At the molecular level this methylation could alter local RNA structure, and/or modulate the binding of specific proteins. We have previously shown that trans-Hoogsteen-sugar (sheared) A:G base pairs can be completely disrupted by methylation, and that this occurs in a sub-set ofD/D k-turn structures. In this work we have investigated to what extent sequence context affects the severity with which inclusion of N6-methyladenine into different A:G base pairs of a standard k-turn affects RNA folding and L7Ae protein binding. We find that local sequence has a major influence, ranging from complete absence of folding and protein binding to a relatively mild effect. We have determined the crystal structure of one of these species both free and protein-bound, showing the environment of the methyl group and the way the modification is accommodated into the k-turn structure.N Inclusi6-methyladenine at the A1n position resulted in no folding being observed up to a concentration of 0.1 M Mg2+ , and undergo folding in response to binding. AfL7Ae binding was studied using gel electrophoresis  and 0.67 (A3b)  . A greatfor Kt-7 , with th6-methyladenine 2b Kt-7 underwent folding on addition of Mg2+ ions, we investigated the structure using X-ray crystallography. Crystals of self-complementary RNA containing two Kt-7 k-turns were obtained with and without bound AfL7Ae, at resolutions of 1.99 and 2.09 Å respectively. The structure of the k-turn containing N6-methyladenine 2b is closely similar in the L7Ae bound and protein free states, superimposing with an all-atom RMSD of 0.52 Å . The structure of the complex is shown in AfL7Ae bound to unmodified Kt-7  is the prevailing Mg2+ ion concentration, AK is the apparent association constant for metal ion binding and n is a Hill coefficient. Data were fitted to this equation by nonlinear regression. The metal ion concentration at which the transition is half complete is given by [Mg2+]1/2 = (1/AK)n1/.where AfL7Ae protein was titrated in to the RNA and added to a final concentration of 2 µM. EFRET as a function of AfL7Ae concentration was fitted to:The same hybrid RNA species were used to observe L7Ae binding-induced folding, and FRET efficiency was calculated using the same approach. 0E is the initial FRET efficiency in the absence of added protein, FRET∆E is the full range of the change in FRET efficiency, AK is the apparent association constant and TP and TR are the total concentration of AfL7Ae and RNA respectively.where AfL7Ae protein to the Kt-7 k-turn RNA and its modified versions was analysed by native gel electrophoresis. 200 nM Cy3-labeled RNA (the same species as used in the FRET experiments) was incubated in 45 mM Tris-borate (pH 8.3) with various concentrations of the AfL7Ae protein in a final volume of 10 µl at 7°C for at least 1 h. An equal volume of loading buffer containing 10% glycerol and 45 mM Tris-borate (pH 8.3) was added, and the samples were electrophoresed in 10% native polyacrylamide gels in 45 mM Tris-borate (pH 8.3) at 20 V/cm at 7°C for 1 h. Fluorescent RNA was visualized using a Typhoon 9500 fluorimager .Binding of 6-methyladenine). This sequence is self-complementary and forms two Kt-7 k-turns with two-fold symmetry. A solution of 1 mM RNA in 5 mM Tris.HCl (pH 8.0), 100 mM NaCl, 10 mM MgCl2 was incubated for 1 min at 95°C. Crystals were grown by vapor diffusion using drops prepared by mixing 1 μL of the RNA with 1 μL of a reservoir solution comprising 0.1 M KCl, 0.002 M spermine tetrahydrochloride, 0.05 M Bis-Tris (pH 8.0) and 15% w/v PEG 2000 MME at 17°C. Crystals appeared after 10 days. They were transferred into the reservoir solution with 30% PEG200 for ~ 3 s. The crystals were flash frozen by mounting in nylon loops and plunging into liquid nitrogen.A 19 nt RNA of sequence GGCGAAG(6mA)ACCGGGGAGCC was crystalized , 100 mM NaCl, 10 mM MgCl2 was incubated for 1 min at 85°C followed by slow cooling. Crystals were grown by vapor diffusion using drops prepared by mixing 1.0 μL of the RNA–protein complex with 1 μL of a reservoir solution comprising 0.01 M spermine tetrahydrochloride, 0.05 M MES (pH 6.5), 25% v/v PEG 400 at 17°C. Crystals appeared after 5 days.A self-complementary 21 nt RNA oligonucleotide CGGCGAAG(6mA)ACCGGGGAGCCG was crystalized as a complex bound to All the crystals were characterized in-house with a MicroMax HF007 copper rotating anode X-ray generator equipped with an ACTOR sample changer system and a Saturn 944HG+ CCD detector (Rigaku). Suitable crystals were stored and subsequently used to measure full datasets on beamline I03 of Diamond Light Source (Harwell, UK. Data were processed by XIA2 .AfL7Ae protein were determined by molecular replacement with Phenix Phaser. The k-turn search model was taken from PDB 4CS1, and the k-turn AfL7Ae complex model was taken from PDB 4BW0. The resulting electron density maps revealed the remaining RNA density, and the model was built de novo on the basis of the difference map. Structural models were built in Coot [The structures of the HmKt-7 variant A2bm6A without and with  in Coot  and refi in Coot . Omit ma in Coot  and the


Central place foragers (CPF) rest within a central place, and theory predicts that distance of patches from this central place sets the outer limits of the foraging arena. Many marine ectothermic predators behave like CPF animals, but never stop swimming, suggesting that predators will incur ‘travelling’ costs while resting. Currently, it is unknown how these CPF predators behave or how modulation of behavior contributes to daily energy budgets. We combine acoustic telemetry, multi-sensor loggers, and hidden Markov models (HMMs) to generate ‘activity seascapes’, which combine space use with patterns of activity, for reef sharks (blacktip reef and grey reef sharks) at an unfished Pacific atoll.Sharks of both species occupied a central place during the day within deeper, cooler water where they were less active, and became more active over a larger area at night in shallower water. However, video cameras on two grey reef sharks revealed foraging attempts/success occurring throughout the day, and that multiple sharks were refuging in common areas. A simple bioenergetics model for grey reef sharks predicted that diel changes in energy expenditure are primarily driven by changes in swim speed and not body temperature.We provide a new method for simultaneously visualizing diel space use and behavior in marine predators, which does not require the simultaneous measure of both from each animal. We show that blacktip and grey reef sharks behave as CPFs, with diel changes in activity, horizontal and vertical space use. However, aspects of their foraging behavior may differ from other predictions of traditional CPF models. In particular, for species that never stop swimming, patch foraging times may be unrelated to patch travel distance.The online version of this article (10.1186/s40462-018-0127-3) contains supplementary material, which is available to authorized users. Central place foraging (CPF) is a ubiquitous behavior seen across animal groups ranging from insects, to birds, and humans . Unlike A key assumption of CPF theory is that an animal rests at the central place, and foraging costs increase with travel distance to a feeding patch. Yet, there are many species of marine predators that exhibit CPF-like behavior, but never stop swimming, and never truly rest. For these animals, energy costs may be independent of travel distance to the patch, and simply a function of swim speeds. Such predators include large coral reef-associated fishes (sharks and teleosts), which swim within a relatively small core area during the day, and move over an expanded area at night, with periodicity of movements related to diel or tidal cycles –9. MarinCPF animals that never stop swimming are almost exclusively ectotherms, so metabolic rates are sensitive to changes in ambient temperature. At any particular time, routine metabolic rates should be a function of body temperature, movement speed, and other aspects of the movement process (e.g. turning costs more than straight line swimming ). While Accelerometers have become popular for measuring both the activity and energy requirements of free-ranging marine animals , 19–21. Carcharhinus melanopterus), and grey reef sharks (C. amblyrhynchos)), whose movements appear similar to a CPF as they use smaller areas during the day than at night [We use multi-sensor loggers and statistical time-series models to build activity seascapes for two species of reef shark , located in the central Pacific Ocean. Palmyra has been a U.S. federal wildlife refuge since 2001, with only a research station housing a small number of scientists and staff. The atoll consists of two lagoons, surrounded by sandflats and backreefs, which transition to forereef habitats  in July 2013. Sensors measured 3D acceleration (sampled at 20 Hz), swimming depth, water temperature (1 Hz), and some animals were also fit with a speed sensor  and video camera . ODBA wN = 2 states, roughly corresponding to behavioral states, which we label ‘relatively high activity’ and ‘relatively low activity’, respectively. The observations can be considered noisy measurements of the behavioral state, which cannot be explicitly observed [state 1) or high state of activity (State 2), based on ODBA data from accelerometers. We could then compute probabilities of sharks changing or remaining within behavioral states based on time of day, tidal state, or swimming depth and water temperature. ODBA values were averaged over 1 s intervals before applying the HMMs, based on observations of behaviors from video footage (see below). We removed the first 4 h of data from each animal so that we did not infer behavior when the animals may still have been highly stressed. All HMMs were built in the statistical environment R using customized code. All HMM details can be found in Additional file Hidden Markov models (HMMs) are stochastic time series models where observed data  are assumed to be driven by an underlying hidden process. We assume that the hidden process can be in either of observed , 26. Traobserved . We deveThe HMMs provide a data-driven, objective approach to analyzing acceleration data, but we still cannot identify which specific behavior  sharks perform while within the various states. We had the unique opportunity to correlate the results of the HMM with the simultaneously collected 22 h of video obtained from two grey reef sharks. Video data allowed us to see what the sharks were doing (and in which habitats) when inferred by the HMM to be in certain states, providing validation for our interpretation of the model. We first observed all 22 h of video noting times of foraging, increased activity  as well as the presence of other sharks. For those specific time periods, we could then compare observations with the behavioral state predicted by the HMM.N = 3) using hourly mean swim speed data. Speed will still likely suffer from serial correlation, which we accounted for by including an AR(1) (first-order auto-regressive) process with time as the position variable. The correlation at lag = 1 was included in the model to specify the correlation structure. The GAM was constructed with a Gaussian error distribution and time of day was modeled with a cyclic smooth spline. Model fit was assessed by examining residual diagnostic plots, and Akaike’s information criterion [mgcv package.We also analyzed swim speed data in grey reef sharks as a direct measure of energy expenditure. To explore diel changes in swim speed, we constructed generalized additive models (GAMs) for each individual grey reef shark (riterion  (AIC) wariterion . GAM anaWe quantified reef shark space use patterns using acoustic telemetry methods. Between 2010 and 2014, sharks were caught on hook and line and surgically implanted with an acoustic transmitter . A small incision was made on the ventral surface, the transmitter was inserted into the body cavity and a single suture was used to close the incision. The sharks were measured, sexed, externally dart tagged and released. These individuals were not the same sharks as those tagged with data-loggers above, although there was temporal overlap between periods of data collection . We acoustically tagged a total of 20 blacktip reef sharks, and 43 grey reef sharks. Of those, 9 blacktip reef sharks and 13 grey