Comparison of satellite-derived chlorophyll-a, backscatter, absorption and remote sensing reflectance at 412 nm suggest that dredging activities led to a decrease in biological health of the region resulting from the smothering of natural benthic habitats and reef complexes with sediment. We anticipate this ex post facto quantification of the connectivity between island-construction, large particulate plumes and a decrease in absorption related to marine life in the water column to establish a starting point for further study into ecosystem impact. The potential associations between these damages and a long-term reduction in ocean life and resources could serve inter-governmental bodies with a baseline metric for evaluating the level of damage caused. This may result in both forward-looking deterrent policies that limit island-building as well as backward-looking compensation.This paper quantifies environmental effects of island-building operations in the South China Sea, which result from dredging and can negatively impact marine flora, fauna, and ecosystems. The extent of the damage caused by island-creation is believed to be large, as the South China Sea reefs support the largest concentration of marine biodiversity on Earth. Through use of satellite imagery, we investigate the island-construction on Mischief Reef in the South China Sea, showing backscatter increases of up to 350% in waters surrounding the reef, with plumes of excess sediment exceeding 250 km This activity allows nations to project military power by adding armaments on these new islands, and to protect their highly important fishing fleets3. In the South China Sea (SCS) between 2013 and 2017, China built 3,200 acres of new land, Vietnam built 120 acres of new land, and Taiwan built eight acres of new land4. Given this level of activity in the SCS and the fact that environmental alterations resulting from dredging can include the loss of species in the benthic community5, it is natural to ask: what impact do these activities have on the surrounding ocean? The potential causality between Chinese island-building operations and environmental degradation is potentially significant, as the Spratly Islands in the SCS form a distinct marine ecosystem, which serves as a significant source of larvae for regional coral reefs7. Increasing demand for fish in the SCS has led to political tensions and even violence as millions of people in the region rely on fishing for food and work8. Further complicating these pressures, the preservation of the transport connectivity between living organisms, as well as, pollutant dispersion occurs across sub-regions and across national boundaries within the SCS2. Nations outside the SCS are also impacted by the ecology therein as the sea sits on the western edge of the Coral Triangle, which hosts the largest concentration of marine biodiversity on Earth including many threatened species9. Although numerous studies have examined the impact of dredging generally11, safety concerns resulting from the tense political climate in the SCS prevent robust in-situ measurements near the sites of recent land-building operations in that region. The work presented herein, based on a case study of Mischief Reef   and/or trailing hopper dredging (THD) often followed by airfield construction°E) Fig.  through way Fig. 13,14.Fighttps://amti.csis.org/mischief-reef/ as of 26 October 2017] of The Center for Strategic and International Studies. Mischief Reef was largely submerged in 2014, above the waterline in 2015 following commencement of dredging, and inhabited by living quarters and an airstrip in 2016 , Landsat 8 Operational Land Imager (OLI), and Sentinel 2A imagery (level 1 C)  daytime granule from January 2013 through December 2018 touching a portion of Mischief Reef was acquired from NASA’s Ocean Color Web site [https://oceancolor.gsfc.nasa.gov/]. The data extracted from each granule for use in this study consisted of the time of the overpass, and, for each pixel in the granule, a measure of the quality of the data (referred to as l2_flags in the dataset), the location of the pixel (latitude and longitude) and the total absorption and total backscatter based on the GIOP model for each of the spectral bands available on MODIS in the visible portion of the spectrum . The study area was covered by the satellite at least once per day but, because the spectral channels of interest are in the visible portion of the spectrum, clear views of the reef and surrounding waters were possible only under cloud-free conditions.To allow for a historical perspective, as well as to provide the data required for this study, every Level 2 (L2)  As part of the regridding process, L2 processing  flags were used to mark, for later exclusion, pixels flagged as high radiance, clouds, low water leaving radiance, absorbing aerosols, chlorophyll out of bounds, suspect atmospheric correction or product failure. Not marked were pixels flagged as containing coccolithophores, turbid water, or moderate glint. A land mask was created by summing the remapped 412 nm backscatter images from 2002–2010  and thresholding the resulting image at 4.55 mTo determine the impacted area, a mean background backscatter value for each visible spectral band in each image was determined for an annulus from 31 to 50 km from the reef, an area not impacted by dredging as will be shown below. The number of pixels in an annulus from 7 to 35 km, which exceeded the mean background backscatter by 30% for the given spectral band, was then multiplied by the area of a pixel yielding the impacted area. Masked pixels may have been impacted but are not counted hence the estimate of the impacted area for a plume is a lower bound on the actual impacted area for that day. Furthermore, the lagoon within Mischief Reef was not included in this calculation because the value within the lagoon often exceeded that of the background in the pre-dredging period as well as, of course, during and following dredging.N is the number of satellite passes for the period of interest, BSi, j,k is the backscatter for the th pixel of the kth image,Backgroundk is the mean background backscatter as described above for the given image, andIn order to estimate the area of the seafloor potentially impacted by sinking sediments, the mean backscatter of pixels, marked as impacted, was determined for 2008 and 2015. The mean backscatter of impacted pixels is given by:The number of impacted pixels was determined for each image with at least 100 clear pixels in the background area and at least one clear pixel between 7 and 35 km from the reef center. Monthly means of the various quantities were determined by averaging the quantity over all images for the given month following Eq. 16, and remote sensing reflectance measured at 412 nm. These data are accessed separately from the GIOP data, although from the same site (the NASA Ocean Color Web site). We again downloaded every L2 daytime OCI granule from July 2002 through December 2018, which touched a portion of Mischief Reef, and followed the same preprocessing steps as described for the GIOP data; i.e., the OCI data were regridded to the same 750 m grid, masked using the same flags  and then binned into 1 km annular rings centered on Mischief Reef. The same land mask was also used. To serve as points of reference, Fig. To estimate the potential longer-term biological impact of dredging, we again use MODIS data from Aqua, this time chlorophyll, estimated with the Ocean Color Index (OCI) algorithmA clear increase in backscatter during 2015 was seen across all visible spectral bands . We present the results for the 412 nm band as this wavelength captures impacts from phytoplankton and sediments  and the red bands traditionally used to detect turbidity were not reliable . The monthly mean backscatter, is shown in Fig. 2) by May 30, 2015 . Ships were observed in the lagoon starting on March 16, 2014 and the first dredging activity  was observed on March 3, 2015. The final satellite image with identified dredging activity was from November 30, 2015. The small (<0.3 km2 day−1) rates of island building between June 2015 and September 2016 are attributed to slight variations in the delineation process as well as a slight shrinking of the land area as the edges were constructed into a well-defined sea wall.Dredging and island building on Mischief Reef began in late January 2015 and the reef had reached it’s maximum area 20.94 km km2 by M2 prior to dredging (2003–2013) as natural variability in the data – visual inspection of pre-dredging images showed that’impacted’ pixels were generally randomly scattered across the region or were grouped on the periphery of areas flagged for one of the reasons outlined in Section 2. The monthly averages of the impacted area for the period 2008–2017 peak at 62 km2 in June of 2015; the area of the plume on 8 June was 262 km2 compared with a pre-dredging background value of approximately 7 km2. The yearly averaged monthly plume area from 2015 to 2017 is 3.8 km2compared with the mean for 2015 of 23 km2. These statistics exclude the area within 7 km of the center of the reef. It is important to stress that these numbers are for plume size averaged over a given month, not the cumulative area covered by plumes, which will be discussed below. Furthermore, these averages do not include potentially impacted areas covered by clouds; i.e., again, these numbers represent lower bounds on the impacted area. We could have estimated the total impacted area by normalizing for the fraction cloud cover in the vicinity of the reef but we decided to present the more rigorous lower bound here.Figure Prior to dredging activity, backscatter was elevated in the center of the reef , compared to the outer reef region, decaying to a constant background level at approximately 8 km Fig. . The curSimilar to backscatter, absorption also shows elevated values within the reef compared to the outer reef region. However, there are differences in the response between these parameters associated with the dredging activity. In 2015, when dredging began, absorption is only slightly higher within the lagoon but statistically identical to that of the previous years outside of the lagoon Fig. . By contThe increase of chlorophyll-a levels Fig.  in 2015,Inspecting remote sensing reflectance at 412 nm, also suggests these patterns Fig. . Prior t−1 for this satellite pass) by a factor of 1.3 (0.0064 m−1) extend more than 30 km from the center of Mischief Reef. Of particular interest with regard to these plots is the shape and location of the plume emanating from the reef and, in particular, the rapidity with which it changes. Consider, for example, the four images in the bottom row of the figure,  2) extending to the southwest, to a significantly larger plume (262 km2) emanating from the north and wrapping around to the east. Although it is possible that the plume on the 4th was advected around the reef contributing to the plume of the 8th, this is unlikely because the magnitude of the backscatter of the plumes shown (incompletely because of flagged pixels) to the south of the reef for the 5th and 6th exceeds that of the plume on the 4th. More likely, the sediment in the plumes sinks relatively quickly, <48 hours, with a concomitant decrease in backscatter and new sediment from the dredging operation is advected away from the reef to form new plumes, which in turn sink relatively quickly. This interpretation is borne out by other pairs of images close in time also displayed in Fig. Figure 1.3 0.006 m−1 exte2, with the impact decreasing rapidly away from the reef. It is difficult to associate a sediment load with the observed backscatter because the characteristics of the sediment in this area are not well known and in situ sampling is not possible due to the political situation. These observations must therefore remain qualitative for the present.Figure 2, although the impact is likely small on the outer edges of the region. As an aside, we note that, although the area of a given plume is generally a lower bound on the plume size because of potentially impacted pixels being obscured by clouds (or flagged for other reasons mentioned in section 2), the cumulative region, shown in Fig. Consistent with the observations of BH2016, we see a significant increase in backscatter from the ocean in and around Mischief Reef associated with an increase of sediment in the water column due to dredging. The increase, approximately a factor of three above pre-2015 levels, begins in 2015, consistent with the dredging activity observed in the Landsat and Sentinel data, and, following cessation of dredging falls to twice the pre-2015 level in 2016, remaining constant at that level through 2018. Of particular interest, the heavy load of sediment introduced into the water column appears to have impacted the ecosystem in the region as seen by the decrease in absorption and chlorophyll concentration beginning in 2016 and continuing through 2018, the period for which data were available for this study. Possible causes of this are significant shading of the water column due to the excess suspended sediment from dredging activities. Further, the excess sediment has likely smothered reef complexes from sinking sediment and reduced light to reef complexes and benthic communities. Although the satellite-borne sensor ‘sees’ only the evidence of sediment in the upper ten meters or so of the water column; impact on the seafloor is inferred based on the rapid decrease in the surface concentration; i.e, the assumption is that the sediment is sinking. This is consistent with rapid rate at which the plumes dissipate Fig.  – signif17. Another paper tested the ability of Planet Dove sensors to identify discrepancies in bottom types near many of these dredging sites18. Yet another discusses the impacts and widespread use of giant clam chopper boats, which can cause silt-sized material to block light in the water column, at Thitu Island19. The amount of silt generated by these operations would have been small relative to the much greater volumes resulting from the dredging and filling operations.As noted above, days in 2015 on which we found significant plumes in the vicinity of Mischief Reef (not shown here) correspond well with those found in the BH2016 study . However, the areas of plumes found by BH2016 were approximately 50% larger than the impacted areas we found. This is because of the different measures used. Had the same measure been used here as that used by BH2016, one would expect the impacted areas we find in 2016 and 2017 to be approximately 50% larger than what we show in Fig. 20, a deterioration consistent with the decrease in chlorophyll-a seen from 2016 through 2018 in the lagoon and surrounding waters. Such destruction of coral reefs does not only impact the immediate area, but also reduces commercially vital fish stocks, and the ability of the Pacific Ocean to detoxify waste that can impact climate21. Additionally, man-made structures such as airfields and the islands themselves remove reef habitats, may cause leeching, and could cause extinction of local fish, invertebrates, and other critical components of the local ecosystem23. Primary production is reduced, the reef topography is changed, and the ability to sustain life, as suggested by our results, is likely diminished. In many cases, the island building and harbor digging could be irreversible24. Despite multiple studies, court cases, and media reports on the subject of Chinese island-building, little quantification of the extent of the disruption to the surrounding ocean existed prior to this paper. It is therefore difficult for law-makers or multi-lateral regulating organizations to create rules around the topic, or to truly understand the ecological damage that such activity causes. This paper serves as a step toward better understanding by initiating a discussion and providing quantitative measurements from which other scientists can base their analyses in the unfolding story of island-building in the SCS. While this study focuses on one particular reef, there is a much larger practice of this activity currently ongoing.The geo-political significance of the impacts identified above could be large. The SCS is bordered by Taiwan and China to the north, Vietnam to the west, Malaysia and Indonesia to the south, and Brunei and the Philippines to the east. Each of these nations claim full entitlement to resources within the portions of the SCS adjacent to their respective coastlines based on the 1982 United Nations Convention on the Law of the Sea. This law, signed by 167 nations including China and the Philippines, set forth boundary limitations, anti-pollution laws, and many other standards. Pollution by one country in another country’s waters aggravates territorial disputes. The most contested sub-regions are the Spratly and Paracel Islands, which are home to many islands that were uninhabitable to humans. According to expert testimonies during the Philippines v. China Arbitration hearings, Chinese island-building represents the quickest deterioration of coral reefs in human history2, although the depth of deposited sediment on the seafloor likely decreases rapidly away from the island. This is certainly not the case within the reef where backscatter increases by a factor of approximately three in 2015 and then, in 2016, falls to a factor of approximately twice that at the same locations prior to dredging operations, where it remains through 2018; the inner reef area is likely heavily impacted.Sediment plumes associated with cutter suction and trailing hopper dredging in the vicinity of Mischief Reef are readily detected from satellite-borne sensors measuring in the visible portion of the electromagnetic spectrum as are the ships responsible for dredging. A pixel is identified as impacted by dredging operations if backscatter in the 412 nm spectral band of the sensor exceeds the mean backscatter for the same day in a region between 30 and 50 km from the reef. The contiguous region of such pixels averaged over the period of dredging extends to a distance of approximately 20 km from the reef center, an area in excess of 1,200 kmOf particular interest is the relative timing of the increase/decrease in absorption, backscatter, chlorophyll-a and remote sensing reflectance relative to the commencement and subsequent cessation of dredging. Backscatter and remote sensing reflectance (at 412 nm) increase rapidly coincident with the start of dredging and then tend to show a slow return toward pre-dredging values to the end of the study period (December 2018). In contrast, the associated decrease in magnitude of both chlorophyll-a and absorption does not begin until after the cessation of dredging and neither shows a recovery to pre-dredging levels in the time period studied. It is thought that dredging activities initially stimulated phytoplankton growth providing nutrients to the surface ocean, but then decreased biological health of the region, evidenced with a decreased in absorption and chlorophyll concentration, by smothering natural benthic habitats and reef complexes with sediment.


Phylogenetic analysis showed high similarity between nucleotide sequences of EqHV in Austrian horses and EqHV circulating in other regions. Despite frequently detected evidence of EqHV infection in Austrian horses, no viral RNA was found in mosquitoes. It is therefore unlikely that mosquitoes are vectors of this flavivirus.Prevalence studies have demonstrated a global distribution of equine hepacivirus (EqHV), a member of the family Flaviviridae. However, apart from a single case of vertical transmission, natural routes of EqHV transmission remain elusive. Many known flaviviruses are horizontally transmitted between hematophagous arthropods and vertebrate hosts. This study represents the first investigation of potential EqHV transmission by mosquitoes. More than 5000 mosquitoes were collected across Austria and analyzed for EqHV ribonucleic acid (RNA) by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Concurrently, 386 serum samples from horses in eastern Austria were analyzed for EqHV-specific antibodies by luciferase immunoprecipitation system (LIPS) and for EqHV RNA by RT-qPCR. Additionally, liver-specific biochemistry parameters were compared between EqHV RNA-positive horses and EqHV RNA-negative horses. Phylogenetic analysis was conducted in comparison to previously published sequences from various origins. No EqHV RNA was detected in mosquito pools. Serum samples yielded an EqHV antibody prevalence of 45.9% (177/386) and RNA prevalence of 4.15% (16/386). EqHV RNA-positive horses had significantly higher glutamate dehydrogenase (GLDH) levels ( Hepacivirus in the family Flaviviridae [EqHV is one of 14 species belonging to the genus iviridae . It is oiviridae .Prevalence studies have demonstrated a global distribution of EqHV. The virus has been detected in horse populations across six continents, in countries including the USA, Brazil, South Africa, New Zealand, Korea, Japan, China, Scotland, France, as well as Austria’s neighboring countries Italy, Germany and Hungary ,14,15,16Many known flaviviruses are horizontally transmitted between hematophagous arthropods and vertebrate hosts . ExampleThe primary aim of this study was to investigate whether various mosquito species, present in areas of EqHV endemicity in horses, carry EqHV nucleic acid and may transmit the virus horizontally between horses. Mosquitoes were collected across Austria and analyzed for EqHV RNA. Concurrently, the occurrence of EqHV was investigated—for the first time—in the horse population of Austria. The geographical locations of analyzed mosquito pools and study horses’ properties of origin were plotted on a map to determine proximity and compare EqHV statuses. Additionally, liver-specific plasma biochemistry parameters were compared between EqHV RNA-positive horses and EqHV RNA-negative control horses. Sequencing and phylogenetic analyses of Austrian EqHV strains were performed.n = 58), teaching horses of the Vetmeduni (n = 50) and privately owned, clinically unremarkable horses enrolled voluntarily (n = 278). The sample population consisted of various breeds and included 156 mares, 187 geldings, 42 stallions and one horse with the sex undisclosed. The horses’ ages ranged from 1 to 31 years (median age = 12.17 years). The geographic locations were recorded for the properties of origin of the horses. In this cross-sectional study, serum and plasma samples were collected for surveillance purposes from 386 horses in eastern Austria between July and October 2017. Sampled horses included patients of the University of Veterinary Medicine Vienna (Vetmeduni) Equine Clinic  [n = 1932 horses; RNA prevalence = 4.7 %) [Considering an estimated population of 120 000 horses in Austria, the sample size was calculated. The expected prevalence of horses positive for EqHV RNA was set to 3.6%, which is the average prevalence of two surveillance studies in horse populations of various breeds and ages, performed in Germany . st Viennese district in August 2017, during a targeted mosquito and virus surveillance program following the identification of an USUV RNA-positive blood donor from that district [st district was included in the study because a high number of investigated horses originated from this district, in which the Vetmeduni is located. A small number of mosquitoes from northeast Italy , collected between June and October 2017, were also included in the analysis. In total, 5338 mosquitoes in 566 pools were investigated for the presence of EqHV nucleic acid. The following species were represented: Aedes albopictus, Aedes japonicus, Aedes koreicus, Anopheles claviger, Anopheles maculipennis, Anopheles plumbeus, Culex hortensis, Culex pipiens, Culiseta annulata and Ochlerotatus geniculatus.4039 mosquitoes collected in 2017 were pooled in 430 pools according to location, time of trapping and mosquito species. The mosquitoes were trapped across Austria and included both native and invasive species. In addition, 1004 mosquitoes were trapped in the 21district . These m®Premix Ex Taq™ II kit  was used, in combination with the previously described primers targeting the 5′ untranslated region (5′UTR) [Mosquito preparation was conducted as described previously . From ea2 GEs per mL of horse serum. For absolute quantification, a serial dilution of a defined DNA plasmid standard was run in parallel with the positive samples. RT-qPCR analysis of horse serum samples was performed by the Institute of Virology, University of Veterinary Medicine Vienna, Austria.Viral RNA was extracted from 200 µL of each horse´s serum using the QIAamp 96 Virus QIAcube HT Kit  according to the manufacturer´s instructions. For screening, EqHV-specific nucleic acids were detected by RT-qPCR using primers and probes as described previously . The RT-Serum samples were frozen between −20 °C and −80 °C prior to analysis for anti-EqHV non-structural protein 3 (NS3)-specific antibodies and shipped on dry ice to the laboratory in Germany. Samples were analyzed in duplicate for the presence of anti-EqHV NS3-specific antibodies, using the LIPS assay as described previously . Relativn = 45). The control horses were randomly selected from the group of privately owned, clinically unremarkable horses enrolled voluntarily. The laboratory’s reference ranges were used for data analysis.Plasma samples were frozen between −20 °C and −80 °C prior to analysis for GLDH, gamma-glutamyl transferase (GGT), bile acids and albumin concentrations at the Central Laboratory of the University of Veterinary Medicine Vienna. These parameters were measured in plasma samples of all EqHV RT-qPCR-positive horses, as well as in plasma samples of EqHV RT-qPCR-negative control horses . The 16 RT-qPCR-positive horses originated from 12 different properties, with between one and four RT-qPCR-positive horses per property (EqHV RNA was detectable in 4.15% of serum samples (16/386). Viral loads in 11 of the samples ranged from 1 × 10property . The geoThe antibody prevalence in the study population was 45.9%, with 177 of the 386 samples antibody-positive. Based on the horses’ EqHV infection-state, the samples could be assigned to four categories: antibody-negative and RNA-negative (Abs–/RNA–); antibody-positive and RNA-negative (Abs+/RNA–); antibody-positive and RNA-positive (Abs+/RNA+) and antibody-negative and RNA-positive  had significantly higher plasma GLDH concentrations (p = 0.013) compared to EqHV RT-qPCR-negative control horses  and RNA prevalence (4.15%) detected in this population of Austrian horses were within previously reported ranges 5.9% and ,30. DespAedes japonicus. A. japonicus is rapidly dispersing in Austria [Mosquito surveillance programs were initiated in Austria in 2011, with the aim of detecting invasive mosquito species ,32 and i Austria , and was Austria . n = 566), consisting of 5338 individuals from various species, representing five mosquito genera  contained no EqHV RNA. Based on these findings, mosquitoes are unlikely to play a role as vectors of EqHV. Mosquito-borne flaviviruses replicate within the invertebrate vector during the extrinsic incubation period—the time between uptake of an infectious blood meal by a female mosquito and subsequent viral transmission to the host . A smallComparable numbers of Austrian mosquitoes enabled us to determine the minimal infection rate (MIR) of WNV in previous investigations . These r3 RNA copies/mL to 7.78 × 106 RNA copies/mL) [Similar to HCV, transmission by means of infected blood and blood products has been demonstrated for EqHV ,23. Expepies/mL) ,23. Conspies/mL) . Painfulpies/mL) . The volpies/mL) ,43. ViraNatural and experimental EqHV infections typically result in transient elevation of concentrations of liver-specific enzymes, indicative of hepatic inflammation. Increased GLDH, sorbitol dehydrogenase (SDH), GGT and aspartate aminotransferase (AST) levels have been reported ,21,23,44In accordance with findings from other regions, the phylogenetic analyses revealed high similarity at nucleotide sequence-level of EqHV circulating in Austria, compared to other countries ,6,10.Despite evidence of EqHV infection being frequently detected in Austrian horses, no indication of viral nucleic acid was found in mosquito populations throughout the country. Consequently, mosquitoes are unlikely to play a role as vectors of this flavivirus. Nucleotide sequence differences between EqHV in Austria compared to EqHV of other origins are minor.


