking out each of these genes, as well as ZC3HC1, another highly ranked hit that is required for TPR localization to the nuclear pore complex . As a control, we targeted the general poly(A) RNA export factor IWS1 . We hypothesized that a factor required for splicing-independent export of NORAD would result in selective trapping of this lncRNA in the nucleus while minimally impacting export of ACTB. Among the validated genes, loss of RBM33, the top-ranked hit in the screen, resulted in the strongest nuclear enrichment of NORAD and associated reduction in GFP fluorescence without affecting ACTB trafficking. Moreover, RBM33 knockout led to a strong decrease in NORAD abundance, possibly resulting from an increased susceptibility to degradation by the nuclear exosome, a phenomenon known to occur upon impaired nuclear export of intronless transcripts and other classes of RNAs . As observed following CRISPR-mediated knockout, RBM33 knockdown resulted in strong nuclear enrichment of NORAD  with a concomitant decrease in overall NORAD levels .Depletion of RBM33 using two distinct sgRNAs similarly reduced expression of the  results A. To verNORAD expression and trafficking, two clonal HCT116 RBM33 knockout cell lines were generated using distinct sgRNAs. Although both clones harbored homozygous out-of-frame indels, RBM33 KO-1 exhibited frame-restoring alternative splicing of mutant transcripts, resulting in the production of an internally deleted RBM33 protein . RBM33 KO-2 displayed a near-complete loss of RBM33 protein. Several lines of evidence demonstrated that both of these mutations resulted in RBM33 loss of function. Both RBM33 knockout clones exhibited strong nuclear enrichment of NORAD  rescued NORAD localization , demonstrating that the observed phenotypes were due to RBM33 loss of function. Notably, RBM33 knockout cells exhibited a high frequency of chromosome segregation defects . In contrast, inhibition of the cytoplasmic exosome by depletion of SKIV2L had no effect on NORAD levels. Importantly, cellular fractionation and RNA FISH demonstrated that the increased pool of NORAD in EXOSC10/DIS3-depleted cells was efficiently exported to the cytoplasm in wild-type cells, but remained trapped in the nucleus in RBM33 knockout cells . Consistent with its minimal effect on NORAD abundance, loss of SKIV2L did not impact NORAD localization. These results provide strong evidence in support of nuclear trapping and degradation of NORAD by the nuclear exosome in RBM33-deficient cells. Our finding that NORAD abundance is regulated by EXOSC10/DIS3 in wild-type cells is in keeping with the previously reported observation that the steady-state abundance of many transcripts, particularly those lacking introns, is regulated by competition between nuclear export pathways and degradation by the nuclear exosome  localized predominantly to the nucleus. Moreover, heterokaryon assays demonstrated that RBM33 shuttled between the nucleus and cytoplasm . Additionally, UV cross-linking and RNA immunoprecipitation (UV-RIP) with FH-RBM33 resulted in strong and specific enrichment of NORAD, consistent with direct binding of RBM33 to this lncRNA .Based on these data, we hypothesized that RBM33 may direct the nuclear export of  factors , endogen factors A or heteNXT1 and THOC6 . Coimmunoprecipitation of FH-RBM33 with THOC5, NXF1, UAP56, and ALYREF was confirmed by Western blotting . Surprisingly, however, loss of ALYREF did not impair NORAD expression or result in its nuclear accumulation , suggesting that this core TREX component is not required for NORAD export.These interaction data implicate the TREX–NXF1 pathway in RBM33-dependent nuclear export, which is consistent with the previously established role of NXF1 in fficking . KnockdoSupplemental Fig. S6D), these assays revealed interactions of RBM33 with UAP56 and NXF1 , UAP56, or NXF1 were performed. Although no detectable interactions were observed between RBM33 and any of the tested THO subunits + RNA, depletion of RBM33 did not impact overall poly(A)+ RNA export , suggesting that it may promote the cytoplasmic transport of a select clientele.Having established an essential role for RBM33 in the nuclear export of RBM33 wild-type and knockout cells . Notably, NORAD was among the most nuclear-enriched transcripts in this data set . Examination of transcript biotypes revealed that the vast majority of transcripts that exhibited RBM33-dependent export were protein-coding, with modest enrichment of a few noncoding RNA classes . Nuclear–cytoplasmic fractionation followed by qRT-PCR validated the nuclear enrichment of several transcripts in RBM33-depleted cells  on nuclear and cytoplasmic RNA from ut cells