Organ transplant shortages are ubiquitous in healthcare systems around the world. In response, several commentators have argued for the adoption of an opt-out policy for organ transplantation, whereby individuals would by default be registered as organ donors unless they informed authorities of their desire to opt-out. This may potentially lead to an increase in donation rates. An opt-out system, however, presumes consent even when it is evident that a significant minority are resistant to organ donation. In this article, we defend a mandated choice framework for consent to deceased organ donation. A mandated choice framework, coupled with good public education, would likely increase donation rates. More importantly, however, a mandated choice framework would respect the autonomous preferences of people who do not wish to donate. We focus in particular on the Australian healthcare context, and consider how a mandated choice system could function as an ethical means to increase the organ donation rate in Australia. We make the novel proposal that all individuals who vote at an Australian federal election be required to state their organ donation preferences when voting. Each year, several hundred organ donors across Australia provide organ transplants for the country’s healthcare system via the national organ donor program DonateLife. Currently, there are roughly 1700 people on the waitlist for organs in Australia, with another 12,000 people on dialysis who would benefit considerably from a kidney or liver donation , or would be a stand-alone requirement for citizens. In our view, citizens should also be required, with appropriate frequency, to reconsider their status as a potential organ donor. That is to say, citizens should be required to revisit their organ donation preferences at regular intervals throughout their lives, as their donor preferences might change with time. Health authorities, furthermore, should fund extensive public education programs so that people can make a truly informed decision about becoming an organ donor.To be clear, a mandated choice is different from a nudged choice. ‘Nudging’ involves attempts to indirectly or subconsciously influence the kinds of options that people choose in a decision situation. We are not concerned with this. Rather, we are concerned with requiring that people make a choice, whatever their decision might eventually be. We would advocate public education about organ donation, but this is different from attempts to indirectly or subconsciously influence the behavior of social agents . We also propose that one’s decision to donate should be revisited each time an individual votes, so that any changes in their decision be recorded on a regular basis. This could occur roughly every 3 years during an Australian federal election. Such a system would not impose any undue or additional burdens on citizens, but would still allow for a regular reconsideration of one’s decision about being a donor, and would give a relatively current picture of one’s preferences with respect to organ donation.For this system to be effective, there would need to be a consequence for those who abstain from registering their decision to donate. Without this, there is the risk that some may ignore or avoid answering the question, thus undermining the concept behind mandated choice. We propose that there be a small financial penalty for people who do not respond to the question of organ donation status—proportionate to the penalty for failing to vote during a federal, state, or council election in Australia. Those who receive a penalty notice should have the opportunity to overturn the fine if they subsequently register their decision to donate through an online portal.impeding consent to organ donation. Over a quarter of registrants said ‘no’ to donation when registering or renewing their driver’s license  for several years had a driver registration procedure that asked registrants about their organ donation preferences. This system was discontinued in 2012 due to concerns that it was actually ense ABC .For a system of mandated choice to be both ethical and effective, it must be preceded by and coupled with far-reaching public education campaigns. Without this, there is a risk that organ donation rates may be reduced, much like what was seen in NSW with the driver registration procedure. We believe that improved public education campaigns about organ donation would help to remedy this issue. There is sufficient empirical evidence to suggest that public education assists in increasing organ donation rates. A 2006 American study of 490 high school students from Michigan, for example, found that a web-based intervention educating participants about the process of organ donation and organ transplantation led to a statistically significant increase in knowledge about issues related to organ donation and an increased likelihood of registering as an organ donor —each person completing a care plan should convey the details of the plan to family members. This would assist the family in being able to ‘let go' of their loved one when the time comes. Family members are much less likely to overrule the prior decision of the person to donate organs if those conversations have been had, not just once but again and again (Bloomer et al. Indeed, education and public awareness are in some ways even more important than a mandated choice system; we do not want our argument to be construed as an attempt to put the horse before the cart. We do, however, believe that both education and a mandated choice framework will be necessary to achieve adequate rates of organ donation in Australia to meet demand.We believe that a system of mandated choice and informed consent would be the most ethical step forward to meeting the needs of the Australian healthcare system for increased organ donation. We have argued that a mandated choice system is more effective in promoting donation than an opt-in system. Indeed, it is more in line with community views on the importance of organ donation. A mandated choice system is also more respectful of patient preferences than an opt-out system. Health authorities should seriously consider a mandated choice framework as a policy option in Australian states and territories. Further research into public education campaigns surrounding organ donation would also be of immense benefit to policy makers. In any case, policy makers ought to closely review the significant contributions to the literature in recent years that present strong evidence in favor of the adoption of a mandated choice framework for organ donation (Lin et al.


Extensive adenosine-to-inosine (A-to-I) editing of nuclear-transcribed mRNAs is the hallmark of metazoan transcriptional regulation. Here, by profiling the RNA editomes of 22 species that cover major groups of Holozoa, we provide substantial evidence supporting A-to-I mRNA editing as a regulatory innovation originating in the last common ancestor of extant metazoans. This ancient biochemistry process is preserved in most extant metazoan phyla and primarily targets endogenous double-stranded RNA (dsRNA) formed by evolutionarily young repeats. We also find intermolecular pairing of sense-antisense transcripts as an important mechanism for forming dsRNA substrates for A-to-I editing in some but not all lineages. Likewise, recoding editing is rarely shared across lineages but preferentially targets genes involved in neural and cytoskeleton systems in bilaterians. We conclude that metazoan A-to-I editing might first emerge as a safeguard mechanism against repeat-derived dsRNA and was later co-opted into diverse biological processes due to its mutagenic nature.  •A-to-I editing is a regulatory innovation originating in the ancestor of metazoans•Evolutionarily young repetitive elements are the primary targets of A-to-I editing•Editing on pairing regions of sense-antisense transcripts is common in some species•Recoding editing convergently targets neural and cytoskeleton systems in Bilateria Zhang et al. profile the RNA editomes of 22 species that cover major groups of Holozoa. Their findings support ADAR-mediated A-to-I editing as a metazoan innovation, which might have first emerged as a safeguard mechanism against repeat-derived dsRNA and was later co-opted into other biological processes due to its mutagenic nature. For example, A-to-I editing is found to occur widely in eumetazoans from coral to humans,Here, we leveraged a matching DNA and RNA sequencing strategy with an optimized RES-Scanner frameworkCaenorhabditis elegans,Acromyrmex echinatior,Octopus bimaculoides,We performed whole-genome DNA sequencing (DNA-seq) and strand-specific RNA-seq on 18 species, including 14 metazoans and four unicellular eukaryotes closely related to animals. For each species, two to three (mostly three) specimens were sequenced to serve as biological replicates, with the average DNA and RNA coverage achieving 75× and 45×, respectively, for each specimen after sequence alignment . TogetheTwo complementary methods were adopted to identify the RNA-editing sites for each species. Briefly, we first employed RES-ScannerTrichoplax adhaerens, a morphologically simple metazoan from Placozoa.We detected very few putative RNA-editing sites (ranging from 23–519) in the four unicellular relatives of metazoans . No domiADAR homologs in the genomes and transcriptomes of the 22 species and classified these homologs into ADAR1, ADAR2, or the catalytically inactivated ADAD based on protein phylogenetic analyses. We found that ADARs exist in all investigated species except T. adhaerens and the unicellular taxa, and more importantly, most metazoans, including the ctenophore and the sponge, have orthologs of human ADAR1 and ADAR2 (ADAR1 and one ADAR2 existed in the last common ancestor (LCA) of extant metazoans. Second, our phylogenetic analysis placed the previously unclassified orphan ADAR of Hydra vulgaris in the ADAR2 clade, suggesting that this model cnidarian underwent a secondary loss of the ancestral ADAR1 during evolution, a scenario that is also observed in insects,ADADs were only identified in some protostomes and deuterostomes but are sister groups of all metazoan ADAR1s  and the sea urchin Strongylocentrotus purpuratus (86%), in sharp contrast with the low percentages  reported previously, which were probably due to inaccurate repeat annotation.,We found that in almost all investigated metazoans, including the earliest branching lineages (ctenophore and sponge), repetitive elements were unambiguously the primary targets of A-to-I editing and harbored on average 83% of the identified editing sites A. Of notWe further compared the editability of different genomic elements by counting the number of editing sites per million transcribed adenosine sites  for each type of genomic element. This revealed that the editability of genic elements  was close to the whole-genome average level in all metazoans. In contrast, repetitive elements, especially DNA transposons, short interspersed nuclear elements (SINEs), and long interspersed nuclear elements (LINEs), usually showed the highest editability C and S3CDrosophila flies and the sea squirt Ciona savignyi represent rare exceptions regarding the primary genomic targets of A-to-I editing, with only 13%–24% of editing sites residing in repetitive elements  of the C. savignyi genome sequences were annotated as repeats, a ratio comparable to many other metazoan genomes  of repeat sequences achieving ≥2× RNA coverage , and, particularly, the sea squirt , implying that bona fide recoding sites are likely scarce or absent in these three species. In contrast, the octopus has one to two orders of magnitude