In recent years, there has been a growing interest in circular RNAs (circRNAs) since they are involved in a wide spectrum of cellular functions that might have a large impact on phenotype and disease. CircRNAs are mainly recorded by RNA-Seq and computational methods focused on the detection of back-splicing junction sequences considered the diagnostic feature of circRNAs. While some protocols remove linear RNA prior to sequencing, many have characterized circRNAs by sorting through total RNA sequencing data without excluding the possibility that some linear RNA can provide the same signal as a circRNA. Recent studies have revealed that circular DNAs of chromosomal origin are common in eukaryotic genomes and that they can be transcribed. Transcription events across the junction of circular DNAs would result in a transcript with a junction similar to those present in circRNAs. Therefore, in this report, we want to draw attention to transcripts from such circular DNAs both as an interesting new player in the transcriptome and also as a confounding factor that must be taken into account when studying circRNAs. There is a growing interest in circRNAs due to their implication in many biological processes and diseases in addition to their biomarker potential. They are mainly detected by the presence of reads mapping their backsplicing junction. Nevertheless, circRNAs are no longer the only transcripts containing such a junction since recent studies have revealed that circular DNAs are common and can be transcribed resulting in transcripts that would mimic a circRNA signal. Therefore, this new type of chimeric transcript can change the way in which circRNA analysis is being done and impact some of the results already reported.Circular RNA (circRNAs) were rediscovered a few years ago as non-canonically spliced RNA forms present in different organisms including humans . They arSince their rediscovery, the scientific community has drawn its attention to circRNAs and has investigated their involvement in several cellular processes in health and disease , their pin vitro and in vivo   and ringCircular DNAs are formed when two ends of a linear DNA are joint together resulting in a junction similar to the backspliced junction on circRNAs commonly called breakpoint junction that is detected based on structural-read variants consistent with a circularization event  Figure and whilInterestingly, in a recent paper Møller et al. identified thousands of eccDNAs in leucocytes and muscle cells in healthy controls. With the idea of investigating whether eccDNAs could be transcribed, an mRNA library was also sequenced from muscle tissue and analyzed for transcription events across the breakpoint junction of the detected eccDNA finding several matches . This fiThe transcriptional evidence of circular DNAs, together with their abundance, lead us to suggest that circular DNAs could be a natural source of a substantial amount of linear RNAs carrying chimeric junctions. In many cases, these chimeric junctions might be indistinguishable from the backsplicing junctions of circRNAs, and therefore they might be confounding factors in circRNA studies. In the following paragraphs, we will explain the data supporting this proposal.As previously introduced, circRNAs are formed though a non-canonical splicing event called backsplicing. Transcripts resulting from this backsplicing event have a covalently closed loop structure with neither 5′–3′ polarity, nor a polyadenylated tail and more importantly, they are characterized by the presence of a scrambled exon order relative to the linear transcript . This scde novo RNA circularization events from genomic regions where no circRNA were annotated by previous studies. Several bioinformatic pipelines have been developed for the detection of circRNAs in RNA-Seq datasets, but all of them are based on the presence of reads crossing over the back-splicing junctions and finding the most reliable one is still a challenge for bioinformaticians  "Investing in your future"). IP-L and BR were supported by the Danish Council for Independent Research, 6108-00171B and LI was supported by the Department of Education of the Basque Government [grant number PRE_2018_2_0081].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.


Although obtaining normal and pathological reticulocyte transcriptome profiles should contribute greatly to our understanding of the molecular bases of terminal erythroid differentiation as well as the mechanisms of the hematological diseases, a basic limitation of these studies is the difficulty of efficient reticulocyte RNA isolation from human peripheral blood. The restricted number of possible parallel experiments primarily concern healthy individuals with the lowest number of reticulocytes in the peripheral blood and a low RNA content. In the present study, an efficient method for reticulocyte RNA isolation from healthy individuals and hemolytic anaemia patients is presented. The procedure includes leukofiltration, Ficoll‐Paque gradient centrifugation, Percoll gradient centrifugation, and negative (CD45 and CD61) immunomagnetic separation. This relatively fast and simple four‐stage method was successfully applied to obtain a reticulocyte‐rich population from healthy subjects, which was used to efficiently isolate the high‐quality RNA essential for successful NGS‐based transcriptome analysis.Despite enormous progress and development of high‐throughput methods in genome‐wide  Young cells contain residual RNA and micro‐organelles such as ribosomes, lysosomes, and mitochondria. The residual RNA is not only functional, but also necessary for the final stages of reticulocyte maturation.Adult peripheral blood is characterized by a low reticulocyte count resulting in an extremely low yield of reticulocyte RNA isolation as compared to cord blood.Herein we propose a novel, simple, and effective method for the isolation of reticulocyte RNA from both healthy individuals and hemolytic anaemia patients. The method was validated on blood samples obtained from Polish individuals who were adult males (aged 25‐40 years): (a) three healthy individuals (including one blood donor), (b) one hereditary spherocytosis (HS) patient22.1EDTA anticoagulated blood was collected from volunteers , HA patients and HS patient by venipuncture (Supporting Information Table SPTB mutation coming from two‐generation Polish C family).A HS patient with moderate symptoms of the disease was recruited  to identify the different reticulocyte populations relative to RNA content as measured by Thiazole Orange (TO). Thiazole Orange  was dissolved in methanol to obtain a 1 mg/mL TO stock solution. The stock solution was kept at −20°C in darkness.Flow cytometric analysis was performed using a BD FACSCalibur flow cytometer to ensure the purity of the isolated CD71A TO working solution (20 μg/mL) was prepared by adding 6 μL of stock solution to 30 mL of PBS (pH 7.4).Samples were stained as follow: 1.3 μL of peripheral blood (or 3 μL of isolated reticulocytes sample) was added to 2.5 mL of TO working solution containing 6 μL of anti‐CD71‐PE antibody (Miltenyi Biotec) or 6 μL of an isotype control . After 20 minutes incubation samples were analysed. The FL‐1 channel (BP 530/30) was employed to detect TO fluorescence whereas the FL‐2 channel (BP 585/42) was employed for PE fluorescence. Single stained samples were used for setting the correct fluorescence compensation.2.3The procedure of purification of reticulocytes from human peripheral blood included four steps Figure :Fresh blood from volunteers and patients immediately after drawing was diluted with PBS‐EDTA pH 7.4 buffer (27 mL: 70 mL) and was passed through a LEUCOBED LCG3 filter  to remove most leukocytes and platelets.The obtained filtrate (approximately 50 mL) was divided into two equal parts, each placed onto separate Ficoll‐Paque PREMIUM density gradient  and centrifuged with reduced acceleration and deceleration . Then cells were washed with PBS‐EDTA pH 7.4 buffer . The supernatants were removed gently, leaving 5 mL above the cell pellets. Finally, each of the cell pellets was resuspended in the remaining supernatant volume.d = 1.096 g/mL and 1.058 g/mL in Falcon, 15 mL test tube) and centrifuged for 30 minutes (250 g at 4°C). Each reticulocyte‐rich layer was subsequently collected into 50 mL centrifuge tubes and washed twice in PBS‐EDTA pH 7.4 buffer  to obtain 1 mL of reticulocyte‐rich suspension, 50% of which were reticulocytes and ˜50% red blood cells. Nevertheless, a few leukocytes and platelets were still present. Then reticulocyte‐rich suspensions were transferred into 2 mL test tubes and washed again under the same conditions. Finally, each of the cell pellets was resuspended in the remaining supernatant (˜2 mL) and centrifuged . Supernatants were gently removed, and the number of reticulocytes and red blood cells determined.The selective removal of red blood cells was performed using a Percoll density gradient . Half the volume of each cell suspension obtained above (2.5 mL) was applied on one of