A. This r classes C. Gene oed cells D. Furtheon RBM33 E. These RBM33 knockout cells. Since NORAD is unspliced, we initially expected that dependency on RBM33 for nuclear export would correlate with exon number or splicing efficiency. Nevertheless, various characteristics related to splicing, including exon number, exon length, exon density, or splicing efficiency, exhibited only weak, albeit statistically significant, correlations with RBM33 dependency . In addition, transcripts that depend on RBM33 for nuclear export did not exhibit altered splicing efficiency in RBM33 knockout cells , indicating that nuclear trapping was not a secondary consequence of impaired splicing.To identify the features that specify RBM33-dependent nuclear export, linear regression analysis was used to identify transcript characteristics that correlated with nuclear enrichment in pendency F. MoreovNORAD in cells depleted of RBM33 leads to NORAD degradation by the nuclear exosome, we observed that GC content also correlated with reduced transcript abundance in RBM33 knockout cells , and eCLIP experiments were performed in both cell lines.To identify direct substrates of RBM33 throughout the transcriptome, as well as to determine the sequence characteristics of RBM33 binding sites, we performed eCLIP with FH-RBM33 . ConditiSupplemental Table S4). Among protein-coding transcripts, RBM33 binding was most enriched within coding sequences, followed by 5′ and 3′ UTRs . Notably, RBM33 binding was depleted from introns, suggesting a preference for binding fully processed, export-competent transcripts, in line with its function as a nuclear export factor. Importantly, RBM33 CLIP targets exhibited preferential nuclear enrichment in RBM33-deficient cells, further establishing that RBM33 promotes the nuclear export of transcripts to which it binds  . Thus, a GC-rich RBM33 binding site at the 5′ end of NORAD is required for efficient nuclear export of this lncRNA.Notably, the RBM33 binding sites in nscripts . To testSupplemental Fig. S9D). In sum, these data demonstrate that RBM33 recognizes GC-rich elements in its target transcripts and promotes cytoplasmic trafficking by recruiting components of the TREX–NXF1 nuclear export machinery.We next examined the sequence characteristics of RBM33 binding sites throughout the transcriptome. In keeping with our finding that GC content correlates with dependency on RBM33 for nuclear export F,G, we oCells use multiple independent features in transcribed RNAs to select those destined for nuclear export. For example, the presence of a 5′ cap, completion of splicing, and association of 3′ end processing factors are among the most well-characterized signals for nuclear export . These fNORAD, a 5-kb transcript that is efficiently transported to the cytoplasm despite lacking introns   . Interest cells) F. These The discovery of RBM33-mediated export provides a mechanistic basis for the long-standing observation that GC-rich elements, especially when located at the 5′ end of a transcript, enhance cytoplasmic RNA localization and increase gene expression. For example, the nucleotide sequences encoding signal sequences , which direct proteins to the endoplasmic reticulum for membrane insertion or secretion, are GC-rich elements that promote nuclear export . These sNORAD conservation is limited to mammals. Therefore, we speculate that NORAD evolved a GC-rich element at its 5′ end, distinct from its PUMILIO binding sequences, to access an existing RBM33-dependent pathway to enable efficient cytoplasmic localization. Unlike NORAD, however, most RBM33 substrates are multiexon transcripts. Notably, the feature with the second highest correlation with RBM33-dependent export was low splicing efficiency, although the correlation was much weaker than that associated with GC content. It is therefore likely that many inefficiently spliced RBM33 substrates use both splicing-dependent and RBM33-dependent pathways to achieve adequate cytoplasmic localization. This possibility emphasizes the need for further investigation of the interplay between splicing-dependent and RBM33-dependent export. For example, regulated RBM33 binding could provide a mechanism to selectively enhance the export of poorly spliced or unprocessed RNAs under selected conditions.RBM33 homologs are present in many vertebrates, while NORAD export can easily be adapted to interrogate the export pathways used by other cytoplasmic coding and noncoding RNAs. It is likely that more uncharacterized nuclear export factors with select clientele remain to be identified. Fluorescent reporter-based genetic screens provide a powerful approach to identify these factors and further illuminate