reef sharks were tagged with V16 PT transmitters that also measured pressure (depth) and body temperature, and 6 blacktip reef sharks were tagged with V13 AP transmitters that measured 3D acceleration in addition to depth. Transmitters were detected by an array of up to 70 subsurface omni-directional acoustic receivers (VR2W) deployed throughout the atoll [adehabitat LT and adehabitat HR packages.We calculated shark spatial utilization distributions (UD) using a Brownian bridge movement model (BBMM), where consecutive acoustic detections between receivers by moving sharks are linked by conditional random walks , 30. TheTo explore diel patterns of vertical habitat use by grey reef sharks, we constructed generalized additive mixed models (GAMMs) using hourly mean depth and body temperature data from the acoustic transmitters. Specifically, we estimated the effect of time of day on swimming depth and temperature, with individual shark modeled as a random effect. All other model components were the same as described above for swim speed. Diel changes in depth and temperature for blacktips were reported in .https://github.com/udemsar upon publication.The acceleration data and HMMs provided probabilities of sharks being in a relatively high active state throughout the diel cycle. We then combined these with three-dimensional UDs calculated over months to years of movement from the telemetry data, to generate an overall visual representation of the ‘activity seascape’ of individual animals within their environment. We used the telemetry data to produce space-time cubes (STC) where the bottom two dimensions represent the geographic space over which the movement occurs and the third dimension is time . In a 2D3.21 where L is total length in cm and W is weight in kg (http://fishbase.org). Routine metabolic rates (M) were then estimated using the equation for ectothermic sharks, Log10M = 0.79*Log10W + 2.31 [10 of 1.65 and 3.0, to include the range of Q10 values seen within tropical sharks [To predict the relative contribution of swimming speed and body temperature on daily energy budgets, we built a simple bioenergetics model for grey reef sharks. We calculated shark mass using W = 0.0045 Ll sharks , 33. To l sharks . Brieflystate 1 (‘relatively low activity’) was associated with fairly constant relatively low levels of ODBA, while state 2 (‘relatively high activity’) involved overall higher activity levels and in particular included any bursts in ODBA . Probability of high activity during the day was as low as 15% and increased to an early evening probability of 40%, depending on tide  from approximately 21:00–06:00, with a peak at 03:00  for the majority of their time . Blacktip reef sharks remained in state 2 for 19–26 s (means), while grey reef sharks were in state 2 for 10–29 s bursts.We recovered behavioral information from data-loggers deployed on four blacktip reef sharks , all female, 16 days) and four grey reef sharks  but overall, individuals were most active at depths of 4–10 m, or at the surface if temperatures were 28 °C. All sharks were in a low activity state (state 1) when they were at the surface in waters > 29.5 °C  were frequently seen in the footage, with > 10 individuals in frame at multiple points in time  and in some cases appeared to be foraging . On three occasions, yellowfin tuna  were observed foraging on the reef near shark B  during the early morning hours Fig. . Foraginime Fig. . With onk B Fig. . Shark BGrey reef sharks (154–159 cm TL) swam at average speeds of 0.51–0.63 m/s with maximum speeds of 3.6 m/s. Although the average speeds differed between the three individuals, they all showed the same diel pattern with increased speeds at 02:00–03:00 and lowest speeds from 12:00–18:00  for an average of 1012 ± 429 days (range 5–1545 d) on the Palmyra forereefs. 92.5% of individuals showed diel movement patterns, being detected on the forereefs during the day with far fewer detections at night, although we also captured the night time habitat use of some individuals  on the backreefs at Palmyra. Sharks were detected for an average of 392 ± 341 days (range 22–1108), although individuals detected for short durations were tagged with transmitters with shorter battery lives (e.g. acceleration transmitters). The majority of individuals (70%) showed evidence of limited diel movement patterns, using a core area during the day and moving over an expanded activity space at night Figs.  and 6. Hls Figs.  and 7. G cm TL onys range –1545 d oShark vertical habitat use appeared to vary relative to the diel cycle and the area of core use. Our previous analysis of blacktip reef shark vertical movements and body temperature (from acoustic telemetry data), revealed very moderate diel changes, with these sharks using water 2–3 m deeper during the day . Grey reDue to our limited sample size of data-logger equipped sharks, and to ensure that shark movement data (from telemetry) at least overlapped temporally with the period of data-logger deployment, we only generated activity seascapes for blacktip reef sharks tagged in the backreef and grey reef sharks tagged along the SW portion of the atoll (locations where data-logger equipped sharks were caught and released). As such, activity seascape data consists of 17 blacktip reef sharks tagged on the backreefs and 17 grey reef sharks tagged within and just outside the channel .There were clear diel changes in estimated routine metabolic rates due to the nocturnal increase in swim speed Fig. . OverallAs predicted, both species of shark used a smaller central place in deeper water during the day when they were less active, before expanding movements into shallow water at night with a concurrent increase in activity. Blacktip reef sharks showed more dramatic diel changes in activity (but much more subtle changes in swimming depth) and were most active during the early evening, while grey reef sharks tended to be most active in the middle of the night. The early evening peak in activity seen in blacktip reef sharks was previously suggested to be a function of increased foraging success  and predator/prey thermal physiology . AspectsChanges in activity were concurrent with diel vertical migrations to and from the central place. Blacktip reef sharks perform small shifts in swimming depth, but tides played a greater role in swimming depth, with individuals moving close to the surface during daytime low tide periods, where they are directly warmed by the sun , 38, 39.some foraging may occur in the central place of grey reef sharks at Palmyra. If foraging has some significance to CPF behavior in grey reef sharks, then we would expect the location of the central place to be in an area of high diurnal prey biomass. We recently conducted a mark-recapture study to determine spatially dependent densities for grey reef sharks at Palmyra [Activity seascapes and video footage suggest that  Palmyra . All fis Palmyra , NOAA Co Palmyra .Although our results match our general predictions, our bioenergetics model for grey reef sharks suggests that body temperatures are having an insignificant effect on routine metabolic rates, at least at the diel scale. Instead, diel changes in routine metabolic rates are driven by changes in swim speed. Similarly, activity made a much larger contribution to the short-term field metabolic rates of sea snakes than changes in temperature . These rWhy would sharks, which do not use a nest/shelter or stop swimming, need a central place? CPF would require some degree of memory although the animal may only have to use basic path integration and memorization of simple landmarks to return to a central place, which should optimize foraging rates , 43. TheIdeally, one would record spatial position and high resolution activity from each individual simultaneously, and over long time periods, improving our ability to identify ‘activity hotspots’ . Doing sbehavior within those habitats. A recent study suggested that even trophic cascades in marine systems may be confined to spatial ‘hotspots’ used by predators . Our acWe develop a new method for simultaneously displaying diel space use and activity, in marine animals where space use and behavior are often measured over different time scales. We use this method to show that reef sharks behave similar to central place foragers, occupying deeper water during the day where they are less active, and being more active in shallower water at night. However, unlike other CPF animals, grey reef sharks at least, showed some evidence of foraging in the central place. Furthermore, diel changes in energy expenditure appear to be regulated by changes in swim speed and not body temperature. The implications are that traditional predictions from CPF theory regarding patch foraging times, may not apply for CPF animals that never stop swimming.Additional file 1:Appendix S1. Map of Palmyra atoll and locations of acoustic receivers. (DOCX 645 kb)Additional file 2:Appendix S2. Details of the hidden Markov model built to analyze shark accelerometer data. (DOCX 15 kb)Additional file 3:Appendix S3. Swimming depth distribution of individual blacktip reef and grey reef sharks fitted with data-loggers. (DOCX 23 kb)Additional file 4:Video footage from a grey reef shark showing a foraging event on the reef. (WMV 10244 kb)Additional file 5:Appendix S5. Table showing percentage time grey reef sharks were in an active state for specific behaviours, determined from animal-borne video cameras. (DOCX 12 kb)Additional file 6:Appendix S6. Diel changes in swim speed for three grey reef sharks fitted with swim speed sensors. Both average changes in speed and a cyclic spline from a generalized additive model are shown. (DOCX 325 kb)Additional file 7:Appendix S7. Diel changes in swimming depth and body temperature for grey reef sharks at Palmyra atoll (n = 13) as determined by acoustic telemetry. The y-axis are the standardized residuals from a generalized additive mixed model. Dashed lines indicate 95% confidence interval around the smooth term. (DOCX 230 kb)Additional file 8:Appendix S8. Spatially dependent densities for grey reef sharks, determined from a mark-recapture study  and ‘potential prey’ abundance determined by diver surveys . (DOCX 409 kb)


Hepatocellular carcinoma is the most common primary liver cancer and the fourth leading cause of cancer death worldwide. A total of 70–80% of patients are diagnosed at an advanced stage with a dismal prognosis. Sorafenib had been the standard care for almost a decade until 2018 when the Food and Drug Administration approved an alternative first-line agent namely lenvatinib. Cabozantinib, regorafenib, and ramucirumab also displayed promising results in second line settings. FOLFOX4, however, results in an alternative first-line treatment for the Chinese clinical oncology guidelines. Moreover, nivolumab and pembrolizumab, two therapeutics against the Programmed death (PD)-ligand 1 (PD-L1)/PD1 axis have been recently approved for subsequent-line therapy. However, similar to other solid tumors, the response rate of single agent targeting PD-L1/PD1 axis is low. Therefore, a lot of combinatory approaches are under investigation, including the combination of different immune checkpoint inhibitors (ICIs), the addition of ICIs after resection or during loco-regional therapy, ICIs in addition to kinase inhibitors, anti-angiogenic therapeutics, and others. This review focuses on the use of ICIs for the hepatocellular carcinoma with a careful assessment of new ICIs-based combinatory approaches. Hepatocellular carcinoma (HCC) is the sixth most common cancer and the fourth leading cause of cancer death worldwide as stated in reports as of 2018. Chronic hepatitis C virus (HCV) or chronic hepatitis B virus (HBV) infections, alcohol abuse, and non-alcoholic steatohepatitis are the main risk factors . TreatmeNevertheless, 70–80% of patients cannot benefit from such opportunities because they are diagnosed at an advanced stage and can receive only palliative care. Sorafenib has been the standard choice for a decade in advanced HCC, even if other Tyrosine Kinase Inhibitors (TKIs) as well  are charThe liver is an organ with a specific blood supply that influences its immune microenvironment. In particular, 75% of the blood vascularises the liver through the portal vein that drains into smaller diameter structures called sinusoids. Therefore, a