Adenosine deaminase acting on RNA 1 (ADAR1) is the master RNA editor, catalyzing the deamination of adenosine to inosine. RNA editing is vital for preventing abnormal activation of cytosolic nucleic acid sensing pathways by self-double-stranded RNAs. Here we determine, by parallel analysis of RNA secondary structure sequencing (PARS-seq), the global RNA secondary structure changes in ADAR1 deficient cells. Surprisingly, ADAR1 silencing resulted in a lower global double-stranded to single-stranded RNA ratio, suggesting that A-to-I editing can stabilize a large subset of imperfect RNA duplexes. The duplexes destabilized by editing are composed of vastly complementary inverted Alus found in untranslated regions of genes performing vital biological processes, including housekeeping functions and type-I interferon responses. They are predominantly cytoplasmic and generally demonstrate higher ribosomal occupancy. Our findings imply that the editing effect on RNA secondary structure is context dependent and underline the intricate regulatory role of ADAR1 on global RNA secondary structure. Adenosine deaminase acting on RNA 1 (ADAR1) edits adenosine to inosine. Here the authors, using parallel analysis of RNA secondary structure sequencing, provide evidence that ADAR1 induces sequence-context-dependent RNA secondary structures changes, often leading to stabilization of the RNA duplex. This modification is catalyzed by the ADAR (adenosine deaminases acting on RNA) protein family. Most editing events are mediated by ADAR1 (gene symbol—ADAR) with two distinct protein isoforms p110 and p150. Double-stranded RNA (dsRNA), often formed between adjacent inverted repetitive (IR) elements, is the obligatory substrate of ADAR. Thus, a large fraction of editing sites occurs in Alu retroelements, interspersed within non-coding regions of mRNA transcripts including introns and untranslated regions (UTRs). The high abundance of the primate-specific Alu retroelements in the human genome, is a major cause of most of the RNA-editing activity in the human transcriptome7. There are millions of editing sites in non-coding regions and although many are edited at only a tiny fraction of the transcripts, there are still thousands of sites where the editing level is significant8, suggesting a functional role.Deamination of adenosine to inosine, A-to-I RNA editing10 apparently due to abnormal induction of a type-I interferon response. In hematopoietic stem cells, loss of ADAR1 led to global up regulation of interferon-stimulated genes and apoptosis11. ADAR1 is also vital for post-natal hepatic development and homeostasis, with hepatocyte-specific depletion of ADAR1 leads to liver inflammation and necrosis13. Likewise, ADAR1 is vital for B lineage development14.ADAR1 is required for normal fetal development. Knocked out mice die at an early embryonic stage (day 11.5) with defects in hematopoiesis and liver disintegration15. An essential role of A-to-I RNA editing is inhibition of the immune response to perfect self-dsRNA by editing such regions.19. Indeed, bi-allelic mutations in ADAR1 were documented to cause Aicardi–Goutieres syndrome, an inflammatory genetic syndrome associated with toxic perturbation of the type-I interferon response (“interferonopathy”)20. Recent studies directly connect the severe phenotypes of ADAR1 deficiency to its mRNA editing activity21. ADAR1 is assumed to prevent activation of relevant cytosolic sensors of nucleic acids (mainly MDA5) by RNA duplexes dispersed in the human transcriptome.dsRNA is a major inducer of anti-viral type-I interferon response via activation of cytosolic nucleic acid sensing pathways22. This may change the stability of the RNA duplex, affect structural determinants recognized by trans-acting factors and can change accessibility of factors to defined regions25. As even a single-nucleotide variant may affect RNA structure28, RNA editing may well affect the transcriptome secondary structure landscape. Furthermore, A-to-I editing events frequently occur in clusters (hyper-edited regions), and such regions may undergo major structural alterations. Indeed, early pioneering studies demonstrated an unwinding activity for ADAR enzymes30.Editing may regulate RNA abundance and fate by changing the local structureDespite the accumulating evidence regarding the regulation of transcript structures by ADAR1 and the role of this regulation in health and disease, no study investigated the structural changes induced by ADAR using an experimental global approach.32. Using such approaches, the global yeast, thale cress, fruit fly, nematode and human transcriptome 2D structures, were mapped35. Methods that are based on chemical probing36, more suitable for in vivo studies, were also developed and applied40.Recently, new methodologies were developed for experimental identification of RNA 2D structure in a transcriptome wide manner using next generation sequencing (NGS). Some are based on probing with single-strand (SS) and double-strand (DS) specific nucleasesHere, we report the use of high-throughput probing techniques to directly examine, the effect of ADAR1 deficiency and A-to-I editing on the whole transcriptome 2D structure and relate the data to the regulation of the cytosolic innate immune response. We show that in human cells, hundreds of transcripts undergo ADAR1 editing-dependent structural changes. In contrast to the prevailing paradigm that ADAR1 activity decreases RNA duplex stability, we find that A-to-I editing may increase the stability of RNA duplexes and that the effect on the global RNA structure is context dependent. The smaller subset of genes whose transcripts are destabilized upon editing, as previously postulated, are significantly enriched for housekeeping genes and genes linked to the anti-viral interferon response. These transcripts tend to be localized in the cytoplasm, and are relevant to the involvement of ADAR1 in dampening innate immune response.32 as detailed in the Methods section. Purified poly-A + RNA samples from control HepG2 cells and ADAR knockdown (KD) HepG2 cells were extracted and in vitro probed with S1 nuclease (S1) and RNAse V1 (V1) that preferentially cleave RNA at SS and DS regions, respectively . We show that the mean PARS score is higher in known DS bases compared to known SS bases . We also verified that calculated PARS scores from a previous study of lymphoblastoid cells transcriptome27 significantly correlate with our scores (Spearman’s R = 0.6), indicating that the PARS-seq approach we utilize reliably captures the global structural features of native long RNA molecules in different cell types. The V1 profiles obtained are significantly different from the S1 profiles in all the samples while the profiles of replicates are nicely correlated  was detected for excess of V1 reads (DS) within Alu retroelements . Indeed, non-accessible (buried) bases were found to have, on average, lower read coverage in both V1 and S1 libraries  were found to be edited in at least one PARS-seq sample. As expected, significant global decrease in RNA-editing level was observed in ADAR1 deficient cells . Moreover, editing sites located in IR Alus in 3′UTR of genes, which are predominantly ADAR1 targets, showed reduction of about 70% in editing level . To further identify sequence reads that are edited at many positions and could not be mapped by standard NGS alignment tools that were used to detect the known 131,086 editing sites, we also applied de novo detection of hyper-edited sites as described in Porath et al.43 Both numbers and levels of editing sites were reduced also in this set in the ADAR1 deficient cells  and scrambled siRNA to generate ADAR1 knockdown (KD) and control cells, respectively (Methods). quantitative reverse transcription (qRT)-PCR and western-blotting , as demonstrated by under-representation of G at (−1) to the editing site . 508 of the sites also passed false discovery rate (FDR) filter (q < 0.1) in the S1 samples or in the V1 samples. These differentially edited sites (DES) are likely specific targets of ADAR1 (Supplementary Data We identified 5644 RNA-editing sites which have significantly lower editing level in ADAR1 KD than in control cells (ADARB1) was increased by ~2.2 fold in ADAR1 KD cells (FDR < 0.05 in both V1 and S1 samples), in line with the previous demonstration of a reciprocal compensatory change in abundance/activity between ADAR2 and ADAR144. Editing sites that demonstrate lower editing level in KD samples are therefore most likely ADAR1 substrates  as an objective score for this analysis and filtered the data to retain only those transcripts with CorDiff > 0 in both V1 and S1 samples, that conform with a random shuffling test to avoid low sampling bias (Methods). 3196 RefSeq transcripts with secondary structure changes (SSC) had CorDiff > 0 in both V1 and S1. In total, 2155 of these transcripts have original CorDiff that is higher than 95% of the random trials  fraction of SSC exons in single isoform genes compared to non-SSC exons . Illustrative example for such cases, reflecting changes in mRNA folding are shown in Fig. 51; this strong duplex was recently used as ADAR “sponge”52, Moreover, the association between PSMB2 3′UTR and ADAR is also supported by the ADAR Clip-seq data we analyzed .We examined not only the minimum free energy structures but also the structural ensembles predicted using constraints taken from the PARS-seq of control and KD samples. The structural ensembles of IR Alus in F11R and PSMB2 differ significantly between control and KD cells with the KD samples showing fewer DS bases  around edited bases (in regions up to 50 bases upstream to the edited adenosine) and the structural profiles of their non-edited version revealed apparent differences in the local 2D structure Fig. . This paMoreover, when comparing the relative PARS score upstream to the editing site between edited and non-edited reads, different patterns were inferred Fig. . Edited p < 0.001). BPNT1 3′UTR was also found to be SSC when comparing KD to control samples. Fig. p = 0.001) for PAICS 3′UTR in window  centered at the editing site in chr4:57326262/hg19. PAICS 3′UTR, which is also hyper-edited, was shown to be involved in nuclear retention54.Some genes show apparent differences in structural profiles in the vicinity of editing sites (50 bases upstream to the edited adenosine) between edited molecules and non-edited molecules (Supplementary Data 53. Pars2spp identifies confident paired (DS) or unpaired (SS) bases in each transcript according to statistical testing of the enrichment of V1 counts and S1 counts, respectively. Using these classifications, we calculated a gene-wise ratio of DS/(DS + SS), and compared it between control and ADAR KD samples. This ratio is found to be significantly lower in the KD samples (Wilcoxon’s test p < 10−15), namely, the number of confident base pairs identified has been decreased .To check how ADAR silencing affects the number of paired (DS) bases, 4021 long and highly expressed transcripts (longer than 100 bases and covered by more than 256 read starts) were subjected to Seqfold pars2spp analysis  is a pseudo-pairing between A and C (A:C) such that deamination of A-to-I, and therefore the formation of I:C pairing, increases RNA stability. We previously3 noted that the number of edited A:C pairing (the formation of I:C pairing) is significantly larger than expected by chance, even though in absolute terms most RNA-editing events target A:U pairing. In the current data the number of A:C pairing is also significantly larger than expected by chance . As depicted schematically in Fig. 57 . Taken together with the above results, we suggest that globally, KD transcripts, which have less defined 2D structures, form a more globular (and less solvent accessible) 3D structure.We next examined if the relative number of buried bases (associated with low digestion frequency by both V1 and S1) differs between control and KD samples. Interestingly, transcripts in the KD samples tend to contain relatively more buried bases than transcripts in the control state (Supplementary