more recoding sites than other metazoans  genes and caused aspartic acid (polar) to glycine (nonpolar) recoding in the NADH-binding domain (LYSMD3) gene  that appeared exactly in the same position in two apoptosis-inducing factor 3 (g domain B and oneD3) gene C. The prD3) gene B and 5C.,ADAR2 in the neural systems of species from these lineages might have contributed to this preference pattern.,,,To systematically uncover the functional preference of genes subjected to recoding, we next conducted Gene Ontology (GO) enrichment analyses for the recoded genes in each species. In agreement with previous reports, we found that the recoded genes were significantly enriched in ion transport and synaptic signal functions in multiple bilaterian lineages, confirming the important role of A-to-I recoding in modulating neural function+ channels (encoded by shab), which are well known to display the same recoding events on two highly conserved amino acid residues within the ion transport domain among insects, cephalopods, and even human.However, despite the genes involved in neural and cytoskeleton functions frequently appearing as the recoded targets across metazoan lineages, we could only identify one to several recoding sites shared by species from two closely related phyla or shared by species within the same phylum E. This iADAR gene family, which encodes the putative adenosine deaminases, originated in the LCA of extant animals,,,Acropora millepora,,,ADARs.While it has been proposed that the ADAR gene presumably evolved from a tRNA-specific adenosine deaminase progenitor (ADAT) through the acquisition of double-stranded RNA binding domains (dsRBDs) that allowed it to work on dsRNA substrates.,ADAR1 and ADAR2 and the catalytically inactivated ADAD observed in extant metazoans.,,ADAR1 and ADAR2 could be clearly dated back to the LCA of modern metazoans. The first ADAD arose probably in the LCA of modern metazoans as well, and the most parsimonious explanation is in the LCA of bilaterians. This challenges a previous view that ADADs originated after Urochordata-Vertebrata divergence.ADAR1 is responsible for hyper-editing of repetitive elements in diverse tissues, while ADAR2 mainly accounts for editing of isolated sites within CDS regions, suggesting a functional divergence between the two ADAR members.A. echinatior and the hydra H. vulgaris retain only a single ADAR2 in their genomes but still display high editing activity in repetitive regions. This suggests that ADAR2 has taken over the hyper-editing role of ADAR1 in these species. A possible explanation is that both ADAR1 and ADAR2 were capable of hyper-editing repetitive elements in stem metazoans, while functional divergence occurred later in some lineages.The first ,,,GRIA2 could be rescued by replacing the unedited GRIA2 allele with the edited allele in the genome.Another remarkable feature of metazoan A-to-I mRNA editing is its prevalence across the animal kingdom, as revealed by our data. Secondary loss of the editing machinery is only observed in Placozoa. This raises a question about the primary driving force for the selective constraint of the editing machinery since it originated in stem metazoans. RNA editing is generally viewed as a repair mechanism that corrects harmful DNA mutations at the RNA level in eukaryotes,,,,Schmidtea mediterranea suggested a bilaterian ancestral role of A-to-I editing in suppressing the activation of harmful dsRNA responses.,T. adhaerens with secondary loss of the editing machinery also lacks RLRs in its genome.Alternatively, recent studies in humans and mice demonstrate that A-to-I editing of endogenous dsRNAs formed by inverted repeats plays a key role in preventing cellular sensing of self dsRNA as nonself , thus avoiding autoinflammation.,,ADARs.The evolutionary constraint of metazoan A-to-I editing is also reflected in the common substrate preference  across distantly related species. This finding might be of particular value for ADAR-based RNA engineering, such as the recently reported approaches that recruit endogenous ADAR to specific transcripts for site-directed RNA editing in human cells and mice,,As an evolutionary novelty that could introduce single-nucleotide mutations into RNA sequences and that has been firmly established since the LCA of modern metazoans, it is rational to expect that the A-to-I editing mechanism could offer a chance to elaborate the gene regulatory networks during the long-course evolution. This could help explain the versatile characteristics of metazoan A-to-I editing uncovered thus far in model species, including protein recoding, RNA relocalization, the influence of RNA splicing and stability, and the interaction with the RNAi pathway.,PCA3 inactivates the tumor-suppressor gene PRUNE2 at the RNA level through an ADAR-mediated mechanism and promotes malignant cell growth.C. elegans.C. savignyi, this mechanism is particularly noteworthy for future investigation given that the majority of A-to-I editing sites in our C. savignyi samples indeed came from sense-antisense pairing regions.Interestingly, in some of the examined metazoans, we found dozens to hundreds of cases with extensive editing of the pairing regions of sense-antisense transcripts. Although once thought to be negligible in mammals,,,,The phenomenon of recoding editing has gained additional research interest, as it has the potential to diversify the proteomes or to compensate for harmful DNA mutations.ADAR gene family, we cannot ascertain which ADAR member(s) encodes the catalytically active enzymes in most examined species. The reason is that duplicated genes could undergo functional divergence through processes such as neofunctionalization and subfunctionalization.ADAR members might have been shifted from catalyzing A-to-I editing to other functions in a focal lineage during the long course of evolution. In addition, while our findings suggest that ADAR-mediated A-to-I editing might serve as a common regulatory mechanism involved in transposon safeguarding, in antisense-mediated gene regulation, and in protein recoding of neural and cytoskeletal genes in diverse metazoans, following up experimental assays of the RNA-editing sites will be necessary to explore their detail biological functions.In this work, we trace the origin and evolution of A-to-I mRNA editing along the phylogeny of Holozoa. While our analyses indicate that A-to-I mRNA editing is a metazoan innovation acquired by the LCA of extant animals via the origin of the liqiye@genomics.cn).Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Qiye Li , geographical origin and providers of each species were listed in ,Mnemiopsis leidyi (three whole adults), the sponge Amphimedon queenslandica (three biopsies from three adults), the sea anemone Nematostella vectensis (three whole adults), the sea hare Aplysia californica (three whole juveniles), the oyster Crassostrea gigas (three whole adults after removing shells), the sea urchin Strongylocentrotus purpuratus , the acorn worm Ptychodera flava (three whole adults), the lancelet Branchiostoma belcheri (three whole adults), the sea squirt Ciona savignyi (two whole adults) and the zebrafish Danio rerio (three whole adults).To rule out that false positives resulted from genetic variation during RNA-editing site identification, matching DNA and RNA sequences generated from the same individual/specimen are the ideal data for use in RNA editing studies.Hydra vulgaris , the fruit fly Drosophila melanogaster , and Drosophila simulans .For metazoan species from which a single individual is not sufficient to allow the simultaneous extraction of sufficient DNA and RNA for sequencing library construction, 10-15 individuals with similar genetic background were pooled together, then both genomic DNA and total RNA were extracted from the same pool of organisms after the whole pool was ground in liquid nitrogen. These included the hydra Sphaeroforma arctica , the filasterean Capsaspora owczarzaki (three cultures), the choanoflagellate Salpingoeca rosetta (three cultures) and Monosiga brevicollis (three cultures), and the metazoan Trichoplax adhaerens (three cultures).For the unicellular species and tiny metazoan species, biomass was first increased by the propagation of a single colony with the same genetic background, then both genomic DNA and total RNA were extracted from the same culture of organisms. These included the ichthyosporean S. rosetta and M. brevicollis was extracted using the RNAqueous Kit . The quality of the RNA samples was assayed by the Agilent 2100 Bioanalyzer  before RNA-seq library construction. In summary, a total of 53 DNA and 53 RNA samples were obtained in this study. After quality control before library construction, two out of the three RNA samples of M. brevicollis and one out of the three RNA samples of N. vectensis were discarded due to poor RNA integrity (RIN <6).Genomic DNA of all species was extracted with the phenol/chloroform/isopentanol (25:24:1) protocol. The integrity of the DNA samples was assayed by agarose gel electrophoresis  before DNA-seq library construction. Total RNA of all species except the choanoflagellates was extracted using TRIzol Reagent according to manufacturer’s protocol . Total RNA of the choanoflagellates The strand-specific RNA-seq libraries for all the RNA samples were prepared using the TruSeq Stranded mRNA LT Sample Prep kit  with 1 μg total RNA as input, then sequenced on the Illumina HiSeq 4000 platform using the PE100 chemistry, according to the manufacturer’s instructions .The genomic DNA samples were either sequenced on an Illumina HiSeq 4000 or a BGISEQ-500RS platform. For the Illumina DNA libraries, 1 μg genomic DNA per sample was fragmented by a Covaris ultrasonicator, followed by end repair, 3′-end addition of dATP and adapter ligation. The ligated fragments were then size selected at 300 bp on an agarose gel and amplified by 10 cycles of PCR. The amplified libraries were purified using the AxyPrep Mag PCR Clean-Up Kit  and then sequenced on the Illumina HiSeq 4000 platform using the PE100 chemistry according to the manufacturer’s instructions . The BGISEQ DNA sequencing libraries were prepared using the MGIEasy DNA Library Prep Kit  with 1 μg genomic DNA as input, and sequenced on the BGISEQ-500RS platform using the PE100 chemistry according to the manufacturer’s instructions . Details about the sequencing platform and data production for each sample were presented in (i)Quality control for raw sequencing data-G -l 20 -q 0.2 -E 60 -5 1 -Q 2.