Plasmodium falciparum has revealed robust variation in steady-state mRNA abundance throughout the 48-h intraerythrocytic developmental cycle (IDC), suggesting that this process is highly dynamic and tightly regulated. Here, we utilize rapid 4-thiouracil (4-TU) incorporation via pyrimidine salvage to specifically label, capture, and quantify newly-synthesized RNA transcripts at every hour throughout the IDC. This high-resolution global analysis of the transcriptome captures the timing and rate of transcription for each newly synthesized mRNA in vivo, revealing active transcription throughout all IDC stages. Using a statistical model to predict the mRNA dynamics contributing to the total mRNA abundance at each timepoint, we find varying degrees of transcription and stabilization for each mRNA corresponding to developmental transitions. Finally, our results provide new insight into co-regulation of mRNAs throughout the IDC through regulatory DNA sequence motifs, thereby expanding our understanding of P. falciparum mRNA dynamics.Genome-wide analysis of transcription in the malaria parasite  Plasmodium blood-stage developmental stages and identify associated regulatory DNA sequence motifs.Transcriptomic analysis often doesn’t differentiate between newly synthesized and stabilized mRNAs. Using rapid 4-thiouracil incorporation, Painter et al. here define genome-wide active transcription throughout  Plasmodium parasites resulting in almost half a million deaths and an enormous economic impact on almost half the world’s population annually1. Efforts to eradicate this pathogen have been at the forefront of infectious disease research for decades. Although it has been over 15 years since the completion of the whole genome sequence2 of Plasmodium falciparum, transcriptional regulation throughout the parasite’s complex life cycle remains poorly understood.Hundreds of millions of annual malaria cases are caused by intracellular protozoan Plasmodium sporozoites from the saliva of an infected Anopheles spp. female mosquito vector to a human host. These sporozoites travel to and colonize a small number of hepatocytes within the liver where they replicate, forming thousands of merozoites. Liver-stage merozoites are released into the circulatory system and initiate the blood stage of infection, which is responsible for the clinical symptoms of malaria. Development during the 48 h intraerythrocytic development cycle (IDC) is comprised of parasite maturation and cell division, resulting in the formation of up to 32 daughter cells, which are released and invade new erythrocytes3. A small proportion of asexual parasites commit to an alternative cellular fate of sexual differentiation during the IDC, eventually resulting in the development of male and female gametocytes. Maturation of P. falciparum sexual stage parasites takes 10–12 days, and it is these sexual forms that are taken up by a mosquito vector for eventual onward transmission to another human host, thus completing the Plasmodium full life cycle4. Differentiation of the malaria parasite in these various cell types and tissues is regulated by coordinated programs of gene expression10.The malaria parasite life cycle commences upon the transfer of 11. Although canonical transcriptional machinery is present, the mechanisms that underlie the regulation and specificity of active transcription remain largely uncharacterized13. To date, only a single family of specific transcription factors, the 27-member Apicomplexan AP2 (ApiAP2) protein family, has emerged as transcriptional regulators with functions across all developmental stages14. However, the challenge of regulating roughly 5500 Plasmodium genes with a small repertoire of transcription regulators suggests a significant role for epigenetic control and post-transcriptional regulation in Plasmodium spp.18. The control of gene expression at the RNA level is evidenced by several studies reporting a significant delay between transcription and translation22, ribosomal influence on the timing of mRNA translation24, and a lack of coordination between active transcription and mRNA abundance during parasite development26. Bioinformatic analyses have suggested that between 4 and 10% of the Plasmodium genome encodes RNA-binding proteins (RBPs)28. While the majority of predicted RBPs remain uncharacterized, several post-transcriptional regulatory factors have been well-studied such as DOZI (DDX-6 class DEAD box RNA helicase), CITH (Sm-like factor homolog of CAR-I and Trailer Hitch), and pumilio family proteins (PUF1 and PUF2) that have been demonstrated to play critical roles in the translational repression of genes essential for Plasmodium transmission29. Additionally, the acetylation lowers binding affinity (ALBA) domain-containing proteins (PfAlba1-4)32, Bruno/CELF family members (CELF1 and CELF2)33, and Pfg2734 have been demonstrated to interact with RNA; however, the exact role has yet to be defined for a majority of these RBPs in parasite development.Gene expression during the IDC is highly periodic and follows a transcriptional cascade with the majority of genes expressed in a “just-in-time” fashion35. Thus, changes in transcript abundance measured by DNA microarray, RNA-sequencing, or RT-qPCR studies reflect the relative rates of both transcription and mRNA stabilization. Since the advent of the complete P. falciparum genome sequence, numerous studies have utilized whole-genome methods to measure transcript abundance from population of parasite-infected red blood cells36 as well as, more recently, single cells38. In addition, other studies have measured transcriptional activity39, mRNA half-lives40, RNA Pol II binding41, and transcription start sites42 throughout development. Although these studies have revealed many important details of the regulation of gene expression in Plasmodium during the IDC, none capture mRNA dynamics on a whole-genome scale without perturbations to the parasite. Measurement of mRNA half-lives is commonly performed following chemical inhibition of transcription, which induces a stress response or cellular death thereby impacting the ability to accurately measure physiological mRNA turnover parameters43. Similarly, whole genome capture of transcriptional activity via nuclear run-on39 or GRO-seq26 methods require isolation of nuclei or permeabilization of cells, which compromises cellular physiology and nascent nuclear transcriptional activity. Therefore, we characterized the mRNA dynamics of the P. falciparum transcriptome by comprehensively capturing nascent mRNA transcription, stabilization, and total abundance of mRNA in vivo throughout the IDC using 4-thiouracil (4-TU) biosynthetic RNA labeling.In all living systems, cellular mRNA levels are determined by the interplay of tightly regulated processes of RNA production, processing, stabilization, and degradation46 across a diverse array of organisms48 including Plasmodium25. In human and yeast cells, short periods of metabolic labeling into nascent RNA has been used to capture RNA synthesis, decay, and splicing rates50. However, thiol-modified RNA capture and kinetic profiling of RNA dynamics are dependent upon pyrimidine salvage, and the evolutionary lineage of Plasmodium has lost this biochemical capacity51. We have previously demonstrated that genetic engineering of the pyrimidine salvage pathway into Plasmodium parasites enables the efficient uptake of 4-TU and biosynthetic capture of thiol-labeled RNAs to examine RNA dynamics during parasite development25.Biosynthetic labeling of pyrimidines has revolutionized the capture and measurement of in vivo cellular mRNA dynamics during development and in response to various stressors25 to measure genome-wide nascent mRNA transcription and stability in vivo