Table We further divided the genes into two sets: 1. Genes with higher DS/(DS + SS) ratio in control cells than KD cells, with presumably a stabilizing editing effect, termed “stabilized while edited”  with the gene set of long (>50 bases) hyper-edited duplexes, computed in accordance with the pipeline of Porath et al.43 Further analysis of the DSWE gene set revealed a significantly lower free energy of confident IR Alu folding in 3′UTRs (Supplementary Table We found that the DSWE gene set was significantly enriched for Alu repeats and editing sites over the SWE gene set Table . The DSWq < 0.05) included housekeeping genes and gene sets involved in a variety of vital biological and metabolic processes, such as protein and RNA biosynthesis. Importantly, enrichment for genes involved in the innate immune response to LPS and type-I interferon response were also detected. Analyses using clusterProfiler  and GOrilla showed similar functional enrichment signatures.To identify the enriched biological processes and molecular functions within the DSWE gene set, we applied Gene Set Enrichment Analysis (GSEA) Fig. . Relevan16 demonstrated that mouse Adar has an important role in destabilizing dsRNA duplexes formed within a very limited number of mRNA 3′UTRs, by folding of complementary inverted sequences, preventing over-activation of the MDA5-dependent interferon response in the mouse. The enrichment for interferon response genes in the DSWE set hints to a similar mechanism in humans. Interestingly, KEGG pathways analyses revealed that genes involved in systemic lupus erythematosus (SLE) are also enriched. While this result should be cautiously interpreted, as most SLE-related genes in our list are histone genes, over-activation of type-I interferon pathway was observed in both SLE and in AGS20. Many symptoms are shared between these pathologies20. Our results are also in agreement with the results of Vitali et al.58 which found that I:U pairs (which characterize the DSWE genes set) suppress the MDA5-dependent interferon response, while I:C pairs that stabilize the RNA duplex induce the interferon response.Liddicoat et al. recentlyp < 10−15) compared to SWE genes  was also obtained by computing relevant GNF microarray data derived from several different tissue types  in control and ADAR1 KD HepG2 cells (Methods section). Genes with SSC in their 3′UTR were found to be enriched for differences between Ribo-seq fold-change (FC) and RNA-seq FC , with DSWE genes consistently showing higher signals. More careful inspection of DSWE and SWE translation profile reveals that DSWE are frequently upregulated in the KD samples , suggesting that KD of ADAR and reduction of RNA editing may contribute to DSWE mRNA stability and increase DSWE gene translation.We found that DSWE are highly translated compared to SWE Fig. , in agreOur experimental data provide insight into the SSC induced by ADAR1 on dsRNA in the entire transcriptome of human cells. We demonstrated that the abundant SSC induced by ADAR1 silencing overlap with A-to-I editing sites in relevant transcripts, implying a direct role for editing in shaping mRNA structure. Yet, it is theoretically possible that some SSC resulted from an indirect editing-independent regulatory function of ADAR1.30. However, our results, rather unexpectedly, show that the effect of editing on the entire transcriptome is to increase the DS/SS ratio. Thus, our data support a modified paradigm whereby RNA editing can enhance or reduce proper intramolecular base pairing in a context-dependent manner. An explanation for the arguably contradicting observations is that in long perfect dsRNA structures, by definition, there are no A:C mismatches, and the only possible effect of editing is to make the structure less stable. However, in the human transcriptome where the dsRNA structures are formed by imperfect Alu repeats, with typically over 15% mismatches, editing that changes A:C mismatches to I:C can contribute to stabilization of the structures.RNA bases can easily pair, intra-molecularly, resulting in RNA folding into a variety of secondary structures. Long intramolecular dsRNAs are the major substrate of ADAR1, and the pioneering studies in the RNA-editing field proposed that ADAR1 primarily unwinds dsRNAs6A and m1A methylation61, are being deciphered. Thus, A-to-I editing can play a significant role in this form of regulation as it affects Watson–Crick interactions.RNA secondary structure acts as an additional layer of regulation which affects several steps in the gene expression program. The current understanding of the effects of small sequence variations and modifications on RNA structure is however still limited. The current study highlights the potential regulatory role of structural changes that take place following RNA modifications. This understanding is especially relevant in the current era, in which the extent and functional roles of various mRNA modifications, like mMda5 and Mavs, rescues Adar null embryos to birth, suggesting that a major biological function for A-to-I editing of IRs is to prevent abnormal activation of MDA5 followed by a toxic type-I interferon response. While sensing of foreign, infectious agent-derived dsRNAs is essential for proper innate immune response, dampening of immune response to transcripts derived from endogenous repetitive elements (“endovirome”) that fold into long dsRNAs, is essential for the prevention of a deleterious response. We show that RNA editing can mediate both dsRNA stabilization (SWE genes) and destabilization (DSWE genes). The DSWE list of ~400 genes is significantly enriched for potential MDA5 ligands  for which editing of A:U pairs into I:U pseudo-pairs reduces stability. We hypothesize that DSWE transcripts are enriched for long, abundant, “perfect” dsRNA, involved in ADAR1-regulated cross talk with the innate immune system, which in the absence of adequate A-to-I editing may cause an overwhelming activation of MDA5/MAVS dsRNA sensing pathway. Interestingly, DSWE transcripts also contain increased numbers of STAU1 binding sites compare to SWE, suggesting that in DSWE transcript reduced ADAR1 levels may lead to escape from Staufen-mediated-decay and increase translation .Combined deletion of genes involved in the cytosolic response to dsRNA, Our study provides the context to evaluate RNA-editing-dependent SSC throughout the human transcriptome and implies multiple post-transcriptional regulatory roles for this vital function of ADAR1.−1 penicillin, 100 μg ml−1 streptomycin and 10% FBS . The cells were routinely checked for mycoplasma contamination.The Human HepG2, hepatocellular carcinoma, cell line (from ATCC) was maintained in Dulbecco’s modified Eagle’s medium, supplemented with 4 mM glutamine, 100 U mlHepG2 cells were stably transfected with validated siADAR1  or scrambled siRNA . Both were purchased from Applied Biosystems. The optimal concentration of siRNA was 20 μM. The silencing was performed for 48 h with ~80% silencing levels. Transfections of the indicated siRNAs were performed using a Nucleofector® Device .Proteins were extracted from cells using RIPA buffer (Sigma-Aldrich) supplemented with protease inhibitor (Roche). Following separation on a SDS-PAGE, proteins were transferred to a nitrocellulose membrane followed by staining with a primary antibody overnight at 40 °C and washed and incubated with the appropriate secondary antibody for 1 h at room temperature. Specific reactive bands were detected using the SuperSignal West Pico Chemiluminescent Substrate (Thermo Scientific). The antibodies used were as follows: anti-ADAR1 (Santa Cruz: sc-73408), anti-actin (Abcam: Ab156302). For ADAR1, the antibody was diluted to 1:2000. For Actin, the antibody was diluted to 1:10,000. The uncropped western blot gel is found in Supplementary Fig. PARS-seq samples were digested using RNase V1 and S1 nuclease independently and the cleavage sites are captured by adapter ligation followed by high-throughput sequencing. Combing structural information obtained from these two enzymes independently creates greater confidence for whether a base is single or double-stranded than used alone. Here, we used PARS-seq to probe RNA structural changes that occur under ADAR1 silencing conditions of HepG2 cells. In brief, 2ug of poly-A selected mRNA was heated at 90 °C for 2 min and then immediately placed on ice for 2 min. Next 10× RNA structure buffer was added to the tubes that were transferred to a thermal cycler where the temperature was slowly increases from 4 °C to 23 °C over 20 min. These steps ensure that the RNA is properly renaturated and folded under in vitro conditions. For the enzymatic cleavage, each sample tube was either cleaved by RNase V1 or S1 at 23 °C for additional 15 min resulting in 5′P overhangs. The enzymatic reaction was inactivated by phenol:chloroform:isoamyl alcohol, EtoH precipitated and resuspended in DDW for further fragmentation of the RNA into 200bases fragments . Size selection of RNA was done by gel electrophoresis and was followed by 5′ adapter ligation. This size selection step removes very short fragments of RNA, generated from the fragmentation step that could ligate to adapters. Fragmentation products with 3′P groups are converted to 3′OH groups by Antarctic phosphatase, enabling these products to be ligated to 3′ adapters. This step is followed by RT, size selection and PCR to produce a cDNA library that is suitable for high-throughput sequencing.Total RNA from HepG2 cells was isolated using Trizol (Invitrogen) and treated with DNase I (Invitrogen). Poly-A mRNA was isolated using mRNA Sequencing Sample Preparation kit (Illumina Proprietary). Random-primed cDNA synthesis was done on 2 μg of total RNA using M-MLV RT (Invitrogen). Quantitative real-time PCR (qPCR) was performed using a Fast SYBR Green Master mix , and qPCR machine ABI 7900HT genetic analyzer (Applied Biosystems) with standard qPCR parameters to analyze the expression of indicated genes compared to the control gene ABL. Results were analyzed by the SDS 2.3 software with the comparative CT method and log10 . Primers and probes sequences are detailed in Supplementary Table 62 (briefly described below), using the TruSeq Small RNA sample preparation kit of the Illumina. We ligated the 5′ adapter as described in the TruSeq Small RNA sample preparation protocol (Illumina) and stopped the reaction with 1 µl stop solution  in 28 C for 15 min. 3′ end treatment with Antarctic phosphatase was done as described in the directional mRNA-Seq sample preparation protocol, followed by its inactivation with ethanol precipitation. 