great number of antigens are in contact through the liver sinusoidal endothelial cells (LSECs) with the liver immune microenvironment, consisting in hepatic stellate cells (h-SCs) , KupfferEfficacy and safety of ICIs have been evaluated in several trials in HCC . In SeptAbbreviation: CP: Child-Pugh; CTLA4: Cytotoxic T-Lymphocyte Antigen-4; DCR: disease control rate; HCC: hepatocellular carcinoma; mOS: median Overall survival; mPFS: median Progression Free Survival; ORR: overall response rate; PD-1: Programmed death 1; PD-L1: Programmed death-ligand 1; PR: partial response; SD: stable disease; TACE: transarterial chemoembolization; TKI: tyrosine Kinase Inhibitor.Unfortunately, the response rate of single agent ICI remains low, differently from the circulating CD8+ T-cells that increased after ICIs treatment, none activity enhancement have been observed for intrahephaticCD8+ T-cells. The combination of anti-CTLA4 and antibody targeting the PD1/PD-L1 axis are also under investigation, based on preclinical studies demonstrating that the 2 pathways are not overlapping, indeed it seems that the combination has a synergistic effect able to reverse the refractoriness of intrahepatic CD8+ T-cells . The comCombined immune checkpoint inhibition (ICI) with tremelimumab and durvalumab in patients with advanced hepatocellular carcinoma (HCC) or biliary tract carcinomas (BTC) .Instead, in the adjuvant setting, for patients who have undergone a remedial resection, toripalimab a anti-PD-1 antibody has being assessed in the JUPTER-04 trial with the primary end-point consisting in recurrence-free survival .Despite the fact that the impact of ICIs on the treatment of malignancies is unprecedented, unlike melanoma and non-small cell lung cancer, the response rate in HCC remains low. In regards to this, as well as for other malignancies, researchers are assessing combined approaches to increase the efficacy of ICIs . The comAter sorafenib, other TKIs have been approved for HCC patients ,9. InterAnother combined approach under investigation is the addition of ICIsto locoregional therapies, in particular, the post-transarterial chemoembolization (TACE), which is associated with antigen release and the exposure of damage-associated molecular patterns. A phase I trial concerning HCC patients treated with TACE, radiofrequency ablation, or cryoablation in combination with tremelimumb, showed 23.5% (4 of 17 patients) of PR . A tumorEven if HCC is known as a malignancy which is highly refractory to chemotherapy, based on the results of the EACH study, FOLFOX4 has been recently recommended as a clinical practice guideline by the China FDA 8.6% of partial response and 38.6% of stable disease have been reported with a median OS of 5.7 months . InteresFinally, in addition to the co-inhibitory receptors CTLA-4 and PD-1 other co-inhibitory molecules have been described, including TIGIT, LAG3, and TIM-3 . The latAs discussed in this manuscript, ICIs are under intensive investigation for HCC patients, as well as other malignancies, ICIs arealready approved for lines subsequent to the first, such as nivolumab and pembrolizumab. However, in the same way as in other solid tumors, the response rate is low, therefore several strategies to improve the efficacy of ICIs are under investigation. Several prospective clinical trials are assessing the efficacy and safety of PD1 blockade in combination with CTLA-4 blockade, since this combination should enhance the results of single agent anti-PD1. This combination should enhance OS and long term survival rates of both localized and metastatic HCC. In any case, it will take several years before obtaining not only results from these data, but also discovering predictive factors able to select patient candidates to ICIs therapy. The combinations of different ICIs with anti-angiogenic therapeuticsor of kinase inhibitors, are now being tested in HCC as well, with the aim to improve the anticancer effectiveness and prolong cancer survival. Interestingly, a unique and promising combinatory approach that is being assessed in HCC patients is the addition of ICIs to locoregional therapy.In the next years, several preclinical and clinical studies on HCC biology and treatment will address tailored therapies and combinations for these malignancies. In this scenario, immune oncology will have a special role in HCC. Even if, currently, the immunotherapy remains a non-curative treatment for HCC patients, the better tolerability of ICIs may display a crucial role in the improvement of the quality of life.


Global RNA sequencing technologies have revealed widespread RNA polymerase II (Pol II) transcription outside of gene promoters. Small 5′-capped RNA sequencing (Start-seq) originally developed for the detection of promoter-proximal Pol II pausing has helped improve annotation of Transcription Start Sites (TSSs) of genes as well as identification of non-genic regulatory elements. However, apart from the most well studied genomes of human and mouse, mammalian transcription has not been profiled with sufficiently high precision.Rattus norgevicus) primary neural progenitor cells. Over 48 million uniquely mappable reads from two independent biological replicates allowed us to define the TSSs of 7365 known genes in the rn6 genome, reannotating 2503 TSSs by more than 5 base pairs, characterize promoter-associated antisense transcription, and profile Pol II pausing. By combining TSS data with polyA-selected RNA sequencing, we also identified thousands of potential new genes producing stable RNA as well as non-genic transcripts representing possible regulatory elements.We prepared and sequenced Start-seq libraries from rat  contains supplementary material, which is available to authorized users. Transcription of genes was thought to be regulated mainly through recruitment of the RNA polymerase to promoters. However, work over the last several years –3 has deC. elegans, and Drosophila . Time-pregnant rats were obtained from a commercial resource (Charles River). Pregnant dams were sacrificed by first deeply anesthetizing them (to minimize pain sensation during decapitation) by intraperitoneal injection of pentobarbital solution and then decapitated using a sharp guillotine. Embryonic animals were decapitated with a sharp pair of scissors, cortices were isolated and subsequently digested in Accutase (Gibco) for 5 min at room temperature. Cultures of cortical neural progenitors were prepared from embryonic day 14 (E14) Sprague Dawley rats of either sex. Single cell suspension was achieved by triturating digested tissue through fire-polished Pasteur pipettes. Cells were washed with Hank’s Balanced Salt Solution (HBSS) without calcium and magnesium, and then plated onto dishes coated with CELLstart (Gibco) in Knockout DMEM/F-12 (Gibco) supplemented with 2% StemPro Neural Supplement (Gibco), 2 mM GlutaMAX (Gibco), 20 ng/ml bFGF (Gibco), and 20 ng/ml EGF (Gibco). Cells were passaged every 2–3 days and routinely collected after the second passage.PolyA selected RNA libraries were prepared from 50 ng of total RNA extracted from frozen cell pellets using Trizol reagent. In addition to the standard Trizol procedure, we included a chloroform extraction step of the aqueous phase after chloroform-induced separation of phases, to remove traces of phenol. RNA Integrity Numbers were calculated by Bioanalyzer and were always > 6.8, to meet the RNA quality guidelines for RNA sequencing service (Novogene). PolyA-selected RNA-sequencing libraries were prepared using NEBNext Ultra II library preparation kit with NEB beads, using 12 cycles of amplification. Libraries were quantified on Bioanalyzer prior to sequencing.scRNAs were prepared based on our earlier procedure , 22, witStart-Seq libraries were sequenced on a MiSeq instrument for quality control locally and re-sequenced on HiSeq2500 using small RNA option (SE50) commercially (Novogene) to the depth of ~ 100 M raw reads per sample. Raw files for Start-seq were mapped to rn6 genome using Hisat2. To filter out highly abundant species with multiple genomic copies such as tRNAs, only uniquely mappable Start-seq reads (Hisat2 mapping score > 3) were considered for analysis. Mapped reads were assigned to annotated genes using rn6 RefSeq annotation.PolyA-selective RNA sequencing was done to an average ~ 140 M raw reads per replicate using a commercial company (Novogene) from Trizol-extracted RNA. Reads were aligned to the rn6 genome using STAR and expression levels (FPKM) were obtained using the Rsubread  and DESeRn6 annotated gene TSS locations were obtained from UCSC and deduplicated to produce a list of unique start site coordinates for each gene. Contaminating RNAs  and micro RNA species were removed from consideration for this study. The deeptools package  was usedAdditional file 1:Supplemental figures and supplemental figure legends. (DOCX 1323 kb)Additional file 2:The list of genes with rn6-based coordinates of TSSs (RefSeq and Start-Seq-based) alongside TSS-RNA signal and RNA-seq signal for each replicate. (XLSX 1592 kb)Additional file 3:Panther GO analysis of highest and lowest PI genes. (XLSX 19 kb)Additional file 4:Stringtie assembly of new transcripts, as a Gene Transfer Format (GTF) file. (TXT 11349 kb)Additional file 5:Regions of bidirectional transcription outside of known genes identified based on TSS-RNA. (TXT 211 kb)


Acropora spp.) and foliose-digitiform (Porites porites and Agaricia tenuifolia) coral species in the back-reef, and a relative increase in non-framework species in the fore-reef (Agaricia agaricites and Porites astreoides). This resulted in a significant decrease in the physical functionality of the back-reef zone. At present, both reef zones have negative carbonate budgets, and thus limited capacity to sustain reef accretion, compromising the existing reef structure and its future capacity to provide habitat and environmental services.Functional integrity on coral reefs is strongly dependent upon coral cover and coral carbonate production rate being sufficient to maintain three-dimensional reef structures. Increasing environmental and anthropogenic pressures in recent decades have reduced the cover of key reef-building species, producing a shift towards the relative dominance of more stress-tolerant taxa and leading to a reduction in the physical functional integrity. Understanding how changes in coral community composition influence the potential of reefs to maintain their physical reef functioning is a priority for their conservation and management. Here, we evaluate how coral communities have changed in the northern sector of the Mexican Caribbean between 1985 and 2016, and the implications for the maintenance of physical reef functions in the back- and fore-reef zones. We used the cover of coral species to explore changes in four morpho-functional groups, coral community composition, coral community calcification, the reef functional index and the reef carbonate budget. Over a period of 31 years, ecological homogenization occurred between the two reef zones mostly due to a reduction in the cover of framework-building branching ( HowevAcropora was historically one of the dominant coral genera and a major shallow-water reef-builder [Orbicella remained as major Caribbean reef builders; however, their populations have decreased in the last two decades in many areas mainly due to diseases and bleaching impacts [In the western Atlantic, a few species of framework-building corals have dominated coral reef habitats throughout the region since at least the late Pleistocene –25. Ecol-builder ,24,26. H-builder , and sin-builder ,30. Afte impacts –34. What impacts –37 and t impacts ,39.Agaricia agaricites and Porites astreoides [The decline of the major reef-building coral species across the Caribbean has been accompanied by a relative increase in the abundance of non-framework coral species, such as treoides –43. Thistreoides ,45. The treoides ,47. By ttreoides –50. A setreoides ,51. Indetreoides .Key to understanding changes in coral communities are long-term studies, but this remains a challenging issue, partly because community shifts may occur slowly and most measures of assessment rely upon the comparison of present status to a defined past reference condition . Further2.2.1.Acropora palmata, which contributed greatly to the structural complexity of the reef; while the