four cold gradients  using the MiniMACS Separator System was applied, in accordance with the manufacturer's procedure with a slight modification. Namely, each reticulocyte‐rich pellet obtained as described above was resuspended in 80 μL of PBS‐EDTA‐BSA pH 7.4 buffer and into each cell suspension 20 μL of CD45 MicroBeads as well as 5 μL of CD61 MicroBeads simultaneously was added. After an additional 15 minutes incubation, the separation was carried out at the appropriate time intervals (the time of a single separation is about 10 minutes) using four MS columns and one MACS Separator (Miltenyi Biotec). The combined flow‐through containing reticulocytes/RBC was centrifuged  to obtain the final reticulocyte‐rich pellet which still contained about 50% RBC. The supernatant was removed to leave 0.4 mL above the cell pellets in which the cells were resuspended. To assess the purity 20 μL of reticulocyte‐rich pellet was directly mixed with 1% Brilliant Cresyl Blue (w/v in 0.9% sodium chloride) in the ratio 1:1, incubated for 30 minutes (RT) and visualized using an inverted microscope with differential interference contrast (DIC)—see Supporting Information Figure 2.4Total RNA was extracted from the reticulocyte‐rich suspension and collected using the miRNeasy Mini Kit , according to the manufacturer's recommendation. In the first isolation step, ~0.4 mL of the reticulocyte‐rich pellet with the supernatant was divided into two aliquots. In further steps we followed the manufacturer's procedure until the material was applied onto an RNeasy Mini Spin Column. During this step, the materials from two aliquots were pooled (to enhance yields of RNA isolation), to ensure fulfilling the minimal column capacity required for efficient RNA isolation. RNA concentrations were calculated based on the absorbance at 260 nm. RNA samples were stored at −70°C. The first strand of cDNA was synthesized using a RevertAid First Strand cDNA Synthesis Kit .2.5HBB, PPARA, PTPRC, ITGB3, and ACTB. Primer sequences are listed in Supporting Information Table To verify the purity of the reticulocyte population the RNA isolates from reticulocyte populations was tested using specific primers for marker gene transcripts: 2.6Next generation sequencing was performed by Heflin Center for Genomic Science Core Laboratories, University of Alabama at Birmingham, AL, USA. Directly prior to the RNA‐Seq procedure, the total RNA integrity was verified by on‐chip electrophoresis  and only samples with high RNA integrity (RIN) values were further processed (>7.5). In addition, quality score analysis was performed confirming the high quality of RNA samples. Following rRNA depletion, the remaining RNA fraction was used for library construction and subjected to 100 bp paired‐end sequencing on an Illumina HiSeq 2000 instrument. Sequencing reads were aligned to the human reference genome assembly (hg19) using TopHat.2.7GeneAnalytics  is a comprehensive gene set analysis tool for contextualization of expression patterns and functional signatures obtained from the post‐genomics Big Data sets, such as next generation sequencing (NGS), RNA‐Seq, and microarray experiments.33.1+ cells were so scarce that no effective RNA isolation was possible. For this reason, we decided to use negative selection of leukocytes and platelets using CD61 and CD45 MicroBeads. The resulting reticulocyte preparation, although containing a reasonable number of red blood cells  was 34 years 25‐40). Differences in the reticulocyte count in hemolytic anaemia patients and healthy individuals are shown in Figure 5‐40. Dif men was 3.2In order to test the usefulness of the described procedure of reticulocyte purification the functional quality of RNA was tested. RNA isolation was carried out as described in the Section 3.3HBB, and “low abundance” PPARA . As a quantitative control β‐actin (ACTB) primers were used. Furthermore, to verify efficient removal of leukocytes and platelets the RNA isolates from reticulocyte populations were tested. Transcripts specific markers for platelets (integrin β3 (ITGB3)) and for leukocytes (CD45 (PTPRC)) were absent.The reliability of RNA‐Seq analysis is based on obtaining a reticulocyte population free of contamination with other blood cells. Hence, to assess the reticulocyte purity we tested the obtained RNA isolates for the presence of high‐ and low‐abundant transcripts characteristic for these blood cells as well as for the absence of transcripts specific for platelets and leukocytes. As shown in Figure 3.4Reticulocyte transcriptome analysis using high‐efficiency gene expression assays was performed by RNA‐Seq for four male subjects only: both HA patients (N61 and N62), one healthy individual (C1) and one patient with HS diagnosis  assigned to 111 metabolic pathways, 104 biological processes, 31 molecular function pathways, 75 diseases, and 22 phenotypes  preferably from freshly drawn blood, after which RNA isolation should proceed. The procedure presented here meets this criterion.The next issue is that cells such as red blood cells, reticulocytes, and platelets have a low RNA content.Finally, variability in the reticulocyte population between healthy individuals and patients with hematologic diseases should be considered. Purification of reticulocytes from patients with hemolytic anaemia without changed osmotic resistance of red blood cells is relatively simple due to the increased reticulocyte count and no excessive hemolysis during isolation. Patients with hemolytic anaemia associated with increased osmotic fragility including conditions such as hereditary spherocytosis or hereditary elliptocytosis are characterized by high reticulocytosis, but usually during the isolation procedure increased hemolysis occurs, which significantly reduces the efficiency of isolation. In our procedure, we tried to optimize the method, to minimize hemolysis. However, the most challenging aspect is achieving efficient separation of the reticulocytes from the peripheral blood of individuals with a normal reticulocyte count, which has been pointed out in some reports.++ and CD71++++) deposited in the UniGene NCBI database: GPA++ library (Lib.11923) and CD71++++ library (Lib.8975) . These data suggest that the differences in identified gene transcripts require further in‐depth analysis considering many factors affecting the gene profiles. Furthermore, it must be noted that the level of expression is regulated by factors such as gender, age, and even individual variations.As shown in Supporting Information Table The ability to efficiently isolate human reticulocytes from peripheral blood should enable development of clinical diagnostic applications and facilitate defining specific defects underlying various human hematopoietic diseases. It needs to be stressed that due to the difficulty of obtaining pure reticulocyte population RNA, the data we have obtained on the reticulocyte transcriptome are among the very few available. Classic investigations of erythroid gene expression were usually focused on predefined sets of genes. The total RNA expression patterns of the purified reticulocytes from healthy individuals have so far been determined by RNA microarraysTo test whether our reticulocyte isolation procedure combined with RNA‐Seq will result in improved coverage of cellular processes and their physiological/functional context, we placed previously published RNA microarrays results Importantly, the extended list of identified transcripts obtained in our study provided much better coverage of gene ontology terms, as reflected by higher scores. Furthermore, using the GeneAnalytics web server we identified in our transcript set of genes associated with 22 phenotypes, whereas microarray data analysis resulted in identification of transcripts associated with 19 phenotypes (Table Taken together, gene ontology analysis supports the conclusion that the experimental approach proposed in this study provides an improved insight into biological processes that govern reticulocyte maturation, function and pathology. Undeniably, obtaining depth and reliable insight into related transcriptome profiles should significantly help to understand these mechanisms.In conclusion, we have presented an efficient procedure of reticulocyte isolation from peripheral blood. This procedure should be useful in particular for normal, healthy individuals, whose blood is poor in reticulocytes, and for hemolytic anaemia patients including HS patients with increased hemolysis. This will increase the statistical power to detect disease‐relevant signatures in patient/healthy individual studies. Furthermore, obtaining reliable normal and pathological reticulocyte transcriptome profiles should contribute greatly to our understanding of the molecular bases of terminal erythroid differentiation, haemoglobin switching and iron metabolism, as well as the mechanism of hematological diseases, prognosis and responses to therapeutics.The authors declare that they have no conflict of interests concerning the contents of this article. Click here for additional data file.


