This work motivated us to assess a greater number of samples and determine the origin of possible contaminations using viral sequences. To detect viruses with high specificity, we developed the publicly available workflow, VirDetect, that detects virus and laboratory vector sequences in RNA-seq samples. We applied VirDetect to 9143 RNA-seq samples sequenced at one TCGA sequencing center (28/33 cancer types) over 5 years.Contamination of reagents and cross contamination across samples is a long-recognized issue in molecular biology laboratories. While often innocuous, contamination can lead to inaccurate results. Cantalupo et al.We confirmed that H-HPV18 was present in many samples and determined that viral transcripts from H-HPV18 significantly co-occurred with those from xenotropic mouse leukemia virus-related virus (XMRV). Using laboratory metadata and viral transcription, we determined that the likely contaminant was a pool of cell lines known as the “common reference”, which was sequenced alongside TCGA RNA-seq samples as a control to monitor quality across technology transitions (i.e. microarray to GAII to HiSeq), and to link RNA-seq to previous generation microarrays that standardly used the “common reference”. One of the cell lines in the pool was a laboratory isolate of MCF-7, which we discovered was infected with XMRV; another constituent of the pool was likely HeLa cells.Altogether, this indicates a multi-step contamination process. First, MCF-7 was infected with an XMRV. Second, this infected cell line was added to a pool of cell lines, which contained HeLa. Finally, RNA from this pool of cell lines contaminated several TCGA tumor samples most-likely during library construction. Thus, these human tumors with H-HPV or XMRV reads were likely not infected with H-HPV 18 or XMRV. Rigorous and reproducible experiments should minimize extrinsic factors that could bias the results. Nevertheless, contamination in molecular biology is a well-described problem . Here weThe other type of contamination uncovered in this study was contamination during the sequencing process , 8–11. TTo detect viruses from RNA-seq data, we developed VirDetect, an open source software based on the principles of digital subtraction –16. VirD6 for low complexity reads and 4.5/106 for human simulated reads to a total of 2/108 mapped reads for low complexity reads and 0/108 human simulated reads.Virus detection can be subject to poor specificity caused by areas of low complexity and sequence similarity to human sequences that are found in some viral genomes. To ameliorate this, the target viral genomes database was optimized to increase specificity by masking the viral genomes for (a) areas of human homology and (b) areas of low complexity Fig. b. We useWe validated the performance of VirDetect using in silico simulations (see methods) of randomly drawn paired-end 50-mers from all virus genomes in our database that incorporated up to 10 base changes in the first read in the pair. For ≤3 mutations, the median sensitivity was 99.6%  in liver cancer. Our data were 83% concordant  to TCGA Research Network . A. A25]. AMost of the UHRR+ samples were sequenced in 2010, when none of the TCGA samples contained XMV43 or HPV18 reads .The low levels of RNA from HPV18 and XMV43 may have only been observed due to an increase in sequencing depth. The sequencing depth in 2010 was lower than in 2011 by an average 20 million reads. The increase in sequencing depth corresponded to a change from the Illumina GAII to the Illumina HiSeq sequencer at the facility. The samples that contained a contaminant had a significantly higher number of reads than samples without a contaminant  compared to ME16C . The lab stock of MCF-7 had 21 nucleotides  compared to the reference XMV43 with an alternative allele frequency > 0.9 and ME16C had 160 nts with alternative allele frequencies > 0.9 with coverage >10X. Also, MCF-7 had >10X coverage across the entire genome in these samples, while ME16C had >10X coverage across just 40% of