fore-reef was mostly of low relief (limited framework development), gentle sloping and colonized by sparse coral grounds, and grades gradually at a depth of approximately 20–25 m into an extensive sand platform [ca 200 000 visitors per year [We conducted this study in the Puerto Morelos reef system, located in the northern part of the Mexican Caribbean. This is a fringing reef system that stretches parallel to the coast (between 1 and 3 km) in a semi-continuous formation. This reef system has an identifiable zonation with a back-reef, reef crest and fore-reef that is mostly strongly influenced by wave exposure and light penetration . Historiplatform ,58. The platform ,60. Duriplatform . Coastalplatform ,62. Sediper year .2.2.This study compares data obtained in 1985 and in 2016. Data for 1985 were obtained by Jordan-Dahlgren , which cIn 1985, the geographical coordinates of each reef site were not obtained as the surveys were before the general use of GPS in scientific research, but to try to ensure realistic site comparisons, we only selected sites in 1985 and 2016 where geographical location could be accurately constrained based on the original maps that indicated surveying locations, depth and distinct geomorphological structures . For the2.2.1.To explore changes in coral community composition between 1985 and 2016, we used two complementary approaches. First, we classified the coral species in four morpho-functional groups to assess how different species with similar characteristics change overtime . Second, we assessed broader changes in coral species composition among years and reef zones.Acropora species; (ii) massive species from the second important group of reef-framework species, in this group, Orbicella is the main reef-builder genus, but we decided to included it with the other massive species because the contribution of Orbicella to the overall coral cover is relatively low; (iii) small non-framework builder species, which some authors define as opportunistic, which are small species that do not contribute greatly to calcification nor to structural complexity [Agaricia tenuifolia and Porites porites), which are considered as part of the opportunistic group by some authors [We distinguished four main groups of corals based on colony morphology and their contribution to reef framework –46: (i) mplexity ,45 and  based on Bray–Curtis similarities of square root transformed coral cover species data in Primer v. 6 . The mat2.2.2.3 m–2 yr−1, by summing the estimated CaCO3 production of each species. We then computed the reef functional index (RFI) (as described below) [3 m−2 yr−1).To assess changes in the functional capacity of studied reefs, we first estimated coral community carbonate production expressed in kg CaCOd below)  that, in−1) and the skeletal density (g cm−3) of the coral skeleton [−1) and skeletal density (g cm−3) for each coral species. By considering the characteristics of each species (morphology and growth), potential overestimations of calcium carbonate production are avoided. The modified estimates of calcification rates calculated here represent the contribution of habitat-forming species to carbonate accumulation. Rates of coral calcification are also dependant on local environmental conditions ; we, hoperature . Data onperature  and therX = /, where x is the value for each variable of each species. This standardization allows variables to have equal ranges (0–1). Then the three standardized variables were averaged to obtain a species-specific functional coefficient (Fc). The RFI is obtained through the fourth root of the summation of the product between live coral cover and the Fc of each species by transect for each reef zone and each sampling year [The RFI is a method proposed to estimate the species-specific functional contribution of Caribbean corals according to their capacity to create complex three-dimensional structures by means of calcium carbonate precipitation and their morphological complexity . One of ing year . The RFIing year .Diadema antillarum (1983–1984) [D. antillarum commonly accounted for up to 75% of the total bioerosion on many reefs in the region [D. antillarum (0.003 ind m−2) and for Echinometra spp. (0 ind m−2) [D. antillarum = 0.06 ind m−2; Echinometra spp. = 0.03 ind m−2; see also electronic supplementary material, table S5). Second, regarding parrotfish bioerosion, recent evidence shows that parrotfish populations in the Mexican Caribbean have undergone a slight recovery due to management regulations [Net carbonate production was determined as the balance between the coral carbonate production and bioerosion rates. Due to the absence of data on bioeroders from 1985, we assumed that bioerosion rates were similar in both periods of time. The rationale for this is that populations of the main reef-bioeroders have changed little during the timespan of our study. This assumption is supported by the following lines of evidence. First, our historical data (1985) were collected soon after the Caribbean-wide die-off of 83–1984) –75. This83–1984) , becausee region . The earind m−2) . The denulations ,80, whiculations –83. In s2) was determined by using a transparent 5 × 5 cm grid, within an area encompassing 0.5 m2 either side of belt-transects of 10 × 1 m. From this, percentage surface area covered by different sponge species can be determined. To estimate sponge bioerosion rates from census data, the methodology used published datasets to derive a relationship between sponge tissue cover and bioerosion rate whereby bioerosion rate = % surface area of sponge tissue/papillae × 0.0231 [D. antillarum and Echinometra spp. differ from other species, separate equations are used to calculate bioerosion rates (kg CaCO3 m−2 yr−1) for D. antillarum, Echinometra and all ‘other urchins’. For parrotfish bioerosion, visual censuses were conducted along 30 × 2 m belt transects (N = 8 transect per site), all parrotfish were recorded at species-level, life-phase and size. Bioerosion rate was estimated using the ReefBudget equations which use a model based on the individual size as a predictor of the amount of eroded carbonate per bite [et al. [3 m−2 yr−1.Rates of bioerosion for 2016 were based on the assessments undertaken at the same study sites in 2017/2018 using the ReefBudget methodology  for the × 0.0231 ,84. For per bite . Due to  [et al.  for site2.2.3.U-tests as the data were not normally distributed, which was verified using the Shapiro–Wilk test using the package stats v. 3.5 from R [Differences between years for each reef zone among all variables  were tested by means of non-parametric Mann–Whitney 5 from R .3.3.1.U-test, p < 0.05, value tests are in electronic supplementary material, table S2). Conversely, coral cover on the fore-reef did not change significantly . The proportion of cover by the four coral groups did change in both zones, but did so in different ways. In the back-reef, the cover of framework-building branching corals (i.e. Acropora spp.) decreased significantly from 14.16 ± 9.96% to 0.07 ± 0.15% , which largely explains the overall decrease in coral cover observed in this zone. The mean cover of foliose-digitiform species also decreased significantly from 5.77 ± 3.37 to 0.84 ± 0.86%  in the back-reef zone. The two species that are included in this group, P. porites and A. tenuifolia, showed similar declines for this zone. By contrast, the cover of non-framework builder species did not change significantly during the last 31 years in the back-reef , and nor did cover of massive species . The apparent increase in massive species is due to the small increases in the cover of Orbicella annularis, Pseudodiploria strigosa and Siderastrea siderea. In the fore-reef zone, the cover of framework-building branching species (0.85 ± 0.94% to 0.45 ± 0.42%), foliose-digitiform species (0.16 ± 0.19% to 1.29 ± 1.02%) and massive species (9.69 ± 5.20% to 10 ± 3.46%) also did not change over time , but the cover of non-framework species increased from 2.57 ± 1.20% to 5.04 ± 1.46% (figure 2b), especially A. agaricites and P. astreoides, being statistically significant between years .From 1985 to 2016, the mean coral cover in the back-reef zone showed a significant decrease from 32.90 ± 9.39% to 16.71 ± 3.55% ; Mann–Whitney R = 0.624, p > 0.05), as well as differences between reef zone groups across years , although with some overlap. The width (space occupied by the community) of the coral community composition was compared between years and between reef zones from the same year with the standard ellipse area (SEAc), which is the measure of the space occupied by the community . The back-reef zone in 1985 had the largest SEAc of all the reef zones, in contrast with the fore-reef zone of 2016 which has the smallest SEAc  in the back-reef zone between 1985 (3.51 ± 1.66 G = kg CaCO3 m−2 yr−1), mean ± 95% confidence intervals (CI) and 2016 (1.38 ± 0.38 G) (a). Conversely, in the fore-reef zone, no significant differences  were recorded in coral carbonate production rates between years .Coral carbonate production decreased significantly (Mann–Whitney  0.38 G) a. ConverU-test, p < 0.01) (b). By contrast, no significant changes occurred in the fore-reef zone between years .The RFI for the back-reef indicates a loss in the contribution of cover, structural complexity and calcification of coral species across the study period, declining from 0.57 ± 0.66 (mean ± CI) to 0.44 ± 0.04, and the drop between years was statistically significant (Mann–Whitney  < 0.01) b. By conU, p < 0.05) from 1985 (−0.16 ± 1.66 G) to 2016 (−2.30 ± 0.38 G) (c). Although, in 1985, net carbonate production was slightly negative on average in the back-reef zone, the variation between transects is very large due to the high cover of Acropora in some transects, while in other transects coral cover was already very low (a). By contrast, only two transects of the back-reef zone had a positive, but near-neutral, carbonate budget in 2016 (c). In the fore-reef, the mean net carbonate budget was negative and significantly different from zero for 1985 (−0.58 ± 0.51 G) and 2016 (−0.36 ± 0.33 G) with most of the transects in a negative carbonate budget for both years (c). For the fore-reef, the net carbonate budget was not statistically different between years .Regarding the carbonate budgets, we found, as expected, that the main carbonate producers were framework-building branching species followed by massive species, while parrotfishes accounted for most of the bioerosion in 2016. Electronic supplementary material, table S5 provides a detailed summary of the rates of erosion and production of each group. We found that in 2016, the back-reef had negative carbonate budgets, as net carbonate production dropped significantly (Mann–Whitney  0.38 G) c. Althouvery low a. By con in 2016 c. In theth years c. For th4.A. agaricites and P. astreoides). The increase in these non-framework species had no measurable effect on the functional potential of the fore-reefs as these species contribute very little to the reef structure and carbonate production [Coral communities in the northern Mexican Caribbean have changed rapidly over the last three decades, leading to a structural and functional convergence of the back-reef and the fore-reef zones. In the back-reef, coral cover declined by almost 50%, largely driven by the significant loss of framework-building branching, foliose and digitiform coral species; coral cover in the fore-reef remained relatively stable despite the significant increase in non-framework building coral species  that were the most important in delineating the back-reef zone  and zoneratures .c). In a wider regional context, González-Barrios & Alvarez-Filip [Agaricia spp. and P. astreoides) currently are widely dominant, while species with high functioning potential, such as Orbicella spp. and Acropora spp., have a limited relative abundance and distribution [Madracis mirabilis over the last four decades has compensated for some of the reduction in production observed on the reefs, but did not compensate the loss of structural complexity provided by other large calcifying species [The increase in non-framework species, especially in the fore-reef zone, is also transforming habitat configuration , figure . Our resfigure 4ez-Filip  found a ribution . It is iribution ); howeve species .3 reported here compromises the ability of coral reefs to sustain high rates of reef accretion, especially in the back-reef, which was previously the best developed zone in the north section of the Mexican Caribbean due to the contribution of the genus Acropora [The net loss of potential to accumulate CaCOAcropora ,80. GrosAcropora ; coral cAcropora ,99). ThiAcropora , althougAcropora . The forAcropora , and theAcropora , while nAcropora .The ecological and functional changes observed in our study sites are likely the result of ecological decline driven both by various regional-scale factors, like coral disease and bleaching, and exacerbated by local factors such as the explosive coastal development that the northern Mexican Caribbean has experienced since the onset of this study ,37,102. sensu [Limones reef, a back-reef site, located within the study area between Nizuc and Bonanza  of many Caribbean reefs has declined over the last 4 decades; there are still sites with abundant colonies of important reef-building corals that create complex reefs and where carbonate production is greater than estimated bioerosion . These ‘sensu ) could b Bonanza , but thaA. palmata (greater than 30%) [A. palmata in this site are highly resilient. In 2005, the cover of A. palmata in Limones reef dropped to less than 10% after the impact of two major hurricanes, but took less than a decade for the cover of this species to recover to its current state [Limones Reef will be crucial to aid management and restoration efforts on our study sites and elsewhere in the Caribbean region.This site has a high cover of The composition of coral assemblages seems to be the most important driver of the functioning of coral reefs, therefore maintaining keystone coral species could enhance the future of coral reefs . If curr