RBPs are involved in the regulation of mRNA processing, localization, stability and translation. Thereby they enable rapid cellular responses to inflammatory mediators and facilitate a coordinated systemic immune response. Specific RBP binding to conserved sequence motifs in their target mRNAs is mediated by RNA binding domains, like Zink-finger domains, RNA recognition motifs (RRM), and hnRNP K homology domains (KH), often arranged in modular arrays. In this review, we focus on RBPs Tristetraprolin (TTP), human antigen R (HUR), T-cell intracellular antigen 1 related protein (TIAR), and heterogeneous ribonuclear protein K (hnRNP K) in LPS induced macrophages as primary responding immune cells. We discuss recent experiments employing RNA immunoprecipitation and microarray analysis (RIP-Chip) and newly developed individual-nucleotide resolution crosslinking and immunoprecipitation (iCLIP), photoactivatable ribonucleoside-enhanced crosslinking (PAR-iCLIP) and RNA sequencing techniques (RNA-Seq). The global mRNA interaction profile analysis of TTP, HUR, TIAR, and hnRNP K exhibited valuable information about the post-transcriptional control of inflammation related gene expression with a broad impact on intracellular signaling and temporal cytokine expression.Innate immune response is triggered by pathogen components, like lipopolysaccharides (LPS) of gram-negative bacteria. LPS initiates Toll-like receptor 4 (TLR4) signaling, which involves mitogen activated protein kinases (MAPK) and nuclear factor kappa B (NFκB) in different pathway branches and ultimately induces inflammatory cytokine and chemokine expression, macrophage migration and phagocytosis. Timely gene transcription and post-transcriptional control of gene expression confer the adequate synthesis of signaling molecules. As  The immune responses against bacteria, viruses and parasites require tight regulation, because uncontrolled, excessive or persisting immune reactions provoke inflammatory diseases . As a ceBy analyzing RNA-protein interaction profiling and RNA sequencing experiments with TTP, HUR, TIAR, and hnRNP K we provide an overview on their target mRNAs, which are regulated at the level of mRNA stability and translation in LPS activated macrophages.Zfp36, has been characterized as critical mRNA destabilizing protein in immune cells  and TTP(-/-) mice exposed to LPS for different times (Four studies examined the impact of TTP on inflammation-related pathways: (I)  identifint times . upon LPS stimulation include not only TNFα and NFκB-related signaling molecules like TNF, CXCL2, CXCL3, but also IER3 and DUSP1, which encode feedback inhibitors of the inflammatory response , a central less conserved basic hinge region and a third C-terminal RRM   and TIA-RRM2 and RRM3 contribute to nuclear accumulation of TIA proteins and nuclear export, respectively . Both in(-/-) mice ((ΔARE) mice, where it is implicated in chronic inflammation  mice  suggests/-) mice . TIA proammation . Furtherammation  and HMMPammation  are TIARInterestingly, TIA proteins have also been shown to contribute to global translation regulation under amino acid starvation in HEK293S cells. TIA proteins bind to the 5′-oligopyrimidine tract of 5′-TOP mRNAs, which encode critical components of the translational apparatus, like ribosomal proteins and PABP-C1 and induce the release of these target mRNAs from actively translating polysomes . Besides(wt)-FLAG and TIAR(ΔRRM2)-FLAG. RRM2 of TIAR, which is required for high affinity mRNA binding (RIP-Chip experiments were performed by  binding  was dele binding . The mRN binding . GO term binding .T-cell intracellular antigen 1 related protein ARE binding specificity was lower than that of TTP , but not3-4 RNA motifs were determined as optimal ligands for KH3 (D values for the isolated domain KH3 are micromolar (Heterogeneous ribonuclear protein K was first described as a structural component of nuclear ribonucleoprotein complexes associated with heterogeneous nuclear RNA . The pro for KH3 . Binding for KH3  and RNA  for KH3  has been for KH3 . The affcromolar . Two U/Ccromolar . Bidireccromolar , 1997.284,353 drives its cytoplasmic accumulation as prerequisite for hnRNP K-mediated mRNA translation regulation (458 by c-Src (As multifunctional protein hnRNP K is associated with transcription activation , pre-mRNgulation . Phosphoby c-Src  and caspby c-Src  control by c-Src .In human Thp-1 monocytes, hnRNP K was shown to be associated with the COX-2 promoter and to control cytoplasmic COX-2 mRNA stability by modulating miRNA binding to the 3′UTR .RIP-Chip analysis of differential mRNA binding in untreated and LPS induced RAW264.7 macrophages demonstrated that 1901 mRNAs were differential bound by hnRNP K in response to LPS. GO term annotation allocated them to biological processes related to metabolism, cell communication, transport, cell cycle, development and immune response . StrikinAs primary responding cells of the innate immune system, macrophages recognize pathogens and become activated to initiate and coordinate the organism-wide systemic immune response by cytokine and chemokine secretion, migration and phagocytosis. These processes require highly coordinated gene expression, which is achieved at the post-transcriptional level by regulated functional RBP-RNA interactions. Specific RBPs, TTP, HUR, TIAR, and hnRNP K, regulate the fate of their cellular target RNAs from synthesis to turnover and translation, thereby contributing to the coordination of the rapid and purposeful immune cell responses. LPS molecules of gram-negative bacteria are abundant and specific ligands that activate macrophages through TLR4 receptor signaling. Systematic analyses of RBP-RNA interaction in untreated and LPS-induced macrophages employing RIP-Chip, iCLIP, PAR-iCLIP, RNAseq, and RiboSeq studies revealed a first insight in the complex protein-mRNA networks that are established by RBPs, which bind mRNAs with different specificities for AREs and U-rich elements, like TTP, HUR, and TIAR and pyrimidine-rich sequence motifs, like hnRNP K based on their individual domain composition. These specific interactions ensure the simultaneous modulation of various target mRNAs, which encode proteins that function in defined biological processes related to the induction and resolution of immune response. Whereas TIAR and hnRNP K mainly modulate mRNA translation, which enables the direct regulation of signaling protein synthesis to initiate immune response, TTP and HUR are primarily involved in the control of mRNA decay and stability that is required to balance and resolve immune reactions.These processes have been studied so far only for a limited number of mRNAs differentially bound by RBPs in response to LPS. It will be essential and informative to investigate the regulation of further target mRNAs of TTP, HUR, TIAR, and hnRNP K discovered in these studies to get more insight in regulatory feedback mechanisms that coordinate the balanced immune response and its dysregulation in chronic inflammation.To this end it is interesting to note that a number of unconventional RBPs, have been identified recently, for which RNA related functions that will expand our understanding of post-transcriptional gene regulation still need to be elucidated .In macrophages, 19 new putative RBPs, which lack well characterized RNA binding domains were identified by RNA interactome capture . PantherIn addition, post-transcriptional RNA modifications  might adAll 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.


These artificial enzymes are designed to force the formation of a bulge in the RNA target, the sequence of which has been shown to be key to the catalytic activity. Here, we present a further investigation into the action of Cu2+-dependent PNAzymes with respect to the dependence on bulge composition in 3- and 4-nucleotide bulge systems. Cu2+-dependent PNAzymes were shown to have a clear preference for 4-nucleotide bulges, as the cleavage of 3-nucleotide bulge-forming RNA sequences was significantly slower, which is illustrated by a shift in the half-lives from approximately 30 min to 24 h. Nonetheless, the nucleotide preferences at different positions in the bulge displayed similar trends in both systems. Moreover, the cleavage site was probed by introducing critical chemical modifications to one of the cleavage site nucleotides of the fastest cleaved 4-nucleotide RNA bulge. Namely, the exclusion of the exocyclic amine of the central adenine and the replacement of the 2′-hydroxyl nucleophile with 2′-H or 2′-OMe substituents in the RNA severely diminished the rate of RNA cleavage by the Cu2+-dependent PNAzyme, giving insight into the mechanism of cleavage. Moreover, the shorter recognition arm of the RNA/PNAzyme complex was modified by extending the PNAzyme by two additional nucleobases. The new PNAzyme was able to efficiently promote the cleavage of RNA when fully hybridised to a longer RNA target and even outperform the previous fastest PNAzyme. The improvement was demonstrated in cleavage studies with stoichiometric amounts of either PNAzyme present, and the extended PNAzyme was also shown to give turnover with a 10-fold excess of the RNA target.Peptide nucleic acid (PNA)-neocuproine conjugates have been shown to efficiently catalyse the cleavage of RNA target sequences in the presence of Cu Selective manipulation of nucleic acid sequences is key for molecular biology research, medical analysis and the treatment of genetic diseases in the clinic. Natural nucleic acid target sequences can be affected by synthetic oligonucleotides (ONs). Moreover, the intrinsic affinity of ONs for their targets can be amplified by the inclusion of critical chemical modifications, which, in addition to improved hybridisation properties, can confer enhanced stability against degradation. Thus, synthetic ONs capable of modulating disease-related RNAs are attractive drug candidates with several approved therapies  and numeTherapeutic ONs can be designed to affect their targets by a range of different mechanisms, depending on the type of processes by which the pathogenicity of the target is manifested ,3. Degra2+ ions +1 calcd 3538.4, found 3538.4; m/z: PNA-phenanthrene conjugate C145H178N70O38 [M]+1 calcd 3508.4, found 3508.8; m/z: PNAzyme II C167H206N86O42 [M]+1 calcd 4088.7, found 4087.0. Concentrations of PNA conjugates were determined by UV absorption at 260 nm on a Varian Cary 300 UV-Vis dual beam spectrophotometer (Varian) and calculated from extinction coefficients obtained by the nearest neighbour approximation −2 calcd 1468.7, found 1469.1; m/z RNA 6 (5′-AGA-GUUC-UAA-GCCC-3′) longer fragment (5′-AGA-GUUC-UA-3′ cyclic phosphate) C86H103N34O63P9 [M]−2 calcd 1449.2, found 1449.6. These MS spectra are available in the RNA cleavage reactions were performed as above. The main RNA fragments were collected from IE-HPLC runs and desalted as described earlier. The collected fractions were analysed by ES mass spectrometry in negative ion mode using a solution of MeCN–water , as suggested for metal aquo ions in solutions [6 of A or O6 of G (possibly via a Cu-bound water molecule) at the same time as coordinating the phosphate and via water, protonating the leaving 5’-oxygen, but it is likely that a substantial conformational change would be needed. Cuolutions . It may 2+-dependent PNA-based artificial ribonucleases and serves as a basis for further developments. For an RNA target that is longer than the PNAzyme, and thus more closely resembling a natural substrate, the highest cleavage rate so far was reported, and the artificial enzyme was shown to give turnover of the RNA substrate.Finally, the shorter RNA/PNAzyme recognition arm was extended by two nucleobases in order to examine whether the ease of dissociation might correlate with the cleavage rate. The extended PNAzyme was shown to perform at an even higher rate when fully hybridised to a longer RNA target, compared to the previous shorter PNAzyme. All in all, the study has added valuable mechanistic insights into the action of Cu