3′ adapter ligation, RT and PCR amplification were performed as described in the TruSeq Small RNA sample preparation protocol. The cDNA was size selected and cleaned using E-Gel 4% agarose (Invitrogen) and Agencourt AMPure XP beads (Beckman Coulter). The library was quantified using Qubit (Invitrogen) and validated using Agilent 2100 Bioanalyzer. Libraries were sequenced on Illumina Hiseq2500 machine. Sequencing yields of the samples are detailed in Supplementary Table Libraries were prepared following the PARS-seq protocol63 in local alignment option . Only uniquely aligned reads were retained for further analysis. To count the number of reads that start at certain position in the genome we considered only reads that their 5′ matched the reference by at least five bases without gaps, carefully paying attention to the read orientation as PARS-seq protocol is strand specific. Samples were normalized such that at the end of the normalization step the sums of all read starts in each sample were equal. bigWig files containing the results of this counting step were uploaded to UCSC genome browser as custom tracks, for visualization proposes and deposited to GEO database under GEO ID: GSE100210. In order to calculate RPKM values for each gene in the PARS-seq samples, coverage of each gene was calculated using coverageBed of Bedtools package64 with RefSeq transcripts annotation65 (coverageBed -split -count -abam BAM_FILE.bam -b REFSEQ.bed). The table with RPKM values can be found on Supplementary Data Reads were aligned to the human reference genome (hg19) using bowtie232ij and S1ij are the normalized count of V1 and S1 read start at base (j) in transcript (i), respectively. PARS scores for the control cells in this study were also applied for the analysis in Dominissini et al.61.We used the definition of Kertesz et al.ij is the Pearson correlation between sample (i) to sample (j). ci stands for control sample i and kdi stands for ADAR knockdown sample i. Genes and genomic regions for which both CorDiff (V1) > 0 and CorDiff (S1) > 0 were considered as containing SSC regions. In order to calculate empirical p-value for this index, we calculated CorDiff based on random shuffle of the reads starts in each region (gene or exon). These CorDiff values were compared with the original CorDiff. Only original CorDiff that was higher than 95% of the random trials  was considered as significant .We defined the correlation difference (CorDiff) as follows:45 and GOrilla46 using a background list of all exons with a similar coverage. Functional enrichment for the DSWE set was done using the GSEA online web site v6.1, available at: http://software.broadinstitute.org/gsea/msigdb/annotate.jsp, employing the major gene sets collections of the MSigDB . GOrilla and clusterProfiler66 were also applied with a background list of all transcripts longer than 100 bases with read starts coverage >256. miR binding sites were taken from TargetScan67. STAU1 hiClip data was downloaded from Sugimoto et al.68. ADAR1 Clip-seq data was downloaded from Bahn et al.47. Histone modification data of HepG2 cells was downloaded from the ENCODE project69. Expression level of nuclear and cytoplasmic fractions in HepG2 cells were downloaded from the ENCODE project.Functional enrichment analysis of SSC exons was done with DAVID53. This script gets the counts of read starts at each position and outputs the secondary structure class (DS or SS), employing Fisher exact test to assess significance. We ran this procedure on all transcripts and compared the relative number of DS bases in control and KD samples.Illumina Hiseq2500 sequence reads were aligned to the knownCanonical transcripts list (downloaded from the UCSC table browser), using bowtie2 with local alignment option . We only used uniquely aligned reads that their 5′ matched with no gaps for at least five bases (considering the read orientation). Read starts at each position of the transcriptome were counted. Samples were normalized such that at the end of the normalization step the sum of all read starts in each sample was equal. To classify bases as DS or SS or undetermined class , we used the pars2spp script of SeqFold package70. Genes with FDR < 0.05 where considered as differentially expressed. Alternative splicing analysis was done using DEXSeq50. Exons with FDR < 0.1 were considered as alternatively spliced exons. To eliminate the option that the FDR < 0.1 is too stringent for our purposes , we also considered exons with more permissive filter of p < 0.05.Differential expression analysis was done using DESeqp < 10−15 by Fisher’s exact test), increasing our confidence in the data and procedures.To further assess the validity of our PARS-seq method following ADAR1 silencing, a differential gene expression analysis was also performed based on the PARS-seq gene coverage. We found that 2412 and 2626 transcripts were significantly differentially expressed in S1 and V1 samples, respectively, based on DESeq statistics. 1884 of them overlapped .Based on gene FC between KD and control, high correlation between RNA-seq and PARS-seq was found (71 (Ribo-seq) reads were aligned to the human reference genome (hg19) using bowtie263 with local alignment option . Only uniquely mapped reads were retained for further analyses. Coverage of each gene was calculated with coverageBed of Bedtools package64 using RefSeq transcripts annotation (coverageBed -split -count -abam BAM_FILE.bam -b REFSEQ.bed) downloaded from UCSC table browser. Using these gene coverage values RPKM values for RNA-seq and Ribo-seq were calculated  was calculated based on the ratio of both FCs:For the calculation of translation efficiency (TE)72 Meta-gene analysis was done in the span of 150 bases upstream/downstream to translation start/stop sites.Ribosome occupancy was calculated using the GWIPS-viz method in Ribogalaxy8 and DANRED42. This list was used as input for mpileup of samtools package73 for detection of variants in defined positions. The mpileup file was parsed using mpileup2snp of VarScan74. Changes from A-to-G were retained.Known RNA-editing sites were examined in the bowtie2 alignment files based on list of editing sites gathered from RADAR43 pipeline. We identified dense editing clusters of high-quality (Phred ≥ 30) A-to-G mismatches, in which the number of A-to-G mismatches was ≥5% of the read length and > 90% of the total number of mismatches. In order to find the editing level of these hyper-edited sites we used the bowtie2 alignment , and the hyper-edited sites list was served as input for the mpileup–VarScan pipeline.De novo RNA-editing sites in hyper-edited regions were detected using Porath et al.p < 0.05) in ADAR KD cells were considered as differential-editing sites (DES).Known and de novo sites for which their editing level G/(A + G) is significantly lower  done on human lymphobalsotid cells were downloaded from GEO (GEO ID: GSE50676). Raw reads (fastq files) for these samples were downloaded from SRA (SRA ID: SRP029656). Mapping, PARS-analysis and editing sites calling were performed as detailed above.Normalized read start count of V1 and S1 treatments for the samples from Wan et al.RNA 2D predictions were performed for selected cases (as in the cases of IR Alu regions of PSMB2 and F11R).75 (RNAfold –C) of the Vienna package75. In addition, editing sites which were significantly changed between control and KD (defined as DES by previous steps), covered by a total of more than 100 reads with editing level G/(A + G) > 0.1 on average in the control samples, were changed from A-to-G prior to modeling.Average PARS scores from both biological replicates were calculated from all bases of the target regions. Bases with PARS score >2.5 were defined as DS and bases with PARS score <−2.5 were defined as SS. Bases with no significant trend were registered as unknown. The binary classifications were then used as constrains for RNAfold75. R-chie76 was used to draw the arc diagrams of the RNA 2D structures .Selected examples  and colored by their PARS scores. Solved 3D structures were assigned to 2D structure using X3DNA/DSSR program77 . Only regions with CorDiff >0 in both V1 and S1 for which the original CorDiff is higher than 95% of the random trials were considered as structurally changed between edited and non-edited versions  repository, under GEO ID: GSE100210. All raw sequencing data (fastq files) from this study were uploaded to GEO under GEO ID: GSE100210. This includes also processed data of reads starts per base in genome coordinates  and in transcriptome coordinates (tab-delimited files). All PARS-seq alignment files  can be downloaded from the following link: http://bioinfo.lnx.biu.ac.il/downloads/Solomon_Paper/The datasets generated during the current study are available in the GEO (Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Supplementary Data 10Supplementary Data 11Supplementary Data 12Supplementary Data 13Supplementary Data 14


Fusarium graminearum that was recently shown to have sexual stage-specific A-to-I RNA editing. One of the genes with premature-stop-codons requiring A-to-I editing to encode full-length functional proteins is AMD1 that encodes a protein with a major facilitator superfamily (MFS) domain. Here, we characterized the functions of AMD1 and its UAG to UGG editing event. The amd1 deletion mutant was normal in growth and conidiation but defective in ascospore discharge due to the premature breakdown of its ascus wall in older perithecia, which is consistent with the specific expression of AMD1 at later stages of sexual development. Expression of the wild-type or edited allele of AMD1 but not un-editable allele rescued the defects of amd1 in ascospore discharge. Furthermore, Amd1-GFP localized to the ascus membrane and Amd1 orthologs are only present in ascocarp-forming fungi that physically discharge ascospores. Interestingly, deletion of AMD1 results in the up-regulation of a number of genes related to transporter activity and membrane functions. Overall, these results indicated that Amd1 may play a critical role in maintaining ascus wall integrity during ascus maturation, and A-to-I editing of its transcripts is important for ascospore discharge in F. graminearum.Ascospores are the primary inoculum in the wheat scab fungus  Fusarium graminearum is one of the causal agents of Fusarium Head Blight (FHB) or scab, a destructive disease of wheat and barley worldwide. Besides causing severe yield losses, the pathogen often contaminates infested grains with deoxynivalenol (DON), zearalenone, and other mycotoxins2. F. graminearum overwinters on plant debris and discharges ascospores into the air in the spring to infect flowering wheat or barley heads. Unlike many other plant pathogenic fungi, sexual reproduction plays a critical role in the infection cycle of F. graminearum because ascospores are the primary inoculum of FHB4. Under field conditions, conidia produced on diseased plant tissues are mainly for spreading infection to vegetative tissues of host plants because of the flowering time of wheat heads.F. graminearum is a homothallic ascomycete and a tractable genetic system for studying sexual development because of its high homologous recombination frequency and fertility7. In the past decade, numerous genes important for sexual reproduction have been identified, including a number of protein kinase, phosphatase, and transcription factor genes and other genes with diverse functions10. Whereas many of these genes also are important for vegetative growth and asexual reproduction, some have specific functions during sexual reproduction in F. graminearum, such GEA1 and PUK1 that have no other defects but ascospore release or morphology12. Interestingly, for the two paralogs of CDK kinase Cdc2 and beta-tubulin, whereas they have overlapping function in vegetative growth, only Cdc2A and Tub1 are important for ascus and ascospore development14, suggesting differences in cell cycle regulation and microtubule cytoskeleton between vegetative hyphae and ascogenous tissues in F. graminearum.F. graminearum12. In animals, A-to-I editing catalyzed by the adenosine deaminase acting on RNA (ADAR) enzymes is the most prevalent type of RNA editing15. Although plants and fungi lack ADAR orthologs, more than 26,000 A-to-I editing sites were identified in F. graminearum, and majority of them occurred in the coding regions and caused amino acid changes12. The PUK1 protein kinase gene known to be important for ascospore development and release8 had two tandem premature stop codons UAG UAG in its open reading frame (ORF) that were edited to UGG UGG during sexual reproduction to encode full-length proteins12. Additional 69 genes with premature stop codons in their ORFs that had PUK1-like editing events in perithecia were identified in F. graminearum12, suggesting the importance of RNA editing during sexual reproduction.Recently, A-to-I RNA editing was found to specifically occur during sexual reproduction in PUK1-like editing events that were selected for preliminary analysis for their roles in sexual reproduction12. In this study, we further characterized the functions of FGRRES_10094 (named AMD1 for ascus maturation and ascospore discharge 1) and its UAG to UGG editing event in ascospore development and release. The amd1 deletion mutant was defective in ascospore discharge, likely due to the premature breakdown of its ascus wall. In addition to stage-specific editing, AMD1 was specifically expressed at late stages of sexual development and its orthologs are only present in ascocarp-forming fungi. Expression of different mutant alleles of AMD1 