This new understanding of the determinants of nuclear retention and cytoplasmic export provides a deeper understanding of how information flow is regulated in eukaryotic cells. Ultimately these processes promote the evolution of complexity in eukaryotes by shaping the genomic content through constructive neutral evolution.Eukaryotes are divided into two major compartments: the nucleus where RNA is synthesized and processed, and the cytoplasm, where mRNA is translated into proteins. Although many different RNAs are made, only a subset is allowed access to the cytoplasm, primarily RNAs involved in protein synthesis . In contrast, nuclear retained transcripts are mostly long non-coding RNAs (lncRNAs) whose role in cell physiology has been a source of much investigation in the past few years. In addition, it is likely that many non-functional RNAs, which arise by spurious transcription and misprocessing of functional RNAs, are also retained in the nucleus and degraded. In this review, the main sequence features that dictate whether any particular mRNA or lncRNA is a substrate for retention in the nucleus, or export to the cytoplasm, are discussed. Although nuclear export is promoted by RNA-splicing due to the fact that the spliceosome can help recruit export factors to the mature RNA, nuclear export does not require splicing. Indeed, most stable unspliced transcripts are well exported and associate with these same export factors in a splicing-independent manner. In contrast, nuclear retention is promoted by specialized  The distinguishing feature of eukaryotic cells is that they are divided into two compartments: the nucleus where pre-messenger RNAs (mRNAs) are made and processed, and the cytoplasm where mature mRNAs are translated into proteins . This isImportantly, non-functional RNAs, whose harmful effects are reduced by eukaryotic quality control systems, are not effectively eliminated by natural selection and some of these can eventually evolve into functional long non-coding RNAs (lncRNAs). These add to the repertoire of bio-active polymers that organisms can use to regulate growth, homeostasis and development. Although some lncRNAs function in the cytoplasm, most operate in the nucleus . As a reFigure 1)  . In addiigure 1) . TREX2, igure 1) . Dbp5, Rigure 1) , althougigure 1) . The meccis-elements  or general features such as splicing, polyadenylation, and RNA modifications. These differences will dictate what proteins are loaded onto the RNA, resulting in the formation of a ribonucleoprotein (RNP) complex that determines the ultimate fate of the transcript.So how are exported RNAs, which mostly code for protein, differentiated from nuclear retained RNAs, which are typically non-coding? Ultimately these two types of RNAs must differ in one or more ways. This can include In this review we shall cover what is known about the RNA features that impact the nuclear retention and cytoplasmic export of mRNAs and lncRNAs. However, before we start, there are a few points to keep in mind. First, although we speak of a given RNA species as being retained in the nucleus or exported to the cytoplasm, few RNAs are completely nuclear or cytoplasmic at steady state. Instead, each RNA species exists at some point along a spectrum between these two extremes. Second, the ultimate steady state distribution of an RNA is dictated not only by the rate of RNA export, but also by the rates of RNA synthesis and of RNA decay in both the nucleus and the cytoplasm. Few studies have taken all these various factors into account with some exceptions. Having said that, it is clear that nuclear retention and cytoplasmic export play critical roles in dictating the ultimate distribution of any RNA species. Third, although it is generally true that most mRNAs are well exported, many are not . Likewiscis-element for them to be exported from the nuclei of mammalian tissue culture cells.Before addressing the question of what sequence determinants impact nuclear export, it becomes necessary to determine whether an RNA which lacks any distinguishing feature is a substrate for nuclear export. In other words, what is the default pathway – nuclear retention or cytoplasmic export? Three pieces of evidence point to the fact that long RNAs do not require any specialized cis-elements or other distinguishing features that may promote or inhibit mRNA nuclear export. More recently, we have demonstrated that two widely used reporters, a mini gene derived from the Drosophila fushi tarazu gene (ftz), and the β-globin mRNA, each have nuclear retention elements . As expected, the three constructs have relatively low CG-content ; however, all three are predicted to have either 5′ splice site motifs or 3′ splice site motifs [scoring ≥ 0.97 according to NNSPLICE 0.9 , with the majority of the resulting RNAs being efficiently exported , weaker processing signals are found throughout the genome. Even comparing mRNAs and lncRNAs, the former are typically more efficiently spliced than the latter . Thus, rSplicing involves the removal of introns by the spliceosome, which in turn can deposit factors onto the newly spliced RNA. By comparing the localization of these spliced RNAs to transcripts synthesized from cDNAs (which lack introns), it has been observed that splicing in some scenarios enhances the extent and the rate of nuclear export . The spl7-methylguanine connected via a 5′ to 5′ triphosphate linkage to the beginning of RNAs which are generated by RNA Polymerase II. This structure recruits the nuclear cap binding complex (CBC), which consists of CBP20 and CBP80. It has been reported that CBP80 can recruit nuclear export factors, such as the TREX component Aly, to the 5′ end of spliced -tail is not absolutely required for export is that circular RNAs, which lack a tail, are efficiently exported in a UAP56-dependent manner  suggest that these processes are not absolutely required. Again, as most RNAs exist on a spectrum between being fully nuclear and being fully cytoplasmic, RNA processing events may help to move the RNA closer to the cytoplasmic end of this continuum.It has been known for quite some time that RNA is extensively modified; however, until recently the majority of these studies focused on these modifications within tRNA and rRNA. More recently it has been observed that mRNA and lncRNAs are also modified. Furthermore, some of these modifications appear to impact nuclear export.NEAT1, which is required for paraspeckle formation  was a substrate for the RNA specific adenosine deaminase (ADAR), which converts adenosine to inosine . This reormation .6-methyladenosine . It should be noted that the Rev response element itself also contributes to the nuclear retention of the late-stage viral mRNAs and of the HIV genomic RNA when Rev protein is not present . This configuration is not only seen in certain viral mRNAs, but also in human mRNAs. For example, a mutation in the LAMTOR2 gene, which is associated with congenital neutropenia, creates a novel 5′ splice site in the 3′ UTR that results in the inhibition of gene expression . Interestingly, the nuclear retained RNAs accumulate in nuclear speckles, subnuclear regions where post-transcriptional splicing is thought to occur . This may explain why many poorly exported mRNAs are also localized to nuclear speckles  before halting transcription with α-amanitin, and then monitoring the newly transcribed RNA by fluorescence ted RNAs  . This finding is in agreement with studies of Bovine Papilloma Virus and HIV RNAs where the recruitment of U1 to a 5′ splice site inhibited proximal 3′ cleavage events . Under normal conditions the transcriptional elongation of these cryptic transcripts is curtailed by the presence of these 3′ cleavage/polyadenylation sites. Early 3′ cleavage promotes RNA degradation, although the exact mechanism in vertebrates remains unclear . Depletion of Mtr4 or ZFC3H1 resulted in the cytoplasmic accumulation of truncated mRNAs that utilized cryptic 3′ cleavage sites from intronic regions  binding protein, PABPN1  , which is essential for the nuclear export of most mRNAs . Association of PTB with mature RNAs is known to inhibit splicing and nuclear export . In addiThe majority of the human genome is composed of dead transposable elements, constituting half to two-thirds of all DNA . AlthougIt is likely that other features associated with transposable elements are recognized by nuclear retention machinery. It was recently found that the reverse complement of the Alu SINE, a primate-specific transposable element, contains a 42 nucleotide long element, named SIRLOIN, that mediates nuclear retention by recruiting the RNA binding protein, hnRNP K . A similcis-elements that promote nuclear retention have been characterized in the literature. As mentioned above, the Rev responsive element promotes nuclear retention  are also ill-defined . The mRNA is then translated into a short isoform of Nxf1 that may play a role in mRNA trafficking , the most well studied is the constitutive transport element (CTE) of type D retroviruses . This laNxf1/TAP . These efficking .cis-elements that promote nuclear export. mRNAs that encode proteins required for the cell cycle, contain an export promoting element in their 3′UTR which consists of a stem loop structure that recruits the eIF4E protein .So how exactly would junk RNA be converted to lncRNA? Likely, this is a step by step process where new entities are created by non-adaptive processes and then acquire functions which can be selected for by natural selection. One example is presented in  the TSS . If the This conversion process may frequently occur in tissues that have a high amount of spurious transcription, such as in developing spermatids . During The nuclear/cytoplasmic distribution and degradation of RNA also facilitates the evolution of alternative splicing. In particular, by retaining and degrading misprocessed mRNAs, they are not efficiently translated into proteins and do not cause much harm to the organism. This reduces the deleteriousness of splicing and polyadenylation errors and prevents their elimination by natural selection. This may explain why splicing appears to be inherently sloppy in mammalian cells. In support of this idea, it has been widely noted that although most genes are alternatively spliced, they typically give rise to only one polypeptide , suggestResults from ENCODE point to a wide diversity of nuclear/cytoplasmic distribution for many different types of RNA molecules . Over thAll authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.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.