Drosophila.Combination of in vitro and in vivo data show that RNA sequence influences Staufen target recognition and that protein–RNA base contacts are required for Staufen function in  Drosophila and mammals. We solved the structure of two dsRBDs of human Staufen1 in complex with a physiological dsRNA sequence. We identified interactions between the dsRBDs and the RNA sugar–phosphate backbone and direct contacts of conserved Staufen residues to RNA bases. Mutating residues mediating nonspecific backbone interactions only affected Staufen function in Drosophila when in vitro binding was severely reduced. Conversely, residues involved in base-directed interactions were required in vivo even when they minimally affected in vitro binding. Our work revealed that Staufen can read sequence features in the minor groove of dsRNA and suggests that these influence target selection in vivo.During mRNA localization, RNA-binding proteins interact with specific structured mRNA localization motifs. Although several such motifs have been identified, we have limited structural information on how these interact with RNA-binding proteins. Staufen proteins bind structured mRNA motifs through dsRNA-binding domains (dsRBD) and are involved in mRNA localization in  These cis elements are bound by trans-acting factors, or RNA-binding proteins that mediate the recruitment of additional components required for transport, anchoring, and translational control of the mRNA. One of the best-characterized trans-acting factors, with many functions in RNA metabolism, is the protein Staufen (Stau).The intracellular localization of mRNAs is a critical gene regulatory mechanism in many eukaryotic cell types and processes  is required for oskar (osk) mRNA transport to the posterior pole of the oocyte, where abdomen and germ cells will develop (bicoid (bcd) mRNA, the anterior determinant (prospero (pros) mRNA and restricts its localization to the daughter cell, which will differentiate into a ganglion mother cell  separated by linkers that are predicted to be unstructured  Fig 1A)Fig 1A). osk mRNA  mRNA. ARF1 mRNA bound to hStau1 is targeted for degradation through SMD  reside in double-stranded regions, formed either intra- or intermolecularly, have an average length of 9–12 bp, with none or few mismatches, but are otherwise poorly defined . For a f in vivo . The locts 3ʹUTR , 1997, its 3ʹUTR . Similarough SMD .ARF1 mRNA. The structure, at 2.9 Å resolution, shows that the tandem dsRBDs of hStau1 recognize A-form RNA, mainly through electrostatic interactions with the RNA backbone. A comparison with the structure of unbound ARF1 SBS, at 1.9 Å resolution, reveals that the target RNA undergoes minor changes upon hStau1 binding. In addition to the RNA backbone interactions, we observe residues from both dsRBDs making direct contact with G and C bases within the minor groove of the target RNA, suggesting some sequence specificity. These base-contacting residues are conserved in Drosophila Stau, and are required for protein function in vivo. Our data show that both dsRBDs 3 and 4 of Stau are important for RNA binding in vitro and in vivo, and provide insights into target requirements in Stau recognition.To understand how Stau recognizes its target RNAs, we determined the crystal structure of the minimal RNA-binding region of hStau1, consisting of dsRBDs 3 and 4, in complex with the 19 bp SBS from ARF1 SBS. Purified recombinant hStau1 FL interacts with ARF1 SBS with high affinity (6 ± 1 nM), but binds a single-stranded version of the same site (ssARF1), used as a control for nonspecific protein–RNA interaction, with a 16-fold lower affinity (96 ± 27 nM)  reduction.To better characterize RNA binding by hStau1, we used fluorescence anisotropy (FA) and determined the binding affinity of the full-length (FL) protein, and truncated versions of the protein, for ± 27 nM) . A C-terARF1 SBS with similar affinity as its untagged version (9 ± 2 vs 14 ± 4 nM), indicating that the presence of a GST tag does not affect RNA binding , pointing to cooperativity within the tandem construct  experiments , but only one dsRBD4 associated to one molecule of RNA. This dsRBD4 is not well defined and could explain the relatively high B-factors of this portion of the structure. One dsRBD4 is disordered and could not be modeled  and ARF1 SBS . The strhemistry . A diffehemistry . This al modeled . In the  modeled . The lin modeled  is disor1UHZ, unpublished) in isolation. For each domain, the interaction surface with the RNA spans the major groove and the two adjacent minor groove surfaces. DsRBD3A and dsRBD4 bind to the RNA next to each other, sharing a heterodimerization interface of 273 Å2   including one and half RNA molecules, co-axially stacked. This arrangement generates a sixfold static disorder, as previously observed in crystal structures of dsRNAs of similar length A, the bacontacts . This isA) or G83 (dsRBD3B)   and S7A.dsRBD3B) .The electron density for dsRBD4 is less defined than that of dsRBD3; however, the side chain of Q293, within helix α1, is directed toward the edge of C90 (4.4 Å distance), suggesting a base-directed interaction  and S7B.ARF1 SBS, but of a random AU sequence (dsAU). We decided to use a dsRNA without any G–C pairs to prevent alternative binding orientations that would be possible on ARF1 SBS (ARF1 SBS when compared with the wt protein (ARF1 SBS (A (with a register of G–X9–G) and dsRBD4, binds with a similar affinity as ARF1 SBS, supporting the role of G–C pairs in target recognition  (bcd III binding in vitro (3.5-fold reduction of affinity when compared with the wt), but dramatically impairs protein function in vivo. These results show that the binding affinity measured in vitro is not strictly predictive of Stau function in vivo, and show that base-directed interactions might be required for in target recognition in vivo.Our structural and biochemical results show that hStau1 target recognition depends not only on RNA shape, but also on sequence. Residues involved in RNA-binding, including those engaging in base-directed contacts, are conserved in Stau family members, including duplexes , contain ovaries . As prevFP-dStau , 2000   Drosophiduction) . Correspduction)  and 7C. duction) . The addDrosophila rescue experiments.Here, we combined crystallography and structure-based mutagenesis to dissect the determinants of RNA recognition by Stau, and tested the in vivo relevance of identified key Stau residues in In the complex, Stau dsRBDs showed a canonical binding mode to the RNA backbone, with some variations. The association of two dsRBD3 molecules to the same substrate and their differential engagement of the canonical contacts in the β1–β2 loop supports a versatility of binding that might be needed to allow Stau recognition of several RNA targets, possibly with different shapes. Indeed, a variety of Stau targets have been identified in vivo . dsRBD3 A conformational flexibility of the β1–β2 loop has also been observed by NMR in the dsRBD3 of dStau  and in tWe showed that the dsRBDs of Stau have different contributions to binding affinity and specificity. In hStau1, both dsRBD 3 and 4 can bind dsRNA independently in vitro; however, efficient target binding requires both domains. A similar cooperativity was also observed for other proteins containing multiple RNA-binding domains . In otheConsistently with its stronger contribution to RNA binding, reducing dsRBD3 affinity for the RNA by mutating residues that interact with the RNA backbone has a dramatic effect on dStau activity in vivo. In contrast, mutations in backbone-interacting residues within dsRBD4 do not significantly affect the phenotypic outcome. One caveat of these rescue experiments is that the proteins are slightly overexpressed relative to the endogenous levels, which may compensate for a certain reduction in RNA-binding affinity, provided that specificity is maintained. We can nevertheless compare the different mutant forms in vivo, because we used the same genomic integration site for all transgenes.Drosophila such as osk, bcd, and prospero Drosophiltrans interactions, bridging multiple RNAs, or cis binding to either adjacent or non-adjacent sites within a target, such as loops III, IV, and V in bcd 3′UTR.We show that base interactions are relevant in vivo and we think that they contribute to the overall sequence selectivity by Stau, possibly together with additional regions of the protein or with other regulators. In particular, the linker connecting dsRBDs 3 and 4 is flexible and could allow different positioning of the dsRBDs relative to each other, enabling the recognition of targets of different sequence and structure. The linker could also permit ARF1 SBS , inhibits SMD by competing with hStau1 binding to dsRNAs in 3′UTRs . From seAAD17531.1), codon optimized (Genscript), and of dStau (GenBank: AAA73062.1) were cloned in a pET-MCN vector (E. coli BL21 (DE3) Star (Life Technologies) cells in Terrific broth medium, overnight at 20°C. For SeMet-substituted protein expression, E. coli DL41 (DE3) cells were used; cells were grown in M9 medium and starved before SeMet addition.The sequence of hStau1 (GenBank: N vector . Stau coARF1 SBS dsRNA (Integrated DNA Technologies) added to recombinant hStau1 at RT, incubated for 1 h at 4°C, and loaded on a size exclusion column .His-tagged Stau constructs were purified by cobalt affinity chromatography in lysis buffer  containing 0.5 mM DTT. After washing in buffer A , the recombinant protein was eluted from the resin with a gradient to 300 mM imidazole. The His-tag was subsequently removed by dialysis in the presence of tobacco etch virus (TEV) protease overnight at 4°C, in dialysis buffer . GST-tagged hStau1 constructs were affinity-purified on glutathione resin in lysis buffer containing 1 mM DTT. After washing in buffer A supplemented with 1 mM DTT, the recombinant protein was either eluted from the resin with a gradient to buffer B (buffer A plus 40 mM reduced glutathione) or the tag was cleaved by TEV protease in batch overnight at 4°C. If required, proteins were further purified on HiTrap CaptoS (hStau1) or Heparin Sepharose 6 Fast Flow (dStau) columns , eluted with a gradient to 1 M NaCl, and finally applied on a HiLoad 16/600 Superdex 200pg column . For RNA-binding assays, proteins were gel filtrated in buffer H . For crystallization, the complex was reconstituted with a 1.2 M excess of Construct boundaries for hStau1 truncations: aa 1–360, aa 182–577, aa 182–360; aa 182–255 ; aa 284–358 . Boundaries for dStau dsRBD3-4 construct: aa 570–786.182–360 (dsRBD3-4 construct) in complex with ARF1 SBS grew at 22°C by vapor diffusion . For data collection, crystals were cryo-protected with mother liquor supplemented with 30% 1,6-Hexanediol and flash frozen in liquid nitrogen. The crystals diffracted to 2.9 Å resolution, belong to the space group P41212 with cell dimensions of a = b = 105.9 Å, c = 169.2 Å, α = β = γ = 90° and contain one complex in the ASU. Data were indexed, integrated, and scaled using XDS 2SO4 and 100 mM Tri-sodium citrate, pH 6.2). Cryo-protection was achieved by shortly transferring the crystals to mother liquor supplemented with 20% glycerol before freezing. The crystals diffracted to 1.9 Å resolution, belong to the space group H32 with cell dimensions of a = b = 43.8 Å, c = 452.1 Å, α = β = 90°, γ = 120° and contain one and a half molecules in the ASU.Crystals of unbound ARF1-hStau1182–360 complex native and derivative) and PXII (ARF1 SBS unbound) beamlines of the Swiss Light Source. 