Circular RNAs (circRNAs) have gained recent attraction due to their functional versatility and particular structure connected to human diseases. Current investigations are focused on the interplay between their ability to sponge smaller species of RNAs, such as microRNAs (miRNAs), thus influencing their regulatory activity on gene expression and protein templates. Therefore, their reported implication in various biological processes axis has resulted in an accumulating number of studies. While the testing and annotation methods of novel circular transcripts are still under development, there is still a plethora of transcript candidates suitable for investigation in human disease. The discordance in the literature regarding the approaches used in circRNAs quantification and validation methods, especially regarding qRT-PCR, the current golden standard procedure, leads to high result variability and undermines the replicability of the studies. Therefore, our study will offer several valuable insights into bioinformatic data for experimental design for circRNA investigation and in vitro aspects. Specifically, we will highlight key aspects such as circRNA database annotation divergent primer design and several processing steps, such as RNAse R treatment optimization and circRNA enrichment assessment. Additionally, we will provide insights into the exploration of circRNA-miRNA interactions, a prerequisite for further functional investigations. With this, we aim to contribute to the methodological consensus in a currently expanding field with possible implications for assessing therapeutic targets and biomarker discovery. Circular RNAs (circRNAs) are species of RNAs with limited coding potential ,2 that aRegarding their biogenesis, circRNAs are derived from pre-mRNA transcripts and are generally composed of exonic sequences circularized in a process named “back-splicing” . SpecifiAlu repeats) [Alu repeats, which act as cis-promoting circularization elements [In this model, internal exon circularization can be promoted by flanking long intronic sequences containing complementary sequences (such as repeats) ,11. Yet,repeats)  or purelrepeats) . In addielements . It is celements ,15. Whilelements . One of elements . The prielements ,17. The elements ,19,20. Telements ,22, and elements ,24. On telements .The characterization of circRNA-miRNA-mRNA interaction networks became a popular model of study for the functional investigation of circRNAs, which have now been proven to be involved in multiple developmental processes , oncologTo exemplify the sequence and structural assessment required for the study of circRNAs, we chose to include four circular transcripts in our study, namely circular Forkhead box O3 RNA (circFOXO3), circular plasmacytoma variant translocation 1 (circPVT1), circular ArfGAP with Coiled-Coil, Ankyrin Repeat and PH Domains 2 RNA (circACAP2), and circular Anaphase-promoting complex subunit 2 RNA (circANAPC2). The first two transcripts are annotated in current databases. They have been investigated in several studies focusing on their functional interaction with miRNAs, yet they are not the main investigated variants ,30,31,32The key structural element to be considered when designing primers is the junction break region, which acts as the key distinguishing feature of circRNAs when compared to the linear cognate mRNAs. As such, the divergent primers should flank or overlap with the junction break in the circRNA sequence, as exemplified in To assess the amplification specificity of the designed primers, we utilized agarose gel electrophoresis to validate the expected size of the amplicons. As circRNA expression can be cell-line specific, we generated a cDNA pool derived from equal amounts of RNA from multiple cell lines.We first confirmed the specificity of the primers using touchdown PCR and demonstrated the size of the resulting amplicons using 2% EtBr-stained agarose gel electrophoresis. We confirmed that the resulting PCR products have the expected size in the case of circFOXO3 (183 bps) and circPVT1 (118 bps), with no other unspecific bands in either RNAse R− or R+ treated samples. Interestingly, the circPVT1 amplicon could not be detected in the RNAse R untreated sample, indicating a post-treatment enrichment of the transcript in the RNA pool. More so, for the pseudo-circRNAs, circANAPC2 and circACAP2, we could not observe any related products indicative of a superficial expression level, undetectable, using EtBr staining. As an additional confirmation, we evaluated the specificity of primers via the melting curve analysis resulting from the qRT-PCR using the cDNA from RNAse R treated and untreated RNA. This indicated a single melting peak in most reactions and replicated. At the same time, in the case of circPVT1 and circANAPC2, amplifications from the RNAse R+ cDNA B produceLinear RNA digestion using RNAse R is a commonly utilized step in processing the RNA samples for either sequencing or qRT-PCR investigations focused on circRNAs. In this case, we wanted to evaluate the linear transcript depletion efficiency and effects on circRNA detection. As such, we prepared individual reactions corresponding to four concentrations  of RNAse and three different time points  and proceeded to evaluate the effect of the various treatments on all investigated circRNAs and their parental linear transcripts.As highlighted in Based on the indicated noticed expression trends, we considered an enzyme concentration of 10 units/reaction and an incubation time of 1h as the optimal treatment conditions for linear RNA depletion. In this way, we were also considering the background RNA degradation associated with longer incubation time noticed in the case of most transcripts, based on the lower detection levels in the samples incubated for 60 and 120 min when compared to the ones which were incubated for 30 min. We also observed a dose-dependent aspect in which the highest amount of RNAse R, namely 20 U/reaction, can have inhibitory effects on the reaction. Referring to the quality of the post-processing RNA, the RNAse R treatment utilizing this time/dose combination (10 units/reaction for 1 h) did not have any impact on the quality of the total RNA after appropriate cleanup, as indicated by the RNA integrity number (RIN) from the Bioanalyzer analysis. Yet, as expected, there was a significant decrease in RNA concertation in the treated samples, related to the degradation of the linear transcripts .For a more accurate assessment of the enrichment of the investigated transcripts following RNAse R treatment, we calculated the circRNA expression data using two different methods. First, we utilized a circRNA-specific method based on the ratios (in percentages) between the averaged CTs in the untreated (representing 100%) and treated samples, as indicated by Panda and Gorospe . Then, wFirst, we wanted to validate whether the expression levels of the circRNAs are reflected by their parental gene’s expression level, an idea consistent with our reported comparative expression level analysis. As such, we proceeded to investigate the enrichment percentages as a form of direct quantification of the effect of the RNAse R treatment (10 units/reaction) level in multiple lung cancer cell lines . OverallFollowing the enrichment assessment, we report a significant and consistent transcript depletion in the case of all linear genes. While varied ratios can be observed in many instances, we assume they can be based on the cell-line-specific expression patterns reflected in their basal expression levels . AdditioT values taken out of context cannot be used as reliable data, only as a first indication, we utilized additional calculation methods [T calculation method, which included multiple normalization steps, factoring RNA input based on reference gene, per sample, and biological group normalizations. Given the susceptibility of the GAPDH mRNA and other normalizing transcripts to RNAse R, we utilized the reference gene values for the mock-treated RNAse R sample instead of its corresponding values. While we noticed similar trends  , circBanDetermining the overlapping circRNA-parental mRNA MREs can highlight a competitive binding potential for the specific miRNAs. Yet, the shared sequence elements (and lack thereof) between the circRNA and the parental gene must be considered. Canonically, miRNAs bind with the 3′ UTR of their targeting mRNA to determine any regulatory effect. In our case, given the exonic sequence composition of circFOXO3, the vast majority of MREs present in the FOXO3 mRNA would not be present  in circFOXO3, and the number would be restricted by the number of MREs present exclusively in the second exons of the circRNA mRNA. After comparing the circFOXO3-miRNA putative interaction list with the linear cognate FOXO3 targeting miRNAs, out of the total 22 circFOXO3 putative miRNAs, 6 were indicated to have a competitive binding potential for both circFOXO3 and the FOXO3 mRNA C. AssessCircular RNAs are currently being intensely investigated, given their functional versatility and regulatory potential of miRNA-target gene interactions, gaining significance as potential targets in pathological processes . TherefoWe focused on the importance of the junction sequence as the crucial circRNA distinctive factor in the primer design rationale. Following the bioinformatic characterization and primer validation for