(ii)Adjustment of reference genome with DNA-seq dataAll the DNA- and RNA-seq reads were first submitted to SOAPnuke--fix snps was set, using the original reference genome FASTA and the DNA BAM files as input. It is noteworthy that we only adjusted SNPs in the reference genomes in order to ensure that the adjusted genomes from different samples of the same species have the same length and the same coordinate system. The version and source of the original reference genome for each species were listed in (iii)Identification of RNA-editing sites with RES-ScannerGiven that many samples were collected from wild animals, which have high levels of heterozygosity, or were from strains which are genetically different from those used for assembling the reference genomes, we employed Pilon(iv)Identification of hyper-editing sitesRNA-editing sites from each sample were first identified by RES-Scanner, a software package that was designed to identify genome-wide RNA-editing sites with matching DNA- and RNA-seq data from the same individual or specimen.Given that most metazoan A-to-I editing sites tend to occur in clusters, the heavily edited RNA reads  which contain many of the same type of substitutions in relation to the reference genome, often fail to be aligned during normal alignment process. In order to capture these hyper-edited reads and the clusters of editing sites they harbor, we next performed hyper-editing detection for each sample following a scheme originally proposed by Porath et al.positive reference, with all As transformed to Gs, and the second version was named the negative reference, with all Ts transformed to Cs.We first collected the RNA read pairs that could not be aligned to the adjusted reference genome or that had mapping quality <20 from the RNA BAM files generated by the RES-Scanner pipeline as described above. We then removed the read pairs for which one or both reads contained more than 10% of Ns along their lengths, or had particularly large (>60%) or small (<10%) percentage of a single-type nucleotide as recommended by Porath et al.positive and negative references by BWA-ALN with parameters -n 0.02 -o 0, yielding the positive and negative alignments, respectively. Then, we filtered both alignments by removing read pairs that were not aligned to the reference genome concordantly, and the reads within concordantly aligned pairs that had mapping score <20. In addition, for positive alignment, we further required that the first read in a pair was the reverse complement of the reference genome, while the second read was aligned to reference genome directly; for negative alignment, we required that the first read in a read pair was directly aligned to reference genome, while the second read was the reverse complement of the reference genome.Next, the transformed read pairs were aligned to both the After the strict quality control for the BWA alignments, we converted the transformed reads to their original sequences, followed by trimming the first and last 10 bases of each read in the alignments. Then we identified hyper-edited reads by requiring the mismatch rate of a trimmed read to be >5%, and the proportion of the expected mismatches (i.e. A-to-G substitution in this example) against all mismatches to be >60% as recommended by Porath et al.(v)Combing the results of RES-Scanner and hyper-editing detectionThe above hyper-editing detection method was undertaken for all of the 12 possible substitution types of RNA editing in each sample of a species, and the results from all the 12 substitution types were combined together by discarding those sites that presented different editing types in any single genomic position.k, n, p), where p was set to be the maximal probability of an RNA base to be a sequencing error , n was equal to the total read depth of a given candidate editing site, and k denoted the number of reads supporting editing. We also used the DNA-seq data from multiple samples to further remove false-positives resulted from genetic variants, by discarding those editing sites for which the genomic DNA showing the same type of substitution as RNA editing  in any one of the multiple DNA samples. RNA-editing sites that displayed different editing types in different samples of a species were also discarded. See To generate the representative RNA-editing sites for a species, and to improve the identification of editing sites in each sample, we combined the editing sites identified by RES-Scanner (step iii) and hyper-editing detection (step vi) in each sample, to obtain a comprehensive map of potentially editable positions in the reference genome of each species. Specifically, if a genomic position was identified as an editing site in either method, we respectively added the numbers of RNA reads supporting editing, and the number supporting non-editing as generated by these two methods. We then retrieved the missed editing sites in each sample in these editable positions using the criteria of at least one RNA read supporting editing and the false discovery rate (FDR)Caenorhabditis elegans ,Acromyrmex echinatior ,Octopus bimaculoides i to v) as described above.To increase the phylogenetic coverage of the investigated species, we collected the matching DNA-seq and strand-specific RNA-seq data from the nematode Protein-coding genes (GFF/GTF and corresponding cds/pep FASTA files) were downloaded from public databases along with the reference genomes, of which the sources were presented in --rf, followed by removing those reads that could be mapped to multiple positions of the genome. Then, transcribed regions with continual RNA depth ≥ 5X were extended from the 5′- and 3′-end of each representative ORF to serve as initial 5′- and 3′-UTRs, respectively. Next, an iterative process was used to further recruit the upstream or downstream transcribed regions that were apart from, but linked by ≥ 5 junction reads to previously defined UTRs. If a gene had different 5′- or 3′-UTRs annotated in different samples, the longest one was chosen as the representative 5′- or 3′-UTR for this gene.5′- and 3′-UTRs for the representative ORFs were annotated using the RNA-seq data used in this study, for all the species except for human. Briefly, RNA-seq reads that passed quality control as described above were first aligned to the reference genome of each species by HISAT2Nematostella vectensis , Drosophila melanogaster (GenBank: NP_569940.2), Caenorhabditis elegans , Crassostrea gigas , Strongylocentrotus purpuratus , Ciona intestinalis (GenBank: XP_002128212.1), Danio rerio  and Homo sapiens  collected from NCBI were used as queries to search for ADAR/ADAD genes in the public reference genome and the de novo transcriptome assemblies  and using Mrbayesprset aamodelpr = fixed(Wag); lset rates = invgamma; mcmcp ngen = 1000000 nchains = 4 samplefreq = 100 burnin = 200), respectively. The AD peptide sequences used for phylogenetic analysis were aligned using PRANK.ADAR genes annotated in each species, including the coding nucleotide sequences, protein sequences, domain annotations are presented in Phylogenetic analysis of ADARs and ADADs identified above, were performed with the adenosine-deaminase (AD) domains  and the transposable element protein database with RepeatProteinMask . For de novo prediction, RepeatModeler was executed on the genome assembly to build a de novo repeat library for each species, respectively. Then RepeatMasker was employed to align the genome sequences to the de novo library for identifying repetitive elements. We also searched each genome assembly for tandem repeats using Tandem Repeats FinderMatch = 2 Mismatch = 7 Delta = 7 PM = 80 PI = 10 Minscore = 50 MaxPeriod = 2000. To confirm the reliability of our annotations, we compared our repeat annotation results of the fruit fly Drosophila melanogaster and the zebrafish Danio rerio with those downloaded from UCSC and observed good consistency  have been well annotated and thus were downloaded from UCSC directly. Repetitive elements in the genomes of the rest species were identified by homology searches against known repeat databases and sistency A and S3BFor each sample of a species, we considered a genomic region containing ≥3 A-to-I editing sites, of which the distance for two adjacent sites was ≤30 nt, as an RNA-editing cluster. The genomic locations of the first and last editing sites in a cluster were assigned as the start and end genomic positions of this cluster. A-to-I editing sites located in the defined editing clusters were regarded as clustered editing sites. To estimate the expected ratio of A-to-I editing sites occurring in clusters in each sample assuming that A-to-I editing randomly occurs in the genome, we randomly selected an adenosine site with comparable RNA depth  for each editing site in a sample, and calculated the ratio of these control adenosine sites occurring in clusters. The significance levels for the difference between the observed and expected ratios were examined by two-tailed paired t-tests in each species B.To compare the editability of different genomic elements, including the protein-coding gene related elements  and the repeat-associated elements , we calculated the A-to-I editing density for each type of genomic element by counting the number of A-to-I editing sites located in this element type, out of the total number of transcribed adenosines (RNA depth ≥ 2X) from this element type. The editing density of each element type was first calculated for each sample of a species separately, then the mean editing density across samples was calculated as the representative value for a species C.We also calculated the editing-level-weighted editing densities for each element type , then divided into 10 equal bins with the same transcribed repeat loci in each bin. Next the editing density for each bin was calculated, as the number of A-to-I editing sites located in repeat loci belonging to this bin, divided by the total number of transcribed adenosines (RNA depth ≥ 2X) from the repeat loci in this bin. The editing density of each bin was first calculated for each sample of a species separately, then the mean editing density across samples was calculated as the representative value for a species. The relationships between repeat divergence rate and editing density in all species were displayed by a heatmap as presented in -F F -e 1e-2. Then a repeat or non-repeat derived genomic site was regarded as locating in a potential dsRNA region formed by intramolecular folding, if a reverse-complement alignment was detected with identity ≥80%, aligned length ≥50 nt, and the aligned region of the query sequence spanned this randomly selected site. The ratio of such sites against all randomly selected sites was calculated to represent the potential of repeat or non-repeat regions to form dsRNA in a species, and the same process was iterated for 100 times to estimate the distribution and significance level , we extracted a 401 nt sequence centered on each editing site, then searched this query sequence against a 4001 nt sequence centered on corresponding editing site using BLASTN with parameters -K N -T binomial -C nucleo_weblogo -y. Specifically, for each species, the eleven-nucleotide sequences with the edited adenosines in the center were used as the foreground dataset, while the eleven-nucleotide sequences centered by the transcribed (RNA depth ≥ 2X) but unedited adenosines locating within ±50 nt of the edited adenosines, were used as the background dataset for Two Sample Logo analysis. Nucleotides were plotted using the size of the nucleotide that was proportional to the difference between the foreground and background datasets  or Ensembl Metazoa  via the BioMart function. For Hydra vulgaris, Aplysia californica, Acromyrmex echinatior, Ptychodera flava and Branchiostoma belcheri that do not have publicly available GO annotations, we first aligned all the proteins of these species to the UniProt database (release-2019_04) using BLASTP-F F -e 1e-5. Then the best hit of each query gene was retained based on its BLASTP bit score, and the GO annotations of this best hit was assigned to the query gene.GO annotations for the protein-coding genes were downloaded from Ensembl (D. melanogaster and D. simulans were only counted once here) were considered as the functional categories preferred by recoding editing in metazoans  annotated to this GO term, and the number of background genes not annotated to this GO term. p-values were adjusted for multiple testing by applying FDR,etazoans D.-maxiters 1000 and filtered poorly aligned positions using Gblocks.D. melanogaster and D. simulans were removed. Only recoding sites in which the mean editing levels were no less than 0.1 across samples of a species, or were shared by at least two samples, were used in this analysis. The complete list of recoding events shared by multiple species was presented in To identify recoding events shared by two or more species E, we firM. leidyi, A. queenslandica, A. californica, C. gigas, A. echinatior, P. flava, B. belcheri, D. rerio and H. sapiens; n = 2 for H. vulgaris, N. vectensis, D. melanogaster, D. simulans and C. savignyi), except for C. elegans , O. bimaculoides  and S. purpuratus (across three gonads and three non-gonad tissues). Information regarding statistical significance is provided in the figures, with “∗” representing p < 0.05, “∗∗” p < 0.01 and “∗∗∗” p < 0.001.All statistical analyses were performed in R. The statistical test used is indicated in figure legends or method details. In