100% of the residues in each structure fall within the allowed regions of the Ramachandran plot.Diffraction data were collected at the PXIII (ARF1 SBS dsRNA was prepared by mixing equimolar amounts of 5′-6-fluorescein amidite (FAM)-labeled sense strand and unlabeled antisense strand (Integrated DNA Technologies). The annealed dsRNA, at a concentration of 1 μM, was incubated with increasing concentrations of purified hStau1 constructs in a final volume of 10 μl, in buffer H (see the Protein expression and purification section). After incubating for 45 min on ice, the samples were loaded on a 6% polyacrylamide gel and run at 220 V for 3–4 h in 1× TG buffer  at 4°C. The gel was then imaged at 488 nm using an Amersham Typhoon gel imager .For EMSAs experiments, 1–360), 430 μg (hStau1182–360), or 350 μg (hStau1182–577) protein were injected on the column. For RNA–protein complexes, 140 μg of wt or truncated protein were pre-incubated with a 1.2 M excess of ARF1 SBS dsRNA. Molecular weight calculations were performed using ASTRA software (Wyatt Technologies).For MALLS, purified hStau1 and truncations were loaded onto a Superdex 200 Increase 10/300 GL column , and connected to a miniDAWN TREOS MALLS detector and Optilab T-rEX differential refractometer (Wyatt Technologies). Runs were performed in buffer . For the proteins alone, 200 μg (FL), 400 μg (hStau1f + (Yb − Yf) × (((L + Kd + X) − sqrt(((L + Kd + X) ^ 2) − (4 × L × X)))/(2 × L)), where L = concentration of labeled RNA, X = protein concentration, Yf = anisotropy of free RNA = (X = 0), and Yb = anisotropy of bound RNA .FA measurements were performed with 5′-6-FAM-labeled RNA at RT (19–21°C) on an Infinite F200 plate reader (Tecan). The RNA, at a concentration of 10 nM, was incubated with different concentrations of purified hStau1 or mutants, in buffer H. The final reaction volume was 50 μl. Each titration point was measured three times per experiment, with an integration time of 40 μs, using 485 nm and 535 nm as excitation and emission wavelength, respectively. The data were analyzed using Prism 6 software (GraphPad) by nonlinear regression fitting to the following equation: Y = YARF1 SBS sense (UGAGUGCCAGAAGCUGCCUC); ARF1 SBS antisense (GAGGCAGUUUCUGGUACUCA); dsAU sense (UAUUAUAUAAAUUAUAAAAU); dsAU antisense (AUUUUAUAAUUUAUAUAAUA); and bcd III (CGCUAUUCGCCUUAGAUGUAUCUGGGUGGCUGCUCCACUAAAGCCCGGGAAUAUGCAACCAGUUACAUUUGAGGCCAUUUGGGCUUAAGCG).The sequences of the RNA oligonucleotides (Integrated DNA Technologies) are as follows (5′ to 3′): CD spectra were recorded on a Jasco J-810 spectropolarimeter, at 20°C. Measurements were performed using 200 μl of recombinantly purified hStau1 (wt or mutants), at a concentration of 0.2 mg/ml, in buffer C . Each spectrum was recorded five times and averaged.stauD3/SM6a, and stauR9/SM6a. For the transgenes, a cDNA fragment of the dStau gene (GenBank: AAA73062.1) was cloned into the pUmat-GFP-attB vector (GenBank: MH367504) via HindIII and NotI, yielding N-terminal GFP fusions of wt or mutated dStau proteins. The purified plasmids were injected into embryos from a recombinant stock with the genotype: y1M{vas-int.Dm}ZH-2A w*; PBac{y+-attP-3B}VK00037 stauD3/SM6a. Transgenic flies were identified in the F1 generation by the presence of orange eyes. Ovaries and embryos used for phenotype characterization were obtained from these transgenic flies crossed to stauR9/SM6a flies, and selected against the presence of the balancer chromosome.The following fly stocks were used: Oregon-R (wt), Early embryos were collected according to standard protocols , on applOvaries were collected according to standard protocols  and lyseARF1 SBS complex and ARF1 SBS, respectively.The coordinates and structure factors have been deposited in the Macromolecular Structure Database of European Bioinformatic Institute with ID code 6HTU and 6HU6 for hStau1-


Renal drug transporters such as the organic cation transporters (OCTs), organic anion transporters (OATs) and multidrug resistance proteins (MRPs) play an important role in the tubular secretion of many drugs influencing their efficacy and safety. However, only little is known about the distinct protein abundance of these transporters in human kidneys, and about the impact of age and gender as potential factors of inter-subject variability in their expression and function. The aim of this study was to determine the protein abundance of MDR1, MRP1-4, BCRP, OAT1-3, OCT2-3, MATE1, PEPT1/2, and ORCTL2 by liquid chromatography-tandem mass spectrometry-based targeted proteomics in a set of 36 human cortex kidney samples . OAT1 and 3, OCT2 and ORCTL2 were found to be most abundant renal SLC transporters while MDR1, MRP1 and MRP4 were the dominating ABC transporters. Only the expression levels of MDR1 and ORCTL2 were significantly higher abundant in older donors. Moreover, we found several significant correlations between different transporters, which may indicate their functional interplay in renal vectorial transport processes. Our data may contribute to a better understanding of the molecular processes determining renal excretion of drugs. The concerted activity of these transport systems allows a vectorial movement of substrates resulting in the reabsorption of many important substances such as glucose from the filtrate into the blood, and the excretion of waste products such as creatinine and xenobiotics (drugs and their metabolites) from the blood into the urine [One of the most important physiological roles of the kidneys is to contribute to the maintenance of body homeostasis, by regulating salt and water excretion and eliminating metabolism waste products and xenobiotics. To achieve these aims, the nephron, that is the functional unit of the kidneys, filters the blood in a structure called glomerulus. The composition of the filtrate is then strongly modified during its passage through the tubules system, before being excreted as urine. The cells of the renal tubules are equipped with a huge number of transport proteins, which are specifically expressed in distinct domains of the cellular plasma membrane  and in distinct portions of the nephron . Quantithe urine . Dependihe urine . Focusinhe urine . It has he urine . Howeverhe urine ,7,8 is sFor this reason we have measured the protein abundance of Multidrug Resistance Protein 1 , Multidrug Resistance Associated Protein (MRP)1-4, Breast Cancer Resistance Protein (BCRP), Organic Anion Transporter (OAT) 1-3, Organic Cation Transporter (OCT) 2-3, Multidrug And Toxin Extrusion protein 1 (MATE1), Peptide Transporter (PEPT) 1-2 and Organic Cation Transporter-Like 2 (ORCTL2)  by liqui2, for example) and exogenous  organic anions [In the following, the functional organization in the kidneys of the transporters identified in this work is given. Transporters for organic cations are involved in the renal secretion of cationic substances, which is accomplished by an uptake from the blood into the proximal tubules cells followed by a transport from these cells into the urine. Organic cations are endogenous substances (neurotransmitters such as dopamine and histamine) and exogenous substances (drugs such as amiloride and metformin) . Basolatc anions  in exchac anions . The excc anions . The apically expressed ORCTL2 is probably involved in the transport of chloroquine and quinidine into the urine .The interested reader can find an extensive description of renal transporters in dedicated reviews ,11,12.+/K+ ATPase, MDR1, MRP1, 2, and 4, OAT1-3, OCT2, ORCTL2, and MATE1. Therefore, for these transporters it was evaluated, whether there was a gender-dependent protein expression. As shown in The first aim of this work was to measure the protein abundance of selected transporters, which play an important physiological and pharmacological role in human renal kidney cortices. While several basolaterally and apically localized transporters were well detectable, the protein abundance of MRP3, BCRP, PEPT1, and PEPT2 was below the lower detection limit of the proteomic assay. OCT3 was measurable only in few samples. Measurable protein amounts could be detected for Na+/K+ ATPase showed high protein levels, followed by the SLC transporters OCT2 and OAT1 and 3. A discrete expression of MATE1 and ORCTL2 was also measured. ABC transporters, together with OAT2 and OCT3 were less abundant than the other proteins.Therefore, the results obtained with samples derived from male and female patients were combined . As expeIn an attempt to determine whether there is any association between the transporter protein abundance and the age of the donors, the protein data was stratified according to the age. We could observe a significant linear relationship between transporter protein abundance and age of donors for MDR1 and ORCTL2; in each case the transporter abundance increasing with age .+/K+ ATPase correlated directly with MRP2/MRP4/OAT2/OCT2 abundance;NaMDR1 with MRP2/OAT2/OAT3/OCT2;+/K+ ATPase/MDR1/MRP4/OAT3/OCT2;MRP2 with Na+/K+ ATPase/MRP2/OAT3/OCT2;MRP4 with Na+/K+ ATPase/MDR1/OAT3/OCT2/MATE1;OAT2 with NaOAT3 with MDR1/MRP2/MRP4/OAT2/OCT2/ORCTL2/MATE1;+/K+ ATPase/MDR1/MRP2/MRP4/OAT2/OAT3/ORCTL2/MATE1;OCT2 with NaOCT3 with MATE1 (inversely correlated);ORCTL2 with OAT3/OCT2;MATE1 with OAT2/OAT3/OCT2/OCT3The analysis of relationships between transporter abundancy revealed several significant correlations : Na+/K+ R ≥ 0.8) was found between OAT3 and OCT2, and MRP2 and MRP4, abundance  was measured in some patients by real-time PCR. Also, in this case, no correlation between mRNA-expression of the transporters and age and gender of the patients was detected . InteresSince the proteomic analysis revealed a substantial amount of OCT2 in the cortex of human kidneys, we performed an immunofluorescence analysis of renal OCT2 to confirm this finding. By co-labeling of proximal tubules with PHA-E a and of The kidneys play an important role in maintaining body homeostasis. In order to execute this vital function, the renal tissue is equipped with a battery of membrane transporters, which are specifically expressed in well-defined apical and basolateral membrane domains, and which work together to attain vectorial movement of substrates through the renal tubules . These pFor this study, healthy parts of human renal cortices derived from tumor nephrectomy of adult patients were used. The samples were immediately processed after surgery.The protein abundance was found here not dependent on sex. Similar results have been obtained with liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics in kidney samples from Afro-Americans and Caucasians . Taken t+/K+ ATPase resulted to be the highest under the transporters investigated in this study. In our opinion, this reflects the extreme importance of this pump, which contributes to maintain the gradients for Na+ and K+ between the extra- and intracellular space, being of primary importance for renal transport processes [+/K+ ATPase. The rank order of the most abundant renal drug transporters was OAT3 ~ OCT2 > OAT1 ~ ORCTL2 > MATE1 >MDR1 (P-gp). Similar findings have been obtained in other works [As expected, the protein abundance of Narocesses . The traer works ,27, evener works  or pmol er works ,26,27,28R) = 0.4–0.5). This was a somewhat unexpected finding as there are many well-documented examples for the net excretion via the respective transporters tandems  and MRP2/MRP4 , suggesting that there may be a membrane domain specific regulation mechanism of protein expression. Interestingly, the correlations between proteins that act as functional counterparts for renal excretion at the basolateral and the apical membrane (e.g. OAT3 - MRP2 (excretion of anions), OCT2 – MDR1 (P-gp) and OCT2 – MATE1 (both excretion of cations) even though significant were rather weak , or immediately frozen in liquid nitrogen, or fixed in 4% paraformaldehyde  for PCR, protein, and immunochemistry analysis, respectively.Human kidney samples were obtained from Caucasian patients . Afterwards, the samples were centrifuged one more time for 15 min at 16,000 g and 4 °C. 50 µL of the supernatant were mixed with 25 µL isotope-labeled internal standard peptide mix . All sample preparation and digestion steps were performed using Protein LoBind tubes . Protein quantification was conducted on a 5500 QTRAP triple quadrupole mass spectrometer  coupled to an Agilent Technologies 1260 Infinity system (Agilent Technologies). Transporter proteins considered to be of clinical relevance were simultaneously quantified using proteospecific peptides , MRP1 (ABCC1), MRP2 (ABCC2), MRP3 (ABCC3), MRP4 (ABCC4), BCRP (ABCG2), PEPT2, OCT1, OCT3, OCTN2, OAT1, OAT2, OAT3, MATE1, OATP1A2, OATP1B1, OATP1B3, OATP2B1, NTCP and ASBT were measured by mass spectrometry-based targeted proteomics using validated LC−MS/MS methods as described elsewhere . In briepeptides . Accurac-ΔCt method [Human renal cortical tissue was homogenized, and total RNA was isolated using the RNeasy Mini Kit (Qiagen). RNA was separated using a RNeasy column (Qiagen) and for cDNA synthesis, 2 µg total RNA was used with the SuperScript-III First-Strand Synthesis SuperMix . Gene expression profiles for OCT2, OAT1-2, and MATE1 were analyzed by real time PCR using SYBR Select Master Mix for CFX  on a CFX Realtime Detection System . Specific primer pairs as listed in t method  using GAt method .Localization of OCT2 in human kidneys was investigated using specific antibodies raised in mouse against OCT2 . Five µmAfter washing in PBS, cryosections were incubated for 1 h at room temperature with secondary antibodies  diluted in PBS, rinsed with PBS, coverslipped with FluoroMount (Sigma) and evaluated by epifluorescence microscopy . Negative control slides were included without addition of primary antibody.