throughout the IDC of the malaria parasite. This method relies on the genetically facilitated scavenging of 4-TU and genome-wide DNA microarray measurements of labeled and unlabeled RNAs. Using this method, we have captured mRNA dynamics during asexual development at hourly resolution and apply a quantitative normalization model to define gene-specific mRNA metabolism. These data provide dynamic transcription and stability information for all mRNAs expressed during the IDC and also recapture known features of the “just-in-time” cascade of mRNA transcription. Additionally, modeling of the mRNA dynamics reveals regulatory mechanisms that cooperate during parasite development, which we used to predict functional roles for putative transcriptional regulators. Our results provide an updated in-depth view of mRNA transcriptional dynamics and gene regulation in P. falciparum throughout the IDC.Herein, we report the application of biosynthetic RNA labeling and captureP. falciparum is not capable of pyrimidine precursor uptake and incorporation into RNA51. We previously reported the use of episomal expression of the bifunctional fusion gene encoding cytosine deaminase and uracil phosphoribosyltransferase (FCU) from yeast to enable parasite salvage of 4-TU25. To avoid cell-to-cell heterogeneity in plasmid copy number expressing FCU, this study uses a single copy cassette that is stably integrated into the attB locus of 3D7attb52 to constitutively express a GFP-tagged FCU protein  was verified by PCR , and unlabeled (stabilized) RNAs were quantified using DNA microarray analysis .To investigate whether in vivo RNA labeling perturbed transcription dynamics, we correlated the total RNA abundance levels from the 4-TU treated 3D72(green/red) values within individual timecourses, the log2 values do not distinguish the relative contributions of the various pools of RNA  to the total RNA signal  when timecourses are directly compared to each other. To circumvent this issue, we developed a statistical model to quantitatively determine the contribution of nascent transcription (labeled) and mRNA stabilization (unlabeled) to the total abundance profile of each gene by comparing the signal intensities for each probe on the DNA microarrays across all three timecourses (Methods). After the three timecourses were separately normalized by Rnits53  ratios and normalized expression values are also available for download.Estimated coefficients for 58. In contrast, nuclear-encoded genes destined for the apicoplast are transcribed prior to apicoplast encoded genes   Fig. , likely 69) Fig. . This sur ≥ 0.50) mechanism acting on each gene based on the correlation of either transcription , and cytoskeletal protein binding  including kinase signaling and microtubule formation. Conversely, genes with peak transcription occurring immediately following invasion outnumber any other hour of the IDC , likely in preparation to increase cellular transcription levels necessary for parasite development and aid in post-transcriptional regulatory processes. Identification of genes stabilized prior to or transcribed upon invasion may facilitate the dissection of the cellular and molecular processes that govern the establishment of the parasite within a new erythrocyte and provide molecular targets for future investigation.Beyond the identification of genes enriched during developmental transitions, we also identified a number of genes whose peak timing of transcription and stabilization occurred at either 1 or 48 hpi. As expected, at 48 hpi the number of stabilized genes 378 genes) outnumbers those that are actively transcribed (140 genes)  are transcribed during the late ring to early trophozoite stages of development and exhibit variation in their expression among parasite clones60. To identify the timing of transcription, we calculated the average normalized expression values (log2 mean centered) for each gene family to determine the peak time of nascent transcription during the IDC  of these surface antigen gene families was being transcribed in this clonal population of transgenic parasites, we determined the expression values of each gene at the peak hour of transcription for each family of surface antigens , including msp7 and msp2, are predominantly regulated at the level of transcription and appear to be minimally influenced by stabilization  have been shown to assist in the establishment of nutrient transporters across the parasitophorous vacuolar membrane following invasion67. Although these genes are transcribed during the schizont stage and their protein products are necessary for invasion, stabilization guarantees that the mRNAs will be available for translation immediately upon invasion to promote proper nutrient transport for the developing parasite as recently demonstrated66. Interestingly, the mRNA dynamics of both sera3 and sera4 reveal a balance of transcription and stabilization  , which is bound by the third AP2 domain of PfAP2-I70, compared to the expression of pfap2-i   algorithmte) Fig. . Of thes2-i Fig. . As expe2-i Fig. . Additiosis Fig. 71. Conve-g2 Fig. , which h22) Fig. . Taken t22) Fig. . Finallytif Fig.  to the t35. Data on gene expression levels in P. falciparum obtained by microarray or RNA-seq62 reflect steady-state quantities of intracellular RNA, which are a product of the rate of both genome-wide transcription and stabilization. However, a major constraint of these analyses is the inability of these methods to differentiate between transcription and stabilization, which contribute to global abundance profiles throughout the IDC. As we have demonstrated, this constraint can be overcome by 4-TU biosynthetic labeling of newly transcribed mRNA providing direct isolation and analysis of nascent transcripts with minimal perturbations and toxic effects to the cell25.Cellular RNA levels are subject to extensive regulation involving alterations in the rates of RNA synthesis (transcription), processing , stabilization, and decayP. falciparum to constitutively express the pyrimidine salvage pathway by single-copy genome integration, enabling the rapid incorporation of 4-TU into nascent mRNA transcripts. Using these parasites, we labeled and captured nascent transcription and mRNA stability and determined their contribution to the total abundance profiles of each gene throughout intraerythrocytic development. Earlier transcriptome studies captured timing and mRNA abundance of each gene by DNA microarray analysis10, revealing a periodicity to gene expression during the 48 h IDC. Here, we demonstrate that the periodicity of each gene is defined by contributions from both transcription and stabilization. However, mRNA regulation is also time-dependent and gene-specific. Given the complexities of genome-wide mRNA dynamics, we examined the contribution of mRNA regulation to gene expression as the parasite progresses through the IDC revealing that transcription and stabilization do not contribute equally to the patterns of abundance observed for a given gene. Our results identify active transcription throughout the IDC . This plasmid was transformed into, replicated in, and isolated from DH5α Escherichiacoli for transfection into P. falciparum 3D7attBattb.The open reading frame of the yeast FCU gene was PCR amplified from P. falciparum strain 3D7attB was obtained from BEI Resources (cat # MRA-845) as a mycoplasma-free frozen stock and has been described in previous studies52. Parasite cultures were maintained under standard conditions77 at 5% hematocrit of O+ human erythrocytes  in RPMI1640 containing hypoxanthine, NaH2CO3, HEPES, glutamine and 5 g/L AlbuMAX II (Life Technologies). The 3D7attB line has been genetically altered to contain an acceptor attB site (from Mycobacterium