Orthornavirae. Genes with RdRp domains from various RNA viruses were clustered based on amino acid sequence similarities. A multiple sequence alignment was generated for each cluster, and a hidden Markov model (HMM) profile was created when the number of sequences was greater than three. We further refined 426 HMM profiles by detecting RefSeq RNA virus sequences and subsequently combined the hit sequences with the RdRp domains. As a result, 1,182 HMM profiles were generated from 12,502 RdRp domain sequences, and the dataset was named NeoRdRp. The majority of NeoRdRp HMM profiles successfully detected RdRp domains, specifically in the UniProt dataset. Furthermore, we compared the NeoRdRp dataset with two previously reported methods for RNA virus detection using metatranscriptome sequencing data. Our methods successfully identified the majority of RNA viruses in the datasets; however, some RNA viruses were not detected, similar to the other two methods. NeoRdRp may be repeatedly improved by the addition of new RdRp sequences and is applicable as a system for detecting various RNA viruses from diverse metatranscriptome data.RNA viruses are distributed throughout various environments, and most have recently been identified by metatranscriptome sequencing. However, due to the high nucleotide diversity of RNA viruses, it is still challenging to identify novel RNA viruses from metatranscriptome data. To overcome this issue, we created a dataset of RNA-dependent RNA polymerase (RdRp) domains that are essential for all RNA viruses belonging to  MoreoveRiboviria based on the classification system of ICTV . Orthornavirae is a major kingdom of Riboviria containing all dsRNA and ssRNA viruses, but excluding retroviruses, which harbor RNA-dependent RNA polymerase (RdRp). RdRp genes may be used as markers for most RNA viruses; however, their nucleotide and amino acid sequences markedly vary, and some have been identified as fusion genes with other protein motifs  . The RdRp construction bioinformatics pipeline and constructed RdRp dataset, including annotation, are publicly available online (https://github.com/shoichisakaguchi/NeoRdRp).The present study collected RdRp domain sequences from 23,410 RNA viruses and clustered them based on their similarity to build 1,182 hidden Markov model (HMM) profiles. Since a HMM profile is based on a multiple sequence alignment, it may identify distantly related sequences more efficiently than a pairwise-based search (https://www.ncbi.nlm.nih.gov/labs/virus/vssi/) on June 9, 2021. These datasets are referred to as Wolf-RdRps and NCBI-RNA-virus, respectively, in the present study.A total of 4,620 amino acid sequences containing RdRp domains annotated by Wolf and his colleagues (The UniProt Knowledgebase (UniProtKB) containing manually curated protein sequences and functional information concerning 565,928 genes (UniProtKB Reviewed [Swiss-Prot] 2021-05-11) .https://www.ncbi.nlm.nih.gov/orffinder/).In addition, potential RNA virus genome sequences obtained from the marine metatranscriptomic analysis by fragmented and primer ligated dsRNA sequencing (FLDS) were used as a benchmark dataset  with Linux OS (Ubuntu 18.04.6 LTS) was used to benchmark each bioinformatics program.https://github.com/shoichisakaguchi/NeoRdRp.The schematic procedure for constructing RdRp HMM profiles is shown in https://github.com/shoichisakaguchi/NeoRdRp.We also conducted comprehensive similarity searches using 426 HMM profiles with 18,790 amino acid sequences of 4,239 RefSeq RNA virus genomes downloaded from NCBI Virus (named NCBI-RNA-Virus). A total of 7,463 viral amino acid sequences were obtained through the HMM search. The amino acid sequences obtained were combined with Wolf-RdRps, resulting in 12,502 amino acid sequences named “NeoRdRp-seq”. By applying the same procedure to construct HMM  with an E-value 1E-10 threshold. Out of 1,182 HMM profiles, 1,012 were evaluated; each hit was scored 1 if “RNA-directed 5′-3′ RNA polymerase activity” (GO:0003968) was included and 0 if it was excluded. We then calculated the mean value of the scores for each NeoRdRp-HMM profile, as summarized in Supplementary i.e., 10 amino acids) were obtained , including 228 sequences annotated as genes with the RdRp domain. The dataset of translated amino acid sequences was named FLDS-data.We benchmarked the ability of NeoRdRp-HMM and NeoRdRp-seq to identify RNA viruses using potentially complete RNA virus genome and genome segment sequences obtained by FLDS associated with marine RNA viromes ; hmmsearch using RVDB-prot took 7 min 11 s; and the search using VirSorter took 11 min 45 s. Furthermore, the database size required for each analysis was 0.37 GB for NeoRdRp, 1.61 GB for RVDB-prot, and 11.3 GB for VirSorter2 . Therefore, users may modify NeoRdRp-HMM using their own sequences. Accordingly, future updates to NeoRdRp-HMM with additional identified RdRp sequences will reduce undetected RdRp sequences and false-positive hits.Nucleic acid contamination from DNA viruses, hosts, and environments may occur when analyzing RNA viromes. To overcome this issue, techniques to selectively extract and sequence RNA virus-derived nucleic acids, such as the FLDS method . Using tThe NeoRdRp dataset was based only on genes containing RdRp domains. Our approach has advantages in the accuracy of RNA virus identification from highly diversified metatranscriptome data, particularly for the presence of known viruses. Since NeoRdRp cannot identify non-RdRp genes in RNA viruses, the NeoRdRp dataset may be applied for RNA virus detection and annotation from metatranscriptome data as the following research design; the assembly of metatranscriptomic data, a subsequent ORF search for each contig, and the RdRp domain identification of each ORF using NeoRdRp-HMM. If more RNA virus sequences are required, further searches using NeoRdRp-seq are expected, but may produce more false-positive hits  and thishttps://github.com/shoichisakaguchi/NeoRdRp). Furthermore, by updating NeoRdRp with new RdRp sequences, it will be possible to find more RdRp sequences with higher accuracy levels from various metatranscriptome data, which may become an essential technique for discovering unknown RNA viruses.In conclusion, NeoRdRp may detect various RdRps with a high degree of accuracy , and theMicrobes Environ 37: ME22001.Sakaguchi, S., Urayama, S., Takaki, Y., Hirosuna, K., Wu, H., Suzuki, Y., et al. (2022) NeoRdRp: A Comprehensive Dataset for Identifying RNA-dependent RNA Polymerases of Various RNA Viruses from Metatranscriptomic Data. https://doi.org/10.1264/jsme2.ME22001Supplementary Material 1Supplementary Material 2


Entamoeba histolytica with esterified 3′ss and 5′ss. Their 5′ss GU-rich elements are essential for their biogenesis and their suggested role in transcription regulation. Here, we explored whether exonic, exonic-intronic, and intergenic circular RNAs are also part of the E. histolytica and E. invadens ncRNA RNAome and investigated their possible functions. Available RNA-Seq libraries were analyzed with the CIRI-full software in search of circular exonic RNAs (circRNAs). The robustness of the analyses was validated using synthetic decoy sequences with bona fide back splice junctions. Differentially expressed (DE) circRNAs, between the virulent HM1:IMSS and the nonvirulent Rahman E. histolytica strains, were identified, and their miRNA sponging potential was analyzed using the intaRNA software. Respectively, 188 and 605 reverse overlapped circRNAs from E. invadens and E. histolytica were identified. The sequence composition of the circRNAs was mostly exonic although different to human circRNAs in other attributes. 416 circRNAs from E. histolytica were virulent-specific and 267 were nonvirulent-specific. Out of the common circRNAs, 32 were DE between strains. Finally, we predicted that 8 of the DE circRNAs could function as sponges of the bioinformatically reported miRNAs in E. histolytica, whose functions are still unknown. Our results extend the E. histolytica RNAome and allow us to devise a hypothesis to test circRNAs/miRNAs/siRNAs interactions in determining the virulent/nonvirulent phenotypes and to explore other regulatory mechanisms during amoebic encystment.Ubiquitous eukaryotic non-coding circular RNAs regulate transcription and translation. We have reported full-length intronic circular RNAs (flicRNAs) in  From their discovery 45 years ago ,2, the wcis-elements. Alu repeats in flanking introns facilitate circularization by looping out of one or more exons [Backsplicing is also activated by splicing proteins and re exons ,8, and Cre exons . In addire exons ,11,12. Fre exons ,13.In keeping with their localization, circRNAs have different functions. Those with exonic sequences localize mainly to the cytoplasm and perform regulatory functions such as microRNAs and protein sponging, translation regulation, mRNA stability, and 5′ cap-independent translation ,16,17,18Shortly following its release from the spliceosome, a lariat becomes a circular intronic molecule after trimming off the 3´-end tail and before it is hydrolyzed by the debranching enzyme (Dbr1). However, numerous introns show cis-elements that confer them stability and accumulate inside the cell, like the stable sequence introns (sisRNAs) . SisRNAsEntamoeba histolytica is the causative agent of amebiasis, a neglected tropical disease that still accounts for 55,500 deaths and nearly 2.4 million disability-adjusted life years [E. histolytica [E. histolytica [Dictyostelium discoideum also [Entamoeba are the stress-induced self-circularized 5′-external transcribed spacer rRNAs in E. histolytica [E. invadens [fe years . Much eftolytica . In agretolytica , the 5′stolytica . We obsetolytica . Strikintolytica . Notwithtolytica  confirmetolytica . miRNAs eum also . Other ntolytica  and the invadens .E. histolytica and if they enable the onset of parasitic infections and invasive diseases. To address this question, we mined available RNA-seq libraries in search of circular exonic transcripts with miRNA sponging potential differentially expressed (DE) in HM1:IMSS (virulent) and Rahman (avirulent) E. histolytica strains. We also searched for circular transcripts in the reptile parasite E. invadens. After validation of the software using synthetic decoy sequences with bona fide back splice junctions (BSJ), we identified 188 and 605 reverse overlapped (RO) circRNAs from the E. invadens and E. histolytica libraries, respectively. The sequence composition of the identified circRNAs was mostly exonic. A total of 416 circRNAs from E. histolytica were virulent-specific and 267 were avirulent-specific. In addition, out of the common circRNAs, 32 were DE between strains, showing no correlation between intron length or the number of introns per locus with the number of circRNAs produced in a given locus. Finally, we predicted that eight of the DE circRNAs could function as sponges of the reported miRNAs in E. histolytica, whose functions are still unknown. Our results allow us to devise a working hypothesis to test the