RNA is the messenger molecule that conveys information from the genome and allows the production of biomolecules required for life in a responsive and regulated way. Most genes are able to produce multiple mRNA products in response to different internal or external environmental signals, in different tissues and organs, and at specific times in development or later life. This fine tuning of gene expression is dependent on the coordinated effects of a large and intricate set of regulatory machinery, which together orchestrate the genomic output at each locus and ensure that each gene is expressed at the right amount, at the right time and in the correct location. This complexity of control, and the requirement for both sequence elements and the entities that bind them, results in multiple points at which errors may occur. Errors of RNA biology are common and found in association with both rare, single gene disorders, but also more common, chronic diseases. Fortunately, complexity also brings opportunity. The existence of many regulatory steps also offers multiple levels of potential therapeutic intervention which can be exploited. In this review, I will outline the specific points at which coding RNAs may be regulated, indicate potential means of intervention at each stage, and outline with examples some of the progress that has been made in this area. Finally, I will outline some of the remaining challenges with the delivery of RNA-based therapeutics but indicate why there are reasons for optimism. The fundamental importance of RNA not only as a messenger molecule, but as a regulator of genes in its own right is increasingly being recognized. The production of mature messenger RNA (mRNA) is dependent on a plethora of processing and regulatory steps involving a complicated repertoire of sequence elements, RNA binding proteins and other regulatory RNA species. Given the complexity of the regulatory machinery, defects in non-coding regions of genes and regulatory genomic regions are common in genetic disease, being present in up to 50% of cases  and are 6A) may be added. Such modifications are added by a series of RNA readers, writers and erasers  synthetic polyamides (SPs) and artificial transcription factors (ATFs) . These all lines , they haRNA splicing is controlled by a complex interplay between ribonucleoprotein complexes and sequence elements in the pre-mRNA. The splicing process consists of two phosphodiester transfer reactions; the first being an interaction between the 5′ splice site and the branch site, and the second comprising cleavage at the 3′ splice site, and joining of the released exons. This occurs due to the action of a family of small nuclear ribonucleoproteins (snRNPs) named U1, U2, U4, U5, and U6, which together with a battery of approximately 80 other ancillary proteins form the core spliceosome and orchestrate the splicing process . The splThe global dysregulation of splicing patterns that occur in complex disease may be addressed by targeting the core spliceosome. There are several compounds of bacterial origin that affect the function of the SF3B component of the U2 snRNP, which are showing promise as anti-cancer agents by causing stalling of the cell cycle at the G1/S or G2/M checkpoints . AlthougFOXO1 and ETV6 was associated with restoration of splicing factor expression and rescue from cellular senescence  gene . This transcript is present at only 10% of SMN1 levels (SMN1. This has formed the basis for a novel therapeutic strategy whereby an AON (Nusinersen) has been designed to influence splicing patterns of SMN2. Nusinersen targets the N1 (ISS-N1) motif in SMN2, and promotes the inclusion of exon 7 and increases levels of compensatory SMN2. Several clinical trials have now been undertaken , or steric hindrance agents such as morpholino oligonucleotides or similar to occlude specific splicing regulatory sequences. This potential of this approach is best exemplified by novel treatments for spinal muscular atrophy (SMA) and Duchenne Muscular dystrophy (DMD) for which therapies for manipulation of splicing have been developed and are now licensed for clinical use. SMA is characterized by progressive neuromuscular disorder caused by mutations in the Survival Motor Neuron (N1) gene . These a1 levels  but has dertaken  and NusiDMD) gene  and lead to the production of a truncated, but still partially functional DMD protein (O-methyl-phosphorothioate oligonucleotides (2OMePS) or phosphorodiamidate morpholino oligomers (PMOs) which can be administered systemically  gene . The maj protein . Similar protein . Most AOemically . One of emically . Other aemically .Polyadenylation is an essential step in mRNA processing, with a pivotal role in maintenance of RNA stability and management of RNA turnover. Many genes contain more than one polyadenylation site and display alternative polyadenylation, producing mRNA transcripts with novel 3′ untranslated regions. These may be differentially targeted by non-coding RNAs such as miRNAs or RNA binding proteins, or have differential translation efficiency . Control2CR levels  . RNA ediR levels , and alsR levels , whereasR levels . AlthougR levels . Over-exR levels . Very reR levels . There aR levels . These eN(6)-methyl-adenosine (m6A), 5-methylcytosine (m5C), 5-hydroxymethylcytosine (hm5C) and N1-methyladenosine (m1A), which have been shown to be widely present throughout the transcriptome by high throughput sequencing   through altering m6A levels  , whereas 5′ UTRs . m5C mar 3′ UTRs . RNA mod 3′ UTRs . RNA epi 3′ UTRs . Disruptunstable . Accordiunstable , and witunstable . The RNAunstable . Similarunstable . StudiesA levels .The activity of genes is also dependent on the correct positioning of mRNAs within the cell. Once processed, RNAs are usually exported through the nuclear membrane into the cytoplasm ready to be translated. This is not a passive process; it is orchestrated by a portfolio of RNA export proteins which escort the RNA molecule through the nuclear pore. Messenger RNAs are primarily transported by Nxf1 and Xpo1, whereas miRNAs are exported by Xpot and Xpo5. The transcription Export complex 1 (Trex1) facilitates binding of Nxf1 to the processed mRNA, and together with a collection of other proteins such as karyopherins or importins causes the processed mRNA to associate with and transit through the nuclear pore . The nucThe repertoire of genes expressed by any given cell in any given circumstances is influenced by non-coding RNA (ncRNA) regulators of gene expression. These ncRNA genes do not encode proteins, but rather encode RNAs that contribute to the regulation of other RNAs. They are classified into 2 broad classes, short ncRNAs such as microRNAs (miRNAs) and longer ncRNAs such as long non-coding RNAS (lncRNAs) and circular RNAs (circRNAs).TTR) gene.MicroRNAs (miRNAs) and siRNAs are short non-coding RNAs 20–25 bp in size. They interact with components of the RNA-induced silencing complex (RISC) to bring about translational blocking or RNA degradation. Each miRNA interacts with specific binding sites in the 3′ UTR of its target genes, which are 6–8 nt in length and are commonly found in the genome; each miRNA is thus capable of targeting hundreds of mRNA target genes simultaneously . Severalcis , or they can map to entirely different genomic regions form their targets  and cause regulation in trans. LncRNAs can also be associated with promoters, enhancers or other regulatory regions and do not have a homogeneous mode of action. They can activate or repress their targets and can work by a number of mechanisms. They are commonly involved in genomic imprinting; one of the first lncRNAs discovered, XIST, coordinates X chromosome inactivation  are a relatively newly discovered class of non-coding RNA regulators found in multiple species . They arThis is an exciting time for RNA-based therapeutics, with several notable examples making it as far as license for clinical usage. Over the next decade, it is likely that there will be a large expansion in the breadth and scope of human disorders that can be treated using these, and similar approaches. Most developed at the present time, are interventions targeted at specific splice events and those involving small RNAs, but future work may harness the potential of targeting other parts of the RNA regulatory milieu .Several barriers do, however, remain to the wide implementation of these opportunities which are focused mainly on delivery, specificity and duration of treatment. Firstly, delivery of specific molecules to their site of action may be challenging. For some applications, such as skin, which may be treated topically or lung, which may be treated via inhalation, therapeutic delivery of interventions may be easier. Delivery to internal organs such as brain, liver or pancreas will require different and systemic approaches. One reason why AONs, readthrough agents and small RNAs have been at the forefront of this emerging field is that their small size and relative stability means that they can be more easily introduced into cells. This may not be true of entities such as lncRNAs or large circRNAs, which may be large molecules with potentially challenging secondary or tertiary structure. Small molecules can readily be introduced into cells using lipid-mediated transfer agents, or endogenous structures such as endosomes or microvesicles, which could be harnessed to deliver cargoes. Secondly, there are questions of specificity. One feature of the therapies that are in clinic currently is their specificity to their sites of action. Gene expression and the regulation thereof is highly tissue specific, and genes may often be required to be expressed only at a specified time, or in response to specific circumstances. It may not be advantageous to produce changes in all tissues or at all times, and effects must of course be limited to their intended targets. Specificity of effect can be achieved by choosing targets that are only present at their sites of action, or by modifying delivery so that cargoes are only delivered to their intended place of action. For example, strategies are emerging now which allow selective delivery of senolytic cargoes to senescent cells only using galactosaccharide nanoparticles, which harness the observation that senescent cells harbor large quantities of lysosomal β-galactosidase . SimilarThe multifactorial control of gene expression, and the complexity of this progress offers multiple points of potential intervention for therapeutic benefit. Over the coming decades, there is likely to be a huge increase in the number of therapies for human diseases that target not the genes themselves, but the expression and regulation of those genes. We are at the dawning of the era of genomic medicine, and the future looks bright.LH planned and wrote the manuscript.