our understanding of this fundamental aspect of gene expression.Finally, we note that the screening strategy used here to dissect the mechanism of NORAD can be targeted by two distinct sgRNAs that recognize opposite strands. Oligonucleotides encoding each of these sgRNAs  were cloned into pX330 (Addgene 42230). HCT116 cells were seeded at 6 × 105 cells per well of a six-well plate and reverse-transfected with either 1.3 µg of donor plasmid alone or 1.3 µg of donor plasmid and 330 ng of pX330. Medium was changed 24 h later. Ten days after transfection, GFP was detectable only in donor/pX330 cotransfected cells. These GFP-positive cells were collected by sorting, and single-cell clones were generated by limiting dilution. Clones were then genotyped by PCR to confirm the insertion of the IRES-GFP cassette at the NORAD locus. Two independent clones, each generated with a different guide and exhibiting homozygous insertion of the IRES-GFP cassette, were chosen for screening.The site chosen for the insertion of the IRES-GFP cassette into Supplemental Material.CRISPR–Cas9-mediated loss-of-function screening was performed as described previously . AdditioSupplemental Material.Fractionation was performed as described previously . AdditioNORAD RNA FISH was performed as described previously  using HiFi cloning. Additional details are in the Supplemental Material.Sequences of all primers used for cloning are in 7) were transfected with 40 µg of pLJM1 empty vector (EV) or pLJM1 FH-RBM33 plasmid using Fugene HD (Promega). Forty-eight hours after transfection, cells were UV cross-linked at 254 nm (400 mJ/cm2). Cells were then scraped in PBS, pelleted, snap-frozen in liquid nitrogen, and stored at −80°C until needed. RIP was performed as described  stably expressing pLJM1 empty (EV) or FH-RBM33 growing in 15-cm plates were scraped in ice-cold PBS, pelleted, snap-frozen in liquid nitrogen, and stored at −80°C. At the time of immunoprecipitation, cells were lysed in 1 mL of lysis buffer  for 30 min on ice and cleared by centrifugation at 14,000g for 10 min at 4°C. For each pull-down, 5 µg of FLAG M2 antibody (Sigma) was bound to 50 µL of washed Dynabeads Protein G (Invitrogen). Lysates were then added to antibody-coupled beads along with 20 µg/mL RNase A. Reactions were incubated on a rotating platform for 2 h at 4°C, and then beads were washed five times with 1 mL of wash buffer . Immunoprecipitated proteins were eluted with 40 µL of elution buffer (36 µL of lysis buffer supplemented with 4 µL of 3× FLAG peptide at 10 mg/mL [Sigma]) with shaking at 1000 RPM for 30 min at room temperature. Each IP was performed in triplicate. Mass spectrometry analysis of eluted proteins was performed at the University of Texas Southwestern Proteomics Core using reverse-phase LC-MS/MS and an Orbitrap Fusion Lumos mass spectrometer. Raw MS data files were analyzed using Proteome Discoverer v2.4 SP1 (Thermo), with peptide identification performed using Sequest HT searching against the human protein database from UniProt.HCT116 cells  were seeded in six-well plates. For each replicate, 48 h later, one well was subjected to total RNA extraction and one well was subjected to nuclear–cytoplasmic fractionation. Whole-transcriptome RNA-seq libraries from 1 µg of DNase I-treated RNA from each sample were prepared with the TruSeq stranded total RNA LT sample preparation kit (Illumina) and sequenced on a NextSeq 500 (Illumina) with 75-bp single-end reads. Reads were mapped to the human reference genome (GRCh38) using STAR v2.7.1a . The longest isoform was used for each gene. GC content, number of exons, transcript length (exons only), longest exon length, exon density (exonic sequence length/gene length), gene length, and splicing efficiency were calculated from GENCODE v30. Splicing efficiency of an intron was calculated as the ratio of reads overlapping exon–exon junctions over the sum of exon–exon- and exon–intron-spanning reads. Splicing efficiency was only calculated for introns in which all exon–exon and exon–intron junctions were covered by at least 10 junction-spanning reads. Mean splicing efficiency refers to the average splicing efficiency across all introns, whereas maximum or minimum splicing efficiency refers to the splicing efficiency of the most efficiently or least efficiently spliced intron, respectively  have been deposited in GEO (accession no. GEO GSE192378). No custom code was generated in this study.