confirmed the importance of RNA editing. Furthermore, Amd1-GFP localized to the ascus membrane and deletion of AMD1 results in the up-regulation of a number of genes related to transporter activity and membrane functions. Overall, our results indicated that AMD1 may play a critical role in maintaining ascus wall integrity and A-to-I editing of its transcripts is important for ascospore discharge and auto-inhibition of ascospore germination in F. graminearum.FGRRES_10094 (=FGSG_10094 of the previous annotation by the Broad Institute) was one of the five hypothetical genes with AMD1 for ascus maturation and ascospore discharge 1) was predicted to contain one intron towards its 5’-end. However, our RNA-seq data12 showed that this intron was incorrectly predicted but the stop codon UAG (631–633) within it was changed to UGG by RNA editing in 97.6% of the AMD1 transcripts in perithecia harvested at 8 days post-fertilization (dpf)  domain and 11 transmembrane helixes (TM)  Fig. . The actTM) Fig. . InteresTM) Fig. ; Fig. S1TM) Fig. ; Fig. S1TM) Fig. .Figure 1AMD1 transcripts were rare in RNA-seq data of hyphae and conidia12, suggesting that AMD1 was almost specifically expressed in perithecia. To verify this result, we assayed AMD1 expression in PH-1 by qRT-PCR with RNA isolated from 12 h YEPD cultures and 8 dpf perithecia. Consistent with RNA-seq data, AMD1 transcription was barely detectable in vegetative hyphae but its expression increased over 1,000 folds in perithecia , dpf Fig. . The abudpf Fig. . In compAMD1 gene replacement construct was generated and transformed into the wild-type strain PH-1 in a previous study12. The amd1 mutant  and AMD1TAA (uneditable) constructs by introducing the A632G and G633A mutations, respectively, and transformed them into the amd1 mutant. The resulting transformants were screened by PCR and examined for defects in sexual reproduction. All the amd1/AMD1TAA transformants had similar defects with the original amd1 mutant in ascospore release and ascus wall integrity  of AMD1 had no functions during sexual reproduction.To determine the function of Aamd1/AMD1WT-GFP transformants had detectable GFP signals in vegetative hyphae and conidia , is also required for ascospore discharge and prevention of ascospore germination inside perithecia19. The Fgkin1 and amd1 mutants has similar defects in ascospore discharge and disintegration of the ascus wall  plates at 25 °C. Conidiation in liquid carboxymethyl cellulose (CMC) medium and growth rate on complete medium (CM) plates were measured as described30. To assay for defects in stress responses, final concentrations of 0.75% sodium dodecyl sulfate (SDS), 0.1% H2O2, and 0.7 M NaCl were added to CM as described8. For sexual reproduction, aerial hyphae of 5-day-old carrot agar cultures were pressed down with sterile 0.1% Tween 2031. Perithecia, cirrhi, asci, and ascospore discharge were examined as described19. Protoplast preparation and polyethylene glycol (PEG)-mediated transformation were performed as described29. Hygromycin B  and geneticin  were added to the final concentration at 300 and 400 μg/ml, respectively, for transformant selection.The AMD1 gene including its promoter region was amplified with primers 094-NF and 094-R (Table XhoI-digested pFL2 (carrying the geneticin resistance marker) into yeast strain XK1–25 by the gap repair approach32. The AMD1WT-GFP fusion construct was rescued from Trp+ yeast transformants and confirmed by sequencing analysis. The same yeast gap repair approach was used to generate the AMD1TGG-GFP, PRP27-AMD1TGG-GFP, and AMD1TAA-GFP constructs. To introduce the A632G and G633A mutations, AMD1 was amplified with primer pairs 094E-F /094E-R and 094S-F /094S-R  were stained with 0.5% (wt/vol) toluidine blue before being examined with an Olympus BX-53 microscope.Perithecia collected from mating cultures at 8 or 10 dpf were fixed with 4% (vol/vol) glutaraldehyde in 0.1 M phosphate buffer (pH 6.8) overnight at 4 °C. Samples were then dehydrated in a series of acetone consisting of 30, 50, 70, 80, 90, and 100% (vol/vol). The dehydrated samples were embedded in Spurr resin as describedTUB2 beta-tubulin gene was used as the internal control34 and the relative expression of each gene was calculated with the 2−△△Ct method. Data from three biological replicates were used to calculate the mean and standard deviation of the expression levels35.For qRT-PCR assays, RNA samples were isolated with the TRIzol reagent  from perithecia collected at 7 dpf. The Fermentas First cDNA synthesis kit  was used for cDNA synthesis. The 5 conidia/ml in sterile distilled water. For each head, the fifth spikelet from the base of the inflorescence was inoculated with 10 μl of conidium suspensions as described37. FHB symptoms were examined at 14 day post-infection to estimate the disease index39. Corn silks were infected with culture blocks and examined as described40.For infection assays with flowering wheat heads of cultivar Xiaoyan 22, conidia were harvested from 5-day-old CMC cultures and re-suspended to 2.0 × 10amd1 mutant were harvested from carrot agar cultures at 7 dpf and used for RNA extraction with TRIzol . For each strain, RNA was isolated from two biological replicates. RNA-seq libraries were prepared with the NEBNext® Ultra™ Directional RNA Library Prep Kit  following the instruction provided by the manufacturer and sequenced with Illumina HiSeq 2500 with the paired-end 2 × 150 bp model at the Novogene Bioinformatics Institute . For each replicate, at least 24 Mb paired-end reads were obtained. The resulting RNA-seq reads were mapped onto the reference genome of F. graminearum strain PH-141 by HISAT242. The number of reads (count) mapped to each gene were calculated by featureCounts43. Differential expression analysis of genes was performed using the edgeRun package44 with the exactTest function. Genes with a FDR  of below 0.05 and |log2FC (log2 fold change)| of above 1 were regarded as differentially expressed genes.Perithecia of PH-1 and RNA-seq data were deposited at NCBI SRA database under accession number SRP100650.Supplementary Information


P<0.05) differentiated between HGSOC and control were identified: AGA to top candidates SiaTn and 6-OSulfo-TF (both IgM) differentiated comparably to CA125. The area under the curve (AUC) of a panel of AGA to 5 glycans  (0.878) was comparable to CA125 (0.864), but it markedly increased (0.985) when combined with CA125. AGA to SiaTn and 6-OSulfo-TF were also valuable predictors for HGSOC when CA125 values appeared inconclusive, i.e. were below a certain threshold. AGA-glycan binding was in some cases isotype-dependent and sensitive to glycosidic linkage switch (α2–6 vs. α2–3), to sialylation, and to sulfation of the glycans. In conclusion, plasma-derived AGA to sialylated and sulfated glycans including SiaTn and 6-OSulfo-TF detected by SGA present a valuable alternative to CA125 for differentiating controls from HGSOC patients and for predicting the likelihood of HGSOC, and may be potential HGSOC tumor markers.Altered levels of naturally occurring anti-glycan antibodies (AGA) circulating in human blood plasma are found in different pathologies including cancer. Here the levels of AGA directed against 22 negatively charged  glycans were assessed in high-grade serous ovarian cancer  patients and benign controls (n = 31) using our previously developed suspension glycan array (SGA). Specifically, the ability of AGA to differentiate between controls and HGSOC, the most common and aggressive type of ovarian cancer with a poor outcome was determined. Results were compared to CA125, the commonly used ovarian cancer biomarker. AGA to seven glycans that significantly ( Though the commonly employed ovarian cancer biomarker CA125 is useful for monitoring response to chemotherapy and detecting disease recurrence, it lacks sufficient sensitivity and specificity, especially for detecting early FIGO stages of the disease [Ovarian cancer and in particular high-grade serous ovarian cancer (HGSOC) is the most deadly gynecologic cancer with an overall survival rate of less than 20% . The poo disease . Since aa (sLea), T  antigen, and Thomsen-nouvelle antigen (Tn). TACA are considered potential diagnostic markers since these glycan structures resemble molecular-level glycomic ‘fingerprints’ which facilitate the discrimination between healthy and diseased states or reflect tumor micro-heterogeneity: not surprising that most clinically used tumor markers are glycoproteins [A number of studies have proposed naturally occurring antibodies to tumor- associated carbohydrate (glycan) antigens (TACA) –8 or to proteins , 11.TACA can be recognized by anti-glycan antibodies (AGA) that, as part of innate immunity system, are present in normal sera without deliberate immunization and serve for pathogen and apoptotic cell clearance –14. AGA e.g. antibodies to glycolyl-neuraminic acid and to glycans bearing it as well as antibodies to SiaLec and to 4’-O-su-LacNAc [Considerable effort has been applied to the development of multiplexed biomarker-based test platforms , 27. Thiu-LacNAc –35), natN-acetylneuraminic acid (Neu5Ac) and N-glycolylneuraminic acid (Neu5Gc), are the most common terminations of glycoconjugates expressed on mammalian cells or attached to secreted molecules [x/SiaLea), sialyl Thomsen-nouvelle antigen (SiaTn), and ganglioside epitopes GM2, GD2, and GD3. Interestingly, SiaLea, SiaLex, SiaTn, and GD3 were found overexpressed in ovarian cancer [x/SiaLea is involved in cancer cell extravasation and metastasis [The sialic acids, olecules . Increasolecules , includin cancer , 38. Sultastasis .In the present study we investigated (i) whether AGA to an extended selection of sialylated and sulfated analogues of known TACA discriminate controls from HGSOC in the SGA, (ii) whether these AGA predict HGSOC, and how the results compare to CA125.Table 1). The high-grade serous ovarian cancer (HGSOC) group consisted of patients with FIGO stages I-IV, whereof two thirds (63.7%) were stage III (n = 22). The control group (n = 31) consisted of samples from patients with benign diseases  or women undergoing medical control due to previous history of breast cancer or harboring BRCA1/2 mutation. Samples were collected either from patients admitted with an adnexal mass to the Gynaecological Cancer Centre of the Royal Hospital for Women, Randwick, Australia or were seen as outpatients at the Hereditary Cancer Centre of The Prince of Wales Hospital, Randwick, Australia. All patients were over the age of 18 years and were prospectively included after giving written informed consent to this study. The responsible ethical committee / Australian Research Ethics Database (AURED) Ref:08/09/17/3.02) specifically approved this study. The processing of blood plasma samples was performed consistently on ice within three hours after collection as previously described [Two groups of female donors were involved in the current study  is a multiplex analysis system permitting the simultaneous analysis of multiple different biomolecules and includes (i) the production of glycopolymers composed of a polyacrylamide carrier provided with end biotin groups and side-pendant glycan residues chemically synthesized or purchased, (ii) the coupling of these glycopolymers to fluorescent microbeads, (iii) the incubation of these beads with serum samples, and (iv) the measurement of the AGA hybridized to the glycopolymers (“binding”) using fluorescently labelled reporter molecules (secondary antibodies) specific for each AGA with subsequent data analysis.1a GM2 and GD3 glycans were purchased from Elicityl  and then used for synthesis of end-biotinylated glycopolymers as described above. Hetero-bifunctional polyethylene glycol  was purchased .To produce these glycopolymers, sialylated and sulfated glycans for the SGA were chemically synthesized . The glycopolymers, used for coupling to fluorescent beads, were produced as previously described . The gly23–NH2 microbead modification was accomplished as described previously [7 microspheres/mL) was vigorously vortexed for 30 sec and sonicated for 15 sec