smegmatis) into the non-essential cg6 locus. This recombinant locus is maintained by continuous selection with 2.5 nM WR99210 78.P. falciparum strain 3D7  was performed as previously described78. Briefly, 5–7% ring-stage parasite cultures were washed three times with 10 times the pellet volume of cytomix. The parasitized RBC pellet was resuspended to 50% hematocrit in cytomix. In preparation for transfection, 100 µg of both pLN-5′cam-FCU-GFP and pINT plasmid, expressing a Mycobacterium Bxb1 integrase that mediates attP and attB recombination, were precipitated and resuspended in 100 μL cytomix. The plasmid and 250 μL of the 50% parasitized RBC suspension were combined and transferred to a 0.2 cm electroporation cuvette on ice. Electroporation was carried out using a BioRad GenePulser set at 0.31 kV, 960 µF. The electroporated cells were immediately transferred to a T-25 flask containing 0.2 mL uninfected 50% RBCs and 7 mL medium. To select for parasites containing both plasmids, medium containing 1.5 µg/µL Blasticidin S (Sigma-Aldrich) and 250 µg/mL G418 Sulfate  was added at 48 h post transfection. Cultures were maintained under constant 1.5 µg/µL Blasticidin S (Sigma-Aldrich) pressure, splitting weekly, until viable parasites were observed. Viable transgenic parasites were then cloned by limiting dilution and genomic DNA isolated to detect the presence of the integrated fusion gene of fcu-gfp was PCR verified using previously published primer pairs52.Transfection of P. falciparum , isolated by saponin (0.01%) lysis. Protein extracts from both 3D7attB wild-type parasites and 3D7attB::FCU-GFP (clone A2) transgenic parasites were run on a SDS-10% polyacrylamide gel and transferred to a nitrocellulose membrane. The membrane was blocked with 5% milk for 30 min. To detect protein, the membrane was exposed to sheep IgG anti-cytosine deaminase primary antibody  diluted 1:500 in 3% bovine serum albumin (BSA) and incubated overnight at 4 °C followed by a 1 h incubation with donkey anti-sheep HRP secondary antibody  diluted 1:1000 in 3% BSA. The membrane was incubated for 1 min in Pierce® ECL-reagent (Thermo Fisher Scientific) and protein detected by exposure to film.Western blot analysis of FCU-GFP protein expression was carried out on mixed stage transgenic P. falciparum-infected erythrocytes were fixed with 4% formaldehyde/0.0075% glutaraldehyde  using the method of Tonkin et al.[FCU-GFP expression in transgenic parasite lines was verified by immunofluorescence imaging analysis. Mixed stage transgenic in et al.. Fixed cattB::fcu-gfp strain compared to wild-type 3D7attb by the addition of 40 µM of 4-TU (Sigma Aldrich) to the culture medium from a 200 mM stock concentration prepared in DMSO as previously described25. After parasites were grown in the presence of 4-TU for 12 h, total RNA was prepared from parasites in 5 mL of TRIzol and resuspended in DEPC-treated water to a final concentration of 0.5 µg/µL. As described in Painter et al.25, total RNA was biotinylated with EZ-link Biotin-HPDP dissolved in formamide to a concentration of (Thermo Fisher Scientific) for 3 h at room temperature under RNase-free conditions to reduce the amount of RNA degradation that can occur. Biotinylated RNA (2.5 µg) was run on an Ethidium Bromide 1% agarose gel at 4 °C for 30 min at 200 V and was transferred to Hybond-N+ nitrocellulose (Amersham) membrane using traditional northern blotting techniques. The RNA was UV-crosslinked to the membrane and probed with streptavidin–HRP (1:1000) (Thermo Fisher Scientific). Biotinylated RNA was detected via incubation with ECL-reagent and exposure to film.Function of the FCU-GFP transgene was verified in the 3D7P. falciparum transgenic parasites were cultured in O+ human erythrocytes  at 5% hematocrit in RPMI1640 complete medium as described above. All transgenic parasites were synchronized with three successive (48 h apart) L-alanine treatments to remove late stage parasites80. To ensure a sufficient amount of mRNA was labeled and captured for further analysis, we grew 48 individual parasite cultures to 15% parasitemia in 100 mL of medium at 5% hematocrit, one culture flask (150 cm2) for each timepoint. Upon invasion, 40 µM 4-TU was added to the medium and parasites were incubated for 10 min followed by total RNA isolation with TRIzol. 4-TU addition, incubation, and RNA extraction was repeated every hour for 48 successive timepoints throughout intraerythrocytic development.P. falciparum was incubated with 4-TU and total RNA was extracted as described above. All RNA was subjected to the biosynthetic modification and magnetic separation as previously published with a few adjustments46. Specifically, 80 µg of total RNA (at a concentration of 0.4 µg/µL) was incubated at room temperature protected from light for 3 h in the presence of 160 µL of 1 mg/mL solution of EZ-link Biotin-HPDP (Thermo Fisher Scientific). Biotinylated total RNA was precipitated and resuspended in DEPC-treated water to a final concentration of 0.5 µg/mL. Incorporation of 4-TU and biotinylation was determined by NanoDrop analysis and Northern blot probed with streptavidin–HRP. 4-TU labeled-biotinylated RNA was purified using Dynabeads® MyOne™ Streptavidin C1 magnetic beads (Life Technologies) at a concentration of 2 µL/µg of RNA. Beads were prewashed as per manufacturers protocol to remove any RNases and blocked with 16 µg of yeast tRNA (Life Technologies). 4-TU labeled-biotinylated RNA was added to the bead slurry and incubated at room temperature for 20 min with rotation. The RNA-bead slurry was placed on a magnetic stand for 1 min, and liquid carefully removed and saved for RNA precipitation. This sample contained RNA that was not thiolated or biotinylated. Then the RNA-bound beads underwent five rounds of stringent washes with buffer consisting of 1 M NaCl, 5 mM Tris–HCl (pH 7.5), 500 µM EDTA in DEPC-treated water. 4-TU labeled-biotinylated RNA was eluted from the beads with 5% 2-mercaptoethanol incubated for 10 min at room temperature, placed back on the magnetic stand, liquid removed and saved for RNA precipitation. The RNA in this fraction contained mRNA transcribed in the presence of 4-TU from FCU-GFP expressing cells.Briefly, transgenic 10 with the addition of control RNAs to aid in the normalization between samples and arrays . To prevent Cy5 degradation by ozone, all steps starting with dye resuspension were carried out in an ozone-free environment. Final cDNA concentration and dye-incorporation was assessed on a NanoDrop ND-1000 spectrophotometer. To reduce sample and time-point bias, cDNA from each time-point was labeled with Cy5 and combined with an equal amount of Cy3-labeled cDNA reference pool generated from equal amounts of ring, trophozoite, and schizont stage mRNA and hybridized to P. falciparum custom arrays . Hybridized arrays were incubated for 16 h in a rotating hybridization oven (10 rpm) at 65 °C. Prior to scanning, arrays were washed in 6× and 0.06× SSPE (both containing 0.005% N-lauryl-sarcosine) , followed by an acetonitrile rinse.Total RNA, unbound, and bound fractions of mRNA are precipitated by traditional methods  followed by resuspension in 20 μL DEPC-treated water. The concentration of each sample is determined by NanoDrop ND-1000. Starting with 1.0–2.5 μg of RNA, single-strand aminoallyl-containing cDNA synthesis and Amersham CyDye-coupling  was carried out as previously describedArrays were scanned on an Agilent G2505B Microarray Scanner (Agilent Technologies) with 5 μm resolution at wavelengths of 532 (Cy3) and 633 nm (Cy5) using the extended dynamic range (10–100%) setting. Normalized intensities were extracted using Agilent Feature Extraction Software Version 9.5 employing the GE2_1100_Jul11_no_spikein extraction protocol.53. Arrays for 45 hpi contained