Liver metastasis is the leading cause of death in colorectal carcinoma (CRC). However, little is known about the mechanisms of transferring effector messages between the primary tumor and the site of metastasis. Exosomes provide a novel transfer message method, and exosomal circular RNAs (circRNAs) play critical regulatory roles in cancer biology. In this study, the results showed that the expression of circPABPC1 was aberrantly upregulated in CRC tissues and exosomes. Exosomal circPABPC1 was considered an oncogene by functional experimental analysis in vitro and in vivo. Mechanistically, circPABPC1 recruited KDM4C to the HMGA2 promoter, reduced its H3K9me3 modification and initiated the transcription process in the nucleus. Moreover, cytoplasmic circPABPC1 promoted CRC progression by protecting ADAM19 and BMP4 from miR-874-/miR-1292-mediated degradation. Our findings indicated that exosomal circPABPC1 is an essential regulator in CRC liver metastasis progression by promoting HMGA2 and BMP4/ADAM19 expression. CircPABPC1 is expected to be a novel biomarker and antimetastatic therapeutic target in CRC. Colon cancer (CRC) is the third most frequent cancer worldwide . ApproxiCircular RNAs (circRNAs) are a subtype of ncRNAs formed by alternative splicing called “back-splicing”, and they have a covalently closed loop structure and are more stable than linear RNAs , 10. OwiIn the present study, RNA sequencing and qPCR analysis were used to identify circPABPC1 in CRC tumors and exosomes . We shown = 3; Ca, colorectal cancer without metastasis, n = 3; N, three adjacent normal tissues). As shown in Fig. P < 0.05 and fold change > 1.5) in CRC tissues compared to normal tissues. In addition, 10 circRNAs were significantly upregulated in the CaM group compared to the Ca group. Among them, hsa-circ-0085159 was the only upregulated and conserved circRNA in the two different cohorts (Ca vs. N and CaM vs. Ca)  Fig. . We thenCa) Fig. . To furtCa) Fig. . FurtherCa) Fig. . SurprisCa) Fig. . To clarCa) Fig. , and theCa) Fig. . FurtherCa) Fig. , and theCa) Fig. . The expCa) Fig. . MoreoveCa) Fig. . The aboBased on differential expression patterns in different CRC cells, we knocked down endogenous circPABPC1 in SW620 and LoVo cells using two siRNAs targeting the back-spliced sequence of circPABPC1, and these siRNAs had no effect on both PABPC1 linear mRNA and protein Fig. . To inveTo accurately clarify the specific molecular mechanism of circPABPC1 in CRC, next-generation sequencing was performed to identify the differentially expressed genes after circPABPC1 overexpression Fig. . As showTo further explore the specific mechanism of circPABPC1 in the HMGA2 transcription process, RNA pull-down assays followed by silver staining and mass spectrum identification were performed Fig. . As Fig.Given that circRNAs have been widely explored as miRNA sponges and circPABPC1 has been demonstrated to be present in the cytoplasm, we next investigated the specific miRNA interactions with circPABPC1. First, we confirmed the interaction between circPABPC1 and AGO2 using RIP assays in both SW480 and SW620 cells Fig. . ThroughRNA fold software prediction allowed visualization of the mature and stable secondary structures of both miR-874 and miR-1292 Fig. . ThroughA subcutaneous tumor formation model was used to detect the function of circPABPC1 in vivo. As shown in Fig. The liver is the most common metastatic site of colorectal cancer (CRC), and 30% to 50% of CRC patients have hepatic metastasis during the development of the disease . The priIn the present study, circRNA microarray analysis identified an oncogenic circRNA, namely, circPABPC1, which was upregulated in CRC tissues compared to matched normal tissues. Moreover, qPCR analysis demonstrated that exosomal circPABPC1 derived from serum was more abundant in CRC patients. To explore the biological functions of circPABPC1, Transwell migration and invasion assays were used to demonstrate the ability of circPABPC1 to promote tumor metastasis in vitro, and a hepatic metastasis model was generated to verify the effect of circPABPC1 on the metastasis of CRC in vivo. Together, these findings suggested that circPABPC1 contributed to the metastasis progression in CRC and that serum exosomal-circPABPC1 may be a potential mediator of intercellular communication in CRC development.It has been well demonstrated that many circRNAs are located in the cytoplasm and perform regulatory functions by miRNA sponging; circRNAs are rarely located in the nucleus to regulate translation . Herein,In summary, as shown in Fig. A total of 60 paired CRC and adjacent normal tissues were obtained from the Surgery Department of First Affiliated Hospital of JinZhou Medical University. All fresh tissue specimens were immediately stored at −80 °C until RNA extraction. Twenty CRC patients and 20 normal control blood samples were collected for exosome extraction. This study was approved