relationships between circRNAs and miRNAs in determining virulent/nonvirulent phenotypes and to explore additional regulatory mechanisms during amoebic trophozoite to cyst differentiation.To cope with protist and bacterial infections, recent works proposed that hosts’ immune response trigger circRNAs–miRNAs–mRNA regulatory networks ,32,33. HE. histolytica and E. invadens, available RNAseq libraries [E. histolytica (run access codes ERR058005–ERR058007 for the virulent HM1:IMSS strain and ERR058008–ERR058010 for the avirulent Rahman strain) and four E. invadens (run access codes GSM4108195–GSM4108198) libraries were used, and the access codes for the reference genomes were GCF_000208925 and GCA_000330505.CircRNAs were identified based on backspliced RO reads as described previously  , and 585 circRNAs were associated with a particular locus , peaking at 140 nt  of circRNAs between the virulent and avirulent strains. To this end, the normalized expression of circRNAs between samples was analyzed. Box plot analysis and principal components analysis (PCA) both show that the circRNAs from the three avirulent replicas have similar distribution and variation, whereas the circRNAs from one of the virulent samples are distributed slightly different and appear to have more variation than the other two samples, while separated from the avirulent circRNAs  and overexpressed (red dots) in the E. histolytica virulent strain with respect to the avirulent strain ; one circRNA has one exon element, and the other two have two exonic elements.Despite the circRNAs . The nort strain ; thus, assess DE . HoweverE. histolytica strains substantially differ  analysis focusing on metabolic processes. Clearly, the metabolic processes potentially regulated by the circRNAs from virulent and avirulent Entamoeba. For instance, according to their prediction score, the GRIP domain RUD3 circRNAs 01_169670 and 18_169670 could potentially sponge Ehi-miR-18, Ehi-miR-136, Ehi-miR-160, Ehi-miR-50, Ehi-miR-88, and Ehi-miR-82, and Ehi-miR-17, Ehi-miR-18, Ehi-miR-160, and Ehi-miR-50, respectively.When we searched for circRNAs sponging potential, remarkably, eight of the twenty DE circRNAs were predicted to have one or more Ehi-miRNA-like target sites , suggestE. histolytica, we used RT-PCR to amplify circRNA 01_169670 , and the rest of the circRNA-producing loci have corresponding orthologs with other amoebozoans. Three circRNAs have orthologs with the free-living Mastigamoeba balamuthi , and fifteen have more than one E. histolytica orthologs. Remarkably, locus EIN_461630 which codes for the splicing factor U1-70 kDa, produced three different circRNAs and has two E. histolytica orthologs.Since mature cyst formation is reached after 72 h incubation in an encystment medium, the circRNAs found in trophozoites transcriptomes were also filtered, including the intergenic circRNAs whose cell-stage expression profile cannot be univocally assigned, thus 40 cyst-specific circRNAs were identified . InteresE. invadens and their corresponding E. histolytica orthologs  circRNAs  we can envisage a circRNA-Eh-miRNA-mRNA virulence/avirulence regulatory network in which, for example, the translation of a virulence-related mRNA could be repressed by an avirulent regulatory Eh-miRNA-like molecule, and such translation repression could be relieved by the overexpression of a virulent regulatory circRNA, which will titter the avirulent regulatory Eh-miRNA (or silencing RNA molecules), and vice-versa. Recently, additional small RNA and antisense reported ,49. HoweSo far, regulatory networks have been predicted at the transcriptional level using the Bayesian inference . Here, wE. invadens and E. histolytica libraries, respectively. The identified circRNAs were mostly exonic. 416 circRNAs from E. histolytica were virulent-specific, 267 were avirulent-specific, and 32 were shared between strains. From the latter, 32 were DE between strains, showing no correlation between intron length or the number of introns per locus with the number of circRNAs produced in a given locus. Finally, we predicted that eight of the DE circRNAs could function as sponges of the reported miRNAs in E. histolytica, whose functions are still unknown, although other epigenetic regulatory roles must be also explored. Our results allowed us to devise a working hypothesis to test the relationships between circRNAs and miRNA-like molecules in determining virulent/nonvirulent phenotypes and to explore additional regulatory mechanisms during amoebic encystment. Furthermore, the in silico prediction of circRNAs in this study would facilitate a deeper comprehension of regulatory epigenetic processes in such pathogenic amoebic protozoa. However, E. histolytica virulence is widely variable worldwide across several strains, and the relevant mechanisms controlling the differential virulent expression need to be investigated more prospectively.In conclusion, we identified 143 and 605 reverse overlapped circRNAs from the E. histolytica RNA-Seq libraries were downloaded from the European Bioinformatics Institute, project PRJEB2766 (Available online: https://www.ebi.ac.uk/ena/browser/view/PRJEB2766?show=reads (21 September 2022)). Three libraries were from the HM1:IMSS virulent strain  and three from the Rahman avirulent strain  were used. Total RNA E. invadens RNA-Seq libraries were downloaded from the GenBank GEO database (Available online: htpps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138449 (21 September 2022)). Four libraries from 24 h encystment induced E. invadens  were used.Total RNA The quality control of the RNA libraries was made using the FASTQC (v0.11.8) and Trimmomatic (v0.39) software packages. To detect and quantify the linear RNAs, we improved the STAR-HTSeq pipeline. STAR software (v2.7.10a)  was usedDEseq2 and ggplot2 to build the normalization of the expression counts, differential expression, statistical analysis, and plots.To make the differential expression of linear RNAs and circRNAs, we used the R-base (v4.1), Rstudio IDE (v1.1.4), and the R libraries E. histolytica strains and E. invadens were uploaded and analyzed by the amoebaDB web (https://amoebadb.org) (accessed on 16 August 2022) to obtain the annotation, GO terms and GO enrichment analysis for each locus. Finally, with this data, we used the Revigo web tool (http://revigo.irb.hr) (accessed on 16 August 2022) to build the GO enrichment graph, and, with Rstudio IDE (v1.1.4), the graph was visualized.GO analyses were carried out using the AmoebaDB data analysis suite. The gene ID of all detected circRNAs in both To assess the prediction of circRNAs as sponges of miRNAs, we used the software intaRNA , which iE. histolytica. These reads were constructed by fragments of this locus to make 10 RNA library decoy reads with a length of 100 nucleotides which includes a BSJ. Additionally, we prepared the RNA libraries extracting 10% of all RNA reads, and we identified the circRNAs presented in this modified library with the described method. Next, we included the 10 artificial reads to this modified library and reidentified the circRNAs in the library.We designed in silico RNA decoy reads from exon end sequences of the locus EHI_110740 of E. histolytica locus EHI_169670 (E2as 5′CTTCTTTTTCTTTTTCTAATTCTTCACCC3´ and E2s 5′AAGAAAGTTAATGATTCTGAGAAAGAG3′) was designed as described [Total RNA was isolated using the TRIzol Reagent as specified by the manufacturer (Invitrogen). For circular RNA isolation, preparations were treated with RNase R (Epicentre). Outward-facing primers targeted the second exon of escribed  for the escribed . PCR proescribed  and were


Ziziphus Jujuba cv. Muzao polysaccharides, ten samples were successfully extracted from aqueous and alkaline solutions, prepared via DEAE-Sepharose Fast Flow through different eluents and Sephacryl S-300 columns, and systematically analyzed. Their characteristics were studied and then compared using chemical testing, high-performance gel permeation chromatography (HPGPC), gas chromatography (GC), methylation analysis, and NMR spectroscopy. The data achieved demonstrated that different jujube polysaccharide fractions possessed different structural characteristics, and most of them belonged to pectic polysaccharides. Overall, the structural information difference of jujube polysaccharides was preliminarily illuminated, which could not only promote the potential application of Z. Jujuba cv. Muzao polysaccharides but also provide an effective way to analyze the structures of polysaccharides from other genera jujube fruit.To investigate the structural information differences of  Zizyphus Jujuba Miller), named “Dazao” or “Hongzao” in Chinese, is mainly found in Asia’s subtropical and tropical regions, particularly in the eastern regions, the Yellow River Valley regions, and the northwest [Chinese jujube , are now often planted in the regions of the Yellow River Valley  [Z. Jujuba cv. Muzao fruit because of its high content of water (68%), titratable acid (0.32%), soluble solids (27.4%), total sugar (21.9 g/100 g), Vc reducibility (376.2 mg/100 g), total procyanidins (184.2 mg GSPE eq./100 g FW), total phenol (541.8 mg GAE eq./100 g FW), cinnamic acid (35.2 µg/100 g FW), total flavonoids (255.5 mg Rutin eq./100 g FW), etc., which make them a crucial source of food for people [Z. Jujuba cv. Muzao’s primary bioactive ingredients are polysaccharides for their positive effects on health, including an anti-inflammatory and hypolipidemic effect and antioxidant properties, as well as their ability to improve intestinal barrier function and control intestinal flora [Z. Jujuba cv. Muzao’s primitive polysaccharides were extracted via ultrasonically aided acidic buffer extraction [Z. Jujuba cv. Muzao has not yet been the subject of a thorough analysis.Chinese jujubes, , China) . Signifi solids 2.4%, totaf water 6%, titratsugar 21. g/100 g,traction , ultrasotraction , and alktraction  and 0.1 Z. Jujuba cv. Muzao polysaccharides extracted using water  and alkaline . Their structural characteristics were examined via high-performance gel permeation chromatography (HPGPC), methylation analysis, gas chromatography (GC), and nuclear magnetic resonance spectroscopy (NMR), which could promote the potential application of jujube polysaccharides to commercial nutritious foods.In the present study, we emphasized the purification of Z. Jujuba cv. Muzao. Regarding dried jujube fruit power, the overall yield of ZMP and AZMP was 3.82% and 3.30%, respectively. The ZMP and AZMP fractions were progressively separated using Fast Flow (DEAE-Sepharose) and gel filtration columns (Sephacryl S-300) to purify them further. Deproteinization, extraction with hot water/alkaline extraction, precipitation of ethanol, and freeze-drying were used to produce ZMP and AZMP from Z. Jujuba cv. Jinsixiaozao, which might be caused by a higher concentration of NaCl-PBS eluent [Z. Jujuba cv. Muzao may have distinct chemical compositions according to these facts.The total carbohydrate, protein content, and phenol of PZMPs and SAZMPs are given in S eluent . The totMw (8.23–141 kDa) was found in PZMPs and SAZMPs. Compared with water-extracted jujube polysaccharides, the Mw of alkaline (0.1 M NaOH solution) extracted polysaccharides was generally lower, which may be explained by the alkaline solution’s influence on the glycosidic bond’s breakdown, accelerating the destruction of the jujube saccharide molecule [Mw jujube polysaccharides may have significant potential benefits for intestinal absorption, as well as for food digestion and the development of intestinally beneficial bacteria [Jujube polysaccharide molecular weight distribution is essential for biological activity. As shown in