an abundance of extreme outliers and were excluded from further analysis. Prior to data smoothing and fitting, probes that are Agilent Controls, rRNAs (28 probes), or found to be not unique (133 probes) were removed. The timecourse profiles of each probe were then smoothed using cubic splines and all negative values set to 0.5. For each probe, contribution of unlabeled (stabilized) and labeled (transcribed) RNAs was modeled to sum up to the total abundances, assuming that contributions are naturally non-negative:Each set of 48 arrays for total, labeled, and unlabeled RNA was normalized using the Rnits (v1.2.0) from the Bioconductor project in Rα and β are the coefficients applied to the probe intensity values on the labeled and unlabeled RNA arrays, respectively. This problem of non-negative least squares is solved by the Lawson–Hanson algorithm (the nnls package in R). As a simple verification that the expression values estimated for both transcription and stabilization were accurate, the predicted total mRNA abundance was computed by adding the estimated unlabeled and labeled expression values. The hourly pairwise-Pearson correlation between the predicted total mRNA abundances and the conventional observed abundances was calculated between every timepoint. From this, the median Pearson correlation was determined from the directly corresponding hourly timepoints. Each probe was summarized by gene using Tukey’s biweight with a parameter c = 5. Finally, three timecourses for each gene are plotted over 48 h. These data are available on http://www.PlasmoDB.org56 on individual gene pages or for download of the full dataset.In this equation, 81 using the available LombScargle package for R. The resulting peak times for each gene can be found in Supplementary Data We utilized the Lomb-Scargle periodogram approach to determine the peak time of total abundance, transcription, and stabilization for each gene as described previouslyRates of transcription for each gene were determined based upon the slope of the calculated expression values from the start of transcription to the adjacent peak. Conversely, rates of decay were calculated by determining the slope of the expression values of unlabeled RNA (stabilized fraction) from the peak to the following trough. Calculated rates of transcription and decay for each gene were then binned into groups based upon the peak timing of nascent transcription or stabilization of that gene http://www.PlasmoDB.org56 and terms that are significantly enriched  are summarized in Supplementary Data GO-term enrichment of select gene groups or clusters was carried out using the Analysis Tool at https://www.ncbi.nlm.nih.gov/geo) under study accession number GSE66669 and on figshare with the identifier 10.6084/m9.figshare.6200792.v1. The authors declare that all other data supporting the findings of this study are available within the article and its Supplementary Information files, or are available from the authors upon request.DNA microarray data that was generated for this study are available on Gene Expression Omnibus (Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3


Atherosclerosis is a complex inflammatory disease of the vessel wall involving the interplay of multiple cell types including vascular smooth muscle cells, endothelial cells, and macrophages. Large-scale genome-wide association studies (GWAS) and the advancement of next generation sequencing technologies have rapidly expanded the number of long non-coding RNA (lncRNA) transcripts predicted to play critical roles in the pathogenesis of the disease. In this review, we highlight several lncRNAs whose functional role in atherosclerosis is well-documented through traditional biochemical approaches as well as those identified through RNA-sequencing and other high-throughput assays. We describe novel genomics approaches to study both evolutionarily conserved and divergent lncRNA functions and interactions with DNA, RNA, and proteins. We also highlight assays to resolve the complex spatial and temporal regulation of lncRNAs. Finally, we summarize the latest suite of computational tools designed to improve genomic and functional annotation of these transcripts in the human genome. Deep characterization of lncRNAs is fundamental to unravel coronary atherosclerosis and other cardiovascular diseases, as these regulatory molecules represent a new class of potential therapeutic targets and/or diagnostic markers to mitigate both genetic and environmental risk factors. Despite intensive research into the underlying pathogenesis of atherosclerosis/coronary artery disease (CAD), this disease still remains a significant public health burden. Atherosclerosis is a complex disease involving both environmental and genetic risk factors resulting in plaque formation and inflammation in the vessel wall. A number of cellular responses have been proposed to contribute to disease progression, including endothelial cell dysfunction, vascular smooth muscle cell phenotypic switching, macrophage/foam cell activation/necrosis/defective efferocytosis, and defective lipid/lipoprotein metabolism , 2. MuchThe formation of the GENCODE project (part of the ENCODE project) and other large-scale initiatives such as NONCODE have revealed 75% of the genome is transcribed, yet only 2% encodes for protein, suggesting alternative functional roles for ncRNA transcripts . Since tLong non-coding RNAs (lncRNAs) represent a heterogeneous class of non-coding RNAs that includes transcripts >200 nucleotides, which lack functional protein coding ability . Within LncRNAs are a heterogeneous class of ncRNAs (>200 nucleotides in length) that do not contain a functional open reading frame . LncRNAsThe mechanism of action of these regulatory factors were categorized into four broad groups proposed by Wang and Chang . Signalicis in order to regulate transcription of the nearby tumor suppressors, CDKN2A and CDKN2B  to regulate other genes that participate in proatherogenic pathways  is a lncRNA upregulated in carotid plaques, which regulates cholesterol homeostasis in primates in liver and macrophages by inhibiting miRNAs, such as miR-33 . NEAT1 pGenome wide association studies (GWAS) have linked genetic variation at the ANRIL locus 9p21.3) to many complex phenotypes including CAD, stroke, type 2 diabetes and multiple cancers . In addi.3 to manin vivo are needed to elucidate its potential role in atherosclerosis. With larger GWAS sample sizes, and complementary eQTL colocalization , these approaches have largely been replaced with the decreasing costs and greater output achieved by RNA-seq . In genemiR-221 and miR-222. Bell et al. conducted RNA-seq in human coronary artery smooth muscle cells and identified 31 previously unidentified lncRNAs , which is upregulated in rat aortic smooth muscle cells upon stimulation with angiotensin II . Lnc-Ang lncRNAs . Notablyigration . In a foigration . MYOCD iigration –128. Oveigration .cis and PACER activates COX2 expression (NEAT1 (nuclear paraspeckle assembly transcript 1) has recently been implicated in promoting the phenotypic switching of VSMCs . Dozens of lncRNAs with no previous evidence for roles in VSMC differentiation were identified in this analysis that warrant further investigation, either as cis transcriptional regulators or suppressing miRNA function  tail, Michalik et al. performed deep sequencing of poly(A)-selected RNA in human umbilical vein endothelial cells (HUVECs) and found over half of total RNA composed of non-coding RNA, many of which are lncRNAs . This stIn another study Miao et al. conducted RNA-seq profiling of endothelial cells subjected to both physiological and pathological flow for various time points . They idin vivo promotes angiogenesis  and M2 activated (via interleukin 4 stimulation) macrophages . This st in vivo . Other r in vivo . Dnm3os  in vivo .LeXis (liver-expressed LXR-induced sequence) that lies adjacent to the Abca1 gene. LeXis regulates several genes with roles in cholesterol biosynthesis, subsequently altering both liver and plasma cholesterol levels. Mass spectrometry was used to characterize the LeXis interactome and revealed binding to RALY, a ribonucleoprotein that acts a transcriptional cofactor in regulation of cholesterol biosynthetic genes (Liver X receptors (LXRs) are nuclear factor transcription factors that are important mediators of lipid and cholesterol metabolism. LXR targets include the ABC family of transporters, ApoE, LPL, and SREBP , 140. Liic genes . In the ic genes . As discic genes . CHROME ic genes . RNA-seqic genes .