the XMV43 genome. The higher expression, higher sequence identity, and complete genome coverage of XMV43 in MCF-7 indicates that this cell line likely contributed to the XMV43 found in TCGA RNA-seq. To determine if the original MCF-7 cell line contained XMV43 or only this lab stock, we assessed publicly available RNA-seq of MCF-7, from Marcotte et al. (GSE73526) [Both of the lab stocks of MCF-7 and ME16C had pre-existing RNA-seq data (prepared on January of 2013). We detected the presence of XMV43-like sequences in both of these cell lines Fig. a. MCF-7 l. GSE735 [26] andSE73526) . The RNAThe incomplete alignments of ME16C sequences to XMV43-like were likely due to the presence of the pBabe-puro hTERT vector, which was used to transduce this cell line . This veWe observed an additional virus signal in the RNA-seq that was likely due to laboratory contamination, however we were unable to determine the exact origin. We observed rabies virus expression with a read count of 2 in 19 samples from 10 different tumor types. These reads had high confidence alignments to rabies virus using BLAST as an independent verification step. Each of the samples had their libraries prepared from November of 2012 to April of 2013 Fig. . Even thContamination in molecular biology has been a long and pervasive problem. RNA-sequencing is so sensitive that it can detect extremely low levels of contamination. Even with its ubiquity, contamination is a hazard to science, with the possibility of false positive claims and associations. We developed and validated a new virus discovery algorithm and database that allowed for high confidence in the virus calls. VirDetect can detect viruses with extremely high specificity because of the masked viral genomes.From RNA-seq of tumor samples, differentiating natural virus infection from contamination is not always obvious and correlation with the presence of viral sequences alone is not evidence for causality. Some studies have used the criteria that a virus must have a certain expression threshold (mRNA levels) for the tumor to be virus-associated and that strength of association is therefore correlated with the strength of viral gene expression. This reasoning is sufficient for viruses and cancer types, where viruses are expected to be present in every single tumor cell, such as Epstein-Barr Virus (EBV) in EBV-associated gastric cancer or lymphoma . It defiRNA-seq contamination may arise from a PCR product, “sample jumping” (from tube to tube during laboratory handling of samples), “sample cross-talk” (read mis-assignment during pooling) , 34, or In addition to these XMRV and Hela specific HPV contaminants, we also detected a small possible rabies virus contamination, albeit with very low read counts . This strengthens the argument for the need for rigor and reproducibility in research, and to assist with this we provide VirDetect, as a robust tool for objective and accurate virus discovery and quantitation.Using RNA-seq and the laboratory metadata from TCGA, we were able to reconstruct the steps that lead to contamination. First the MCF-7 cell line was infected with an XMRV during local expansion, specifically XMV43. RNA from this cell line was then added to a pool of cell-line derived RNA (UHRR) that already contained HeLa. This pool of cell lines was sequenced contemporaneously and repeatedly with TCGA RNA-seq and during processing, a fraction of the TCGA sample RNAs were contaminated with the RNA from the standard pool of cell lines (UHRR+).https://github.com/dmarron/virdetect) database comprised of 1893 manually-curated vertebrate virus reference genomes from GenBank, downloaded on December 16, 2015. RNA-seq reads were aligned to hg38  using STAR v2.4.2a . Unmapped reads were aligned to a masked viral FASTA using STAR v2.4.2a . Vertebrate viral FASTA (1894 viruses) was downloaded from GenBank and masked for increased specificity. All viruses were masked except for the human endogenous retrovirus K113 (NC_022518), which we used as a positive control. Regions