the selected circRNAs, we experimentally optimized the main RNA processing steps focusing on starting concentration, RNAse treatment intensity, and RNA quality control. Based on our experience, we do not recommend starting with less than 1 ug of total RNA to account for the losses associated with the RNAse R treatment and further purification step. Through the RNAse R optimization step, we highlighted the inhibitory effect of increased RNAse R concentrations upon the degradation of linear transcripts. We indicate that an optimal incubation time and concentration are reflected in the efficient degradation of linear RNAs and the enrichment of stability of circRNA in the investigated sample. This can be seen in the comparative enrichment analysis, which highlights the importance of including the untreated control samples for assessing the RNAse R treatment’s efficiency in enriching the circRNA fraction ratio out of the total RNA pool. Regardless, the comparative enrichment analysis’s full extent can only be based on contextualized normalized data, which can consider the dynamicity of circRNA expression in the total RNA pool. In our case, we noticed sample and circRNA-specific variations in enrichment levels. High levels of post-treatment enrichment, such as circPVT1, can be attributed to its increased dilution in the total untreated RNA pool, resulting in a lower initial detection level.The two unannotated pseudo-circRNAs (circANAPC2 and circACAP2) displayed lower enrichment levels in several samples, which we assume to be associated with (a) their deficient expression levels and (b) the possibility that they are not bonafide circular transcripts. Higher RNAse R concentrations have been reported to affect circRNA stability, confirming the requirement for transcript-specific optimization of the RNAse R input . Yet, boAdditionally, since RNAse R is a 3′->5′ exonuclease, its efficiency can be limited by multiple transcript-specific factors. Highly structured 3′ ends with overhangs shorter than 5 nucleotides, short polyA tails, and an overall prevalence of secondary structures can hinder its efficiency. Therefore, optimization for the specific removal of these resistant transcripts is required for an efficient depletion. To address this limitation, additional steps to the RNAse R digestion methods were developed, such as polyadenylation of resistant transcripts (post-digestion) and their subsequent depletion using polyA removal kits can efficiently deplete resistant transcripts . OverallThe principal investigated the function of circRNAs as the biological effect of their sponging interaction with specific miRNA, which in turn ablates their regulatory activity upon other RNAs. Focusing on circFOXO3, we exemplified a thorough approach using the online databases tools to select the relevant putative miRNA candidates for further functional validation. The databases rely on mostly different alignment algorithms, so we recommend choosing the miRNA target candidates highlighted in multiple tools provided lists. We emphasized the differential binding ability of specific miRNAs that display numerous binding sites in the circRNA sequence, presenting a higher critical potential, such as miR-143-3p. Even if the literature on circFOXO3 is still restrictive, the interaction between miR-143-3p and circFOXO3 has been previously investigated . The twoAs such, selecting these methods is case-specific and based on experimental design and available resources. In our case, we focused on the RNAse R and qRT-PCR optimization of the validated transcripts while also including two not yet validated circRNAs, as an initial screening of potential transcripts based on their sensitivity to RNAse R treatments.2 under saturated humidity.Immortalized human bronchial epithelial cells (BEAS-2B) and human lung cancer cell lines A549, Calu6, H522, H1792, SKMES-1 were purchased from the American Type Culture Collection ; BEAS-2B cells were cultured in BEBM serum-free medium , A549 cells were cultured in F12-K media supplemented with 10% fetal bovine serum and Calu6, H522, H1792, and SKMES-1 cells were cultured in RPMI-1640 medium  containing 10% fetal bovine serum at 37 °C and 5% COCell lines were cultured until 70–80% confluency, washed, and dissolved in TripleXtractor . Total RNA was extracted using the phenol-chloroform method, and the resulting pellet was resuspended in RNAse/DNAse-free water. DNAse treatment was carried out utilizing TURBO DNA-free™ Kit  following the manufacturer’s instructions. The resulting RNA was quantified using NanoDrop 3000 and Qubit™ RNA High Sensitivity Assay Kits  to assess the amount and quality.2, and 1 M KCl, NaCl or LiCl) in a total reaction volume of 20 µL and incubated at 37 °C for the mentioned time. For each RNA sample, a corresponding control sample was prepared in which water was added instead of RNAse R.Dilutions of 1 ug of total RNA were prepared and subjected to RNAse R treatment to deplete linear RNAs. The selected concentration of RNAse R (10 U/µL)  was added to the RNA sample with 2 µL of 10× RNAse R Buffer (0.2 M Tris–HCl (pH 8.0), 1 mM MgClThe resulting RNA from the RNAse R and untreated samples were purified using RNeasy Kit , following the manufacturer’s instructions. Total RNA was eluted in 20 µL of nuclease-free water. The resulting RNA was quantified using Nanodrop 3000 and Qubit fluorimeter . Qubit measurement was executed using Qubit™ RNA High Sensitivity (HS) assay kit using 1 µL of the RNA sample, 198 µL of kit Qubit working solution, and 1 µL of the provided fluorophore. RNA amount was normalized based on the standard curve and input. The quality of the RNA was evaluated using the Bioanalyzer 2100  RNA 6000 Nano kit using the manufacturer’s instructions. Samples with a RIN > 8 were considered adequate for further analysis.TM cDNA Synthesis Kit  in a 20 µL reaction volume in the Veriti™ 96-Well Fast Thermal Cycler . Kit-provided random hexamers instead of oligo dT primers were utilised to amplify both circular and polyadenylated RNAs non-discriminately.A total of 100 ng (based on amounts indicated from Qubit quantification) was reverse transcribed into cDNA using AzuraFlexhttps://www.realtimeprimers.com, accessed on 1 April 2022). The primer annealing temperature was assessed using a temperature gradient approach based on the calculated primer TM. Primer sequences can be found in Corresponding PCR amplification reactions using cDNA from RNAse R treated and untreated were carried out using Phusion™ High-Fidelity DNA Polymerase following the manufacturer’s instructions. circRNA primers were synthesized by RealTimePrimers  using 1 µL of 1:5 diluted cDNA from both RNAse R treated and untreated samples (with either 30 or 100 ng of RNA input). qRT-PCR assays were performed on ViiA 7 Real-Time PCR System using the recommended amplification protocol . The total reaction volume was 10 µL, and GAPDH was used to normalize and evaluate RNAse R treatment efficiency. Technical duplicates were utilized for all reactions. Utilized primer sequences are presented in https://circinteractome.nia.nih.gov, accessed on 1 April 2022) and circBank (www.circbank.cn accessed on 1 April 2022). Linear transcript sequences were downloaded from Ensembl (www.ensembl.org accessed on 1 April 2022), and the exonic circRNAs were constructed using SnapGene Software (www.snapgene.com accessed on 10 April 2022). The divergent primer design tool in the circInteractome tool was utilized for the primer design. Putative binding miRNAs were assessed using the online tools provided by the circInteractome (https://circinteractome.nia.nih.gov accessed on 15 May 2022), ENCORI-Starbase (https://starbase.sysu.edu.cn accessed on 15 May 2022), Cancer-Specific circRNA Database (http://gb.whu.edu.cn/CSCD accessed on 15 May 2022), and Circ2GO (https://circ2go.dkfz.de accessed on 15 May 2022) online databases. Venn diagrams were generated using the following online tool (https://bioinformatics.psb.ugent.be/webtools/Venn/ accessed on 15 May 2022). CircRNA-miRNA-Target gene networks were constructed using miRTargetLink 2.0 (https://ccb-compute.cs.uni-saarland.de/mirtargetlink2 accessed on 20 May 2022). Data representation was carried out using GraphPad prism 9. All data are reported as the mean ± standard deviation (SD). Statistical comparisons between two groups are made using Student’s two-tailed unpaired t-test, and p < 0.05 is considered statistically significant.Reference circRNA sequences and IDs were downloaded from circInteractome (CircRNAs have recently emerged as important players, along with miRNAs, in the dogmatic shift of post-transcriptional regulation of gene expression. While the recent influx of emerging studies has established their relevance in a plethora of mechanisms, it has also outlined the methodological shortcomings and complexity of circRNA investigations. This study provides a step-by-step overview of the critical design and optimizing steps in circRNA investigations. Our results emphasize that optimizing the prerequisite RNAse R treatment step and considering RNA quality is crucial for adequate detection of circRNAs by RT-qPCR. Such methodological developments, along with correct bioinformatic sequence assessment and consensus regarding circRNA nomenclature, will facilitate and accelerate circRNA investigations, thus offering a clear understanding of their regulatory roles and therapeutic utility.