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Extracellular vesicles (EVs) mediate cell-to-cell communication by delivering or displaying macromolecules to their recipient cells. While certain broad-spectrum EV effects reflect their protein cargo composition, others have been attributed to individual EV-loaded molecules such as specific miRNAs. In this work, we have investigated the contents of vesicular cargo using small RNA sequencing of cells and EVs from HEK293T, RD4, C2C12, Neuro2a and C17.2. The majority of RNA content in EVs (49–96%) corresponded to rRNA-, coding- and tRNA fragments, corroborating with our proteomic analysis of HEK293T and C2C12 EVs which showed an enrichment of ribosome and translation-related proteins. On the other hand, the overall proportion of vesicular small RNA was relatively low and variable (2-39%) and mostly comprised of miRNAs and sequences mapping to piRNA loci. Importantly, this is one of the few studies, which systematically links vesicular RNA and protein cargo of vesicles. Our data is particularly useful for future work in unravelling the biological mechanisms underlying vesicular RNA and protein sorting and serves as an important guide in developing EVs as carriers for RNA therapeutics. Microvesicles and apoptotic bodies are both formed by outward budding of the cell membrane3. While microvesicles reflect the composition of the cytosol, apoptotic bodies can also contain cytoplasmic organelles and/or nuclear fragments3. Though both vesicle types tend to be larger than exosomes, the inherent heterogeneity of all populations stresses the need that biogenesis mechanisms should rather be used as the basis for their primary distinction4. In this study the term ‘extracellular vesicles’ is used to refer to an exosome-enriched pool of vesicles.Extracellular vesicles are important mediators of cell-to-cell communication. These lipid bilayer vesicles of around 30–2000 nm in diameter are secreted by virtually all types of cells either constitutively or upon specific stimuli. The biogenesis of EVs includes a range of complex mechanisms, which in itself could contribute to disparate sorting of vesicular cargo and thereby support cell type specific biological effects of the vesicles. Based on their biogenesis pathways, there are three broad types of EVs - exosomes, microvesicles, and apoptotic bodies, each of those being highly heterogeneous in their own. Exosomes are intraluminal vesicles of the multivesicular body (MVB) that are released from the cell upon MVB fusion with the cell membrane, a process which is largely regulated by ESCRT proteins, Rab GTPases, and neutral sphingomyelinase5), which can either reflect that of their cell of origin or display enrichment of certain miRNA subsets6. Which miRNAs are enriched in EVs often depends on the cell type and its physiological status7, yet miRNA traits such as DICER independence, presence of specific nucleotide sequences or -interaction with certain RNA binding proteins seem to promote the sorting of a subset of miRNAs into EVs (reviewed in 7).EVs mediate their native biological effects by transferring or displaying their cargo to target cells, whereas the effects are either related to their overall complex cargo signature, or to certain individual biologically active macromolecules. Some EV effects have been attributed to their specific miRNA content , RD4 , Neuro2a (neuroblastoma cells), C17.2  and C2C12  cell lines.EVs were characterized by Nanoparticle Tracking Analysis, transmission electron microscopy and western blot, confirming their size around 100 nm, presence of cup-shape morphology and the enrichment of ALIX and TSG101 throughout the tested samples Fig. .Figure 129.The parental cells as well as EVs were subjected to next generation sequencing followed by data analysis of the vesicular- and parental cell derived short RNAs. Due to our specific interest in vesicular small RNAs, short RNA centred size-selection of the libraries and length-restricted data analysis in the size range of 17–35 nucleotides was carried out by using a custom in-house workflow. Here we performed sequential annotation discriminating between ‘small RNA’, ‘rRNA’ and ‘other RNA’ categories  Fig. . InverseAdditionally, the annotated RNA species across EV samples were also more variable than across source cells Fig. . For exaversus 3%) and a reduction in miRNA annotations (mean 25% versus 77%)  in all tested parental cell types could be attributed to miRNA genes with very low levels of reads annotating to piRNA loci  Fig. . Though miRNA expression scatter plots unfolded a good correlation between miRNA levels in EVs and their parental cells  and mmu_piR_002962 (DQ548183)) which tended to accumulate in EVs  fragments . It should be noted that only a small number of individual genes contributed to the vast majority of total RNA reads  both in the case of ‘small RNA’ and ‘other RNA’, as illustrated by the cumulative histograms of RNA reads  were more abundant in all tested cell line EVs. This could also be seen from the list of overall top-ranking RNA genes across all RNA categories  in this study. While in the cell samples the prominence of individual miRNAs was very clear, the EV samples were dominated by highly abundant ‘rRNA’ and ‘other RNA’ annotations  overlapped with annotations in the manually curated Vesiclepedia databasedia Fig. . The 212dia Fig. . ~90% of32 using a reference list of all detected protein identifications per EV source. Among the commonly overrepresented Gene Ontology (GO) classes for both vesicle types we found overrepresentation of entries related to ribosomes, mRNA catabolism, translation initiation, protein targeting to membranes, unfolded protein binding, extracellular matrix, focal adhesion, blood microparticles and extracellular exosomes  of the EV proteome, we employed the Panther Statistical Overrepresentation Testmes Fig. . Howevermes Fig.  and S11.mes Fig.  and S6.http://www.ebi.ac.uk/QuickGO/). This set of proteins constituted 29% and 22% of all identified proteins in HEK and C2C12 EV samples, respectively, which is in line with the mean reported frequency (21%) of RNA binding proteins in Vesiclepedia database  according to the QuickGO database  and the number as well as abundance distribution of these proteins within each GO child term was verified Fig. . GO clasEVs have gained widespread interest due to their native components such as proteins and RNA, thereby serving as a rich source of molecules with therapeutic and biomarker potential. EV-mediated transfer of bioactive components, as well as their involvement in disease pathogenesis has been described in numerous studies. However, a lack of detailed knowledge of the cooperation of biomolecules with basic biological mechanisms still impedes employing the full potential of EVs for therapeutic interventions.35, many of these concentrate on only one cell type. Hence, there is a strong need for additional comprehensive comparisons with improved capacity to unfold biological mechanisms controlling EV cargo loading.This study involves small RNA transcriptomics and proteomic approach to describe the inherent heterogeneity of EV cargo. Even though several EV  RNA profiling studies have previously been published37 and as a highly abundant miRNA in blood38, its enrichment in FBS and thereby carryover to cell-culture settings could lead to misinterpretation of the biological abundance39. The usage of serum supplemented medium prior to conditioned media collection may also have had an influence in our dataset, revealing potential serum-confounding miRNAs with read counts in vesicular samples exceeding those of parental cells. Screening the top three FBS-enriched miRNAs previously reported by Wei et al.39 (in addition to miR-451a), we indeed found potential FBS-confounding miRNAs, as they were less abundant in cells than EVs. Nevertheless, this observation was either not consistent throughout the tested cell lines or the particular miRNAs were low abundant by not ranking among the top 50 most abundant miRNAs (covering 84–92% of the miRNome in cells and EVs). Hence, when focusing on total EV miRNA levels, the concern of miRNA carryover from FBS into our EV samples is low.The study at hand investigated the overall RNA diversity of parental cells and EVs from five different cell types. Expectedly, the parental cells predominantly contained ‘small RNAs’, of which a great majority represented miRNA sequences, strongly affirming the reliability of the applied methodology. In contrast, the ‘small RNA’ content in EVs was modest and highly variable across the studied samples. Nevertheless, there was a large overlap and a good correlation of vesicular and parental cell content in terms of the relative abundance of miRNAs. Yet, this correlation excluded certain individual miRNAs, e.g. miR-451a which was more enriched in EVs than would be expected from the parental cell background. Enrichment of this non-canonically processed miR-451a has been reported in a number of studiesIn addition to miRNAs, vesicle samples throughout the tested cell lines exhibited a remarkable richness in sequences derived from piRNA loci, which however lacked the correlation with their parental cell expression level. The vesicular enrichment of piRNAs was quite different from miRNAs and mostly showed cell-line specific EV enrichment of certain annotations. Yet, piR_000935 stood out as the most abundant piRNA in practically all mouse cells and EVs and thereby caught our attention. As the genomic location of piR_000935 overlaps with Rny1 gene (Ro-associated Y1), we cannot rule out that the sequences at hand might instead represent 5′ Y RNA fragments, which due to the choice of stepwise annotation could have become underrepresented .42, corroborating well with the data presented here. The presence of rRNA fragments have often been denoted as impurities in EV preparations or unspecific degradation products, displaying a high abundance that can already be anticipated from their richness in the cell. Yet, an increasing number of studies have highlighted the precise cleavage patterns of rRNA43. These fragments (when overexpressed) are able to affect cell viability44 and are capable of entering the RNA interference pathway45, indicating a potential role in gene regulation in recipient cells, even across kingdoms46.Whereas ‘small RNA’ sequences in EVs represented a relatively modest part (22%) of all annotated reads, we found a large amount (60%) of rRNA fragments within the 17–35 nt long sequences. Overall, the rRNA content in EVs reflected the pattern of their parental cells. Interestingly, in human samples, the majority of these fragments were derived from the large ribosomal subunit sequences, whereas in mouse samples we detected a higher quantity of small subunit fragments. Additionally, though mitochondrial rRNA fragments were detected in low amounts in cell samples, virtually none of these fragments was found in EV samples. Despite performing stringent evaluation on cell viability throughout EV production, we cannot rule out that some of the rRNA in our EV samples is derived from apoptotic bodies. Yet, in EVs as compared to cells, the overall level of rRNA fragments is too high to merely be attributed to contaminating factors. In fact, even though contradicting evidence on the vesicular rRNA content exist, the vast majority of vesicular deep sequencing studies report a strong predominance of rRNA fragmentation products in EVs47. Herein, we found a notable predominance of vesicular tRNA-Gly-GCC, tRNA-Glu-CTC and tRNA-His-GTG corroborating well with previous findings25. Since we restricted the analysis to reads of 17–35 nucleotides in length, the observed sequences likely correspond to tRNA fragmentation products, with a predominance of 28–35 nucleotides long sequences of uniquely tRNA-annotated reads for both cellular as well as vesicular samples. To date, a wide variety of tRNA derived fragments  have been identified, some with a direct capability to inhibit protein synthesis and function as miRNAs (reviewed in 88). It has yet to be determined if any of the detected fragments in the current dataset could belong to any one of these subclasses and contribute to any biological functions.The most prominent biotypes in the ‘other RNA’ category were tRNAs-, protein coding- and miscellaneous RNA (including Y RNAs). Regardless of the number of detected distinct RNAs, the bulk of the ‘other RNA’ reads originated from around 20 transcripts, with tRNAs and Y RNAs being the most abundant RNA species. The high abundance of tRNAs as well as enrichment of particular tRNA/Y RNA-derived fragments have previously been reported in several EV-based studies, despite the employment of short read-length sequencingThe highly variable and relatively scarce representation of miRNAs in EVs led us to further investigate the association of the small RNA transcriptome to the vesicular proteome by choosing HEK and C2C12 EVs as a basis for our further analysis. Similarly to transcriptomic results in which a relatively small number of RNA sequences contributed to a large proportion of total detected RNA reads, ~200 most abundant proteins were found to make up 75% of the total protein mass in EVs. Also, in line with the finding of a high abundance of ribosomal, coding and tRNA fragments in the sequencing data set, we discovered high levels of rRNA-, poly(A)- and tRNA binding proteins in the proteomic dataset for both HEK- and C2C12 EVs.52, we first