were masked in two ways. (1) Viral reads of length 75 were simulated from the entire viral FASTA and then mapped to hg38 using STAR v2.4.2a . If the viral simulated reads mapped to the human genome, they were masked in the viral FASTA. (2) Areas of low complexity , 7 or more repeating double nts, 4 or more repeating nt patterns of 3, 3 or more repeating nts patterns of 4, 2 or more repeating patterns of 5, 2 or more repeating nt patterns of 6) were masked. Viruses were then quantified using the resultant SAM file. Vector component sequences were manually curated using available sequences at Vector Builder (https://en.vectorbuilder.com), AddGene (https://www.addgene.org), and Algosome .The VirDetect , 2 , and 3 . Low complexity reads from this pool were randomly chosen and a random number of mutations were added to the first read pair. The second read was a reverse transcribed version of the first read pair, but without the mutations. 100 simulated samples, each with 1000 reads were generated.The UHRR+ was generated by adding 0.3 μg mRNA from MCF7 and 0.3μg mRNA from ME16C2 per 100 μg Stratagene Universal Reference RNA (Cat#740000–41). This was added to increase coverage of genes expressed in estrogen receptor positive and estrogen receptor negative breast cancers. One μg of total RNA from either UHRR or UHRR+ was converted to cDNA libraries using the lllumina mRNA TruSeq kit (RS-122-2001 or RS-122-2002) following the manufacturer’s directions. Libraries were sequenced 48x7x48bp on the Illumina HiSeq 2000 as previously described . FASTQ fhttps://github.com/sararselitsky/RNA-contamination-scripts/blob/master/HPV18_from_HeLa.pl. To determine the proportion of HeLa specific HPV18 SNPs  we calcggplot2, reshape2, and gplots.All plots, except Fig. Additional file 1. Virus count table. The columns are in the following order: analysis ID, cancer type, and then raw virus counts for all viruses with counts >0 in at least one sample.


C. elegans, and find that this process requires factors involved in mutant mRNA decay, as in zebrafish and mouse. We further uncover a requirement for Argonaute proteins and Dicer, factors involved in small RNA maturation and transport into the nucleus. Altogether, these results provide evidence for transcriptional adaptation in C. elegans, a powerful model to further investigate underlying molecular mechanisms.Transcriptional adaptation is a recently described phenomenon by which a mutation in one gene leads to the transcriptional modulation of related genes, termed adapting genes. At the molecular level, it has been proposed that the mutant mRNA, rather than the loss of protein function, activates this response. While several examples of transcriptional adaptation have been reported in zebrafish embryos and in mouse cell lines, it is not known whether this phenomenon is observed across metazoans. Here we report transcriptional adaptation in  Transcriptional adaptation is the ability of certain mutations in a gene to modulate the expression of related genes, referred to as adapting genes . At the Understanding the mechanisms of transcriptional adaptation will help us better comprehend why for a given gene some mutations cause disease while others do not . HoweverOnly a few factors are known to be involved in the transcriptional adaptation response thus far, and others, including some involved in RNA processing and transport, are likely required. In addition, it is not clear whether the mechanisms of transcriptional adaptation are common or whether each particular case occurs in a different manner, especially at the step leading to transcriptional modulation. Also, as different paralogs or related genes are expressed in distinct tissues and/or at different times , it is cCaenorhabditis elegans and show the ectopic expression of an extrachromosomal reporter in a tissue where it is not normally expressed. In addition, we analyze these transcriptional adaptation models after RNAi-mediated knockdown of different genes involved in RNA metabolism