Bombyx mori cytoplasmic polyhedrosis virus (BmCPV), an RNA virus belonging to Reoviridae, is a major pathogen of silkworm (B. mori). The genome of BmCPV consists of 10 segmented double-stranded RNAs (S1-S10) from which viral RNAs encoding a protein are transcribed. In this study, chimeric silkworm-BmCPV RNAs, in which the sequence derived from the silkworm transcript could fuse with both the 5’ end and the 3’ end of viral RNA, were identified in the midgut of BmCPV-infected silkworms by RNA_seq and further confirmed by RT-PCR and Sanger sequencing. A novel chimeric RNA, HDAC11-S4 RNA 4, derived from silkworm histone deacetylase 11 (HDAC11) and the BmCPV S4 transcript encoding viral structural protein 4 (VP4), was selected for validation by in situ hybridization and Northern blotting. Interestingly, our results indicated that HDAC11-S4 RNA 4 was generated in a BmCPV RNA-dependent RNA polymerase (RdRp)-independent manner and could be translated into a truncated BmCPV VP4 with a silkworm HDAC11-derived N-terminal extension. Moreover, it was confirmed that HDAC11-S4 RNA 4 inhibited BmCPV proliferation, decreased the level of H3K9me3 and increased the level of H3K9ac. These results indicated that during infection with BmCPV, a novel mechanism, different from that described in previous reports, allows the genesis of chimeric silkworm-BmCPV RNAs with biological functions.Polymerases encoded by segmented negative-strand RNA viruses cleave 5’-m7G-capped host transcripts to prime viral mRNA synthesis (“cap-snatching”) to generate chimeric RNA, and trans-splicing occurs between viral and cellular transcripts.  It has previously been reported that start codons with cap-snatched host transcripts or trans-splicing can generate chimeric RNAs on ssRNA and dsDNA viruses; however, whether chimeric RNAs can be generated on dsRNA viruses remains a mystery. We identified host-virus chimeric RNAs in a dsRNA virus infection model (BmCPV in silkworm), which is a novel phenomenon. What’s more, our results indicated that the selected chimeric RNA HDAC11-S4 RNA 4 (derived from silkworm histone deacetylase 11 (HDAC11) and the BmCPV S4 transcript encoding viral structural protein 4 (VP4)) was generated in a BmCPV RNA-dependent RNA polymerase (RdRp)-independent manner and could be translated into a truncated BmCPV VP4 with a silkworm HDAC11-derived N-terminal extension. Further, We found that the chimeric RNA inhibited virus proliferation and decreased histone methylation, and increased histone acetylation. That is to say, the chimeric protein has activity and provides novel functionality compared to either of the normal versions of the two components on their own. It has been known that two distinct RNA transcripts can be joined by trans-splicing to form chimeric RNA . A previ7G) cap structure for their mRNAs  A letter containing a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).Important additional instructions are given below your reviewer comments.Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.Thank you again for your submission. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.Sincerely,Laura B. Goodman, PhDGuest EditorPLOS PathogensSara CherrySection EditorPLOS PathogensKasturi HaldarEditor-in-ChiefPLOS Pathogensorcid.org/0000-0001-5065-158XMichael MalimEditor-in-ChiefPLOS Pathogens  orcid.org/0000-0002-7699-2064  ***********************Thank you for your patience in the review process. We have obtained the following reviews, which you are invited to consider and resubmit your manuscript after making the indicated changes. Please pay particular attention to the concerns raised about the appropriateness of controls and the validation of the probes for several of the experiments.Reviewer's Responses to QuestionsPart I - SummaryPlease use this section to discuss strengths/weaknesses of study, novelty/significance, general execution and scholarship.Reviewer #1: Pan et al. have discovered several novel chimeric RNAs whereby the silkworm RNA has fused with the BmCPV virus. It has previously been reported that start codons with cap-snatched host transcripts or trans-splicing can generate chimeric RNAs on ssRNA and dsDNA viruses; however, whether chimeric RNAs can be generated on dsRNA viruses remains a mystery. Here the authors use BmCPV (a dsRNA virus) infection of the silkworm to demonstrate the presence of several host-virus chimeras including HDAC11-S4 RNA4, derived from the silkworm histone deacetylase 11 and the BmCPV S4 transcript encoding viral structural protein 4 (VP4).They validated the presence of the RNA chimera using northern blot and in situ hybridization, then showed that the transcript could be translated into a truncated BmCPV CP4 with a silkworm HDAC11-derived N-terminal extension. Further, they found that the chimeric RNA inhibited virus proliferation and decreased histone methylation, and increased histone acetylation.Reviewer #2: The manuscript titled ‘A novel chimeric RNA originating from BmCPV S4 and Bombyx mori HDAC11 transcripts regulates proliferation’ by Pan et al. show the presence of host-viral chimeric RNA in the midgut of BmCPV-infected silkworms. Using RNA_seq and Sanger sequencing they observed the chimera of host histone deacetylase 11 and BmCPV S4 RNA HDAC11-S4 RNA in BmN cells transfected with cDNA of BmCPV S4 both in presence or absence of S2 cDNA encoding RNA dependent RNA polymerase (RdRp), denoting that the chimeric RNA was not mediated by RdRp. The authors make the point that this is the first instance that a RdRp independent chimeric RNA mechanism of synthesis is being observed in silkworm-infected with virus. They further demonstrate the characteristics/fate of the chimeric RNA using qPCR that the expression increases upon infection but decreases 140 hrs after infection, finally showing that these RNAs cannot be packaged into virions. By monitoring the expression of other viral genes like vp1 and protein expression of VP7, they found that the expression of viral genes were decreased when infected with these chimeric RNAs., suggesting that the chimeric RNA causes inhibition of BmCPV replication. They then observe using Western blot that this chimeric HDAC11-S4 RNA decreased trimethylation of histone 3 lysine 9 but increased the histone 3 lysine 9 acetylation, highlighting a possible biological effect of such chimeric RNA on host cells. Western blotting detection using anti-VP4 antibody in the BmCPV infected midgut cells showed not only the presence of viral protein VP4 but also a truncated NesVP4 protein product translated from another ORF starting at the N-terminal extension derived from the host RNA. NesVP4 protein product was also detected when in vitro transcribed HDAC11-S4 mRNA was transfected into the BmN cells.Overall the work is sound on technique and establishes the presence and effect of host-viral chimeric RNA in silkworms upon BmnCPV viral infection. The only issue for this reviewer is the way the text has been presented in the introduction misleads the readers to think that this work is based on yet another host-viral cap-snatching mechanism of chimeric RNA formation. On that note, the text highly resembles that of previously published papers on cap-snatching. While the introduction has tried to summarize all the diverse examples of chimeric host-viral chimeric RNA origins, it fails to lead into the main take-home of this work, which is the identification of a distinct mechanism of chimeric RNA in silkworm-infected with BmnCPV. Although chimeric RNA formation using a cap-snatching mechanism has been previously reported for many different host-virus infections, this work shows and characterizes for the first time the occurrence of silkworm-BmCPV chimeric RNA possibly generated using a different mechanism, further attempting to characterize the biological effect of this chimeric RNA in virus-infected BmN cells.Reviewer #3: Pan et al. identified host-virus chimeric RNAs in a dsRNA virus infection model (BmCPV in silkworm), which is a novel phenomenon. They do follow-up experiments with one specific chimeric RNA and suggest it may be functionally active and biologically relevant.The key experiments do demonstrate that the chimeric protein has activity but fall somewhat short of proving that the chimeric protein provides novel functionality compared to either of the normal versions of the two components on their own.**********Part II – Major Issues: Key Experiments Required for Acceptanceabsolutely required to validate study conclusions.Please use this section to detail the key new experiments or modifications of existing experiments that should be Generally, there should be no more than 3 such required experiments or major modifications for a "Major Revision" recommendation. If more than 3 experiments are necessary to validate the study conclusions, then you are encouraged to recommend "Reject".Reviewer #1: For Figure 4, since the probe targets the junction , I am surprised that no signal is observed from the control sample with no infection (I would have expected some binding to this region). Need evidence to show that the probe is binding the junction and not BmCPV on its own.I have the same concern about the FISH probe in figure 4. Need evidence to show that the probe is binding to the junction and not just the BmCPVReviewer #2: (No Response)Reviewer #3: • Lines 222-224: No data are shown to support the claim that the chimeric HDAC11-S4 RNA 4 is not packaged into virions.• Figure 6 and related text:o What was the rationale for choosing chimeric HDAC11-S4 RNA 4 for further workup? Was it the most abundant? Or was it chosen randomly?o Why did the authors not choose wild-type HDAC11 and/or the short N-terminal fragment found in the chimeric protein and/or wild-type VP4 as a control for this experiment, and also transfect that in increasing doses? This would not only be a better control in general (see my next point), it would also let them address whether this chimeric protein offers any additional functionality compared to the normal cellular HDAC11 and the normal viral VP4.o To demonstrate that the changes in vp1 RNA, VP7 protein, H3K9me3 and H3K9ac are all specific effects mediated by increasing dosages of HDAC11-S4 RNA 4, all experiments shown in this figure should be repeated with matching increasing dosages of a control RNA. Using only a single dose of GFP RNA doesn’t rule out non-specific effects.