−9 m in diameter, where instrumental electric current changes are utilized to decipher the identity of each nucleotide  offer long-read sequencing using single-molecule, real-time (SMRT) sequencing, in which the sequence of a full-length transcript is captured in a single read . Despitecleotide .Since lncRNAs are typically less abundant than protein coding genes , they remain a challenge to study in bulk transcriptomic datasets. To improve the detection and annotation of lncRNAs, a method known as RACE (Rapid Amplification of cDNA Ends)-Seq was developed , howeverDespite their low abundance, lncRNAs are known to function through specific molecular interactions with other RNA species and RNA binding proteins. Several high-throughput methods are now available to uncover the genomic DNA sequences that lncRNAs interact with and likely regulate . ChromatCapture hybridization analysis of RNA targets (CHART) , 155 is in vivo or on cells and reveal the genomic target sites of lncRNAs  is a new unbiased method to capture global RNA-interactions  that can lncRNAs .in vivo . HyperTRIBE extends upon the TRIBE procedure by introducing a hyperactive mutation into the RNA editing enzyme, which improves the RNA editing efficiency and reduces the sequence bias of editing (TRIBE (targets of RNA-binding proteins identified by editing) is designed for identifying RNA molecules that bind to RNA binding proteins (RBP)  167). A. A167).  editing .RNA-centric RNA antisense purification (RAP) is a general approach to identify and study lncRNA functions . This mein situ Hybridization (FISH) has been a traditional method to identify the subcellular localization of RNA within cells, however it lacks sensitivity for lowly expressed lncRNAs. Single-molecule RNA FISH (smFISH) is a quantitative technique that provides the sensitivity to detect these lncRNAs and measures absolute transcript levels by using multiple short probes per target RNA  and precision run-on sequencing (PRO-seq) assays, could enable comprehensive detection of transient RNA transcriptional events for multiple RNA species, including mRNA, lncRNA, and eRNA . While mAnother technique, ICE-seq   represenGenomic annotation of lncRNA sequences requires defining the precise genomic coordinates of lncRNA exons and their respective transcription start sites. LncRNA annotation also involves functional annotation with respect to predicted biological mechanisms, subcellular localization, and affected cell types/tissues. While lncRNAs share some similarities with mRNAs such as transcript length and splicing structure , proper de novo from experimental reads and later aligned to a particular reference genome. Fu et al.  and exhaustive annotation. Compared to these other databases, NONCODE has collected more lncRNA transcripts (excluding tRNAs and rRNAs) and provides unique annotations of lncRNAs  . NONCODEThere are now an array of computational tools to annotate the sequences and functions of the expanding catalog of lncRNAs, as described in Unlike protein functions that can be inferred from protein-coding sequences, it is more difficult to infer lncRNA function from RNA sequences. Zhou et al. developed a tool, lncFunTK that calculates a Functional Information Score (FIS) to quantitatively measure the functional importance of a lncRNA , based oLike other ncRNAs, lncRNA functional annotation also depends on accurate secondary structure prediction. There are several computational tools to predict lncRNA structures such as pysster , RNAfoldThe emergence of RNA-seq and other omics technologies in the past decade have catalyzed the identification of a plethora of novel lncRNAs. To date, more than 30 lncRNAs with functional relevance to CAD have been characterized , yet num−/− or LDLR−/− backgrounds) or zebrafish. However, with the majority of human lncRNAs being poorly conserved across species, they may be better suited to studies in primary human cells or induced pluripotent stem cell (iPSC) derived vascular cells. In the context of CAD and other cardiometabolic disorders, genetic manipulation of lncRNAs via antisense oligonucleotides (For conserved lncRNAs with predicted roles in altering CAD pathogenesis, loss of function studies can be performed in animal models, such as the mouse (ApoEleotides  or CRISPleotides , 223 or leotides , 225. UnAT and CM conceived of the manuscript. AT, DW, MK, CD, MP, and CM wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Here, we demonstrate that DXO also catalyzes the hydrolysis of RNAs bearing a 5′-hydroxyl group (5′-OH RNA). The crystal structure of DXO in complex with a 5′-OH RNA substrate mimic at 2.0 Å resolution provides elegant insight into the molecular mechanism of this activity. More importantly, the structure predicts that DXO first removes a dinucleotide from 5′-OH RNA. Our nuclease assays confirm this prediction and demonstrate that this 5′-hydroxyl dinucleotide hydrolase (HDH) activity for DXO is higher than the subsequent 5′-3′ exoribonuclease activity for selected substrates. Fission yeast Rai1 also has HDH activity although it does not have 5′-3′ exonuclease activity, and the Rat1-Rai1 complex can completely degrade 5′-OH RNA. An Arabidopsis DXO1 variant is active toward 5′-OH RNA but prefers 5′-PO4 RNA. Collectively, these studies demonstrate the diverse activities of DXO/Rai1 and expands the collection of RNA substrates that can undergo 5′-3′ mediated decay.Modifications at the 5′-end of RNAs play a pivotal role in determining their fate. In eukaryotes, the DXO/Rai1 family of enzymes removes numerous 5′-end RNA modifications, thereby regulating RNA turnover. Mouse DXO catalyzes the elimination of incomplete 5′-end caps (including pyrophosphate) and the non-canonical NAD N7-methylguanosine (m7G) cap  RNAs for rapid decay by the cytoplasmic processive 5′-3′ exoribonuclease Xrn1  cap . The m7Gng m7GDP . As a rease Xrn1 ,11.7G capping does not always proceed to completion and a 5′-end capping quality surveillance mechanism exists in the nucleus to remove the incompletely-capped RNAs. This surveillance pathway is mediated by the DXO/Rai1 family of decapping enzymes (7G caps was first demonstrated with Schizosaccharomyces pombe Rai1 (SpRai1), which possesses RNA 5′ pyrophosphohydrolase (PPH) activity (hydrolyzing 5′ triphosphate RNA (pppRNA) to generate pyrophosphate and 5′-PO4 RNA)   and non-PO4 RNA) . Rai1 foPO4 RNA) ,17, whicPO4 RNA) , includiPO4 RNA)  and mammPO4 RNA) .4 RNA and can completely degrade RNA independent of Rat1/Xrn1 exoribonucleases  activity instead of PPH activity . Additioucleases ,15,18. Cana DXO1 .Structural studies showed that DXO/Rai1 enzymes share a common fold and utilize the same catalytic machinery to perform their various activities ,15,18,20+) capped RNAs  , demonstrated that the same active site is used to perform the deNADding reaction and that this active site can accommodate the entire NAD+ cap  . The cryNAD+ cap .4 group of the substrate is specifically