decided to check the interplay of miRNAs and their binding proteins. Though C2C12 EVs were substantially richer in miRNAs than HEK EVs, we were unable to detect any major differences in the miRNA-related proteome. Based on our custom-curated GO list we detected 33 miRNA-related proteins, showing a negligible contribution (<1%) to the proteome for both samples. From the RISC-loading complex, only a very low amount of DICER1 and TARBP1 (found only in HEK EVs) as well as a low amount of MOV10 RISC complex RNA helicase (in both samples) were detected. Additionally, in contrast to previous studies54, we were unable to detect any Argonaute proteins. Considering the discrepant abundance of miRNAs in these EV samples together with a good correlation of cellular and vesicular miRNA levels, regarding this dataset, it is difficult to speculate whether miRNA sorting into EVs is dependent on a specific miRNA binding protein. Number of different proteins have been demonstrated to be involved in miRNA secretion within EVs, thus multiple sorting mechanisms may co-exist simultaneously.As one of interests of the study was to verify whether the RNA repertoire of the EVs would correspond to the proteome, we were especially interested in the correlation of RNA binding proteins with respect to the related RNA species. Since passive as well as active mechanisms of miRNA loading into EVs have been suggested57. Herein, despite the high number of piRNA sequences, piRNA-related proteins remained undetected, aligning well with our observation that the sequences annotated as piRNAs in this study rather represent reads mapping to piRNA loci.In contrast to the relative depletion of miRNA reads, EVs showed a high number of piRNA sequences. Initially, we hypothesized that this is contributed by the EV protein composition. However, this was not the case as none of the proteins annotated as ‘piRNA binding’ in the GO database were found in EVs. The presence of piRNA binding proteins in EVs has so far (in low amounts) been reported only in a few studiesA high abundance of rRNA reads in all EV samples led us to investigate the ‘rRNA binding’ (GO:0019843) proteins, which were found to constitute ~10% and ~3% of HEK and C2C12 EV proteomes, respectively. Considering the richness of reads annotating to rRNA loci, it seems that the rRNA is largely disconnected from the loading of ribosomal proteins. Concomitantly, we cannot exclude that the high abundance of rRNA reads could be brought about due to limitations in EV sample preparation, though contamination markers  in vesicle preparations were present in negligible amounts.58.The highest number and contribution to the proteome for both datasets was seen for proteins classified under “poly(A) RNA binding” term. Though, a few protein coding genes did rank high in the EV transcriptome, we believe that the short read-length sequencing used in the present study is not sufficient to serve as a basis for further elaborations. The high contribution of proteins described by “translation factor activity” term was found to corroborate well with the increased abundance of tRNA sequences in the EV secretome, thereby supporting earlier studies describing the abundance of transcriptional/translational factors in the EV proteome and transcriptomeAn increasing number of studies are concentrating on understanding the loading and interplay of bioactive EV macromolecules. This study, combining the vesicular RNA and protein cargo composition, serves as a valuable source of information not only in terms of knowledge in basic EV biology but also for the development of EV-based carrier systems for therapeutic RNA interventions. Nonetheless, as we are only considering a handful of cell types, there is still a need for additional studies utilizing other EV enrichment methods and cell types to fully understand and seize the underlying potential of vesicular biology for therapeutics.2. 3 × 106  or 5 × 106 (HEK293T) cells were first seeded onto 15 cm cell culture dishes. After 24 hours, cells were washed with 0.01 M phosphate buffered saline (PBS) to ensure removal of any residual FBS before a media change to OptiMEM  supplemented with 1% Antibiotic Antimycotic Solution . After 48 hours, cell viability was evaluated by trypan blue exclusion method and cultures displaying <95% viable cells were excluded from further processing. The supernatant from the cell cultures passing the quality control step was collected and EVs were harvested by differential ultracentrifugation (UC). Briefly, conditioned medium (CM) was spun at 300 g for 5 minutes, followed by a spin at 1,500 g for 10 minutes and 0.22 µm filtration to remove dead cells, cell debris and larger particles. EV pelleting was performed by two consecutive pelleting steps at 110,000 g for 90 minutes, with an intermediate washing of the EV pellet in 25 ml of PBS. The final EV pellet was resuspended in PBS and either stored at −80 °C for proteomic analysis as indicated below or mixed with Trizol LS  and stored at −80 °C until RNA extraction for small RNA sequencing analysis. All UC steps were performed at 4 °C, using a fixed angle Type 70 Ti rotor from Beckman Coulter .Neuro2a, RD4, C17.2, C2C12 and HEK293T cell-lines were maintained in high-glucose (4.5 g/l) Dulbecco’s modified Eagle’s medium with GlutaMax  supplemented with either 10%  or 20% (C2C12) fetal bovine serum . All cells were cultured in a humidified atmosphere at 37 °C and 5% CONanoparticle Tracking Analysis (NTA) was performed by using the NanoSight NS500 nanoparticle analyser  to measure the size distribution and concentration of the purified EVs. The EV samples were diluted in PBS and the movement of the particles was recorded within five 30 seconds videos that were subsequently analysed using the NTA Software 2.3  at detection threshold 5, camera gain 350 and shutter setting 800.Transmission electron microscopy (TEM) was performed by applying the purified HEK293T EV sample onto Formvar/Carbon type B coated electron microscopy grid . The grid was washed with double distilled H2O, blotted dry with filter paper and stained with 2% uranyl acetate  diluted in distilled water. The grid was dried with filter paper and analysed with a FEI Tecnai 10 transmission electron microscope (FEI) at an accelerating voltage of 100 kV.Western blotting (WB) was performed as described previously59. Molecular weight was estimated according to PageRuler Plus Prestained Protein Ladder . For probing, 1:1000 primary antibody dilutions were used for anti-ALIX , anti-TSG101 , anti-Calnexin , anti-SDCBP (syntenin)  and 1:5000 dilution anti-ß-actin . For detection, 1:15,000 dilution of secondary antibodies  were employed. The membranes were visualized on the Odyssey infrared imaging system and further analysed by using Image Studio Lite Version 5.2 .Total RNA extractions were performed according to manufacturer’s instructions using TRIzol and TRIzol LS  for cells and EVs respectively. Improved RNA precipitation was gained by adding 2 µl of PolyAcryl Carrier PC 152 polymer  per reaction. The RNA integrity of the cell samples was verified on Bioanalyzer RNA 6000 Pico Total RNA Kit  and the RNA concentration for all samples was measured with the Qubit 2.0 Flurometer by using the Qubit RNA HS Assay Kit . 250 ng of total RNA was subjected to small RNA library preparation by using the NEBNext Multiplex Small RNA Library Prep Set 1 for Illumina  kit according to the manufacturer’s instructions. The barcoded samples were size selected on the 6% Novex TBE PAGE gel  and the fragments corresponding to microRNA range were cut and subjected to purification with the NucleoSpin Gel and PCR Clean-up kit . Thereafter, the products were quantified by using the KAPA Library Quantification Kit  and pooled at equimolar ratio. Two libraries  were generated in parallel, each one eventually containing a pool of 12 barcoded samples. The readymade libraries were further checked on the High Sensitivity D1000 ScreenTape  and quantified by using the KAPA Library Quantification Kit to enable precise loading of the flow cell. The clusters were generated by using the cBot and one replicate per lane was sequenced on the HiSeq 2500  with a 1 × 51 setup in RapidRun mode.28. The Gene Ontology (GO) term enrichment and -overrepresentation analysis were performed by using the Protein ANalysis THrough Evolutionary Relationships (PANTHER) software (release 20161020)32. The abundance of distinct proteins was calculated from the MS Area of the particular protein over the total MS Area of the sample proteome. The Panther Statistical Overrepresentation Test was based on reference protein list containing all protein identifications of the input list.UC-purified EVs and HEK cells were analysed by LC-MS/MS as described previouslyhttp://www.ebi.ac.uk/QuickGO/, Gene Ontology Database release 2016-10-27) as well as human/mouse proteomic entries in the Vesiclepedia31 database for experiments with a minimum of 500 proteins identified. For GO term analysis of miRNA related proteins, a list of 50 miRNA related GO terms was compiled, followed by downloading the corresponding protein annotations using the QuickGO browser. All proteomic analysis is based on unique protein identifiers, thereby taking into account different isoforms of the same protein.The fraction of RNA binding proteins was calculated by basing on the list of “RNA binding” proteins (GO:0003723) obtained via the QuickGO browser  were subjected to subsequent mapping on the Ensembl 38.85 releases of the mouse and the human genome by using Bowtie1 (release 0.12.6)63 in -v1 alignment mode and best alignment stratum reporting option.Raw sequencing reads were quality controlled by FastQC64 in stranded mode. Briefly, reads were first annotated against ‘small RNAs’, followed by ‘ribosomal RNA’ and ‘other RNA’ annotations with intermediate filtering steps allowing only the reads with no found feature to continue down the pipeline. Gene biotype classification was done following the classification details in Vega Genome Browser release 68. MicroRNA annotations were retrieved from the miRBase65 release 21, snoRNA and snRNA annotation from Ensembl 38.8566 annotation file and piRNAs from piRNAbank67 followed by the UCSC liftOver68 of the hg18 and mm8 chromosomal coordinates to genome release 38 coordinate system. The ribosomal RNA annotations consisted of mitochondrial rRNA annotations from Ensembl 38.85 and a combination of the UCSC Table Browser hg38/mm10 RepeatMasker ribosomal RNA entries with ribosomal RNA annotations from the Ensembl 38.85 release that using BEDTools/2.26.069 had less than 50% reciprocal overlap with the aforementioned RepeatMasker entries. The ‘other RNA’ annotation gathered annotation entries from Ensembl 38.85 which were not included in either of the ‘small RNA’ or ‘rRNA’ annotation files, plus tRNA annotations of the respective genomes which were retrieved from UCSC Table Browser. The absence of human RNY5 and its pseudogenes’ annotations from Ensembl 38.85 was compensated by including manual annotation entries from Ensembl GRCh38.p10 to the gained ‘other RNA’ annotation file. tRNA read counts originating from different loci were pooled according to the isoacceptors of a given tRNA. If applicable, the miRNAs/piRNAs with read counts ≥3 were normalised over the total number of miRNA/piRNA reads in the respective samples. The online analysis software Morpheus  was used to generate heatmaps as well as perform hierarchical clustering. For both analysis, normalised read counts were used and entries with zero read count throughout the tested samples were excluded. Hierarchical clustering was performed by utilizing one minus Pearson coefficient as the clustering distance measure. Base composition analysis for reads mapping to piRNA loci was performed with FastQC analysis followed by aggregating the results with MultiQC v1.370.Annotation was performed in a stepwise manner with HTSeq (release 0.6.1)Statistical analyses were performed using GraphPad Prism Version 6 .The small RNA sequencing data has been deposited to NCBI Sequence Read Archives under accession number SRP118970 (BioProject: PRJNA408072).Supplementary Information