in a water bath prior to its use. The tube with bead suspension  was placed into a magnetic separator  for 30–60 sec and the supernatant carefully removed. The pellet was resuspended in bead wash buffer  by vortexing and sonication, and applied for magnetic separation as described above. After gentle removal of supernatant, the pellet was resuspended in 80 μl of bead activation buffer (Bio-Plex amine coupling kit), vortexed and sonicated. Sulfo-N-hydroxysuccinimide sodium salt (S-NHS) and 1-ethyl-3-3,3-dimethylaminopropyl carbodiimide hydrochloride (EDC) , were prepared immediately prior to use, and 10 μl of each solution was added to the bead suspension, followed by vortexing for 30 sec. Beads were agitated in dark on rotator at room temperature for 20 min. The activated beads were applied for magnetic separation and supernatant removed. Bead pellets were resuspended in 150 μl of biot–PEGm–NH2 solution , agitated in dark on rotator at room temperature for 2 h. Obtained biotinylated and PEGylated beads were pelleted by magnetic separation and resuspended in 150 μl of 50 mM ethanolamine  in 0.1 M NaHCO3, pH 9.0 to quench unbound activated groups. Beads were agitated in dark on rotator at room temperature for 30 min. After magnetic separation the pellet was washed twice with 500 μl PBS, pH 7.4 and resuspended in streptavidin-solution . Suspended beads were vortexed and agitated in dark on rotator at room temperature for 2 h. Beads were washed twice with 500 μl PBS using magnetic separator. Glycan-PAA-biot1 solutions  were added to the reaction tubes with streptavidin-coated beads. The mixture, protected from light, was agitated on rotator at room temperature for 6 h or overnight at 4°C. Modified microspheres were applied to magnetic separator, supernatant removed and beads washed twice with 500 μl of bead storage buffer (Bio-Plex amine coupling kit). Beads were resuspended in 100 μl of bead storage buffer and concentration determined using a hemocytometer  before storing at 4°C, protected from light until use.Biotinylated glycopolymers were coupled to fluorescent Bio-Plex Pro™ Magnetic COOH beads of 6.5 μm diameter with distinct spectral “addresses” . Each bead’s region was embedded with a precise ratio of red and infrared fluorescent dyes allowing its identification using Bio-Plex 200 Suspension Array System (Bio-Rad Laboratories Inc.). Coupling of biotinylated glycopolymers to microbeads incorporating biot–PEGeviously . BrieflyThe Bio-Plex 200 Suspension Array System is a multiplex analysis system that permits the simultaneous analysis of up to 200 different biomolecules in a single microwell plate. The constituents of each well are drawn up into the flow-based Bio-Plex array reader, which quantifies each specific reaction based on its bead color using fluorescently labelled reporter molecules specific for each target protein followed by Bio-Plax Manager software data analysis.Incubation buffer , Sigma-Aldrich Chemise GmbH) incorporating 2500 beads of each region per well (50 μl/well) was added to a Bio-Plex Pro 96-well flat bottom microplate (Bio-Rad Laboratories Inc.). The plate was washed twice with washing buffer (PBS-0.02% (v/v) Tween-20, pH 7.2) using a Bio-Plex Pro II Wash Station (Bio-Rad Laboratories Inc.). Human plasma samples, diluted 1/40, or incubation buffer alone as a control were added to wells (50 μl/well) and vigorously agitated for 30 sec on a microplate shaker before incubation on a shaker with medium speed for 1 h at room temperature in the dark. After incubation, the plate was washed thrice with washing buffer using the Bio-Plex Wash Station. Secondary antibodies (goat anti-human IgM and IgG antibodies conjugated to R-phycoerythrin (R-PE) , 25 ng/well in incubation buffer, 50 μl/well or incubation buffer alone as a control were added and incubated for 30 min on the plate shaker in the dark. The plate was washed thrice with washing buffer; beads were resuspended and shaken for 30 sec vigorously in 125 μl of washing buffer before being analyzed on the Bio-Plex array reader. Data were acquired in real time, analyzing 100 beads by their MFI (median fluorescence intensity) using computer software package (Bio-Plex Manager 5.1).To obtain reliable data following experimental setups and controls were incorporated. SGA experiments were performed in duplicates three times in an independent manner. The same four control plasma samples were used in every run. The opened reduced form of D-glucose (aminoglucitol), which is not present as a structural component of regular glycosylation  was usedS1 Table) based on the absence of cross-reactivity among correspondent human plasma AGAs tested in preliminary experiments. Cross-reactivity was evaluated by comparing data obtained in singleplex (each single type of glycan-coupled microbeads in separate reaction sample) and multiplex settings using eight randomly chosen human plasma samples. The mean % coefficient of variation (CV) obtained for the same glycan in singleplex and multiplex settings did not exceed SGA inter-assay variation, described previously [The multiplexing of SGA was performed by mixing several types of glycan-coupled microbeads in one reaction sample. For multiplex assays glycans with different structural motifs were combined in three sets  according to the provided protocol. Initial dilutions of plasma samples were 1/5 for control and 1/10 for HGSOC. The samples generating values out of the range for reliable determination of CA125 concentration were rescreened with adjusted dilutions.The quantitative measurement of CA125 (units/ml) in blood plasma samples was performed by Abcam’s CA125 P-values based on Mann-Whitney U-Test are presented across study groups (univariate) and were graphically displayed. P-values < 0.05 were considered statistically significant. Prior to further evaluation, raw data  were log10-transformed to achieve approximate normal distribution.In a first step, descriptive statistics including median, interquartile range (IQR) and https://web.stanford.edu/~hastie/Papers/Glmnet_Vignette.pdf and especially for the choice of the fixed parameter alpha. The advantage of the "elastic-net" is to perform feature selection and discrimination in one step. Additionally a “Random forest”  were assessed. L1 penalized logistic regression was performed using the package “glmnet” within the package "caret" implemented in the statistical software R , 46. In Forest”, , 49) waset al., 2011 [Subsequent ROC curves with corresponding AUC's were presented and compared within the framework of "caret" . Due to l., 2011 .https://cran.r-project.org).As an exploratory tool, a tree-based model with the most important predictors and CA125 is performed to visualize potential interactions between variables . This moTable 1) to 22 sia- and sulfo-glycans with separate detection of AGA of the IgM-and IgG-isotype using our previously modified SGA [We and others have previously reported that human plasma contains a set of AGA directed against a variety glycans including known TACA , 54–56. fied SGA .Fig 1) showed generally higher glycan-antibody binding intensities  for IgM- compared to IgG isotype AGA: exceptions are anti-GM3, anti-6-SLN(Gc), and 3’siaTn. 6-O-Sulfo-GlcNAc displayed the highest AGA binding for both isotypes (MFI>1000), followed by AGA against SiaTn (IgM), 6-OSulfo-TF (IgM), and 3’-O-Sulfo-Lec (IgM and IgG), and by AGA against GM3 (IgM), 6-SLN(Gc) (IgM), Neu5Acα2-6Gal, 6-SiaTF, 6-OSulfo-LN, 6-SLN, and SiaLex  (MFI<500). Binding intensities are usually lower in HGSOC than in control or comparable in either group for both isotypes .The SGA results presented . Interestingly, AGA against 7 out of 22 glycans highly significantly discriminated controls from HGSOC (P<0.001): anti-SiaTn (IgM), anti-6-OSulfo-TF (IgM), anti-GM2 (IgG), anti-SiaTn(Gc) (IgG), anti-GD3 (IgG), anti-3’SiaLec(Gc) (IgM), and anti-GM3 (IgM) . Detailed listing of all glycans  and the significance of discrimination between HGSOC and controls based on AGA binding is given in S2 Table.We determined whether one or more of these 22 glycans have a “discriminatory value”, i.e. whether plasma-derived AGA directed against one or more of these glycans can discriminate between controls and HGSOC. The plasma level of CA125, the today most commonly used tumor marker, was included as a reference. The results are presented in Table 2) show that CA125 (1.27) was the “best predictor”, followed by anti-SiaTn IgM (-0.75), anti-O-Sulfo-TF IgM (-0.25), anti-6-OSulfo-LN IgG (0.13), anti-SiaLea IgG (-0.03), anti-GM2 IgG (-0.02).In order to define the “most relevant” predictors  an L1-penalized logistic regression was calculated (feature selection = selection of predictors to discriminate between control and HGSOC). Thus, the obtained regression coefficients are directly comparable among each other. These values  and SiaLea (IgG)). The results obtained from the penalized logistic regression were verified by “Random forest” (rf) as an independent popular algorithm for feature selection. The rf algorithm revealed CA125, anti-SiaTn (IgM), anti-6-OSulfo-TF (IgM) (order of descending magnitude of significance) as the most relevant predictors, a finding that supports the stability of the selection made . The respective AUC values were 0.8644 (CA125), 0.8783 (AGA panel) and 0.9853 (combination of CA125 and AGA panel), indicating that the combination of CA125 and AGA panel (AUC of nearly 1.0) exhibited a very strong diagnostic performance for this prediction. The diagnostic performance was validated by 5-fold cross-validation revealing a significantly increasing AUC value by a combination of CA125 together with individual or both AGA (anti-SiaTn (IgM), anti-6-OSulfo-TF (IgM))  curves and corresponding AUC (area under the curve) values were calculated based on the penalized logistic regression for CA125 alone, for a panel of selected AGA based on the feature selection, and for the combination of CA125 and the panel of selected AGA to predict the diagnostic performance of this setup (F (IgM)) .n (IgM) or anti-6-OSulfo-TF (IgM)) was computed . This model provided an accurate likelihood to predict HGSOC in individuals with CA125 serum levels of less than a certain value. Our computation for this cohort proposes a 90% likelihood for HGSOC, if CA125 serum values are higher than 328 units/ml. For values lower than 328 units/ml, levels of anti-SiaTn or anti-6-OSulfo-TF rather than CA125 values are accurate predictors for HGSOC: here anti-SiaTn MFI values lover than 2316 predict an 80% likelihood for HGSOC  and accordingly an 85% likelihood for HGSOC for anti-6-OSulfo-TF values less than 1258 . These results demonstrate that, apart from CA125, IgM-isotype AGA against SiaTn and O-Sulfo-TF are highly significant predictors for HGSOC.A tree-based model  with CA125 and the two best predictors (anti-SiaTn is different for IgM-isotype (discriminating) and for IgG-isotype (not discriminating) AGA and that IgM-isotype AGA against SiaTn discriminated between control and HGSOC but its analogue 3-SiaTn did not . SiaTn and 3-SiaTn differ in their glycosidic linkage (α2–6 vs. α2–3), indicating that the type of this glycosidic linkage “decides” between discriminating or non-discriminating, i.e. the discrimination is lost when SiaTn (α2–6) is replaced by 3-SiaTn (α2–3). These observations suggest that AGA-glycan binding is a fine-tuned matter worthwhile looking into it in more detail . The substitution of Neu5Ac in SiaTn by NeuGc in SiaTn(Gc) decreased IgM AGA binding in both groups and increased IgG binding in the control group and abrogated the discrimination of control and HGSOC for the IgM-isotype but produced discrimination for IgG-isotype. Likewise, the substitution of Neu5Ac in 3’SiaLec by a sulfo-group in 3’-OSulfo-Lec increased in immunoreactivity of both, the IgM- and the IgG-isotype AGA, without affecting the non-discrimination. Likewise, substitution of Neu5Ac in 3’SiaLec by non-human Neu5Gc slightly decreased IgM immunoreactivity and produced discrimination between control and HGSOC (P = 0.026) whereas it slightly increased IgG immunoreactivity without affecting