recognized in the active site of DXO for its exonuclease activity  activity by biochemical studies. Finally, we demonstrate that both SpRai1 and Arabidopsis DXO1(ΔN194) have HDH activity, and that the yeast Rat1–Rai1 complex is capable of robust 5′-OH exoribonuclease activity due to removal of the 5′-OH end by Rai1 followed by processive decay by Rat1.The recent identification of additional DXO targets engenders the notion that DXO may regulate RNAs with other, less thoroughly studied 5′ ends. While the 5′-POactivity , here weEscherichia coli BL21 (DE3) Rosetta cells. His-tagged DXO and SpRai1 proteins were produced and purified as previously reported (Full-length mouse DXO or SpRai1 in pET28a was used to transform reported . BrieflyE. coli BL21 (DE3) Rosetta cells. After induction with 0.3 mM IPTG and growth at 18°C for 18 h, cells producing Rat1 were lysed and sonicated with or without cells producing Rai1 to generate Rat1 protein alone or Rat1–Rai1 complex respectively  and Rai1 in pET26b (producing Rai1 with no affinity tag) were separately used to transform ectively . Rat1/Ra°C with a reservoir solution containing 21–26% (w/v) PEG 3350 (2 for 1 h followed by soaking in 10 mM 5′-OH U(S)6 (in a fresh drop) for an additional hour at 20°C in buffer containing 25% (w/v) PEG 3350. Soaked DXO crystals were cryo-protected with 25% (w/v) PEG 3350 and 25% (v/v) ethylene glycol before being flash frozen in liquid nitrogen for diffraction analysis and data collection at 100 K.DXO crystals were obtained using the hanging-drop vapor diffusion method at 20PEG 3350 . To geneP21 with 1 molecule in the asymmetric unit. The structure refinement was performed using PHENIX (X-ray diffraction data were collected at the Advanced Photon Source (APS) beamline 24-ID-E. The wavelength used was 0.97918 Å. The crystal to detector distance was 250 mm, and each image covered 0.25° rotation of the crystal. The diffraction images were recorded on a Dectris Eiger 16M detector, processed and scaled with standard parameters using the XDS program . Reflectg PHENIX  and manug PHENIX . Rebuild2) is higher than that for the protein  polyacrylamide electrophoresis (PAGE) gel in 1× Tris/Borate/EDTA (TBE) buffer and visualized on a Typhoon FLA 7000 .Exoribonuclease assays were performed at 37°C for the indicated time periods with reaction mixtures containing 30 mM Tris (pH 8.0) (or pH 6.0–9.0 with appropriate buffers as indicated), 50 mM NH5′-end hydrolysis assays. RNA substrate (60 nt: P-AGTCCTCTCTCTCTCCTCTCTCTCCTCTTCCTTCTCTTCCTTCTCCTCTCCTCTTCCTTC) was designed with a T7 ϕ2.5 promoter and a single G nucleotide at the second position to enable the discrimination between mononucleotide and dinucleotide released from the RNA 5′ ends. Radioactively labeled RNA was obtained by in vitro transcription with T7 RNA polymerase in the presence of [α-32P]GTP  and AMP (Sigma) to generate pRNA that was further treated with alkaline phosphatase FastAP (Thermo Fisher) for 2 h at 37°C to produce OH-RNA. Reactions were carried out in buffer containing 10 mM Tris (pH 7.5), 50 mM KOAc, 2 mM Mg(OAc)2, 2 mM MnCl2, 1 mM DTT, 0.1 mM spermine, 20 U RiboLock RNase inhibitor, 20 cps of radiolabeled RNA and indicated amount of recombinant protein. Reactions were stopped with 0.05 M EDTA and resolved on polyethyleneimine-cellulose TLC plates in 0.7 M KH2PO4 (pH 4.5). Plates were analyzed with PhosphorImager Typhoon FLA 9000.4 RNAs, and this 5′-PO4 group is recognized by interactions with Arg132 (conserved motif I) and Gln280 (conserved motif V)  label  . Surprisn) label . As expey Figure . DXO alsA Figure . DXO’s pA Figure . For bote Figure . More imA Figure . As a coA Figure , consist4 or a 5′-OH group. In order to more clearly distinguish the products, we used a shorter 5′-OH RNA (25 nucleotides) than 5′-PO4 RNA (30 nucleotides). The level of the intact 5′-OH RNA decreased faster than intact 5′-PO4 RNA, demonstrating that, depending on the composition, RNA with a 5′-OH can be the preferred substrate for DXO at similar RNA concentrations 6,  revealed that the RNA body is accommodated in a positively charged pocket. The active site is located near the bottom of this pocket, where divalent cations bind to position the RNA scissile phosphate (between the first and second nucleotide) for nucleophilic attack.We previously illuminated the mechanism of DXO 5′-3′ exoribonuclease activity toward 5′-POleotides . The cry4 group. As we demonstrated with another RNA, 5′-PO4 RNA treated in this way was successfully degraded by DXO but not by Xrn2 6 RNA and with calcium as the divalent cation to further block hydrolysis. The structure was determined at 2.0 Å resolution and has excellent agreement with the X-ray diffraction data and the expected bond lengths, bond angles and other geometric parameters 6. OH-U(S)6 was generated by incubating pU(S)6 with calf intestinal alkaline phosphatase (CIP) to remove the 5′-PO2 Figure , confirmrs Table .4 group during the CIP treatment 6 RNA Figure  and a cat Figure . We weret Figure , which a0, U(S)1, U(S)2, and U3, so that the scissile phosphate is located between U1 and U2  Figure , and thi Figures , D.0 base has π stacking interactions with the mostly conserved Trp131 side chain, and it also makes three hydrogen-bonding contacts: to the backbone carbonyl of Arg102 and the side chain of His105 directly and to the backbone amide of His105 through a water molecule 6 and pU(S)6 1 base in the pU(S)6 structure would clash with the 5′-OH of the OH-U(S)6 RNA 6 RNA, while it is anti in pU(S)6. In comparison, the conformation of the U2 and U3 nucleotides in OH-U(S)6 RNA is nearly the same as that in pU(S)6.The overall structure of DXO in the OH-U(S)6 complex is essentially the same as that of the pU(S)6 complex, with rms distance of 0.3 Å for 358 equivalent Cα atoms between the two structures. The conformation of most of the side chains in the active site region is similar between the two structures as well Figure . However6 Figure . The posA Figure . In addi0 nucleotide is accommodated deeper within the DXO active site  to separate the reaction products. Consistent with our crystal structure and gel based assays, DXO released a 5′-OH dinucleotide from 5′-OH RNA but single nucleotides from 5′-PO4 RNA  variant, which lacks the N-terminal 194 plant-specific amino acids, has PPH activity (4 or 5′-OH. DXO1(ΔN194) was also able to hydrolyze 5′-OH RNA, but, in contrast to mouse DXO, it had a reduced activity toward this substrate and showed a preference for 5′-PO4 RNA  as a common product  cannot be degraded . Our assays here indicate that activity toward 5′-OH RNA appears to be strongly sequence-dependent and in substrates lacking G at their 5′ ends the 5′-OH RNA is preferentially digested in comparison to the 5′-PO4 RNA. The decreased activity toward RNA with 5′ Gs may explain why DXO was previously reported to be inactive toward 5′-OH RNA (4 GG dinucleotide.DXO activity toward 5′-OH RNA was previously tested but the enzyme was found to be inactive . This di′-OH RNA . On the 4 RNA. The differing activities of DXO homologs toward these RNAs further demonstrate the diversity of activities within the DXO/Rai1 enzyme family and suggest that the extent of degradation of 5′-OH RNAs in vivo may vary depending on the organism. At least in S. pombe, the HDH activity of SpRai1 licenses the Rat1–Rai1 complex the ability to completely degrade 5′-OH RNA, which is a novel activity for Rat1–Rai1 and could lead to uncovering new functions for this complex.We demonstrate that SpRai1 and AtDXO1 can also degrade 5′-OH RNA, thereby extending the HDH activity to other DXO homologs. Similar to DXO, SpRai1 has a strong preference for 5′-OH RNA, although AtDXO1 prefers 5′-POgkz1107_Supplemental_FileClick here for additional data file.