molecule . Low Mw bacteria . Differebacteria .Information on the monosaccharide composition is far more crucial for understanding jujube polysaccharides’ physiochemical and structural characteristics. As can be seen in f were the central glycosidic bonds in all ZMP and AZMP samples. (3) In the PZMPs, the galacturonic acid proportion increased with the concentration of eluent sodium chloride [f/Galp/Glcp/Rhap residues was about equivalent to the total amount of branching residues indicates that all PZMPs and SAZMPs underwent successful methylation.Determining glycosyl linkages in jujube polysaccharides may be achieved using GC-MS to examine methylation, which is a reliable and effective method. The findings are shown in chloride . No uronchloride . (4) The1H NMR spectra were identified. (3) The same glycosidic bond types might have different C/H proton signals under the same/different NMR conditions. (4) The NMR glycosidic bonds of C/H signal assignment were similar to methylation results. (5) Through NMR and methylation analysis, the structural characteristics and structural types of jujube polysaccharides could be determined, and most of the jujube polysaccharides belonged to pectin polysaccharides [NMR analysis was performed on the PZMPs and SAMPs to shed light on their structural details further. charides ,29.Z. Jujuba cv. Muzao. GE Healthcare Life Sciences  offered Sephacryl gels (S-300) and anion-exchange Sepharose Fast Flow (DEAE). Sigma Chemical Co.  provided standard monosaccharides. The remaining substances were all of analytical grade.Loess Plateau Experimental Orchard  provided the fruit bodies of Z. Jujuba cv. Muzao polysaccharides (ZMP). An alkaline solution was used to treat the insoluble residues, and the alkaline extracted supernatants were combined with 95% ethanol to create ZMP (AZMP). Then, ZMPs and AZMPs were decolorized and deproteinized. The ZMP/AZMP solutions were put onto a Fast Flow column (DEAE-Sepharose), sequentially eluting the column with a gradient of NaCl solutions (0 and 0.2–0.4 M)/(0–0.3 M) and phosphate-buffered saline  and at 1.5/1.2 mL per minute flow rate, to obtain ZMP fractions (PZMP1-4)/AZMP fractions (AZMP1-4). Following that, utilizing a gel-permeation chromatography column (Sephacryl S-300), each fraction was cleaned, which was eluted using deionized water at a 0.8 mL per minute flow rate to collect ZMP fractions /AZMP frs . The toThe phenol–sulfuric acid technique was used to determine the total sugar content of PZMPs and SAZMPs, using glucose as the benchmark . Using tPZMPs and SAZMPs were identified as monosaccharides and quantified using GC analysis, as previously mentioned . The monPZMPs and SAZMPs were analyzed using HPLC utilizing Agilent-LC 1200 equipment and a TSK-gel G3000PWxl/G5000PWxl column (7.8 mm × 300 mm) to establish average molecule weights and uniformity . A calib4 and EDC (1-ethyl-3-(3-dimethyl aminopropyl) carbodiimide), PZMPs/SAZMPs were carboxyl reduced [4, and hydrolysis with trifluoroacetic acid. Using GCMS-QP2010A equipment with , a capillary column  and ) and another capillary column , as well as electron ionization spectra, the resulting partly methylated alditol acetate derivatives were discovered.The reduction methods methylated the samples containing uronic acid. With NaBD reduced . The sta reduced . All ZMP2O (0.5 mL), and NMR spectra (1H and 13C) were obtained using a Brucker AVANCE III 500 MHz NMR [An NMR spectrometer  was used to acquire the NMR spectra in one and two dimensions of PZMPs. SAZMPs swapped for deuterium were diluted in D MHz NMR .Z. Jujuba cv. Muzao polysaccharides through various extraction and purification methods and found some interesting interrelations concerning the physicochemical properties of varying Z. Jujuba cv. Muzao polysaccharides. The molecular weight ranged from 8.23 to 141 kDa, and the monosaccharide composition was composed of various molar ratios of rhamnose, arabinose, galactose, galacturonic acid, etc. Arabinofuranosyl had methylated sugar derivatives of Z. Jujuba cv. Muzao polysaccharides, which belong to pectic polysaccharides. The present work might methodically aid in a more significant comprehension of the many Z. Jujuba cv. Muzao polysaccharide structures and offer a thoroughly relevant bibliography for more structure–function correlations and precise structural details for other species of jujube polysaccharides.The present study prepared a series of


The biological function of lncRNA ELF3-AS1 remains largely unknown in cancers. The cause of SNAI2 overexpression in tumor metastasis remains largely unclear. The molecular mechanisms underlying the high co-expression of antisense lncRNAs and adjacent protein-coding genes remains unclear.RNA-seq, CHIP and dual-luciferase reporter assay were performed to identify lncRNAs regulated by SNAI2. MicroRNA-seq and RNA-seq studies were conducted to reveal the biological function of ELF3-AS1 in GC. RNA pulldown and CHIRP assays were conducted to identify the protein that interacts with ELF3-AS1.A total of 123 lncRNAs were identified to be regulated by SNAI2 in GC by RNA sequencing. The ELF3 gene and antisense lncRNA ELF3-AS1 were both transcriptionally repressed by SNAI2 or SNAI1. Down-regulation of ELF3-AS1 and ELF3 predicted poor prognosis in GC. Nuclear localized lncRNA ELF3-AS1 negatively regulated GC cell cycle progression via suppressing G1/S transition and histone synthesis. ELF3-AS1 mainly inhibited GC metastasis by repressing SNAI2 signaling. Additionally, ELF3-AS1 modulated ELF3 mRNA stability by RNA-RNA interaction. The RNA duplexes formed by ELF3 mRNA and lncRNA ELF3-AS1 directly interacted with the double-stranded RNA (dsRNA) binding protein complex ILF2/ILF3 (NF45/NF90). In turn, the ILF2/ILF3 complex dynamically regulated the expression of ELF3-AS1 and ELF3 by affecting the dsRNA stability.. The ILF2/ILF3 complex plays a critical role in regulating dsRNA stability. In addition, our work provides a direct evidence that head-to-head antisense lncRNAs can share promoters with neighboring coding genes, which make their expression subject to similar transcriptional regulation, leading to high co-expression.The SNAI2-ELF3-AS1 feedback loop regulates ELF3 expression at transcriptional and post-transcriptional levels and drives gastric cancer metastasis by maintaining SNAI2 overexpressionThe online version contains supplementary material available at 10.1186/s13046-022-02541-9. Gastric cancer (GC) is the third most common cause of cancer-related deaths , 2. AlthThe transcription repressor SNAI2 , which belongs to the SNAIL transcription factor family, is known to be one of the master regulators of epithelial–mesenchymal transition (EMT) . AccumulLong non-coding RNAs (lncRNA) are a group of classic endogenous non-coding RNAs with a length of more than 200 nucleotides . Recent Antisense lncRNA ELF3-AS1  is located at chromosome 1q32.1 and broadly expressed in human tissues. ELF3-AS1 was reported to be a cell cycle associated lncRNA that was enriched in S-phage . RecentlHuman gastric cancer cell lines AGS, NCL-N87, MGC803 and HGC-27 were purchased from GeneChem . The human gastric cancer cell lines  and the normal gastric cell line GES-1 were purchased from the Shanghai Cell Bank of the Chinese Academy of Sciences. The siRNAs listed in Table SThe study protocol was approved by the Human Research Ethics Committee of Hubei University of Medicine (2018-TH-035). The procedures were in accordance with the Helsinki Declaration of 1975. Written informed consent was obtained from all patients. Tissue samples were immediately frozen in liquid nitrogen after resection and stored at − 80 °C until use. All samples were pathologically confirmed.The total RNA in GC cells was extracted to perform RNA sequencing (RNA-seq). A total amount of 1.5 μg RNA per sample was used as input material for the RNA sample preparations. The whole step of library construction and sequencing was performed at Shanghai Lifegenes Technology Co., Ltd. The RNA-seq data was uploaded on the GEO section of the NCBI web server. The GEO accession numbers were GSE161551 (SNAI2/SNAI1 overexpression), GSE161291 (ELF3-AS1 knockdown) and GSE161544 (ILF2/ILF3 knockdown).After knocking down ELF3-AS1 expression in GC cells, the total RNA of each sample was extracted and then sent to BGI company  for microRNA purification and miRNA sequencing analysis. The normalized expression level of each microRNA was calculated by TPM value. The Log2FC value was calculated to estimate between-group differences. For each microRNA, if the fold change was more than 1, the difference between the negative control and the matched target samples was set to be significant. The microRNA-seq data was uploaded on the GEO section of NCBI web server. The gene expression omnibus accession number is GSE161553.6) were injected into the subcutaneous tissue of female BALB/c nude mice. After 28 days, all the mice were ethically euthanized, and the tumors were collected for weighing and volume measurement. The tumor volume was calculated using the following formula: volume = length × (width)2/2. The study protocol was approved by the Experimental Animal Research Ethics Committee of Hubei University of Medicine (2019-056).Four-week-old female BALB/c nude mice were purchased from the Laboratory Animal Center of the Hubei University of Medicine and maintained in a temperature-controlled (21 °C) and light-controlled pathogen-free animal facility with free access to food and water. All animals were treated in accordance with guidelines of the Committee on Animals of the Hubei University of Medicine. GC cells  was purchased from RiboBio . The experiment was performed according to the manufacturer’s instructions. The 5’FAM-ELF3-AS1 probes were designed and synthesized by Sangon Biotech (Shanghai). The images were taken with a confocal microscope (Zeiss).Chromatin immunoprecipitation (CHIP) assays were performed using a CHIP Assay Kit  according to the manufacturer’s protocol. Briefly, the SGC7901 cell line was collected and fixed for 10 min at 37 with 1% formaldehyde, followed in sequence with SDS lysis and DNA shearing, protein and DNA immunoprecipitation, cross-linked DNA reversal and DNA purification. Finally, the immunoprecipitated DNA fragments were detected by PCR assays. The normal rabbit IgG was used as the negative control.Gastric cancer cells were lysed in RIPA buffer with 1 mM PMSF. Total protein (10-100 μg) was electrophoresed through 10% SDS polyacrylamide gels and was then transferred to a PVDF membrane. After blocking with skim milk at 4 °C for 1h, the membrane was incubated with primary antibody at 4°C overnights. The blots were then washed and incubated with horseradish peroxidase (HRP)-conjugated secondary antibody  for 1.5 h at room temperature. Detection was performed using a SuperLumia ECL HRP Substrate Kit (Abbkine) and visualized using a Bio-Rad Imaging System (USA). The primary antibodies used in this study were ILF2 , ILF3 , ELF3 , β-Actin , TARBP2 , SNAI2 , SNAI1 , YBX1 .After crosslinking with 0.5% formaldehyde for 10 min at room temperature, cells were harvested and lysed in RIP lysis buffer with RNasin (1000 U/ml), DNase I (50 U/ml) and protease inhibitor cocktail. After the genomic DNA was digested, lysates were further subjected to sonication. Supernatants cleared by centrifugation were incubated with the anti-ILF3 antibody  or IgG overnight at 4 °C. Protein A/G beads were added for a further 4 h incubation at room temperature. After the beads were washed, immunocomplexes of proteins and RNAs were de-crosslinked at 95 °C for 15 min. The immunoprecipitated RNAs were then purified for RNA sequencing and qRT-PCR analysis.Briefly, 831 bp length of sense and