by the Ethics Committee of the First Affiliated Hospital of JinZhou Medical University.In brief, total RNA was extracted from tissues or cells using TRIzol reagent . The concentration of total RNA was measured by Qubit 4.0. Then, 2 μg of isolated RNA was used for the reverse transcription reaction with the PrimeScript reverse transcriptase (RT) reagent kit . Finally, qRT–PCR was performed using SYBR green PCR mix (Takara). GAPDH or U6 served as internal controls.All the cell lines used were obtained from American Type Culture Collection . For pLCDH-circPABPC1 plasmid generation, the sequences of exons 2-9 of PABPC1 were cloned into a pLCDH-ciR-vector . The pLCDH-ciR empty vector was used as a negative control. Cells were seeded in 6-well plates, and Lipofectamine 3000  was used according to the manufacturer’s instructions for transient transfections.7 CRC cells were transfected with the pLCDH-circPABPC1 overexpression plasmid or negative control. Forty-eight hours after transfection, total RNA was isolated and incubated with probes and streptavidin magnetic beads. Unbound proteins were washed away, and bound proteins were collected for silver staining and mass spectrometry.circPABPC1-specific RNA pull-down was performed using a Magnetic RNA Protein Pull-down Kit (Thermo). A 5’ biotin-labeled oligonucleotide probe targeting the junction site of circPABPC1 was obtained from KeyGEN Company . All sequences used are listed in Table The RIP assay was performed using the MagnaRIP RNA-Binding Protein Immunoprecipitation Kit (Merck Millipore) according to the manufacturer’s instructions. In brief, cell lysates were incubated with magnetic beads coated with protein A/G. AGO2 (5 µg) and KDM4C primary antibody  were added and incubated at 4 °C overnight. circPABPC1 and miRNAs were then detected by qRT–PCR.Briefly, CRC cells were fixed with 4% paraformaldehyde and then incubated with glycine for 10 min. After glycine treatment, cells were lysed with ChIP lysis buffer. The whole genome DNA was then sonicated to 400~800 bp fragments. The lysates were immunoprecipitated with magnetic protein A/G beads conjugated with anti-H3K27Ac  or rabbit nonimmune IgG (negative control). Finally, the precipitated DNA was analyzed by PCR.In brief, RIPA buffer was used to lyse cells, and total proteins were separated by 10% SDS–PAGE and electroblotted onto a PVDF membrane (Millipore). After blocking with nonfat milk for 1 h, membranes were incubated with specific primary antibodies overnight. The membranes were then washed with PBS three times and then incubated with horseradish peroxidase-coupled secondary antibodies  for 2 h. After washing with PBS, the protein bands were detected using an ECL western blotting kit .Human serum exosomes were extracted from patient blood samples using ExoQuick Exosome Precipitation Solution  according to the manufacturer’s instructions. TEM and NTA were used to identify exosomes. The protein markers of exosomes, including TSG101, CD63 and CD81, were detected by western blot assay.4 per well and cultured overnight. Cells were then cotransfected with a mixture of pmirGLO-wild circPABPC1 or pmirGLO-mutant circPABPC1 plasmids and miR-874/miR-1292 mimics using Lipofectamine 3000 (Invitrogen). Twenty-four hours later, the luciferase activity was detected by a dual-luciferase reporter assay system .In brief, HEK-293T cells were seeded in 96-well plates at a density of 1 × 10https://portal.gdc.cancer.gov). The candidate miRNAs were predicted by the RegRNA and circRNA interactome databases. The TargetScan, starBase, miRDB and miRWalk databases were used to detect miRNAs and their target genes. Cytoscape software was used to construct circRNA/miRNA/mRNA networks.CRC-relevant RNA-Seq data from TCGA were downloaded from TCGA database . One week later, the collected exosomes containing circPABPC1 or Vector was subsequently injected into mice via the tail vein (5 μg/mouse) every 3 days. One month later, the mice were sacrificed, and tumor tissues were collected.6 SW620 cells were injected into the spleen with a 30-gauge needle. Six weeks later, the mice were sacrificed, and their livers were dissected out and further measured.A hepatic metastasis model was used to detect the effect of circPABPC1 on the metastasis of CRC cells in vivo. Mice were anesthetized, and 2 × 10t test. Statistical significance was expressed as a P value  as indicated in the individual figure legends.SPSS 20.0 software and GraphPad Prism 5 were used to perform statistical analyses. Data are presented as the mean ± SD as indicated. Comparisons between two groups were assessed using an unpaired two-tailed SUPPLEMENTAL MATERIALSupplemental materials-Original blot