non-discrimination. AGA binding to 6-OSulfo-TF was higher than to its sialylated-analogue 6-Sia-TF for both isotypes, and anti-6-OSulfo-TF IgM highly significantly discriminated between control and HGSOC (P = 0.005) while this discrimination was lost for 6-Sia-TF. While uncharged TF  did not, its sulfated analogue 6-OSulfo highly significantly (P = 0.002) discriminated between the two groups , indicating that the observed discrimination of anti-6-OSulfo-TF was attributed to the sulfation of TF antigen.We observed that binding to SiaTS2 Fig) identified two major clusters: one comprising mostly IgM AGA and one mostly IgG AGA. While discriminating AGA against GM2 (IgG), SiaTn(Gc) (IgG), GD3 (IgG), 3’SiaLec(Gc) (IgM), and GM3 (IgM) belonged to definite clusters, our two top discriminating candidates anti- SiaTn (IgM) and anti-6-OSulfo-TF (IgM) were at the margin of the IgM cluster  distinguished with comparable power. Secondly, the predictive value (AUC) of the 5 top candidate AGA together  is comparable to CA125, but was markedly higher (nearly 1.0) if combined with CA125. Thirdly, SiaTn and 6-OSulfo-TF were also valuable predictors for HGSOC when CA125 values were inconclusive, i.e. below a certain threshold. Another finding was that the AGA-glycan binding in the SGA was in some cases antibody isotype-dependent or sensitive to a switch in the glycosidic linkage and even to minor chemical modification in the glycans. The following conclusion may be drawn: Plasma-derived AGA to particular glycans (e.g. SiaTn and 6-OSulfo-TF) are a valuable alternative to CA125 for the discrimination of controls from HGSOC patients and for predicting the likelihood of HGSOC in a cohort, proposing these newly identified glycan-antibody interactions as potential HGSOC tumor markers in the SGA setting.Three major findings emerged from this investigation. Firstly, AGA to seven out of the 22 investigated glycans significantly differentiated plasma samples from control women and HGSOC patients in the SGA: the two top AGA, anti-SiaT2, GM3, GD3), Thomsen-nouvelle (SiaTn and SiaTn(Gc)), Thomsen-Friedenreich (6-OSulfo-TF), and “Lewis” related antigen, indicating the absence of any obvious systematic or preference. Most of them and their non-modified analogues like TF and Tn are well-described TACA [a, SiaLex, SiaTn, GD3) have been shown to be overexpressed in ovarian cancer [The herein identified candidate glycans may, however, at this point not replace the currently used ovarian cancer biomarker CA125 but certainly may serve as a complementary marker and predictor for HGSOC in the diagnosis of this disease. The identified candidate glycans do not belong to one specific group of glycan antigens but to gangliosides  abrogated discrimination between HGSOC and control groups, and the glycosidic linkage switch from α2–6 in SiaTn into α2–3 in 3-SiaTn, respectively abrogates this discrimination. Interestingly, α2–6 (in contrast to α2–3) sialylation is a hallmark of malignant transformation [in vivo [We observed that even minor modifications of the glycans alter AGA binding reactivity and consequently their discriminating properties, highlighting the high specificity of (certain) AGA in the recognition of their glycan epitopes. Our finding that 6-OSulfo-TF but not its non-sulfated analogue TF, was (apart from CA125) the second-best HGSOC from control discriminator is noteworthy, because the role of glycan sulfation  has not yet been studied in ovarian cancer. On the other hand, the discriminating property of 6-OSulfo-TF was lost with its sialylated-analogue 6-Sia-TF. The sulfation of SiaLeelectins . In addiormation  and a me[in vivo .a IgM antibody, which is apparently elevated in HGSOC compared to controls. GM1a ganglioside has been suggested to inhibit cellular proliferation and migration, and to enhance differentiation [The AGA-glycan binding intensities were generally lower in HGSOC than in control or comparable in either group, which is fully consistent with previous studies including ours and indicates that cancer patients commonly had lower serum AGA levels , 60: thentiation , but it In regards to early detection of ovarian cancer, we have shown that AGA to sialylated and sulfated glycans compete with and improve the detection of CA125 alone. Moreover, our experimental setup allows simultaneous measurement of CA125 and selected AGA in only a minute amount of plasma samples, which would minimize the health costs. Multiplex measurement of CA125 together with other biomarkers has already been validated in a multiplexed system  and therS1 Appendix(PDF)Click here for additional data file.S2 Appendix(PDF)Click here for additional data file.S3 Appendix(PDF)Click here for additional data file.S1 FigP values, Mann-Whitney test).Significant difference between control (black) and HGSOC (gray) is indicated ((PDF)Click here for additional data file.S2 FigA), HGSOC (B).Heatmap is based on non-parametric Spearman correlation comparing all AGA and CA125 against each other. Red color (positive correlation), blue (negative correlation), white (no correlation). Control group ((PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 TableP values for comparison of HGSOC vs. control are defined by Mann-Whitney test on log-transformed data; FDR  adjusted P values less than 0.1 are shown. P values considered statistically significant (<0.05) are shown in red.(PDF)Click here for additional data file.


Microsatellites, or simple tandem repeat sequences, occur naturally in the human genome and have important roles in genome evolution and function. However, the expansion of microsatellites is associated with over two dozen neurological diseases. A common denominator among the majority of these disorders is the expression of expanded tandem repeat-containing RNA, referred to as xtrRNA in this review, which can mediate molecular disease pathology in multiple ways. This review focuses on the potential impact that simple tandem repeat expansions can have on the biology and metabolism of RNA that contain them and underscores important gaps in understanding. Merging the molecular biology of repeat expansion disorders with the current understanding of RNA biology, including splicing, transcription, transport, turnover and translation, will help clarify mechanisms of disease and improve therapeutic development. In 1991 it was discovered that a microsatellite sequence expansion is the cause of two distinct neurological disorders, Fragile X syndrome (FXS)  and spinTremendous progress has been made in understanding the metabolism of expanded tandem repeat-containing RNA (xtrRNA). Nonetheless, various gaps in our understanding of the underlying molecular biology and pathology remain, which in turn limits identification of promising therapeutic approaches. The goal of this review is to help address these gaps by discussing the potential impact of xtrRNA on cellular RNA metabolism. We begin with an overview that covers microsatellite origin, evolution, and expansion. We then follow xtrRNA through its life cycle, beginning with transcription and continuing through splicing, folding, protein interactions, localization, turnover, and translation. We rationalize the logic of current molecular disease models, note where important mechanistic information is lacking, and emphasize new pathways to consider for mechanistic insight. We use this discussion to also highlight areas where therapeutic intervention may be useful.Microsatellite sequences comprise approximately 3% of the human genome, about twice as much as protein coding sequence , 171. MiAlu and L1 ).A major source of microsatellite expansion in dividing cells is DNA replication, although mitotic recombination is also recognized as a contributing factor , 242. DuRepeat expansion events are intimately tied to the repair of non-canonical DNA structures and DNA damage. Multiple DNA damage control pathways have been implicated, including mechanisms that replace DNA bases, like base excision repair (BER) or nucleotide excision repair (NER), especially as sources for repeat expansion in non-dividing cells . HoweverAn important question is how repeats are able to expand out of control, sometimes into the hundreds or thousands of perfect tandem copies, without accumulating significant interruptions? Microsatellites that are evolutionarily neutral, typically in intergenic regions, become highly mutable when they exceed thresholds above just a few tandem repeats , 95, 320Mechanisms have been proposed that could provide large expansions in a single step, including template switching replication models where repeats are already sufficiently large enough , 266 andIncremental expansions, such as those caused by MMR, are typically on the order of 1-3 repeats at a time . Could tA common theme among sources of repeat instability and expansion is DNA metabolism associated with strand separation and reannealing at microsatellite sequences. These events can lead to formation of non-canonical structures and recruitment of DNA damage responses that ultimately and inadvertently add more repeats. Thus, mechanisms meant to maintain and protect the genome can also lead to large tandem repeat expansions and cause human disease , 333.Since it was first discovered that microsatellite expansions can cause disease, at least two dozen microsatellite repeat expansion disorders have been subsequently reported Table . The latMicrosatellite expansions cause disease through two broad molecular mechanisms Fig. : loss-ofC9ORF72-associated frontotemporal dementia and amyotrophic lateral sclerosis (C9FTD/ALS) . T. T327]. Sequence specific interactions may not entirely explain xtrRNA localization or foci formation. While certain proteins that prefer to bind G-rich sequence, like hnRNP H/F, have been found to associate strongly with the GGGGCC repeats of C9FTD/ALS, other interacting proteins do not appear to have strong GGGGCC sequence-binding specificity, such as ALY/REF, SC-35, SF2, and nucleolin , 175. ImWhether there is a specific localization pattern of xtrRNA inside cell nuclei is not entirely clear. Foci might be expected to nucleate at the site of transcription. DMPK mRNA usually localizes to SC-35 splicing speckles after transcription. However, when containing CUG repeat expansions, the DMPK mRNA has been shown to localize peri-transcriptionally outside of SC-35 splicing speckles . RNA conNuclear bodies can be built around RNA and the molecular forces that govern nuclear body formation may help explain xtrRNA foci formation and localization. For example, nuclear paraspeckles depend on the long noncoding RNA NEAT1 (nuclear paraspeckle assembly transcript 1) . NuclearDMPK repeat expansion, only a handful of repeat containing antisense transcripts were quantified per cell . N. N267]. For xtrRNA embedded in mRNAs, either as exons or introns, mRNA surveillance mechanisms should act to reduce translation. Activation of these pathways will lead to degradation by the cytoplasmic version of the exosome and XRN1, a 5'-3' exoribonuclease. Accessory factors that guide cleavage include the Ski complex  and the Ski7 protein . HoweverC. elegans expressing a (CUG)123 repeat expansion in a 3'-UTR of GFP [npp-4, was also a suppressor in this screen. Interestingly, smg-2, a conserved helicase and central component of the NMD pathway, was a strong suppressor. Knock-down of NMD resulted in a several-fold increase in GFP-(CUG)123 RNA expression levels and increased GFP translation. The substantial increase in 3'-UTR GC-content was identified as the likely trigger for NMD of the GFP-(CUG)123 RNA [Smg-2 was also identified as a suppressor of poly-glutamine aggregation previously, likely through NMD of aberrant repeat-containing HTT transcripts [Some studies have uncovered potential RNA turnover mechanisms associated with repeat expansions. In a recent RNAi screen several RNA processing factors were identified as suppressors of toxicity in R of GFP . These f)123 RNA . Smg-2 wnscripts . These rRNA export from the nucleus involves several distinct pathways depending on the RNA and the various protein factors that constitute the