**********Part III – Minor Issues: Editorial and Data Presentation ModificationsPlease use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity.Reviewer #1: 1. Sometimes RT-PCR is referred to as PCR in the text2. It would be helpful if the sequences for BMSK_chr11 were aligned in Figure 2a and 2b (they are currently offset by a few nucleotides) and a reference sequence for BMSK_chr11 the viral inserts were aligned there as well.3. Same comment above for the other examples in figure 2 and figure 3, reference sequences would be helpful to see sequence similarities, etc.4. Did all instances of the host transcripts found in chimera form become this way, or is there still a fraction of these transcripts that does not become a chimera? Can the authors comment on or estimate the percentages?5. For figure 4, the full gel, including the size markers, should be shown rather than a cutout.6. In the methods section where the FISH experiment is described, there is a typo–streptomycin should be cy3-labeled streptavidin, and the images in figure 4 should have scale bars.7. Axis labels for figure 5Reviewer #2: Minor points:Line 268 - Rephrase for grammar error, maybe like - ‘because the host genomic DNA region integrates viral DNA and then is transcribed’Reviewer #3: • Figure 6 and related text:o If the authors want to suggest that the chimeric protein encoded by HDAC11-S4 RNA 4 is potentially biologically relevant, they should comment on its abundance. If the RNA is vanishingly rare, it will likely not matter in vivo. Their NGS data should enable the authors to discuss this point.o Lines 189-192: RNA 4 also does not match the reference sequence (see fig.3D). It has a 1nt mismatch (T895A). Do the authors think this is an artifact? Would this affect the amino acid sequence?• Figure legends are missing important information, for example:o Figure 1A: What do the red and blue lines in the centers of the Circos plots indicate?o Figure 1A: The legend should say that “BMSK_x” indicates the individual silkworm chromosomes.o Figure 1B: What are the circles at one end of the wavy lines representing transcripts?o Figures 5 and 6: What is the basis for the error bars? How many replicates are shown? Biological replicates or technical replicates? Is any of it significant?**********what does this mean?). 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Read more information on sharing protocols at  27 Aug 2023AttachmentResponse Letter of PPATHOGENS-D-23-00227.docxSubmitted filename: Click here for additional data file. 17 Nov 2023Dear Dr. Gong,We are pleased to inform you that your manuscript 'A novel chimeric RNA originating from BmCPV S4 and Bombyx mori HDAC11 transcripts regulates virus proliferation' has been provisionally accepted for publication in PLOS Pathogens.Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. 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All press must be co-ordinated with PLOS.Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Pathogens.Best regards,Sara CherrySection EditorPLOS PathogensSara CherrySection EditorPLOS PathogensKasturi HaldarEditor-in-ChiefPLOS Pathogensorcid.org/0000-0001-5065-158XMichael MalimEditor-in-ChiefPLOS Pathogens  orcid.org/0000-0002-7699-2064  ***********************************************************Reviewer Comments :Reviewer's Responses to QuestionsPart I - SummaryPlease use this section to discuss strengths/weaknesses of study, novelty/significance, general execution and scholarship.Reviewer #1: The authors have addressed all of the points from the reviewersReviewer #2: The authors have addressed my comments.**********Part II – Major Issues: Key Experiments Required for Acceptanceabsolutely required to validate study conclusions.Please use this section to detail the key new experiments or modifications of existing experiments that should be Generally, there should be no more than 3 such required experiments or major modifications for a "Major Revision" recommendation. If more than 3 experiments are necessary to validate the study conclusions, then you are encouraged to recommend "Reject".Reviewer #1: The authors have addressed all of the points from the reviewersReviewer #2: (No Response)**********Part III – Minor Issues: Editorial and Data Presentation ModificationsPlease use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity.Reviewer #1: (No Response)Reviewer #2: (No Response)**********what does this mean?). If published, this will include your full peer review and any attached files.PLOS authors have the option to publish the peer review history of their article  are generated on a different schedule and may not be made available as quickly.Soon after your final files are uploaded, the early version of your manuscript, if you opted to have an early version of your article, will be published online. The date of the early version will be your article's publication date. 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RNA velocity analysis of single cells offers the potential to predict temporal dynamics from gene expression. In many systems, RNA velocity has been observed to produce a vector field that qualitatively reflects known features of the system. However, the limitations of RNA velocity estimates are still not well understood.We analyze the impact of different steps in the RNA velocity workflow on direction and speed. We consider both high-dimensional velocity estimates and low-dimensional velocity vector fields mapped onto an embedding. We conclude the transition probability method for mapping velocity estimates onto an embedding is effectively interpolating in the embedding space. Our findings reveal a significant dependence of the RNA velocity workflow on smoothing via the k-nearest-neighbors (k-NN) graph of the observed data. This reliance results in considerable estimation errors for both direction and speed in both high- and low-dimensional settings when the k-NN graph fails to accurately represent the true data structure; this is an unknown feature of real data. RNA velocity performs poorly at estimating speed in both low- and high-dimensional spaces, except in very low noise settings. We introduce a novel quality measure that can identify when RNA velocity should not be used.Our findings emphasize the importance of choices in the RNA velocity workflow and highlight critical limitations of data analysis. We advise against over-interpreting expression dynamics using RNA velocity, particularly in terms of speed. Finally, we emphasize that the use of RNA velocity in assessing the correctness of a low-dimensional embedding is circular.The online version contains supplementary material available at 10.1186/s13059-023-03065-x. Cell cycle positions are estimated using the tricycle Bioconductor package . For thek nearest neighbors in Euclidean distance of the top 30 PCs (default setting) and assigns weights to each edge  and Here, For the velocity latent time, we cannot determine whether the latent time spans a complete period. Therefore, we fit a standard loess model instead of the periodic model described above for the velocity latent time.In the simulations, we know the true values, such as the true RNA velocity at the gene level. We use both PCC and NRMSE to quantify how good the estimations are. The NRMSE is calculated asn is the number of observations. The standard deviation of the true values Here, Additional file 1: Contains Figs. S1-S20 and supplementary notes on “The differences between implementations of RNA velocity analysis” and “Visualization of 2D vector fields”.Additional file 2. Contains the review history.


In addition to the well-known coronavirus genomes and subgenomic mRNAs, the existence of other coronavirus RNA species, which are collectively referred to as noncanonical transcripts, has been suggested; however, their biological characteristics have not yet been experimentally validated in vitro and in vivo.To comprehensively determine the amounts, species and structures of noncanonical transcripts for bovine coronavirus in HRT-18 cells and mouse hepatitis virus A59, a mouse coronavirus, in mouse L cells and mice, nanopore direct RNA sequencing was employed. To experimentally validate the synthesis of noncanonical transcripts under regular infection, Northern blotting was performed. Both Northern blotting and nanopore direct RNA sequencing were also applied to examine the reproducibility of noncanonical transcripts. In addition, Northern blotting was also employed to determine the regulatory features of noncanonical transcripts under different infection conditions, including different cells, multiplicities of infection (MOIs) and coronavirus strains.In the current study, we (i) experimentally determined that coronavirus noncanonical transcripts were abundantly synthesized, (ii) classified the noncanonical transcripts into seven populations based on their structures and potential synthesis mechanisms, (iii) showed that the species and amounts of the noncanonical transcripts were reproducible during regular infection but regulated in altered infection environments, (iv) revealed that coronaviruses may employ various mechanisms to synthesize noncanonical transcripts, and (v) found that the biological characteristics of coronavirus noncanonical transcripts were similar between in vitro and in vivo conditions.The biological characteristics of noncanonical coronavirus transcripts were experimentally validated for the first time. The identified features of noncanonical transcripts in terms of abundance, reproducibility and variety extend the current model for coronavirus gene expression. The capability of coronaviruses to regulate the species and amounts of noncanonical transcripts may contribute to the pathogenesis of coronaviruses during infection, posing potential challenges in disease control. Thus, the biology of noncanonical transcripts both in vitro and in vivo revealed here can provide a database for biological research, contributing to the development of antiviral strategies.The online version contains supplementary material available at 10.1186/s12985-023-02201-0. Coronaviridae, order Nidovirales, are common contagious pathogens of humans and animals, causing widespread and costly diseases, including COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [Coronaviruses (CoVs), which belong to the family S-CoV-2) , 4. The S-CoV-2) .During coronavirus infection, in addition to synthesis of the coronavirus genome (referred to as coronavirus replication), a 3′-coterminal nested set of subgenomic mRNAs (sgmRNAs) are also produced (in referred to as coronavirus transcription), from which structural and accessory proteins are translated . Synthescis-acting elements required for gene expression in their 5′ and 3′ termini, they are employed as surrogates for the ~ 30 kb full-length genome in studies on coronavirus replication, transcription and translation [The defective viral genome (DVG) is a mini version of the viral genome because it consists of a deleted virus genome synthesized presumably through a recombination process. DVG has been identified in most RNA viruses during infection –11. In cnslation , 13–19.In addition to the well-known coronavirus genomes and sgmRNAs described above, other coronavirus RNA species, which are collectively referred to as noncanonical transcripts, have been suggested. However, their biological features have not yet been experimentally characterized in cell cultures and animals. In the current study, with the assistance of nanopore direct RNA sequencing, the synthesis of coronavirus noncanonical transcripts