and find that the upregulation of the adapting genes requires factors involved in the maturation and transport into the nucleus of small RNAs (sRNAs).In this study, we provide examples of transcriptional adaptation in β-Actin (Actb) display increased expression of other Actins including α- and γ-Actin (ACTA and ACTG1/2) as measured by Western blots  display increased mRNA levels of Actg2 and Actg1, respectively, and this upregulation is triggered not by the loss of protein function but by mutant mRNA decay  mutants compared to wild type  allele, hereafter referred to as act-5(ptc), does not exhibit any obvious phenotype (act-5(ptc) mutants  partial deletion allele, hereafter referred to as act-5(Δ1), (act-5 mRNA levels in homozygous mutants compared to wild type (act-3 mRNA levels in act-5(Δ1) mutants were not changed compared to wild type  (act-5(Δ2). The ok1397 deletion removes part of the promoter region and the first two exons (act-5(Δ1) deletion allele, we found no changes in act-5 or act-3 mRNA levels in act-5(Δ2) mutants compared to wild type ,  and founild type . Notablyild type . To furt(ok1397) , hereaftwo exons . We examwo exons . As withild type .C. elegans, act-3 is expressed in the pharynx  mutants  mutants  which exhibit lower levels of mutant mRNA compared to wild type , we found that sax-3 was upregulated in all three unc-89(ptc) alleles  in unc-89, hereafter referred to as unc-89(Δ), using CRISPR/Cas9 genome editing. This deletion removes part of the promoter region and the first several exons (unc-89 isoforms are not observed in unc-89(Δ) mutants (unc-89(Δ) worms are maternal-effect sterile and exhibit growth defects, phenotypes not observed in the unc-89(ptc) alleles. In the RNA-less unc-89(Δ) allele, sax-3 was not upregulated  alleles is a second example of transcriptional adaptation in C. elegans.To identify an additional example of transcriptional adaptation in e family . Due to entified . We focuild type  and lack alleles , both at alleles  and pre- alleles  levels. al exons . Hence,  mutants . Homozygegulated , indicatact-5(ptc) and unc-89(ptc) mutants were specific, we measured unc-89 and sax-3 expression in act-5(ptc) mutants as well as act-5 and act-3 expression in unc-89(ptc) mutants. We observed no significant differences , smg-4 (Upf3) and smg-6 (Smg6). Knockdown of smg-2 and smg-4 blocked the transcriptional adaptation response in all three unc-89(ptc) alleles but not in the act-5(ptc) allele  allele but not in the three unc-89(ptc) alleles  allele . Convers alleles . A diffe alleles .smg-2, smg-4, or smg-6 mutant alleles and the act-5(ptc) and unc-89(ptc) alleles to exclude the possibility of tissue-specific knockdown. Analysis of the double mutant strains confirmed the observations made in the RNAi experiments  and smg-4; act-5(ptc) double mutants than in smg-2 and smg-4 single mutants, and that the levels of the adapting gene’s mRNA were higher  animals, the mRNA levels of the mutant (unc-89) and adapting (sax-3) genes were similar to those in smg-4 single mutants. Furthermore, these animals exhibited a mild uncoordinated phenotype and grew slowly, suggesting a lack of functional compensation. These data further indicate that smg-4 is required for transcriptional adaptation in the unc-89 model. We could not obtain smg-6; act-5(ptc) viable mutants due to severe larval lethality, possibly as a consequence of blocking the transcriptional adaptation response, that is act-3 upregulation. smg-6; unc-89(ptc) mutants exhibited lower levels of unc-89 mRNA and higher levels of adapting gene mRNA in comparison to single smg-6 mutants  mRNA levels similar to wild-type levels. Furthermore, the transcriptional adaptation response was blocked, suggesting that the degradation and processing of mutant transcripts is important to trigger transcriptional adaptation.Previous data indicate that the exonuclease Xrn1 is involved in regulating the transcriptional adaptation response in mouse cells . Therefone xrn-1  and the   . SR-prot alleles . We also89 model , possiblisoforms .i.e., the mutant mRNA was still degraded but the adapting gene was not upregulated) (act-5(ptc) or unc-89(ptc) alleles with ergo-1, nrde-3, and rrf-3  biogenesis, maturation and transport into the nucleus. We tested several pathways  and obsegulated) . These Rnd rrf-3 , and allogenesis , suggestTogether, these results indicate that mRNA decay as well as small RNA biogenesis and transport are critical in triggering transcriptional adaptation.C. elegans. By carrying out a small RNAi screen and a follow up analysis using double mutants, we identified several new factors that regulate transcriptional adaptation and further validated previously identified ones.Recent advances in reverse genetic tools have significantly expanded our ability to generate genetic modifications in a wide range of organisms . HoweverC. elegans act-5 model, the mutant gene and related adapting gene  are primarily expressed in distinct tissues. However, using an extrachromosomal transcriptional reporter, we observed that in act-5(ptc) mutants, the act-3 promoter adapts to drive transcription in the primary site of act-5 expression, the intestine. As act-5(ptc) mutants do not exhibit any obvious phenotype when the transcriptional adaptation response is intact, we predict that ACT-3 and/or other proteins are able to compensate for the loss of ACT-5. Indeed, when we disrupted transcriptional adaptation, act-5(ptc) mutants did not survive. Thus, transcriptional adaptation can in some cases entail the change in the pattern of expression of related gene(s) and suppress phenotypes that would alter the animal’s fitness.In the act-5(ptc) mRNA decay, while SMG-2 (UPF1) and SMG-4 (UPF3) impact unc-89(ptc) mRNA decay. Similar observations were made in mouse Actb and Rela mutant cells in which siRNA-mediated knock down of SMG6 blocked the transcriptional adaptation response in Actb mutant mESCs but had little influence on Rela mutant MEFs. Conversely, siRNA-mediated knockdown of UPF1 blocked the transcriptional adaptation response in Rela mutant MEFs but not in Actb mutant mESCs  with vacuum; antibiotics  were added  to eliminate remaining food bacteria, and the worms were then incubated on a shaker at room temperature for 15 min. Worms were centrifuged at 3000 rpm for 5 min to pellet early larval stage animals. The buffer was aspirated and 1 ml of fresh buffer was added to resuspend the pellet. Samples were confirmed to be primarily L1 and L2 stage larvae by observing two 5 µl samples on a 6 cm nematode growth medium plate. Starving cultures or cultures that had more than one male were excluded from the experiments.cdc-42 and Y45F10D.4 (iscu-1) were used as reference genes as described previously . For reverse transcription (RT), Superscript III reverse transcriptase  was used following manufacturer's instructions. We used 1–2 μg total RNA for each RT reaction. The qPCR experiments were performed on a CFX Connect Real-Time System (Biorad-Roche Diagnostics) as described previously . cdc-42 eviously , and theY45F10D.4 (forward 5’- CGAGAACCCGCGAAATGTCGGA-3’ and reverse 5’- CGGTTGCCAGGGAAGATGAGGC-3’), cdc-42 (forward 5’-AGCCATTCTGGCCGCTCTCG-3’ and reverse 5’- GCAACCGCTTCTCGTTTGGC-3’), act-1 (forward 5’-ACGACGAGTCCGGCCCATCC-3’ and reverse 5’-GAAAGCTGGTGGTGACGATGGTT-3’), act-2 (forward 5’-GCGCAAGTACTCCGTCTGGATCG-3’ and reverse 5’- GGGTGTGAAAATCCGTAAGGCAGA-3’), act-3 (forward 5’-AAGCTCTTCGCCTTACCATTTTCTC-3’ and reverse 5’-ACAGAGCAAATTGTAGTGGGGTCTTC-3’), act-4 (forward 5’-AGAGGCTCTCTTCCAGCCATCCTTC-3’ and reverse 5’-TGATCTTGATCTTCATGGTGGATGG-3’), act-5 (forward 5’- AAGTGCGATGTCGACATCAGAAAG-3’ and reverse 5’- TAATCTTGATCTTCATTGTGCTTGG-3’), act-5d (forward 5’- AAGTGCGATGTCGACATCAGAAAG-3’ and reverse 5’- TAATCTTGATCTTCATTGTGCTCCGG-3’), unc-89 (forward 5’-AAGGCTGAACTTGTCATCGAAGGAG-3’ and reverse 5’-TCATCTCCACAACATTACCCTCGTG-3’), sax-3 (forward 5’-TGCCGTTTGTCCCGTAACAACTATG-3’ and reverse 5’-ATCTTCTGAAGCTGACGGGGAGAAC-3’), act-3 pre-mRNA (forward 5’-TTTTTCAGAACCATGAAGATCA-3’ and reverse 5’-GAAAATGGTAAGGCGAAGAGC-3’), sax-3 pre-mRNA (forward 5’-TGTAAACCGCACTGCACAAT-3’ and reverse 5’-TCCACCAAGAGCCTGAAAAC-3’). PCR efficiency was determined using external standards on plasmid mini-preparation of cloned PCR products. Expression levels were analyzed by basic relative quantification. qPCR data are based on three biological replicates and three technical replicates for each biological replicate.The following primers were used to amplify the cDNA of target genes: act-5(Δ2) mutant adults was isolated using TRIzol (ambion by Takara). 