RNP particle . For nucC9ORF72 GGGGCC RNA repeats [The mRNA-associated adapter proteins and complexes represent a complicated matrix of possible interactions that dictate export efficiency , 60. NXF repeats . TREX as repeats , 204 and repeats . In addi repeats , 53, 157C9ORF72 transcripts and blocked RAN translation. Thus, SRSF1 might serve as a therapeutic target in C9FTD/ALS. This report highlights the value of understanding RNA biology in the context of repeat expansion disorders.A recent study connected NXF1 transport of C9FTD/ALS intronic xtrRNA via interaction with the export adapter SR-rich splicing factor 1 (SRSF1) . SRSF1 aMost disease-associated xtrRNA is embedded in exonic or untranslated regions Table  and therExport of intronic xtrRNA would be expected to require aberrant splicing that resulted in its retention in mRNA, as has been implicated for the intronic C9FTD/ALS repeat expansion . AlternaDrosophila melanogaster [Nuclear exit of RNP granules, such as nuclear xtrRNA foci, might also be possible through nuclear envelope budding Fig. . This menogaster , 277. Honogaster , suggestnogaster .If xtrRNA can successfully exit the nucleus it is a potential candidate for translation. However, mRNAs that contain expanded tandem repeats are possibly the only practical source for translation of repeat expansion polypeptides since they contain the prerequisite sequence elements and protein factors to mediate canonical cap-dependent translation. These typically include 5' cap structures, bound eukaryotic initiation factors (eIFs), a poly-A tail, and appropriate mRNP complexes like the EJC , 315. Tr7G cap-dependent where a pre-initiation complex scans the RNA looking for a start codon [The translation of noncoding xtrRNA irrespective of a canonical start codon was recently discovered and termed repeat-associated non-AUG (RAN) translation , 339. Rert codon , 141. Whrt codon , 339. A rt codon , 96. Thert codon , 339.The mechanism of RAN translation may be related to translation of upstream open reading frames (uORFs), a widespread phenomena revealed through high-throughput ribosomal footprint profiling . RAN traRecent investigations have demonstrated that certain RAN translation products of C9FTD/ALS disrupt the function of membrane-free cellular organelles, such as stress granules, Cajal bodies and the nucleolus , 182. ThIn vitro and cell-based model systems suggest that RAN translation can proceed uninterrupted through an entire repeat expansion [Several important questions remain concerning the mechanisms of RAN translation. For example, how similar are the mechanisms of RAN translation across diverse repeat expansion and sequence contexts , 96? RANxpansion , 340. Yexpansion ? Also, wRNA species that contain simple tandem repeat sequences occupy an underexplored world of RNA biology. Recent studies have begun to revisit the transcription and translation of repeat expansions. However, significant gaps remain for processes like cellular transport and turnover of xtrRNA. Placing repeat expansion disease mechanism studies in the context of current RNA biology will help reveal a better understanding of how the cell deals with xtrRNA and identify mechanisms unique to repeat expansions.Investigations into the biology of xtrRNA promise to unlock new approaches to therapeutics. Transcription across repeat expansions has opportunities for therapeutic development, such as modulating the function of Supt4h. Likewise, translation of repeat expansions, especially RAN translation, may become more targetable as molecular mechanisms become better characterized and specific factors identified. Selectively blocking both the synthesis of xtrRNA or its translation are attractive therapeutic approaches since they could extrapolate to multiple repeat expansion disorders. Turnover of xtrRNA should become increasingly important since several potential therapeutic strategies employ targeted and selective degradation of repeat expansion-containing RNA, such as antisense oligonucleotides and small interfering RNAs , 275.


Escherichia coli without background DNA amplification. Therefore, this method can potentially detect almost all types of RNA molecules without reverse transcription and reveal full-length sequence information.RNA-primed rolling circle amplification (RPRCA) is a useful laboratory method for RNA detection; however, the detection of RNA is limited by the lack of information on 3′-terminal sequences. We uncovered that conventional RPRCA using pre-circularized probes could potentially detect the internal sequence of target RNA molecules in combination with RNase H. However, the specificity for mRNA detection was low, presumably due to non-specific hybridization of non-target RNA with the circular probe. To overcome this technical problem, we developed a method for detecting a sequence of interest in target RNA molecules via RNase H-assisted RPRCA using padlocked probes. When padlock probes are hybridized to the target RNA molecule, they are converted to the circular form by SplintR ligase. Subsequently, RNase H creates nick sites only in the hybridized RNA sequence, and single-stranded DNA is finally synthesized from the nick site by phi29 DNA polymerase. This method could specifically detect at least 10 fmol of the target RNA molecule without reverse transcription. Moreover, this method detected GFP mRNA present in 10 ng of total RNA isolated from  We previously reported RNA-primed rolling circle amplification (RPRCA) using phi29 DNA polymerase, circularized probes, and SYBR Green II for the real-time detection of mRNA from living microbes3. RPRCA is a simple and easy method, as it does not require reverse transcription (RT), DNase treatment of RNA samples, or a thermal cycler, and it does not entail non-specific DNA amplification.Many recent studies have focused on rolling circle amplification (RCA) for detecting biological moleculesHowever, there are two technical disadvantages associated with conventional RPRCA. First, although conventional RPRCA requires the 3′-terminal sequence of target RNA as a primer for DNA synthesis, available sequence database information on the 3′-terminal sequences of prokaryotic mRNAs is limited at present. Currently prevailing RNA-seq technology using next-generation sequencing (NGS) allows the rapid accumulation of growing numbers of prokaryotic mRNA sequences; however, cDNA is usually prepared by RT with random primers in prokaryotic mRNA analysis, and thus, the RNA-seq data lack 3′-terminal sequences. The 3′-terminal sequence of the target mRNA is predictable based on current genomic sequence data. However, available microbial full genome sequences are also limited, specifically regarding metagenomics, as metagenomic sequence data often exist as fragmented information, even when using current NGS and bioinformatics technology.4. Without RT, the main targets of current RPRCA are certain RNAs that do not contain poly(A) tails such as microRNAs5 in eukaryotes. For the simple detection of most types of RNA molecules in prokaryotes and eukaryotes, it is necessary to modify the RPRCA procedure to work without full-length and/or 3′-terminal sequences of the target RNA molecule.Second, conventional RPRCA is rarely applied to eukaryotic mRNA detection due to poly(A) tails at 3′ termini, which are approximately 250 bases long6. Thus, the use of RNase H should permit RNA detection if the target RNA sequence is partially known. However, specific mRNA detection via RNase H-assisted RPRCA with a pre-circularized probe only works in the absence of non-target RNA molecules in the reaction mixture, presumably because pre-circularized probes can hybridize with non-target RNAs and initiate DNA synthesis upon RNA digestion by RNase H. A similar result was reported previously7. Therefore, the specificity of RNase H-assisted RPRCA should be improved to make RNA detection simple and practical.Our recent findings suggest that the addition of ribonuclease H (RNase H) to the reaction mixture leads to DNA synthesis from a nick site in the RNA/DNA hybridization region9. The padlock probe is linear ssDNA that has a complementary sequence to target DNA molecules divided into two at both the 5′ and 3′ ends (designated as “arms” hereafter) via the linker sequence  and T4 RNA ligase 2 (T4Rnl2), can be used to seal an ‘RNA-splinted padlock probe’. T4Dnl can recognize an RNA-splinted padlock probe as a substrate by reducing the adenosine triphosphate (ATP) concentration in the reaction mixture to 10 µM24, which is commercially available as SplintR ligase , can seal RNA-splinted DNA with high efficiency15. In this study, we developed a novel RPRCA procedure for the direct detection of mRNA molecules in combination with RNase H, a padlock DNA probe, and SplintR ligase, which can prepare a circular probe from an RNA-splinted padlock DNA probe with higher ligation efficiency than T4Rnl2 and T4Dnl. This RNase H-assisted RPRCA together with SplintR ligase provides higher specificity even in the presence of non-target RNA, suggesting that this technique represents a simple and reliable method for detecting any type of RNA molecule.Recently, it was demonstrated that the ATP-dependent DNA ligase of chlorella virus PBCV-1Figure 20.In our strategy, both the detection sensitivity and specificity depend on the sealing efficiency of the RNA-splinted padlock probe. Therefore, we first examined whether SplintR ligase can more efficiently seal an RNA-splinted padlock probe than T4Dnl and T4Rnl2, which were used previously15. CircLigase was also used to prepare circular ssDNA probes as a control for gel electrophoresis. After ligation, the ligated products were treated with multiple exonucleases to remove linear ssDNA probe remaining in the reaction mixture and successively purified and analyzed using polyacrylamide gel electrophoresis (PAGE) in the presence of 5% urea.In this experiment, each ligase was tested under different ATP concentrations because T4Dnl could seal the RNA-splinted padlock probe only under low ATP concentrations15. A comparison of the fluorescence intensities of the circular ssDNA probes suggested that the sealing efficiency of T4Dnl is lower than that of SplintR ligase in the presence of 400 µM ATP  is the most efficient for sealing RNA-splinted DNA fragments. However, the sealing efficiencies of P1 (54.6 ± 8.1%) and P5 (55.4 ± 7.0%) were not significantly different from those of P2 (41.6 ± 5.3%) and P4 (40.4 ± 6.6%), which had inferior pairs  in the report. These results suggest that the sealing efficiency may be slightly affected by the secondary structure of RNA rather than the Tm and nucleotide pair of the padlock probe. In any case, this experiment clearly illustrated that the padlock probe can be set at an arbitrary position in the target RNA molecule, with some differences in efficiency.According to a previous reportRNase H is generally used at higher concentrations to completely degrade RNA species on RNA/DNA hybrids; however, several nicks are required for this experiment. Therefore, in the next step, optimization of the RNase H concentration was necessary for RNase H-assisted RPRCA. After hybridization and ligation of the padlock probe by SplintR ligase, RNase H-assisted RPRCA was performed in the absence or presence of various concentrations of RNase H. Initially the resulting amplified ssDNA was analyzed by agarose gel electrophoresis.We found that ssDNA products did not arise in the absence of both GFP mRNA and the padlock probe or in the presence of only GFP mRNA or the padlock probe. Rather, the addition of RNase H to the samples promoted the RPRCA reaction  consisting mainly of ribosomal RNA (rRNA) and transfer RNA (tRNA). In addition, to investigate the sensitivity of each probe, we measured the yield of synthesized ssDNA with SYBR Green II in real time for 2 h. According to the real-time monitoring, the detection sensitivity was at least 5 fmol for the higher-sensitivity probes  and at least 10 fmol for the lower-sensitivity probes (P1 and P5) . DNA-free phi29 DNA polymerase can reduce contaminating DNA including ssDNA27. Consequently, the