antisense ELF3-AS1 sequences were cloned into pGEM-T Easy (Promega). In vitro transcription was carried out and RNA was purified and labeled with Biotin at 3′ ends. Cells were harvested and resuspended in freshly prepared lysis buffer supplemented with 50 U/mL RNase inhibitor (Takara) and a protease/phosphatase inhibitor cocktail (Roche). Sense and antisense RNAs were captured on magnetic beads (Pierce) and were incubated with cell lysates in protein-RNA-binding buffer (Thermo Scientific) overnight at 4 °C with agitation. RNA-binding protein complexes were washed five times with ice-cold wash buffer and were boiled in SDS lysis buffer for western blot assay and mass spectrometry (MS) analysis.Briefly, the CHIRP assay was carried out to verify the interaction between ELF3-AS1 and RNA binding proteins. A 3′ end Biotin modified-DNA probe targeting ELF3-AS1 was designed and synthesized by Sangon. Before crosslinking, SGC7901 cells were grown and seeded into 10 cm dishes. Cell lysates were harvested after incubation of 48 h with a confluence of 60-80%. Cells were cross-linked with 1% formaldehyde and sonicated for the hybridization reaction. After the chromatin was sheared into 100–500 bp fragments, the cell lysates were incubated with the biotinylated DNA probe solution for 4h at 37 °C. The binding complex was covered with streptavidin-conjugated magnet beads. The proteins were finally eluted and purified from the magnet beads for real-time qPCR or mass spectrometry and western blotting analyses.t-test or one-way ANOVA test. For all experiments, a minimum of triplicates per group and repetition of at least three times was applied to achieve reproducibility. All tests with p values less than 0.05 were considered statistically significant.For gene expression analysis of different subtypes of GC, the P values were estimated using Mann–Whitney nonparametric test. Survival curves were calculated using the Kaplan–Meier method, and differences between the curves were analyzed using the log-rank test. All the rest of the experiments were used an unpaired To explore the target genes of SNAI2, RNA sequencing studies GSE161551) were conducted in the GC cell line (SGC7901) overexpressing SNAI2. A total of 318 coding genes, 70 lncRNAs were strongly repressed by SNAI2, while 55 coding genes and 53 lncRNAs were greatly upregulated by SNAI2  of the epithelial tumor suppressor gene LncRNA ELF3-AS1 is abundant in human cells and can be effectively captured by magnetic beads when RNA sequencing. In order to make our results more convincing, we used RNA-seq studies to visualize the expression of ELF3-AS1 and ELF3. As expected, RNA-seq analysis and qRT-PCR assay together showed that ELF3-AS1 and ELF3 were downregulated by SNAI2/SNAI1 overexpression  database. LncRNA ELF3-AS1 was low expressed in diffuse and poorly differentiated GC tissues . However, no significant changes in ELF3-AS1 expression levels were observed between GC patients with different TNM stages (data not shown). Overall survival analysis showed that GC patients with a lower expression level of ELF3-AS1 possessed a shorter overall survival time .Besides, analysis of ELF3-AS1 expression in 30 pairs of GC tissues showed that ELF3-AS1 was down-regulated in more than 80% of GC samples compared to the corresponding normal samples . Interestingly, when the ELF3-AS1 was effectively knocked down in GC cell lines, ELF3 mRNA as well as its protein were significantly reduced to approximately 60-70% . These results together suggested that ELF3-AS1 inhibited the proliferation and metastasis of GC cells in vitro and in vivo.To determine whether ELF3-AS1 has a tumor-suppressive effect in GC, loss- and gain-of-function studies were performed. Cell apoptosis assay showed that depletion of ELF3-AS1 remarkably accelerated early apoptosis of GC cells Figure SA. BesideNext, we analyzed the differentially expressed miRNAs after ELF3-AS1 knockdown by miRNA sequencing  in GC  analysis of the differential bands located at 45 Daltons Fig. A, there ELF3 gene has different transcripts due to alternative splicing. Among those different types of ELF3 transcripts, ELF3-201, ELF3-202 and ELF3-203 can encode full-length ELF3 protein. The ELF3-201 transcript and the ELF3-AS1 transcript overlapped by about 664 nucleotides  is a key factor leading to the poor prognosis in GC patients. Oh et al. previously reported that GC patients with mesenchymal phenotype has a poorer prognoses compared to the GC patients with an epithelial phenotype . SimilarIn this study, we took SNAI2 as a breakthrough point to screen lncRNAs regulated by SNAI2 in GC. Overexpression of SNAI2 caused a 2-fold change in the expression of about 123 lncRNAs. ELF3-AS1 was one of the top 10 lncRNAs most significantly repressed by SNAI2 overexpression. Furthermore, ELF3-AS1 and ELF3 gene were identified to be directly repressed by SNAI2 and SNAI1 at the transcriptional level. Although SNAI1 had a similar effect to SNAI2 in inhibiting the expression of ELF3 and ELF3-AS1 or any other downstream target genes, the regulatory efficiency of SNAI1 on the expression of target genes is much weaker than that of SNAI2 (Fig SThe ways led to the co-expression of antisense lncRNAs and nearby protein-coding genes are diverse, including transcriptional level and post-transcriptional level. At the transcriptional level, a possible mechanism is that antisense lncRNAs share a promoter with nearby genes, thereby suffering from similar transcriptional regulation. Bartl and colleagues have reported that lncRNA HHIP-AS1 and HHIP shared promoters, and this promoter activity was negatively regulated by DNA methylation . Herein,The biological effects of transcriptional repression of ELF3-AS1 by SNAI2 remains unknown. SNAI2 is a rapid-turnover protein . RecentlIn summary, a novel double-negative feedback loop between SNAI2 and lncRNA ELF3-AS1 was identified in GC. The SNAI2-ELF3-AS1 feedback loop drives GC metastasis by continuously activating SNAI2 signaling and regulating ELF3 expression at transcriptional and post-transcriptional levels Fig D. In GC,Additional file 1.Additional file 2.Additional file 3.Additional file 4.Additional file 5.Additional file 6.


Traditionally, intracellular ADP-ribosylation has been considered mainly as a protein posttranslational modification. To date, it is not clear whether RNA ADP-ribosylation occurs in cells. Here we present evidence that different RNA species are ADP-ribosylated in human cells. The modification of cellular RNA is mediated by several transferases such as TRPT1, PARP10, PARP11, PARP12 and PARP15 and is counteracted by different hydrolases including TARG1, PARG and ARH3. In addition, diverse cellular stressors can modulate the content of ADP-ribosylated RNA in cells. We next investigated potential consequences of ADP-ribosylation for RNA and found that ADPr-capped mRNA is protected against XRN1 mediated degradation but is not translated. T4 RNA ligase 1 can ligate ADPr-RNA in absence of ATP, resulting in the incorporation of an abasic site. We thus provide the first evidence of RNA ADP-ribosylation in mammalian cells and postulate potential functions of this novel RNA modification.RNA function relies heavily on posttranscriptional modifications. Recently, it was shown that certain PARPs and TRPT1 can ADP-ribosylate RNA  The m7G-cap (Cap 0) is essential for initiation of translation and protects nascent mRNA form premature degradation by 5′→3′ exonuclease activity. In addition, the m7G-cap also serves as a scaffold for recruiting protein factors involved in pre-mRNA splicing, polyadenylation and nuclear export , can be attached to the 5′-end of RNA in yeast and human cells  is higher in NAD+-capped RNA populations, suggesting certain transcript-preference in NAD+-capping. NAD+-capped RNA is not translated and is instead actively degraded  moiety is transferred from the cofactor NADolecules . Similarolecules ,15. Introlecules ,17. Out olecules . Howeverolecules . ADP-ribolecules . MARylatolecules .in vitro. Contrary to the known toxins, PARP1–3 modify DNA on terminal phosphates at sites of DNA breaks , 50 mM KCl buffer or RNase free water.The sequences of the oligonucleotides used in this study are listed in For GFP-PARP overexpression PARP10, PARP11, PARP12 and PARP15 were sub-cloned from pDONR221 to a pcDNA5/FRT/TOgw-N-mEGFP gateway vector using LR clonase mix (Thermo Fischer Scientific). The destination vector pcDNA5/FRT/TOgw-N-mEGFP was made in house using the NEBuilder® HiFi DNA Assembly Cloning Kit (New England Biolabs). MACROD1 and TARG1 were cloned to pDEST17 as described . The pOTg for 15 min at 4°C. Bacterial pellets were suspended in lysis buffer and cells were lysed using the Digital Sonifier 250 Cell Disruptor (Branson). Sonication settings varied depending on the expressed construct and pellet size . The cell lysates were cleared by centrifugation at 15 000 × g for 45 min at 4°C. Proteins were purified via affinity purification with Glutathione Agarose (Pierce) or TALON Metal Affinity Resin (Takara Bio), for GST-tagged and His-tagged constructs, respectively. Eluted protein fractions were dialysed and quality checked via SDS-PAGE  to remove all phosphates or to obtain monophosphorylated RNA oligos, respectively.2, 1 mM DTT, 500 μM NAD+, 40 U RNase inhibitor (New England Biolabs)) for 30–60 min at 37°C. In reactions with synthetic RNA oligos 1–5 μM RNA was incubated with 1–2 μM transferase or hydrolases. Proteins were digested with 20 U Proteinase K (New England Biolabs) for 20 min at RT before samples were resolved on denaturing urea-PAGE. Samples were completed with RNA loading dye (New England Biolabs), heated up for 3 min at 85°C and loaded on pre-run urea polyacrylamide gels , 0.2% APS, 0.4% TEMED). Gels were run in TBE buffer  at 7 W and stained as required with SYBR™ Gold nucleic acid gel stain (Invitrogen). If radiolabelled 32P-β-NAD+ was used for in vitro RNA modification or the samples were used in subsequent assays, ADP-ribosylation reactions were purified after Proteinase K treatment using the Monarch® RNA Cleanup Kit (New England Biolabs). ADP-ribosylation of the GLuc reporter was performed as described for the synthetic oligos, after treating the product of in vitro transcription (IVT) with RppH to obtain mono-phosphorylated GLuc mRNA. Additionally, the ADPr-GLuc reporter sample was treated for 1 h at 37°C with XRN-1 (New England Biolabs) to remove non-modified RNA. RNA concentrations were determined by spectrophotometric measurements (NanoDrop ND-1000 Spectrophotometer).ADP-ribosylation assays and hydrolase assays were performed in ADPr-reaction buffer  or RtcB ligase (New England Biolabs). Reactions were assembled according to the manufacturer's protocols and supplemented with 7.5% PEG 8000 and 40 U RNase inhibitor T4 Rnl1 reactions were incubated at 16°C for 16 h or at 25°C for 2 h. RtcB ligase reactions were incubated for 1 h at 37°C. Apurinic/apyrimidinic Endonuclease 1 (APE1) (New England Biolabs) was used to cleave the phosphodiester backbone of double stranded DNA:RNA hybrids 5′ to abasic sites. RNA ligation products were hybridised with a reverse complementary DNA oligo by heating at 80°C for 5 min and cooling-down to RT. Hybridised samples were supplemented with 1 μl NEBuffer 4 and 5 U APE1 in a total volume of 10 μl. Reactions were incubated at 37°C for 1 h.In vitro transcribed ssRNA oligos were generated using the MEGAshortscript™ T7 Transcription Kit (Invitrogen). Reactions were assembled according to the manufacturer's protocol. For IVT product_21nt and IVT product_40nt 3 μg DNA template was used in 20 μl reaction volume and reactions were incubated at 37°C overnight. The radiolabelled NAD+-capped RNA oligo was