This database includes a comprehensive collection of A-to-I editing sites in six filamentous fungal species, together with extensive annotations for each editing site. In FairBase, users can conveniently search editing sites and obtain editing levels for each editing site in various RNA-seq samples. In addition, the pathways involving RNA editing are built in FairBase to help users understand the functions of RNA editing. Furthermore, each fungal species has a genome browser (JBrowse) that allows users to explore A-to-I editing in a genomic context. FairBase is the first fungal RNA editing database.Frequent A-to-I RNA editing has recently been identified in fungi despite the absence of recognizable homologues of metazoan ADARs (“Adenosine Deaminases Acting on RNA”). In particular, there is emerging evidence showing that A-to-I editing is involved in sexual reproduction of filamentous fungi. Here, we report on the creation of FairBase — a  RNA editing is a class of co−/post-transcriptional modification that can alter hereditary information in the genome by changing the nucleotide sequence of RNA molecules . A-to-I Ganoderma lucidum . REDItool was used to call RNA variants present in at least five reads with a minimum frequency of 3% and minimum coverage of 10 reads  data from RNA-seq strains were aligned to reference genomes to add genomic support for the exclusion of SNPs at the transcript level  GenThe editing detail page contains two sections of information for an editing site including annotation of editing site and editing levels in RNA-seq samples . In the When users submit a query in the browse page or click the JBrowse icon in the retrieval results table, the genome browser JBrowse opens for users to view editing sites in the genomic context . In addiMany studies have shown the A-to-I RNA editing is involved in various biological processes in animals, while we have very little knowledge about fungal A-to-I RNA editing. To help understand A-to-I RNA editing in fungi, we developed the FairBase database to collect fungal A-to-I RNA editing sites and provide retrieval functions. In FairBase, GO/Pfam functional annotations of edited genes are used to help users quickly lock up editing sites of interest in function-related edited genes. In addition, FairBase provides the BLAST search function, which not only enables the retrieval of editing sites through sequence similarity, but also contributes to the cross-species functional verification between edited genes in FairBase and out of FairBase. Furthermore, KEGG pathways and JBrowse genome browser are built in FairBase for users to explore editing sites in a pathway and genome context. Compared with several animal RNA editing databases , FairBasIt is challenging work to identify RNA editing sites from public available data, because many factors, such as sequencing errors, SNPs among different strains, and other problems can affect the reliability of results. Thus the strict strategies were used in this study. For example, only RNA-seq samples with at least 70% mapped reads can be used for identification of RNA editing events. In addition, in view of the fact that noncanonical RNA edits are found to be false-positives , 36 and Supplementary DataClick here for additional data file.


AZIN1) RNA is emerging as a key epigenetic alteration underlying cancer pathogenesis.Adenosine-to-inosine (A-to-I) RNA editing is catalyzed by adenosine deaminases acting on RNA (ADAR) enzymes. Recent evidence suggests that RNA editing of antizyme inhibitor 1  patients.We evaluated AZIN1 RNA editing levels and ADAR1 expression were significantly elevated in GC tissues compared with matched normal mucosa ; and AZIN1 RNA editing was positively correlated with ADAR1 expression. Elevated expression of ADAR1 significantly correlated with poor overall survival (P = 0.034), while hyper-edited AZIN1 emerged as an independent prognostic factor for OS and disease-free survival in GC patients . Increased AZIN1 RNA editing and ADAR1 over-expression were significantly correlated with key clinicopathological factors, such as advanced T stage, presence of lymph node metastasis, distant metastasis, and higher TNM stages in GC patients. Logistic regression analysis revealed that hyper-editing status of AZIN1 RNA was an independent risk factor for lymph node metastasis in GC patients . Conclusions: AZIN1 RNA editing levels may be an important prognostic biomarker in GC patients, and may serve as a key clinical decision-making tool for determining preoperative treatment strategies in GC patients.Both The online version of this article (10.1186/s12967-018-1740-z) contains supplementary material, which is available to authorized users. RNA editing refers to the post-transcriptional epigenetic modification of RNA sequences through insertion, deletion, or nucleotide conversion, resulting in an increased diversity of the transcriptomic repertoire. Adenosine-to-inosine (A-to-I) RNA editing is primarily mediated by adenosine deaminase acting on RNA (ADAR) enzymes, and is the predominant form of RNA editing in humans . It invoAZIN1 RNA was specifically enhanced in HCC tissues, and significantly correlated with disease progression in HCC patients. AZIN1 belongs to the antizyme inhibitor family, and plays a role in maintaining polyamine homeostasis which are important for various cellular functions, including cell growth [AZIN1 RNA editing permitted unimpeded tumor growth and proliferation [AZIN1 confers a gain-of-function phenotype frequently through A-to-I conversions via ADAR1, which can promote ornithine decarboxylase (ODC) and polyamines accumulation—conditions that are associated with aggressive tumors [Chen and colleagues performed the first systematic and comprehensive analysis using a sequencing-based approach , and deml growth , 8. Thisferation . Recentle tumors , 9.The incidence of gastric cancer (GC) in developed countries has fallen significantly, however, this malignancy remains the fourth most common cancer and the second leading cause of cancer-related deaths worldwide . ApproxiCurrently, several well-known antigens, including carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9) and cancer antigen 72-4 (CA72-4), or serological biopsy using Pepsinogen I and II have been investigated in the context of GC , 12. AltAZIN1) and the expression pattern of its regulatory protein, ADAR1, in the primary tumor tissues and matched normal mucosa from patients with gastric cancer, with an emphasis to gain insights into the clinical significance of these events in this malignancy.Work from our group and others have previously identified several epigenetic alterations that could serve as biomarkers for diagnosis, prognosis, and metastasis prediction in patients with various gastrointestinal cancers –16. MoreRNAlater following surgical resection  and stored at − 80 °C until RNA extraction. Written informed consent was obtained from each patient, and the study was approved by the institutional review boards of all institutions.This study included analysis if 280 gastric tissues obtained from 140 patients (110 men and 30 women) who underwent surgery for GC at the Mie University Hospital, Japan, from 2000 to 2009. The study included patients from whom matched tumor and normal mucosa tissues were available for analysis. The mean patient age was 66.8 years range 18–90 years). No patient received chemotherapy or radiotherapy prior to surgery and no perioperative mortality was observed. The diagnosis of GC was confirmed in all 140 patients based on clinicopathological findings. All patients were classified according to the Japanese Classification of Gastric Carcinoma [–90 yearsRNAlater-preserved surgical specimens were homogenized with a Mixer Mill MM300 homogenizer (Qiagen). Total RNA from tissues was isolated using RNeasy Mini kits (Qiagen) according to the manufacturer’s instructions. cDNA was synthesized from 1.0 µg total RNA using an Advantage RT PCR-kit .AZIN1 was analyzed by RNA editing site-specific quantitative PCR developed by Crews and colleagues [AZIN1  [AZIN1 edited/wild-type ratio was calculated based on the differences in Ct values in a SYBR Green-based real-time PCR assay, using the formula 2-(Ct edit − Ct wild-type). Primer sequences for these reactions are shown in Additional file RNA editing of lleagues . In brieon:Exon) , 21 wereQuantitative reverse transcription PCR analysis was performed using the StepOne Real Time PCR System . ADAR1 and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) mRNA expression levels were measured using Power SYBR Green Master Mix (Applied Biosystems). Sequence information on these primers is provided in Additional file 2 text, Mann-Whitney test, and one-way ANOVA, as appropriate. F-tests or