RNA editing is phenomenon that occurs in both protein coding and non-coding RNAs. Increasing evidence have shown that adenosine-to-inosine RNA editing can potentially rendering substantial functional effects throughout the genome. Using RNA editing datasets from two large consortiums: The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) project, we quantitatively analyzed human genome-wide RNA editing events derived from tumor or normal tissues. Generally, a common RNA editing site tends to have a higher editing level in tumors as compared to normal samples. Of the 14 tumor-normal-paired cancer types examined, Eleven of the 14 cancers tested had overall increased RNA editing levels in the tumors. The editomes in cancer or normal tissues were dissected by genomic locations, and significant RNA editing locational difference was found between cancerous and healthy subjects. Additionally, our results indicated a significant correlation between the RNA editing rate and the gene density across chromosomes, highlighted hyper RNA editing clusters through visualization of running RNA editing rates along chromosomes, and identified hyper RNA edited genes  that embody a large portion of cancer prognostic predictors. This study reinforces the potential functional effects of RNA editing in protein-coding genes, and also makes a strong foundation for further exploration of RNA editing’s roles in non-coding regions. RNA editing is the molecular process by which ribonucleic acid (RNA) molecule’s nucleotide sequences are modified enzymatically after RNA has been generated by RNA polymerase. There are two types of canonical RNA editing: adenine-to-inosine (A-to-I) and cytosine-to-uracil (C-to-U). The mechanisms of these two types of RNA editing have been thoroughly studied. The A-to-I editing is mediated by adenosine deaminase acting on RNA (ADAR) , and C-tMost well characterized functional editing sites are found in transcripts for neuronal transporters and channel proteins in the brain . Recent Given a large amount of paired DNA-RNA sequencing data accumulated over the last decade, it became feasible to detect RNA-DNA Difference from direct comparison of DNA and RNA nucleotide sequences, and millions of RDDs have been documented in RNA editing databases, such as REDIportal . REDIporAbundant high-throughput sequencing data of human cancers enable us to study the differential RNA editing level in tumor samples relative to normal. Here, in various perspectives, we performed RNA editing level analyses on 6,236 samples from 14 cancers from TCGA, aiming to obtain global views on RNA editing levels across different sample sources , genomic locations , and gene features . Because of the dominance of A-to-I RNA editing, our study primarily focused on the canonical A-to-I editing type.We obtained 230,079 RNA editing events across 107,049 genomic positions from a previous RNA editing study by The level and rate of RNA editing were computed using the following formulas:Gene edit frequency was defined as number of RNA edit within the gene divided by the gene length. Hyper RNA edited genes were identified by rank the gene edit frequency from large to small.Furthermore, 4.66 million known RNA editing events from database REDiportal  were dowp-value <0.05 was used as the significant threshold.In the present study, RNA editing in chromosome 1–22, X and Y were studied thoroughly, while the mitochondrial genome was omitted. Annotation of the RNA editing positions was done using ANNOVAR . Wilcoxor = −0.04, p = 0.9, In the TCGA data, across all 14 cancer types, 230,079 RNA editing events across 107,049 genomic positions were identified , as compr = 0.94). Upon further examination, we found that when comparing the abundance of RNA editing events across chromosomes, it is not the chromosome length but the gene density that should be accounted for. Gene density can be represented as the exome percentage per chromosome calculated as sum of all exon length within a chromosome divided by the chromosome length (r = 0.91), and with that from GTEx as well (r = 0.91). The correlations between lincRNA gene density and RNA editing rates are relatively weaker, with Spearman correlation coefficients 0.62 for TCGA and 0.57 for GTEx  larger than GTEx (1.61%). The overall Chi-square tests between TCGA and GTEx was also significant with p < 0.0001. Such a difference might be related to the sample source difference, as TCGA subjects were all cancer patients and the normal samples were adjacent normal tissues whereas GTEx subjects were all considered healthy individuals.Because current sequencing data mostly target protein coding regions, it is not surprising that a majority of the RNA editing events reported from GTEx and TCGA were found in or close to exome regions. In TCGA, we observed that 53.58% of the RNA editing events occurred in intronic regions, followed by 3′UTR (25.10%). Non-coding RNA accounted for 2.89%, and intergenic regions accounted for only 11.77% of all RNA editing in TCGA. In GTEx, 51.03% of RNA editing occurred in introns and 1.61% occurred in 3′UTRs. Non-coding RNA accounted for 5.89%, and intergenic regions accounted for 37.08% of all RNA editing in GTEx . The dist-tests to detect any significant RNA editing level differences. Stratifying by cancer types, of the 14 types of cancer with tumor-normal pairs, 11 types of cancers had higher RNA editing levels in tumor and 3 types of cancer  had higher RNA editing levels in normal , we conducted paired n normal . UCEC haNext, we examined RNA editing levels between tumor and normal samples per RNA editing site. The RNA editing events were categorized based on their genomic location: intronic, exonic, 3′-UTR, 5′-UTR, upstream, downstream, splicing, ncRNA, and intergenic. As expected, the number of significantly differentially edited positions are dominated by intronic and 3′-UTR RNA editing events and influenced by the sample size in each cancer type . The genUsing RNA editing data from both GTEx and TCGA, we sought to identify hyper RNA editing genes. The top 10 hyper RNA edited genes from TCGA and GTEx data are displayed in We compared the RNA editing rate between GTEx and TCGA in three categories: protein coding, lincRNA, and pseudogenes. The total number of RNA editing events identified in GTEx is substantially greater than TCGA, the number of overlapped genes with RNA editing are displayed in Finally, we computed the genome-wide RNA editing frequency using both GTEx and TCGA data. The genome-wide RNA editing frequency was measured as number of RNA editing events observed in a moving window with the size of 10,000 nucleotides. RNA editing hotspots can be observed in both GTEx and TCGA data. However, these hotspots are most likely to be associated with gene density. For illustration purpose, the RNA editing frequency for chromosome 1 is displayed in Our analyses found that the RNA editing rate is highly associated with gene density, especially protein-coding gene density. Chromosome 19 was found to harbor the highest RNA editing rate among all chromosomes (excluding mitochondria). The highest RNA editing rate can be explained by the highest gene density in chromosome 19. The correlations between RNA editing rate and protein-coding gene density is higher than the correlations between RNA editing rate and lincRNA density. This could result from the bias of the source data. The TCGA RNA editing events were detected by comparing exome sequencing and RNA-seq data. Exome sequencing targets protein coding regions primarily. RNA-seq, depending on library preparation method, can target protein coding or total RNA. However, when using exome sequencing data as a reference, the detection range for RNA editing events is limited to protein-coding regions. Furthermore, the RNA editing detection is also limited to gene expression. No RNA editing can be detected with non-expressed genes. Frankly, the majority of the RNA editing source sequencing data were not designed for RNA editing detection initially but were data mined for RNA editing at a later time. The focus of protein-coding regions of the source data resulted that the current detected RNA editing events heavily reside in protein coding regions.A majority of the RNA editing events were found in either intronic regions or 3′-UTRs for TCGA and GTEx data. This ubiquitous phenomenon has been discovered in previous findings . SignifiThe intronic RNA editing is less likely to cause functional consequence. The 3′UTR contains key regulatory elements such as miRNA response elements, AU-rich elements, and poly(A) tails. These elements can affect mRNA stability, export, and translation efficiency. Thus, it has been proposed that RNA editing in 3′UTR can up-regulate mRNA expression by acting as a miRNA sponge, repressing miRNA expression . It has There have been multiple reports that RNA editing events tend to occur in close vicinity , these pA portion of the RNA editing events do occur in non-coding RNAs, which have gained substantial interest in recent years. One of the common types of non-coding RNA that we explored in our study is lincRNA, which are traditionally thought to be non-functional. The increasing reports of lincRNA-disease associations over the last decades suggest that there are unknown mechanisms by which lincRNA exerts its influence . There hThis study uses publically available data downloaded from GDC data repository. It does not contain any patient information or patient data.MC, YG, DS, and Y-yZ wrote the manuscript. MC, HY, and WY performed the analyses and designed the figures and tables for the first submission. YG designed the study. SN, QS, and OO performed the additional analyses and designed the new figures during revisions.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.