molecular numbers of the 3′ end of ssDNA were significantly reduced in the reaction compared with the findings in previous experiments. For this reason, we believe that DNA-free phi29 DNA polymerase is an important component to secure the reproducibility and specificity of the RCA reaction. A bench-top extra cleanroom classified as ISO-1 featuring an ionizer to eliminate static charges from plastic ware28 was used to extract total RNA and prepare all reaction mixtures including those for in vitro transcription. Airborne particles, which cannot be recognized by the naked eye, affect DNA amplification29, and the ionizer lessened accidental contamination regardless of the operator’s experience. Using these two special tools, background DNA synthesis was suppressed in both whole genome amplification (WGA) and RCA reactions.Unexpectedly, no background DNA synthesis was detected in this study. The main reason is that our strategy, rolling circle DNA synthesis, does not start unless the formation of a primer after circularization of the padlock probe by RNase H is functioning accurately. Conversely, we believed two other factors eliminated background DNA synthesis, namely DNA-free phi29 DNA polymerase and the use of a bench-top extra cleanroom classified as international standard ISO-1 according to ISO 14644-115. T4Rnl2 has been routinely used to ligate DNA oligonucleotides to the 3′ end of RNA30. However, it is unknown whether T4Rnl2 can seal RNA-splinted padlock probes. Therefore, we sought to determine which ligase was most efficient for sealing RNA-splinted padlock probes. Our results clearly illustrated that T4Rnl2 had little ability to join nicked DNA strands even when the DNA annealed to RNA. By contrast, T4Dnl and SplintR ligase could seal RNA-splinted padlock probes, and SplintR ligase was more suitable for this process. Therefore, we speculated that the results of previous reports using T4Rnl220 for RPRCA reflected background DNA synthesis from non-circularized padlock probes or contaminating DNA in the reaction, which frequently occurs in both RCA and WGA using phi29 DNA polymerase31. Incidentally, we could not perform the ligation experiment in the presence of 400–500 mM ATP as described previously19 because ATP was not dissolved in the buffer at these concentrations.Interestingly, both the detection sensitivity and specificity of our strategy depended on the sealing efficiency of the RNA-splinted padlock probe. Therefore, selecting the optimal ligase was important for our strategy. T4Dnl could seal the RNA-splinted padlock probe only in the presence of low ATP concentrations33. However, the 3′ to 5′ exoribonuclease activity of phi29 DNA polymerase has not been confirmed by our team or other researchers34. Furthermore, our results revealed that RNase H was more effective for RNA sequence detection in RPRCA even though phi29 DNA polymerase has 3′ to 5′ exoribonuclease activity.Meanwhile, previous reports described that phi29 DNA polymerase degraded RNA from the 3′ end to the RNA/DNA hybridized region with 3′ to 5′ exoribonuclease activity (or in combination with RNase III to remove the double-stranded RNA region), permitting phi29 DNA polymerase to transform the target RNA into a primer36 reported that in situ RCA can detect eukaryotic mRNA using a padlock probe and SplintR ligase. Previously, RCA for detecting eukaryotic mRNA was performed after RT using target-specific primers34. Therefore, this method combining a padlock probe with SplintR ligase enabled the RCA reaction for in situ mRNA detection without RT. Thus, RNase H-assisted RPRCA would be also suitable for in situ mRNA detection even if the RNA has a poly(A) tail.Two recent papersSaccharomyces cerevisiae). RNase H cannot convert “DNA-splint” into a primer; therefore, our procedure using RNase H can detect only target RNA molecules even if SplintR ligase can also seal the DNA-splinted padlock probe.However, different from our method, this previous method employed an extra primer to recognize the padlock sequence for RCA as a detection primer. Moreover, the previous methods do not allow setting of the padlock probe at an arbitrary region in the target RNA molecule. Because SplintR ligase can also seal a DNA-splinted padlock probe, the detection primer could amplify the circularized padlock probe generated via hybridization with genomic DNA. To prevent DNA synthesis from the DNA-splinted padlock probe in their method, the padlock probe was set at an exon-exon junction on the mRNA molecule to detect only RNA. Thus, the method is not suitable for detecting single-exon mRNAs . Therefore, further improvement of the detection limit cannot be expected unless the detection method is changed.Contrarily, this RNase H-assisted RPRCA did not have better detection sensitivity than the previous technique using the 3′ end of RNA as a primer. We believe that the detection sensitivity of both RPRCA strategies depends on the sensitivity of SYBR Green II (1 ng/reaction). By our calculations, the detection limit of RPRCA using SYBR Green II is nearly 1 × 10In summary, our procedure has the potential to detect almost all types of RNA molecules without RT and full-length sequence information, especially for 3′-terminal sequences.AWAY .To avoid contamination from the laboratory environment, prepared solutions supplied by the manufacturers were used as much as possible in this study. UltraPURE™ distilled water and Tris-HCl solution (pH 7.5) were purchased from Thermo Fisher Scientific . All homemade solutions and buffers were filtrated and sterilized using a 0.1-µm-pore-size polyethersulfone membrane bottle top filter unit . Similarly, disposable sterile plastic ware was used whenever possible to reduce the likelihood of DNA and RNase contamination. Aerosol-resistant filter tips were purchased from Molecular BioProducts/Thermo Fisher Scientific , and microcentrifuge tubes and PCR-grade 0.2-ml tubes were obtained from Eppendorf . The 1-kb DNA ladder marker was acquired from Maestrogen . The 20-bp ladder marker was purchased from Takara Bio . All solutions and mixtures were prepared using dedicated sets of pipettes in an exclusive bench-top cleanroom  that was classified as ISO-1 after cleaning using RNase http://sg.idtdna.com/calc/analyzer) from Integrated DNA Technologies under the following conditions: oligo concentration, 10 µM; Na concentration, 50 mM; Mg concentration, 10 mM; and target, RNA. In our preliminary experiments, the linker should be longer than the sum of the arm sequences. We believe this is probably due to the physical effect of the rigidity of ssDNA. In our preliminary experiments, the secondary structure of the probe significantly affected the ligation efficiency, especially when the arm region hybridized with the linker region (data not shown). Therefore, we evaluated the secondary structure of the probe using OligoAnalyzer 3.1 at the probe design stage. All padlock probes were designed on the basis of these findings.Unlike PCR primer design, padlock probe design does not have a fixed rule. In many cases, the probe length is less than 100 nucleotides, and the length of the arm is less than 20 nucleotides. As the process basically involves the hybridization of nucleotides, the Tm of the arm should be higher than the reaction temperature in the ligation step. The Tm of the arm was calculated using OligoAnalyzer 3.1 . All padlock probes were purchased from Eurofins Genomics, Inc. . All oligomers were dissolved in 0.1x TE buffer  in the cleanroom as described previously. The sequences and Tm values of padlock probes for detecting GFP mRNA are shown in Supplementary Table To prepare the hybridization mixture, 25 pmol of the ribonucleotide  and 100 pmol of the padlock probe for testing ligation efficiency  were added to a mixture containing 20 mM Tris-acetate (pH 7.5), 50 mM potassium glutamate (KGlu), and 0.1 mM EDTA in a final volume of 10 µl. Then, the hybridization mixture was incubated at 95 °C for 1 min followed by immediate cooling to 40 °C and incubation for 10 min at 30 °C. After hybridization, 10 µl of a ligase mixture containing 20 mM Tris-acetate (pH 7.5), 20 mM magnesium acetate (MgAc), 50 mM KGlu, 20, 800, or 2000 µM ATP, and each ligase  were added to the hybridization mixture and then incubated at 37 °C for 1 h to seal the padlock probe, followed by enzyme inactivation at 65 °C for 10 min. After ligation, 10 µl of a nuclease mixture containing 20 mM Tris-acetate (pH 7.5), 20 mM MgAc, 50 mM KGlu, 1 mM ATP, 10 units of Plasmid-Safe DNase , 10 units of exonuclease III (Takara Bio), and 10 units of exonuclease I (New England BioLabs) were added to the ligation mixture, which was then incubated at 37 °C for 15 min to degrade linear single-stranded DNA (ssDNA). After enzyme inactivation at 80 °C for 15 min, the circular ssDNA was purified using a High Pure PCR Cleanup Micro Kit . The purified DNA was analyzed using 10% PAGE containing 7 M urea (Tris-Borate-EDTA buffer) and visualized by staining using UltraPower™ DNA/RNA Safedye  and a blue-light transilluminator. The gel images were analyzed using NIH Image software (ImageJ) for comparisons with the known concentration of the pre-circularized probe made by CircLigase. The yield of each padlock probe was calculated by setting the control as 100%. These ligation reactions and electrophoresis were both performed five times.In vitro transcription of mRNA was performed using a HiScribe™ T7 High Yield RNA Synthesis Kit (New England BioLabs) according to the manufacturer’s protocol. After linearization via NotI (Takara Bio) digestion, 1 µg of pET-AcGFP3 was added to the transcription reaction mixture, which was incubated at 37 °C for 2 h. After RNase-free DNase I (Takara Bio) treatment to remove the template DNA, the transcribed mRNA was then purified using a NucleoSpin® RNA Clean-up XS kit  according to the manufacturer’s protocol, and RNA concentrations were determined using a Qubit® fluorometer  with Qubit® RNA BR Assay Kits (Invitrogen). After denaturation with formamide, RNA quality was checked via agarose gel electrophoresis  and visualized by staining using UltraPower™ DNA/RNA Safedye and a blue-light transilluminator. The transcribed mRNA was stored at −80 °C until required.in vitro transcribed GFP mRNA and 100 pmol of the each padlock probe   was transformed with pET-AcGFP3 and then grown on an LB agar plate  containing 50 µg/ml ampicillin to select clones transformed with pET-AcGFP. These cells were then grown in LB medium for 8 h at 30 °C. The cultures were diluted 1:1000 in fresh LB medium with or without the Overnight Express™ Autoinduction System (Novagen) to induce GFP mRNA transcription and incubated at 30 °C with shaking for 12 h. The E. coli strain BL21, which has no vector, was also cultured at 30 °C for 8 h with LB medium. Cells were harvested in a 50-ml conical tube by centrifugation at 2150 × g for 20 min at 4 °C. Total RNA was isolated using a Cica Geneus Total RNA Prep kit  according to the manufacturer’s protocol. Total RNA concentrations were determined using a Qubit® fluorometer with Qubit® RNA BR Assay Kits. After denaturation using formamide, a small amount of genomic DNA contamination and degradation of RNA were confirmed in each sample via agarose gel electrophoresis  and visualized by staining using UltraPower™ DNA/RNA Safedye and a blue-light transilluminator.The in vitro-transcribed GFP mRNA or total RNA 2SO4), 10 mM KGlu, 2.0 mM deoxynucleoside triphosphate, 10 mM dithiothreitol, 0.002 units of pyrophosphatase (New England BioLabs), an appropriate number of units of RNase H  in a 96-well PCR plate, and fluorescence signals were measured every 10 min for 2 h with the FAM filter  of the Thermal Cycler Dice Real-Time System II . All real-time RNase H-assisted RPRCAs were performed in triplicate to estimate the experimental variance. After real-time detection, the PCR plate was additionally incubated for 2 h followed by enzyme inactivation at 65 °C for 10 min, and the products in each well were visualized using a blue-light transilluminator to confirm the fluorescence signals.Supplementary information and text