was experimentally validated, and the biological features were characterized in cell cultures and animals. The identification of the biological characteristics of coronavirus noncanonical transcripts may assist the coronavirus research community in obtaining insights into coronavirus gene expression and pathogenesis and provide a database for a variety of biomedical studies.2 as previously described [The Mebus strains of BCoV (GenBank: U00735.2) and MHV-A59 (GenBank: NC_048217.1) were obtained from David A. Brian . Human rectum tumor (HRT)-18 cells and mouse L (ML) cells were also obtained from David A. Brian . BCoV was grown in HRT-18 cells , and MHVescribed . Mice we6 PFU of MHV-A59 in 500 µl of DMEM. The livers of MHV-A59-infected mice were collected at 3 days postinfection. TRIzol  was used to collect total cellular RNA from MHV-A59-infected cells and MHV-A59-infected livers according to the manufacturer’s instructions. Poly(A)-tailed RNA used for nanopore direct RNA sequencing was obtained using oligo d(T)25 magnetic beads  according to the manufacturer’s instructions.For nanopore direct RNA sequencing in vitro, HRT-18 and ML cells were infected with BCoV and MHV-A59 at a multiplicity of infection (MOI) of 0.1, and total cellular RNA was collected at 24 and 20 h postinfection, respectively. For nanopore direct RNA sequencing in vivo, 3-week-old male and specific pathogen-free BALB/c mice  were infected by intraperitoneal inoculation of 10For nanopore direct RNA sequencing, 500 ng of poly(A)-containing RNA was used for library preparation with yeast enolase II (YHR174W) mRNA as a calibration standard according to the manufacturer’s instructions . The prepared library was loaded onto an ONT FLO-MIN106D flow cell, and sequencing was conducted for 24 h on a MinION device (Oxford Nanopore Technologies).The data collected from the MinION device were base called by Guppy v5.0.11) with a qscore of 7. The base-called data were first mapped to the host genome , yeast enolase II (NC_001140.6) and virus genomes  using Minimap2 (v2.17-r941) 1 with the parameters “-k 14 -w 1 –splice -u n –MD -a -t 6 –secondary = no” to generate SAM files for analysis of the amount of the coronaviral transcripts in infected cells or mice  of 0.1, and total cellular RNA was collected at 8, 12, 24 and 48 h postinfection with TRIzol . For reproducibility, the aforementioned procedure was repeated independently with the same BCoV inoculum, and total cellular RNA was collected.For the experiment with the same HRT-18 cells infected with BCoV from different passages or origins, HRT-18 cells were infected with 0.1 MOI of BCoV inoculum . After 48 h of infection, total cellular RNA (VP0 RNA) was harvested, and the supernatant (designated VP1 BCoV) was collected to infect another batch of fresh HRT-18 cells. Total cellular RNA (designated VP1 RNA) was then harvested after 48 h of infection. For the same HRT-18 cells infected with BCoV from different cell origins, HEK-293 T cells were infected with 0.1 MOI of BCoV inoculum (VP0 BCoV). After 48 h of infection, the supernatant (designated VP1 HBCoV) was collected to infect another batch of HRT-18 cells at an MOI of 0.1. Total cellular RNA (designated VP1 HRNA) was then harvested after 48 h of infection. For HRT-18 cells infected with 0.1 and 10 MOI of BCoV inoculum, total cellular RNA (VP0 RNA) was harvested at 16 and 48 h postinfection.To obtain BCoV-p95 inoculum, HRT-18 cells were infected with BCoV. The infected cells were passaged every third or fourth day depending on the cell condition. The virus collected at 95 days from the supernatant of HRT-18 cells with persistent BCoV infection was designated BCoV-p95 (GenBank: OP296992.1). For the BCoVp95 experiment, the BCoV-p95 isolate (VP0 BCoV-p95) was used as an inoculum to infect fresh HRT-18 cells. Total cellular RNA was then collected (VP0 RNA), and the supernatant (VP1 BCoV-p95) was used to infect another batch of fresh HRT cells. The virus passage step was repeated (VP1-VP6 BCoV-p95) until VP6 RNA was collected. Total cellular RNA collected from VP0, VP4, VP5 and VP6 was used for Northern blotting.6 PFU of MHV-A59 in 500 µl of DMEM by intraperitoneal inoculation. The livers of MHV-A59-infected mice were collected at 3 days postinfection, and total cellular RNA was prepared.For determination of the synthesis of noncanonical transcripts in mice, 3-week-old male and specific pathogen-free BALB/c mice  were infected with 1032P-5′-end-labeled oligonucleotides  by vacuum blotting for 3 h, followed by UV crosslinking , prehybridization and hybridization  at 45 °C for 16 h . The memTo determine the amounts and structures of the noncanonical bovine coronavirus (BCoV) transcripts in HRT-18 cells, nanopore direct RNA sequencing was employed. Quantification by read counts revealed that ~ 30% of the total cellular RNA was BCoV transcripts  in addition to the previously well-defined genomes Fig. A and canWhile analyzing the structures of noncanonical BCoV transcripts Fig. , it is scis-acting elements, it is assumed that DVGs without sequence elements from 3′ UTR and 5′ UTR cannot replicate; thus, (+)-strand DVGs are the end products. Consequently, it is speculated that when coronavirus RdRp internally initiates (+)-strand synthesis using the (−)-strand genome as a template and acquires the sequence at the 3′ UTR to finish (+)-strand synthesis with or without template switching, (+)-strand Δ5′DVG with a 3′ but lacking a 5′ UTR is produced  and noncanonical transcripts R = 0.7473) were largely reproducible  Northern blotting can detect and quantitate noncanonical transcripts and (ii) the aim of the experiment was simply to examine whether the synthesized RNA patterns that represent the noncanonical transcripts (but not the specific RNA population) were altered under different infection conditions, a Northern blotting assay was selected for this aim. Consequently, it is hypothesized that, based on the RNA patterns detected by Northern blotting assay, whether the species and amounts are altered under different infection conditions can then be determined. We first tested whether noncanonical transcripts were reproducible when the same HRT-18 cells were infected with BCoV from different passages or origins. For this, HRT-18 cells were infected with BCoV inoculum, which was designated viral passage 0 BCoV (VP0 BCoV)  and with supernatant from different passages of BCoV-p95 (VP1-VP6 BCoV-p95)  coronavirus inoculum isolated from different cells  experimentally determined the synthesis of noncanonical transcripts, (ii) demonstrated that the species and amounts of noncanonical transcripts are largely reproducible during regular infection but can be regulated under altered infection environments and (iii) found that the characteristics of noncanonical transcripts in vivo are similar to those in cell culture. The biological significance based on the findings is as follows: (i) classification of experimentally validated noncanonical transcripts extends the current model for coronavirus gene expression; (ii) synthesis of a variety of noncanonical transcripts may assist the coronavirus genome in overcoming error catastrophe via its recombination with the transcripts under harsh environments; and (iii) the regulated noncanonical transcripts in terms of species and amounts under different environments may have the potential to contribute to the pathogenesis of coronaviruses. Consequently, the identified biological characteristics of noncanonical coronavirus transcripts may lead to further research questions, including (i) what are the molecular mechanisms driving the synthesis of noncanonical transcripts? (ii) How are noncanonical transcripts regulated in response to altered infection conditions? (iii) How do alterations of populations in noncanonical transcripts impact virus evolution and adaptation to new hosts? (iv) How do host factors impact the synthesis and activity of noncanonical transcripts? Although the current study on coronavirus noncanonical transcripts may pose challenges in the control of coronavirus diseases, the answers obtained from the aforementioned studies may contribute to the development of antiviral strategies.In the current study with BCoV and MHV-A59, we experimentally validated the synthesis and biological characteristics of noncanonical coronavirus transcripts both in vitro and in vivo. The identified features of noncanonical transcripts in terms of abundance, reproducibility and variety extend the current model for coronavirus gene expression. The capability of coronaviruses to regulate the species and amounts of noncanonical transcripts may contribute to the pathogenesis of coronavirus during infection. The identification of the biological characteristics of noncanonical coronavirus transcripts may assist the coronavirus research community in answering previously unanswered questions on coronavirus gene expression and pathogenesis and provide a database for a variety of biomedical studies.Additional file 1 of Biological characterization of coronavirus noncanonical transcripts in vitro and in vivo.


Actinidia chinensis (Ach) and Actinidia eriantha (Ace)) with markedly different degrees of disease resistance. A total of 497 and 499 PPRs were identified in Ach and Ace, respectively. All the kiwifruit PPRs could be phylogenetically divided into four subfamilies. There were about 40.68% PPRs predicted to be localized to mitochondria or chloroplasts. A synteny analysis showed that the expansion of the kiwifruit PPRs mainly originated from segmental duplication. Based on RNA-seq data from the fruit over 12 periods of development and maturity, a weighted correlation network analysis suggested that two PPRs, Actinidia20495.t1 and Actinidia15159.t1, may be involved in fruit development and maturation. In addition, we observed different responses with respect to the expression of PPRs and RNA editing between resistant and susceptible kiwifruits following infection with pathogenic bacteria, indicating the regulatory role of PPRs in the stress response via the modulation of RNA editing. The differentially expressed upstream transcription factors of the PPRs were further identified; they may regulate resistance adaption by modulating the expression of the PPRs. Collectively, these results suggest that PPRs play roles in the development and disease resistance of kiwifruit and provide candidate genes for further clarifying the resistance mechanisms in kiwifruits.Kiwifruit is a perennial fruit tree with high nutritional and economic value; however, various pathogen stresses have resulted in reductions in its yield and quality. Pentatricopeptide repeat proteins (PPRs), characterized by tandem repetitions of 35 amino acid motifs, play roles in RNA editing, mRNA stability, and splicing. They may also regulate plant development and growth. Nevertheless, the roles of PPRs in plant development and disease resistance remain unclear. In this study, we focused on the roles of PPRs in the