Levene tests were used to assess the equality of variance for comparable groups. For time-to-event analyses, survival estimates were calculated by Kaplan–Meier analysis and groups were compared using log-rank tests. Receiver operating characteristic curves were established to determine the cut-off values for analyzing each aim of prognosis by Youden’s index. Overall survival was measured from the date the patient underwent surgery until the date of death resulting from any cause, or until the last known follow-up in patients that were still alive. In the entire GC population cohort we analyzed, the highest sensitivity and specificity thresholds for determining OS were found using a peak AZIN1 RNA editing levels and ADAR1 expression cut-off point of 0.057 and 0.062, respectively. Disease-free survival was measured from the date the patient underwent curative surgery to the date of disease recurrence, death from any cause , or until last contact with the patient. In the curatively resected GC population, the highest sensitivity and specificity for DFS was determined using a peak AZIN1 RNA editing levels and ADAR1 expression cut-off point of 0.096 and 0.062, respectively. Cox proportional hazards models were used to estimate hazard ratios for death or recurrence. Assumption of proportionality was confirmed for Cox proportional hazards analyses by generating Kaplan–Meier survival curves  and by ensuring that the two curves did not intersect. Multivariate logistic regression models were used to predict factors influencing lymph node metastasis. Forced-entry regression was used to include these variables in all multivariate equations to determine if any of the predictors affected the outcome after adjusting for known confounders. All P values were two-sided, and P < 0.05 was considered statistically significant.Results were expressed as mean ± standard deviation, and all statistical analyses were performed using Medcalc version 16.4.3 . Differences between groups were analyzed by χAZIN1 RNA editing levels and expression of its regulatory enzyme ADAR1 to assess their expression patterns in GC tissues. Profiling analysis revealed that AZIN1 RNA editing levels were significantly elevated in GC tissues compared with matched normal mucosa  0.69–0.8) and 0.66 (95% CI 0.6–0.72), respectively .We first analyzed AZIN1 RNA editing levels and ADAR1 expression with various clinicopathological factors to determine the clinical significance of our findings in GC patients , presence of lymph node metastasis , and higher TNM stages (P = 0.028) in GC patients. Furthermore, over-expression of ADAR1 was also significantly associated with presence of LNM (P = 0.029), distant metastasis (P = 0.006), and more advanced TNM stages (P = 0.004) in these patients  and disease-free survival (DFS) in GC patients. We determined survival cut-off thresholds for each candidate derived from the ROC curve analyses with Youden’s index. Interestingly, both AZIN1 RNA hyper-editing status and overexpression of ADAR1 were significantly correlated with poor OS  emerged as independent prognostic factors for DFS in GC patients , with significant associations between AZIN1 editing and poor disease free survival (DFS). Fifth, multivariate Cox regression analysis revealed that increased AZIN1 editing emerged as an independent prognostic factor for both OS and DFS in GC patients. Finally, our data revealed that higher levels of AZIN1 RNA editing were an independent risk factor for lymph node metastasis (LNM) in patients with GC, highlighting its biomarker potential in the identification of high-risk patients that may experience tumor recurrence post-surgical treatments.Emerging evidence indicates that epigenetic alterations encompassing RNA editing may play a central role in post-transcriptional gene regulation, and might control the expression of various cancer-related genes. However, the role of RNA-editing and the expression patterns of its regulatory enzymes, as well as their clinical significance in patients with gastric cancer (GC) remains unclear. Our study provides first evidence supporting a potential clinical impact of dysregulated RNA editing and its regulatory enzymes in GC. First, we observed that AZIN1 RNA was specifically enhanced in HCC tissues, and that significantly correlated with disease progression in HCC patients. This group recently expanded their research to other cancers within the upper gastrointestinal tract, and successfully demonstrated that reciprocal changes in ADAR1 and ADAR2 coordinated cancer pathogenesis via hypo-editing of the podocalyxin-like protein 1 gene (PODXL) [AZIN1 RNA editing and expression pattern of ADAR1 in GC patients remains unclear; which was the very basis of undertaking the present study. A key finding of our current study was our observation for the increased RNA editing levels of AZIN1, as well as dysregulated expression of its regulatory enzyme, ADAR1, in GC tissues vis-à-vis normal gastric mucosa. To date, overexpression of ADAR1 and increased AZIN1 RNA editing in cancer tissues has been demonstrated in various other types of cancers, including HCC, non-small-cell lung [AZIN1 RNA editing is an important phenomenon in this malignancy as well. Furthermore, enhanced AZIN1 RNA editing and over-expression of ADAR1, significantly correlated with poor OS and AZIN1 RNA editing also significantly correlated with poor DFS. Hyper-edited levels of AZIN1 RNA were an independent prognostic factor for both OS and DFS in GC patients. Taken together, our data for the first time, suggest that measurement of AZIN1 RNA editing status could be a promising prognostic biomarker for tumor recurrence and survival in patients with GC.Cancer cells acquire specific characteristics, including escape of cell cycle checkpoint controls, continuous proliferation, invasion, and metastasis. Over the past decades, data suggest that alterations in DNA sequences of the key tumor suppressors and oncogenes may influence the progression of tumorigenesis through functional control of the proteins encoded by these genes . Althoug (PODXL) . Howeverell lung , esophagell lung , and colell lung . In lineAZIN1 RNA editing levels and lymph node metastasis in GC patients. The presence of regional LNM mainly affects disease recurrence and prognosis in GC patients following curative resection. While recent neoadjuvant therapies may offer treatment options for GC patients with LNM [AZIN1 RNA in primary tumor tissues significantly correlated with the presence of LNM, while logistic regression analysis identified it to be an independent risk factor for identifying LNM in GC patients. These findings suggest that the assessment of AZIN1 RNA editing levels in pre-surgical biopsy specimens might potentially help in the identification of high-risk GC patients with lymph node metastasis.Our study also demonstrated an intimate correlation between with LNM , 33, andwith LNM , neitherAZIN1 as a most representative RNA editing site in this study, and emerging evidence suggests that there may be potentially other oncogenic RNA editing sites in other genes, which remain an area of active investigation. Therefore, further studies including a broader, unbiased comprehensive analysis may potentially identify additional RNA editing-based markers to assess the risk for oncological outcomes with a higher sensitivity and specificity in GC patients in future. Second, although we have successfully demonstrated our novel findings using a relative-large cohort GC specimens, our cohort was still somewhat smaller, retrospective in nature, and lacked an external independent validation cohort GC specimens. In addition, the clinical materials analyzed in this study were solely from Asian patients, and analytical method for AZIN1 RNA editing level maybe influenced by several cofounding factors. To overcome these hurdles, larger prospective, multi-institutional studies using same analytical method may be needed to further clarify the prognostic potential of AZIN1 RNA editing and ADAR1 expression for GC patients.We would like to acknowledge several potential limitations of our study. First, we focused on AZIN1 RNA editing and altered expression of its regulatory enzyme ADAR1 in GC. These findings highlight the overarching importance of even small changes in ADAR regulatory cascade, and suggest that AZIN1 RNA editing may serve as a potential prognostic biomarker in GC patients, and may assist in clinical decision-making for deciding pre-operative treatment strategies in GC patients, as we usher into the era of precision medicine for cancer patients.In conclusion, this study provides first evidence for the clinical significance of dysregulated Additional file 1: Table S1. Primers used for quantitative real time PCR analysis.