generated by the addition of 32P-β-NAD+ to the standard IVT reaction of IVT product_40nt; its template sequence was designed with one exclusive thymidine at the 5′-end of the DNA to enable exclusively labelling of NAD+-caps. GLuc reporter was generated by using 1 μg of template DNA and incubation at 37°C for 4 h. GLuc reporter was poly(A) tailed using E. coli Poly(A) Polymerase (New England Biolabs). Reaction was assembled according to manufactures protocol and incubated for 30 min at 37°C. All IVT reactions were DNase treated for 30 min at 37°C, using 1 μl TURBO™ DNase (Invitrogen). RNA was purified using the Monarch® RNA Cleanup Kit (New England Biolabs).Gaussia luciferase reporter construct containing a T7 promoter, a short 5′-UTR and minimal 3′-UTR was purchased as a gBLOCK from Integrated DNA technologies. The construct was amplified by PCR and used for in vitro transcription after column purification as described. The in vitro transcribed mRNA was poly(A) tailed, purified and m7G-capped using the Vaccinia Capping System (New England Biolabs) or ADP-ribosylated using human TRPT1 after dephosphorylation using RppH to produce monophosphorylated RNA suitable for ADP-ribosylation. These mRNAs were then used in in vitro translation assays using the PURExpress®in vitro protein synthesis kit (New England Biolabs) according to the manufacturer's protocol with 2 μg of m7G-capped, ADPr-capped or non-capped GLuc reporter mRNA. Alternatively, capped GLuc mRNA was co-transfected with m7G-capped firefly luciferase (FLuc) mRNA in HEK293T cells using Lipofectamine MessengerMAX (Invitrogen). The cell medium was collected for measurement of secreted GLuc at indicated time points. Cells were lysed and FLuc activity was measured in lysates to check for transfection efficiency. GLuc activity was measured with the GAR-2B Gaussia Luciferase assay (Targetingsystems). FLuc activity in cell lysates was measured using the Steady-Glo Luciferase Assay System (Promega).A Isolation of total RNA fractions was carried out with the RNeasy Mini Kit (Qiagen) or the RNeasy Plus Mini Kit (Qiagen) according to the manufacturer's protocols. Small (≤200) and large (≥200) RNA fractions were isolated using the microRNA Purification Kit (Norgen) according to the manufacturer's protocol. Enrichment of RNA was performed with the Dynabeads™ mRNA DIRECT™ Purification Kit (Invitrogen) from the total or large RNA fraction. 200 μl oligo (dT) 25 beads were used for 100 μg of total RNA. After equilibration of the beads in lysis/binding buffer, total RNA, diluted in lysis/binding buffer, was added to the bead suspension and incubated for 5 min at RT while rotating. Beads were washed according to the manufacturer's protocol and eluted in elution buffer while shaking at 750 rpm at 80°C for 2 min.+ membrane (Amersham) using the Slot Blot Blotting Manifold (Hoefer). The membrane was pre-wetted in 10xSSC-buffer, pH 7.0 . Slots were rinsed with 200 μl 10× SSC-buffer before loading. 40–500 ng RNA in 200 μl SSC-buffer was applied to the membrane. After the membrane was dried for at least 30 min samples were UV-cross-linked with 120 mJ/cm2. For antibody staining the membrane was blocked with 5% non-fat milk in PBST (PBS with 0.05% Tween 20) for 60 min at RT and subsequently incubated with the Anti-PAR/MAR ) in 1:7000 dilution in PBST at 4°C overnight. The HRP-conjugated Peroxidase AffiniPure Goat Anti-Rabbit IgG (H + L) secondary antibody (Jackson) was diluted 1:7,500 in 2% non-fat milk in PBST and incubated for 1 h at RT. Multiple washing steps with PBST were performed after both antibody incubations for at least 5–10 min. Chemiluminescence signals were detected using the WesternBright Chemiluminescence Substrate Quantum (Biozyme) and the detection system Azure600 (Azure Biosystems) or X-ray films (Fuji).RNA was blotted on Hybond-N2 and were cultivated in DMEM with high glucose and GlutaMAX™ (Gibco) supplemented with 10% heat-inactivated foetal bovine serum (Gibco). Hydrolase knock-downs were performed by reverse transfection using Dharmacon siRNA smartpools or single siRNAs (GLuc mRNA was transfected using Lipofectamine messengerMAX transfection reagent (Invitrogen). For detection of ADPr-RNA upon cellular stress, HeLa cells were treated with MG132 , hydrogen peroxide , sodium arsenite  and interferon alpha . Cell starvation was done by washing cells twice in PBS and incubation in EBSS, containing calcium and magnesium (Gibco), for 3 h.HeLa S3 cells were kept at a humidified atmosphere at 37°C with 5% COe siRNAs  and LipoCell protein extractions were performed using RIPA buffer ) supplemented with protease inhibitor cocktail, followed by benzonase treatment (Santa Cruz Biotechnology). Proteins were separated on 10–15% gels and blotted onto nitrocellulose. Membranes were blocked with 5% non-fat milk in TBST (TBS with 0.05% Tween 20) for 1 h at RT, primary antibodies were diluted in TBST and incubated overnight at 4°C, secondary antibodies were diluted in 5% non-fat milk in TBST and incubated for 1 h at RT. Wash steps were performed in between and after antibody incubations with TBST at RT for at least 5 min. The HRP-conjugated Peroxidase AffiniPure Goat Anti-Rabbit IgG (H + L) secondary antibody (Jackson) was diluted 1:7500 in 2% non-fat milk in PBST and incubated for 1 h at RT. Chemiluminescence signals were detected by either exposure to film or using the Azure600. A monoclonal antibody that recognises TARG1 was raised against the full-length His-tagged protein in rat . ARH3 wain vitro ADP-ribosylated by several human PARPs . While non-capped RNA and NAD+-capped RNA are not recognised by the antibody, both auto-modified PARP10cat as well as purified ADPr-capped RNA were detected . This confirms the specificity of the used antibody for ADPr-modification independent of the substrate-backbone and enables the usage of this reagent for the detection of ADPr-RNA.Two previous studies showed that short 5′-phosphorylated RNA oligos can be an PARPs ,36, howean PARPs . Based oin vitro  or shrimp alkaline phosphatase (rSAP), to obtain monophosphorylated and non-phosphorylated oligos, respectively  mRNA  and used the oligo as RNA-donor in a ligation assay with T4 Rnl1. The radiolabel of the ADP-ribosylated RNA-donor disappeared upon ligation but did not reappear at the size of the expected ligation product. We did not measure potential release of AMP, however, we could detect AMP bound to the ligase -N'-(d-biotinoyl)] hydrazine (ARP) which reacts with the aldehyde groups that are exposed at oxidised abasic sites pp(5)G intermediate in a three-step reaction (ATP-dependent RNA ligases join 3′-hydroxyl and 5′-phosphorylated RNA termini via three reaction steps: (i) the ligase reacts with ATP to form a covalent ligase-(lysyl-Nζ)–AMP intermediate with concomitant release of pyrophosphate; (ii) AMP is transferred from ligase-adenylate to the 5′-phosphorylated RNA to form an adenylylated RNA intermediate (App-RNA); 3) the 3′-hydroxyl of the RNA acceptor attacks the adenylylated RNA to join RNA ends through a phosphodiester 3′→5′ bond  45–48)..45–48). A Figure . In contA Figure . This coA Figure . The apoe Figure . This ine Figure . Abasic e Figure . To probs Figure . Using As Figure . To furts Figure . Synthets Figure . The ligs Figure . Howevers Figure . Whethers Figure . Contrarreaction ,55. Therreaction . In summOur initial experiments indicate that the level of ADP-ribosylated RNA in cells is low due to reversal by hydrolases and increases upon TRPT1 overexpression Figure  and C. Win vitro activity of full-length PARPs on RNA, we tested whether PARP10, PARP11, PARP12 and PARP15 are important for the modification of RNA in cells, as cellular co-factors may allow them to modify RNA. These PARPs were chosen because their catalytic domains were able to modify RNA molecules with ADPr in vitro or evidence in literature exists about their involvement in RNA metabolism  and influence their dynamics . We haveO-glycosidic bonds and is not able to cleave the ester bond between the last ADPr moiety and the acceptor protein, however, it can reverse RNA ADP-ribosylation  under the tested conditions. However, E. coli RtcB is not able to use ATP for ligation and is strictly dependent on GTP, potentially explaining the lack of activity toward ADPr-RNA. It will be interesting to test whether human RTCB is able to use ADPr-RNA as a substrate in the presence of archease and whether ligation of RNA through ADPr plays a role in mammalian cells.We observed that overexpression of TRPT1 in combination with hydrolase knock-down increases the cellular ADP-ribosylation signal in the pool of small RNAs. This RNA pool contains mostly tRNA and 5S rRNA. Despite several attempts, we were not able to detect transferase activity of TRPT1 on protein substrates. The lack of activity towards protein substrates makes human TRPT1 a splicing . TRPT1/Tsplicing . Howeverequences ,70. Knocequences . Importaat shock . Interesat shock . Extrapoligation . We showligation  and confligation  a later ligation . Besidesligation ,74–76. Iligation ,54,77,78ligation ,80. ContOur study has clear limitations: although we have optimised the purification and detection of ADP-ribosylated RNA from mammalian cells, the downstream readout is only semi-quantitative. Slot-blotting with an anti-ADPr antibody has allowed us to demonstrate that the modification exists in cells and is dynamic, however, we cannot confidently conclude which enzymes modify preferentially which RNA species. We furthermore sometimes observe an increase in signal upon control siRNA transfection, which implies that sample preparation and analysis need to be very careful to avoid inducing cellular stress and might thus further hint that ADPr-RNA is upregulated during cellular stress. More quantitative methods need to be developed for future analysis of the contribution of single enzymes to the ADPr-capping of RNA, ideally combined with chemical genetics approaches, knock-downs of individual enzymes and protein-RNA interaction studies to confidently identify the target RNAs of individual PARPs. Finally, our results indicate that ADPr-RNA can be ligated by a bacteriophage T4 RNA ligase, however, we have not identified the human ligase. This needs to be further investigated: which human ligase performs this reaction? Studying the mechanism via which the abasic site arises will also help to clarify whether the detected C3′-linked ligation product is the only reaction product or whether there might be an equilibrium between C1’ and C3′-linked products.In summary, we provide the first evidence of the presence of ADP-ribosylated RNA in cells and moreover show that different pools of cellular RNA can be modulated by different ADP-ribosyltransferases and hydrolases. ADPr acts as novel mRNA cap that does not support translation but increases the stability of modified RNA by blocking degradation by exonuclease XRN-1. In addition, we observed that ADPr-RNA has a highly dynamic nature in cells with a fast turnover rate, at least partially mediated by ADP-ribosylhydrolases. Finally, ADP-ribosylated RNA can be ligated in an ATP-independent manner, resulting in a non-canonical ligation product with an abasic site. These data provide the basis for future research focused on the identification of ADPr-capped RNAs, on deciphering the role of ADPr as a novel RNA modification in cells as well as pinpointing the unique roles of the diverse ADP-ribosyltransferases and hydrolases.All experimental data is available in the main text or in the supplements. Expression plasmids generated will be available from Addgene. Cell lines are available on reasonable request from the authors.gkac711_Supplemental_FileClick here for additional data file.