fruit development and pathogen stress of kiwifruit and conducted a series of analyses of the PPR gene family in two representative kiwifruit species ( Actinidia chinensis, Ach), also called the Chinese gooseberry, is a type of popular horticultural fruit rich in vitamin C, dietary fiber, minerals, and other nutrients beneficial for health. Due to its enormous nutritional and economic value, the kiwifruit industry has a promising future [Pseudomonas syringae pv. actinidiae (Psa), has become one of the severe threats in the cultivation and production of kiwifruit [Actinidiae chinensis var. deliciosa in Shizuoka, Japan, in 1984, and today, it has been reported worldwide, including in China, Chile, and European countries [Actinidia chinensis (Ach), such as ‘HongYang’, ‘Hort 16A’, ‘Gold3’, and ‘Hayward’, which are generally sensitive to Psa. However, there are still certain kiwifruit species or cultivars that show resistance to Psa, such as Actinidia eriantha (Ace) cv. ‘HuaTe’. The pathogen stress represented by bacterial canker has caused severe economic losses to the kiwifruit production industry. Therefore, it is of great significance to study the disease resistance mechanism and breed a resistant germplasm in kiwifruit.Kiwifruit , organelle RNA recognition motif-containing proteins (ORRMs), protoporphyrinogen IX oxidases (PPOs), and multiple organellar RNA editing factors (MORFs), which comprise an RNA editing complex and interact with each other to mediate RNA editing ,18,19. Ang sites . PPRs cong sites . Based ong sites . Approxing sites .OsPPR11 has been proven to function in chloroplast development by affecting group II intron splicing in rice [PPRs are widely distributed across various plant lineages, comprising more than 400 family members. They have been identified in many different plants, with 450, 477, and 486 members of PPRs predicted in the genomes of Arabidopsis, rice, and foxtail, respectively . General in rice . PPRs ha in rice . With thHowever, the functions of PPRs in kiwifruit, especially their roles in disease resistance, remain unclear. Furthermore, the underlying roles of RNA editing are not fully understood. Accordingly, in this study, we conducted a comprehensive analysis to evaluate the evolution, expansion, distribution, and expression patterns of PPRs in kiwifruit, particularly focusing on the responses of expression and RNA editing profiles to pathogen infection. Based on the results, we observed that PPRs and RNA editing exhibited a noticeable response to infection, with differing responses detected in two kiwifruit varieties with different resistance levels. Additionally, we explored candidate upstream transcription factors that may regulate responses by modulating PPR gene expression. Our findings provide insights into the biological functions of PPRs in response to pathogen stress in kiwifruit and will contribute to a better understanding of the roles of RNA editing in plant immunity.Ach genome using 450 known Arabidopsis PPRs as queries. Through HMM [Ach proteins, respectively. We retained the 497 overlapping PPRs that were identified in both searches as PPRs in Ach. Similarly, we identified 499 putative PPRs in Ace. Detailed information about the results of the BLAST searches is presented in Ach, and 247, 74, 102, and 76 in Ace, respectively. In addition, the types of the identified PPRs were further verified through their phylogenetic relationships with known representative PPRs in Arabidopsis from different clades. Among the Ach PPRs, P-type PPRs were the most abundant, while DYW-type PPRs were the least common. Conversely, in Ace, P-type PPRs were the most abundant, and E-class PPRs were the least common  and esters (like ethyl butyrate) during kiwifruit development and ripening. The orthologs of Actinidia20495.t1 and Actinidia15159.t1 are PCMP-E48 and PCMP-E88 in Arabidopsis, both of which belong to the plant combinatorial and modular protein (PCMP) subfamily, specific to land plants. They mainly function in RNA binding and modification. However, their underlying molecular functions in fruit development remain to be explored.Furthermore, we utilized the turquoise module to identify the hub PPRs with higher degrees within the module. These hub PPRs can better represent the overall expression pattern of genes in this module and exhibit stronger correlations with specific characteristics . Hub genAce) and susceptible  kiwifruits during early infection of Pseudomonas syringae pv. Actinidiae (Psa), we analyzed the expression of PPRs between these two different kiwifruit species  that regulated the expression of differentially expressed PPRs (Actinidia25020 and Actinidia28434) in both ‘HongYang’ and ‘HuaTe’, indicating their common regulatory function. One TF gene, Actinidia00657, encoding dehydration-responsive element-binding protein 2C (DREB2A), was down-regulated in both ‘HongYang’ and ‘HuaTe’ and negatively regulated the expression of the PPR gene Actinidia25020 at 48 hai. Another upstream TF gene, Actinidia36651, encoding the DELLA protein (GAI1), which acts as a repressor of the gibberellin (GA) signaling pathway, was up-regulated in both ‘HongYang’ and ‘HuaTe’ and positively regulated the expression of the PPR gene Actinidia28434. These differentially expressed TFs may regulate the expression of PPR genes, thereby affecting RNA editing under pathogen stress.To explore the underlying pathways that may regulate the expression of PPRs in kiwifruit, we selected the differentially expressed PPRs at 48 hai and obtained their upstream transcription factors (TFs) from the PlantRegMap database, only keeping those that demonstrated differential expression at 48 hai. Finally, we constructed the regulatory network of PPRs and upstream TFs, consisting of 9 differentially expressed PPRs and 12 upstream TFs in ‘HongYang’, and 10 differentially expressed PPRs and 17 upstream TFs in ‘HuaTe’, as shown in Ach and Ace) with different disease resistance. A total of 497 and 499 PPRs were identified in ‘HongYang’ and ‘HuaTe’, respectively. The results indicated that the expansion of the kiwifruit PPR family mainly resulted from segmental duplication. The comparable number of families in the two kiwifruits suggest that the expansion of the PPR gene family occurred before species differentiation. Most kiwifruit PPRs were predicted to be localized in mitochondria or chloroplasts, which is consistent with studies of PPRs in other plants.Due to its richness in vitamins and antioxidants, kiwifruit has become a popular horticultural fruit with high economic value. However, various diseases threaten its yield and quality. In plants, RNA editing acts as a post-transcriptional modification and plays multiple roles in the processes of growth, development, and stress response. PPRs are important subunits of RNA editing machinery and some function as organelle-specific RNA-binding proteins, thereby playing a crucial role in RNA editing regulation. PPRs are extensively distributed across plant lineages, comprising more than 400 family members . Some PPAce) and susceptible  kiwifruits during the early stages of Psa infection. This analysis allowed us to investigate the expression of PPRs between these two different kiwifruit varieties. For both kiwifruit varieties, the largest number of differentially expressed PPRs was observed at 48 hai after infection, indicating a critical immune response at this time point. These results indicated that PPRs also play a role in responding to Psa infection, highlighting their involvement in plant immunity. When comparing differentially expressed PPR genes, we found that more differentially down-regulated PPRs were detected than up-regulated ones in both kiwifruit varieties, particularly in ‘HuaTe’. Moreover, ‘HuaTe’ exhibited a greater number of differentially expressed PPRs compared to ‘HongYang’, with larger fold changes in gene expression. We also investigated the corresponding RNA editing events in chloroplasts and observed a reduction in or loss of editing efficiency in some sites, particularly in ‘HuaTe’, following Psa infection. Based on these results, we propose that PPRs may play a role in regulating RNA editing and the response to disease resistance in kiwifruit. Furthermore, we identified several transcription factors associated with PPRs, including DREB2A, and GAI1. These differentially expressed transcription factors may regulate the expression of kiwifruit PPRs in response to both development processes and stress conditions.Based on RNA-Seq data during kiwifruit’s fruit development and maturation, we observed differential expression patterns of PPRs at various time points, suggesting their involvement in fruit development. Additionally, we conducted further transcriptome analysis using RNA-seq data from resistant  of both PPR and MORF genes in kiwifruit , as well as decreased RNA editing in resistant kiwifruit. ndhB encodes the subunit B of the chloroplast NADH dehydrogenase-like complex (NDH), which constitutes an important component of cyclic electron flow (CEF) in photosystem I. Therefore, we speculated that the reduced editing efficiency of these genes may trigger impaired CEF, leading to the activation of reactive oxygen-mediated retrograde signaling and significantly enhanced disease resistance to pathogens , which act as key defense molecules in the plant immune response . Therefotivities . In thisathogens . PPR andAch and Ace were retrieved from NCBI , with versions ‘ASM966300v1’ and ‘White_v1.0’, respectively. Using the known 450 PPRs in Arabidopsis as the query reference [http://pfam.sanger.ac.uk/, accessed on 15 January 2022) domain PF01535, and sequences containing fewer than two PPR motifs were excluded. The phylogenetic tree was constructed using the maximum likelihood (ML) method implemented in MEGA v5.2 [The genome sequence and annotation files of eference , includieference . FinallyEGA v5.2 . Based ohttps://www.genscript.com/psort.html, accessed on 1 May 2022) to predict the putative subcellular localization of kiwifruit PPRs. In addition, the physical distribution of the PPRs on chromosomes was obtained from the genome annotation files, and a sketch map of the genes’ physical locations was drawn using TBtools v2.001 [We used TargetP v2.0 , Predotas v2.001 .Ach and Ace. Based on the self-blast results, we used the ‘Duplicate_gene_classifier’ command of MCScanX to clarify the origins of the duplicate genes into several types, including whole-genome/segmental, tandem, proximal, or dispersed duplications. All intragenomic synteny relationships were visualized using Tbtools v2.001 [We conducted a self-blast by comparing proteins against their respective genomes using BLASTP v2.13.0+ with an E-value of 0.00001. All BLASTP hits were then used as inputs for the MCScanX v1.0  softwares v2.001 .Ach, RNA-seq data of fruit samples were retrieved from the NGDC database  under the accession number PRJCA003268 [Ach and Ace, RNA-seq data of leaves in response to Psa after early infection were retrieved with accession number PRJNA514180 [https://bioconductor.org/packages/release/bioc/html/edgeR.html, accessed on 1 July 2022). A heatmap of gene expression was generated using Tbtools v2.001 [To examine the expression profiles of kiwifruit PPRs, we performed transcriptome analysis using two sets of RNAseq data. For CA003268 . Six devNA514180 . TranscrNA514180 . We meass v2.001 .Ach, we employed WGCNA v1.0 [Using RNA-seq data obtained from fruit samples of CNA v1.0  to identTo begin, we mapped all the RNA-seq data against the chloroplast genome reference using HISAT2 v2.2.1 software with default parameters . We utilhttp://plantregmap.gao-lab.org/, accessed on 10 July 2022) to retrieve the transcriptional regulatory map of kiwifruit [https://www.uniprot.org/, accessed on 20 July 2022), and we visualized the regulatory relationships using Cytoscape v3.8.2 [We employed the PlantRegMap database (iwifruit . The date v3.8.2 .Ach and Ace, and provided their expression patterns at different stages of fruit development and under pathogen stress. The results showed that PPRs were differentially expressed at various stages of fruit development and maturation, indicating their role in kiwifruit’s fruit development and maturation. Differences in the expression and RNA editing profiles of PPRs between resistant and susceptible kiwifruit were observed after pathogen infection, indicating the roles of PPRs in the stress response. Similar to MORF genes, PPRs were also associated with resistance and influenced RNA editing sites in chloroplasts. This suggests that RNA editing involving PPR and MORF genes may be linked to chloroplast-mediated immunity. The findings of this study will serve as a reference for further understanding the molecular mechanism of plant immunity and for breeding kiwifruit varieties with enhanced resistance.In conclusion, this study analyzed the chromosomal positions, phylogenetic relationships, and evolution of PPRs in


RNA turnover pathways ensure appropriate gene expression levels by eliminating unwanted transcripts. Dis3-like 2 (Dis3L2) is a 3′–5′ exoribonuclease that plays a critical role in human development. Dis3L2 independently degrades structured substrates, including coding and noncoding 3′ uridylated RNAs. While the basis for Dis3L2’s substrate recognition has been well characterized, the mechanism of structured RNA degradation by this family of enzymes is unknown. We characterized the discrete steps of the degradation cycle by determining cryogenic electron microscopy structures representing snapshots along the RNA turnover pathway and measuring kinetic parameters for RNA processing. We discovered a dramatic conformational change that is triggered by double-stranded RNA (dsRNA), repositioning two cold shock domains by 70 Å. This movement exposes a trihelix linker region, which acts as a wedge to separate the two RNA strands. Furthermore, we show that the trihelix linker is critical for dsRNA, but not single-stranded RNA, degradation. These findings reveal the conformational plasticity of Dis3L2 and detail a mechanism of structured RNA degradation. The authors employ cryogenic electron microscopy and kinetic analysis to characterize the discrete steps of how the Dis3L2 3′–5′ exoribonuclease recognizes and degrades structured RNA targets. Dis3L2 targets are oligouridylated by the terminal uridylyl transferases (or TUTs)16. The specificity toward uridylated RNAs is conferred through a network of base-specific hydrogen bonds along the protein’s extensive RNA-binding surface, as demonstrated by the structure of Mus musculus Dis3L2 (MmDis3L2) in complex with a U13 RNA17.RNA quality control and turnover are vital for cellular function, yet little is known about how nucleases deal with the diverse universe of structured RNAs. Dis3-like 2 (Dis3L2) is an RNase II/R family 3′–5′ hydrolytic exoribonuclease that plays an important role in development and differentiation1. The first reported physiological substrates of Dis3L2 were the uridylated precursors of let-7 microRNAs13, which play an important role in stem cell differentiation by silencing growth and proliferation genes such as HMGA2, MYC and Ras23. Many other noncoding RNA targets have since been reported, including other microRNAs25, transfer RNA fragments16, small nuclear RNA26, the intermediate of 5.8S ribosomal RNA processing 7SB27, the long noncoding RNA RMRP28, and the 7SL component of the ribonucleoprotein signal recognition particle required for endoplasmic reticulum-targeted translation7. The latter is probably responsible for the Perlman syndrome phenotype, with aberrant uridylated 7SL leading to endoplasmic reticulum calcium leakage that perturbs embryonic stem cell differentiation, particularly in the renal lineage7.Genetic loss of Dis3L2 causes Perlman syndrome, a congenital overgrowth disorder that is characterized by developmental delay, renal abnormalities, neonatal mortality and high rates of Wilms’ tumors29. Little is known about how Dis3L2 or other capable RNase R/II family nucleases independently degrade structured RNA. We determined the structures of an RNase R/II family nuclease bound to a series of structured RNA substrates and analyzed the kinetic profiles of wild-type Homo sapiens Dis3L2 (HsDis3L2) and engineered mutants to reveal how this nuclease achieves highly efficient degradation of structured RNA.Unlike a number of structurally similar homologs, Dis3L2 can degrade structured RNAs independent of external helicase activityD391N residues 1–858: carboxy (C)-terminal truncation of residues 859–885; and an engineered catalytic mutation of Asp for Asn at residue 391 in Dis3L2) (see 13) (root mean square deviation (RMSD) = 1.2 Å, calculated over all Cα pairs)17. Thus, the apoenzyme is preorganized to bind single-stranded RNA (ssRNA).To understand the presubstrate binding state, we used cryogenic electron microscopy (cryo-EM) to determine the structure of RNA-free HsDis3L2 to 3.4 Å resolution (construct Dis3L23L2) see . RNA-fre3L2) see . The OB 3L2) see . The ove14 (16-nucleotide) overhang as the uridylated tail  and also forms numerous base-specific hydrogen bonds with the protein ein Fig. . As in tnel Fig. , which c12; Fig. 12 in which the double-helical stem of the RNA hairpin is clearly visible and nestled between the two CSDs and the S1 domain . The basal junction of the hairpin interacts with the S1 and CSD1 domains, while the apical loop interacts with CSD2 , since this is the minimal ssRNA length needed to reach the active site from the opening to the tunnel , is no longer pointing towards the S1 domain and N663 as it is in the vase conformation (nucleotide U28 in hairpinA–GCU14)  Fig. . Instead14) Fig. .Fig. 5ThUpon close examination of our cryo-EM data, we noticed that heterogeneous refinement yielded not only the high-resolution structure of the prong, but also a smaller three-dimensional (3D) class representing the vase  and elementary rate constants for RNA binding (association (kon) and dissociation (koff)) and degradation (forward step (kf)) for wild-type and mutant forms of Dis3L2 at single-nucleotide resolution  as a substrate , requiring approximately three binding events before cleaving the first nucleotide , or when the overhang was composed purely of Us (hairpinA–U16) .Using a 5′ ate Fig. , we founide Fig. . This maide Fig. . This pakoff decreases . The kon also decreases with RNA length, probably due to the loss of substrate interaction points (fewer 3′ U binding sites) necessary for stable association  or nonproductively. Examples of the latter include: the terminal nucleotide not binding fully into the active site; misorientation of the RNA; or a nonproductive/inactive conformation of Dis3L2. We observe roughly tenfold tighter nonproductive compared with productive binding for the very first step  that mimic the 3′ end of the 7SL RNA  and one hairpin with a longer stem (hairpinI–GCU14)  and takes the longest to reach the very high processivity seen with hairpinA–GCU14 in the second phase, possibly due to the bulkiness of this substrate. The 7SL mimic hairpinF–U16 (P16 = 0.21 ± 0.026) and hairpinI–GCU14 (P16 = 0.28 ± 0.080), which both harbor a single hairpin, have a kinetic profile more similar to hairpinA–GCU14. Nevertheless, the overall features for all these substrates are similar.To assess whether these observations could be applicable to other substrates, we carried out additional processivity analyses of Dis3L2 degradation on two hairpins   Fig. . This shK½ = 4.2 ± 0.41 nM (wild type) versus 8.5 ± 0.73 nM (ΔCSD)) and removing them improves the productive binding fivefold (productive K½ = 508.3 ± 1.27 nM (wild type) versus 97.7 ± 0.35 nM (ΔCSD)). During the following ssRNA degradation steps, ΔCSD has a similar processivity to wild-type Dis3L2   led to lower processivity for the very first step, largely due to a lower forward rate constant, indicating that the CSDs play a role in augmenting the rate of catalysis for the first nucleotide cleavage Fig. . Further3L2 Fig. . Howeverff) Fig. . Thus, t7 complex structure shows that the trihelix linker provides the final barrier before the narrow tunnel to the active site, suggesting a role in dsRNA unwinding. Deletion of the trihelix and linker (residues P612–M669: Δ123H) has a striking effect on substrate degradation and a buildup of intermediate species is observed at lengths close to the start of the double strand of hairpinA–GCU14  increases significantly and the forward rate (kf) plateaus, leading to a dramatic drop in processivity and a buildup of species with three- and two-nucleotide overhangs . While the RNA substrate provided was only 13 nucleotides in length, electron density for 14 nucleotides was observed. This was due to two different positions of the RNA: with the 3′ end either right in the active site (in a productive configuration) or removed away by one nucleotide, leaving the active site open. The latter position represents a nonproductive state. Nonproductive binding has been measured in other nucleases such as RRP6 (ref. 30).An example of nonproductive binding was observed in the crystal structure of MmDis3L2 –U through its CSDs. This enabled the production of Rac1b, an isoform that promotes transformation and tumorigenesis3.The large contribution from nonproductive binding might indicate that Dis3L2 functions in other roles that do not require nuclease activity. A recent study of hepatocellular carcinoma appears to have identified one such case31. The Dis3L2 homolog in Saccharomyces cerevisiae, Ssd1, is an example of this, losing both canonical RNase II/R catalytic residues and acquiring a loop insertion that blocks the tunnel to the active site. Ssd1 has been reported to act as a translational repressor of certain messenger RNAs involved in cell growth and cytokinesis, and deletion of Ssd1 was found to have pleiotropic effects on stress tolerance32.Evolutionary analysis of Dis3L2 has revealed that the protein has lost nuclease activity at least four times during fungal evolution, while the CSDs have remained conserved, thereby suggesting a role for the protein outside of RNA degradation7 with known structures of RNase R/II family nucleases suggests that most would have to undergo a similar conformational change to allow the double-stranded portion of the RNA access to the trihelix linker wedge. Biochemical studies of Escherichia coli RNase R have also demonstrated the importance of the trihelix in dsRNA degradation33, suggesting that the mechanism proposed here could be conserved in other members of the RNase R/II family of nucleases. Collectively, this work unveils a molecular mechanism for efficient, regulatory degradation of structured RNAs by a vital nuclease.Combining our cryo-EM and kinetic data, we propose the following model: RNA degradation by Dis3L2 proceeds via a minimum of six sequential steps: 1) substrate association and quality control; (2) initial nucleotide cleavage; (3) 3′ single strand degradation; (4) double strand engagement; (5) dramatic domain realignment; and (6) concurrent double strand unwinding and degradation Fig. . During  substrat34. Benchling (https://www.benchling.com) was used for sequence analysis and primer design. Expression and purification followed a similar protocol to that detailed by Faehnle et al.17. All constructs were expressed in SF9 cells grown in HyClone CCM3 Media (Thermo Fisher Scientific) at 27 °C for 60 h. Cells were then pelleted and resuspended in wash buffer (50 mM Tris (pH 8), 100 mM NaCl and 5 mM dithiothreitol (DTT)) and a protease inhibitor cocktail was added before snap freezing with liquid N2 for storage at −80 °C. After thawing, cells were lysed by increasing NaCl to 500 mM, followed by one round of sonication. 0.1% poly-ethylene imine was added to the lysate and cell debris were cleared by 45 min of ultracentrifugation at 35,000 r.p.m. and 4 °C. The solution was then incubated with Strep-Tactin Superflow resin (IBA BioTAGnology) for 30 min while on a rolling shaker. The slurry was applied to a gravity column and washed with 20 column volumes of wash buffer before eluting the protein with 2 mM desthiobiotin in wash buffer. The Strep-Sumo-TEV tag was cleaved using TEV protease overnight at 4 °C. Cleavage efficiency and sample purity were assessed by sodium dodecyl sulfate polyacrylamide gel electrophoresis. The protein was then diluted to a final salt concentration of 50 mM in 25 mM HEPES (pH 7.5) and 5 mM DTT and applied to a HiTrap Heparin HP affinity purification column (GE Life Sciences) equilibrated in 50 mM NaCl, 25 mM HEPES (pH 7.5) and 5 mM DTT. The bound protein was eluted by applying a linear increasing salt gradient (0.05–1 M NaCl). Pooled fractions of protein were then concentrated and loaded onto a 10/300 Superdex 200 Increase gel filtration column (GE Life Sciences) equilibrated in 20 mM HEPES (pH 7.5), 150 mM NaCl and 5 mM DTT. Protein purity was assessed by the quality of the chromatogram and by running sodium dodecyl sulfate polyacrylamide gel electrophoresis gels. The concentrated sample was frozen in liquid N2 and stored at −80 °C.Full-length human Dis3L2, mutants with domain deletions, point mutations, and HsDis3 were cloned as amino (N)-terminal Strep-Sumo-TEV fusion proteins in a pFL vector of the MultiBac baculovirus expression systemhttp://rna.tbi.univie.ac.at) and diagrams were made using Forna , 150 mM NaCl and 5 mM DTT and heated to 95 °C for 3 min before stepwise cooling . Complexes of human Dis3L2 and various RNAs were prepared by mixing equimolar ratios of Dis3L2 and RNA, incubating for 15 min and loading onto a 10/300 Superdex 200 Increase gel filtration column (GE Life Sciences) equilibrated in the same buffer . Next, 4 µl of sample was applied to glow-discharged grids and a Vitrobot plunger (Thermo Fisher Scientific) was used to freeze the grids in liquid ethane .RNA oligos were purchased from Dharmacon, then RNA secondary structure predictions were done using the Vienna RNAfold web server  were imported into CryoSPARC where 2D classification was done. A subselection of particles were made taking the best 2D classes with the highest resolution (below 4 Å for those that led to a high-resolution structure) and largest particle number  with protein-like features. This particle selection was then used in multiclass ab initio reconstruction. The classes were evaluated and then used as starting references for heterogeneous refinement, this time using all of the good particles from Warp’s picking process. The best heterogeneous refinement classes and their particle subsets were then used for homogeneous refinement and in some cases nonuniform refinement in CryoSPARC 40. The Dis3L2–hairpinA–GCU14 dataset was also processed in Relion using their 3D classification, refinement, contrast transfer function refinement and particle polishing43. Two representative workflows (processing of the Dis3L2D391N–hairpinA–GCU14 and Dis3L2–hairpinD–U7 datasets) are shown in Supplementary Fig. Data were collected on a 300 kV Titan Krios electron microscope at either 160,000× (0.67 Å pixel size) or 130,000× (0.64 Å pixel size) on a Gatan K2 or K3 detector equipped with an energy filter. A similar pipeline was used for all datasets (see below). Representative micrographs are provided in Supplementary Figs. 8 #2, hairpinD–U9 #2 and hairpinD–U7 #2); and (4) the resulting five ab initio models were used as starting references for heterogeneous refinement using all of the good particles found by the WarpEM picker  particles from the datasets were picked using WarpEM’s neural network-based picker; (2) good particles were then classified in CryoSPARC’s 2D classification; (3) the best 2D classes (as described above) were selected for ab initio reconstruction using five classes  accession code 4PMW) was used as a starting reference for model building17. Once the reference structure was fit into the cryo-EM map, Real-Space Refine was used, with morphing, simulated annealing and rigid body fit in the first rounds45. After manual building and correction of geometric outliers and clashes using Coot, further rounds of refinement were done using secondary structure restraints, as well as global minimization, refinement of atomic displacement parameters (B factors) and local grid search. Refinements of complexes with RNA contained further base pair and base stacking restraints in the double-stranded regions. RNA–protein interactions were found with PDBePISA (https://www.ebi.ac.uk/pdbe/pisa/) and examined manually. Final model validation metrics are provided in Table 48.Atomic model building and refinement were done in Coot and Phenix (version 1.18-3855-000)2, 1 mM DTT and Dis3L2 were preincubated for 5 min. Presteady-state reactions were started by the addition of 5′ radiolabeled RNA substrate to a final concentration of 1 nM. The concentrations of Dis3L2 were in far excess of the RNA and ranged from 5–1,000 nM, as indicated. Measurements were taken at the time points 7 s, 15 s, 30 s, 1 min, 2 min, 3 min, 5 min, 10 min and 15 min, except for long-time-course experiments for which the times are indicated , 50 mM NaCl, 5% glycerol, 100 µM MgClt1). At t1, an excess of cold scavenger RNA  was added to a final concentration of 5 µM. After incubation for the indicated time (t2), aliquots were removed and quenched in stop buffer. Samples were analyzed on sequencing gels and processed as for the above-described presteady-state reactions.Pulse–chase reactions were performed under conditions identical to those for presteady-state reactions. Reactions were initiated by the addition of enzyme and allowed to proceed for a defined period of time , processivity values (P) and K½ and kobsmax values for each reaction species. Observed rate constants (kobs) were calculated from presteady-state experiments by fitting each experiment separately using the global data-fitting software GFIT52 to a model that calculates rate constants for a series of irreversible, pseudo-first-order reactions. Initial parameters for GFIT were obtained by fitting the disappearance of a 34-nucleotide substrate to a first-order exponential: y = a1 × exp(−b1 × t) + c, where a1 is the amplitude, b1 is the observed rate constant (kobs) and c is the offset. Processivity values for individual degradation steps were determined from the distribution of substrate species before and after scavenger addition30  was defined as: P = kf / (kf + koff).Kinetic parameters were obtained using a global fit of the data from presteady-state titrations and pulse–chase experiments. Global data fitting was performed using the Kinetic Explorer software 30. To derive the K½ and kobsmax values, we fit kobs versus Dis3L2 concentration data to a binding isotherm function defined as: kobs = (kobsmax × [Dis3L2]) × (K½Dis3L2 + [Dis3L2])−1. K½ is the functional equilibrium dissociation constant and kobsmax is the maximal observed rate constant at enzyme saturation  were used as initial constraints on the ratio of kf and koff. The global data fit was done in an iterative manner by alternating combinations of fixed and floating variables while tracking the overall χ2 value. The goodness of the fit, R2 = 0.94, was calculated by plotting the experimental datasets versus the corresponding simulated data from the kinetic model K½, were calculated via the error propagation formulas shown below.Errors for elementary rate constants represent standard errors of the mean from the global data fitting. Errors for compound rate constants, such as processivity and Further information on research design is available in the Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41594-023-00923-x.Supplementary InformationSupplementary Tables 1–4 and Figs. 1–14.Reporting SummaryPeer Review FileSupplementary Video 114. The the complex of Dis3L2 with hairpinA–GCU14 represents initial substrate binding, at which point the dsRNA is not engaged by the enzyme. After shortening of the overhang to roughly 12 nucleotides, the double helix is cradled between the S1 and CSD domains, shown here by the structure of the complex of Dis3L2 with hairpinC–U12. When the overhang length is roughly eight nucleotides long, the structured portion of the RNA substrate would clash with the enzyme and triggers a dramatic 70 Å domain movement of CSDs to the other side of the enzyme. A morph created in ChimeraX shows the transition between the vase and prong conformation, with the side view of the transition highlighting the large distance that the CSDs travel. This conformational change exposes the trihelix linker that acts as a wedge to separate the two RNA strands and shortens the approach to the active site. The double helix is further stabilized by the S1 domain in the structure of the complex of Dis3L2 with hairpinD–U7.Structural changes during the different stages of structured RNA degradation by Dis3L2. The RNA-free Dis3L2 and domain composition in the vase conformation are shown, followed by the complex of Dis3L2 with hairpinA–GCU