5’ and 3’ RACE ready cDNA was synthesized by reverse transcription PCR using a SMARTer RACE cDNA Amplification Kit following manufacturer's protocol . PCRs were performed using an Advantage 2 PCR kit . The following gene-specific primers and nested gene-specific primers were used to amplify 3’ and 5’ cDNA ends: act5GSP2 (5’-ACCACCGGAATCGTTTTGGACACCGGAG-3’), act5NGSP2 (5’-GAAGGATATGCCCTCCCACATGCCATCC-3’), act5GSP1 (5'-AAAAATCAGCTTAGAAGCACTTTCGGTG-3’), act5NGSP1 (5’-TCGATGGGCCGGACTCGTCGTACTCCTG-3’), unc89GSP2 (5’-TTTGGTACCATTTGTATAGAGGCGAGTG-3’), unc89NGSP2 (5’-TTCTGAACTGGACAAATCTTGCTTTTCG-3), unc89N1GSP2 (5’- ACTTTCCAGTATCTCCTGGATGTTGCTTC-3’), and unc89N2GSP2 (5’- TTTGAATACTTTTTGATGAACCGTGTGC-3’). RACE experiment revealed an isoform with an alternative start which is present only in act-5(Δ2) mutants  fused to turboRFP in a pUC19 vector. Similarly, a pUC19 vector containing turboRFP was fused with an act-3 promoter region (4.5 kb from V:11073234 to 11077791). The germ line of wild-type animals was injected with the generated plasmids (10 ng ul−1). The transgenic lines were subsequently crossed with act-5(ptc) mutants to transfer the extrachromosomal array to the mutant background.To study the expression of A Zeiss LSM 700 confocal microscope was used to image adult worms.RNAi was performed by feeding double-stranded RNA-expressing bacteria at 25°C from the early larval stage through adulthood (60–75 hr) as previously described . For theunc-89 deletion allele (bns7000), two sgRNAs  were injected with Cas9 protein (0.35 ug/ul), and a dpy-10 sgRNA (2.5 uM) was used as a co-injection marker along with a repair oligo  (To generate the CRISPR/Cas9-induced 0.73 uM) .GGTAGTTAGCGACCCCATGAGGG-3′.sgRNA1: 5′-ACAGACTGGTAAACAAACGAGGG-3′sgRNA2: 5′-ATACCACCACATGTCTCTTC-3’), dunc-89–2 forward (5’-GCTAAAAGTCAGAGTTCCAC-3’), dunc-89–3 reverse (5’- GGATGGGTTTACATAAAAT-3’), dunc-89–4 reverse (5’-TGAAAAAGAAACAACAAAA-3’), dunc-89–5 forward (5’-TAACAAAAAGCTCAAAATG-3’), dunc-89–6 reverse (5’-GGATAGATTTCTGTTGGAGA-3’). The external primers flank a 19612 bp region in wild types and amplify a 3601 bp fragment in bns7000 mutants. The internal primers with different combinations amplify 500-2600 bp products in wild types.The following primers were used for genotyping: dunc-89–1 forward (5’-act-5(ptc); nrde-3 double mutants exhibited act-5 mRNA levels as in the RNAi experiments but also some upregulation of the adapting gene, unlike what was observed in the RNAi experiments . In addition to demonstrating similar genetic requirements as in vertebrates, the authors report the involvement of factors important for small RNA maturation and transport into the nucleus, which provides new mechanistic insight into transcriptional adaptation.Decision letter after peer review:Caenorhabditis elegans" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Jessica Tyler as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Michael Patrascheck (Reviewer #1); Scott Kennedy (Reviewer #2).Thank you for submitting your article "Transcriptional adaptation in The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.C. elegans. They show for two independent case that mutations in mRNAs of either act-5 or unc-89 that destabilize the mRNA can lead to a compensatory increase in related genes. They then use a limited RNAi screen to identify components related to RNA metabolism to be required in different aspects of transcriptional adaptation.In this manuscript the authors describe the discovery of transcriptional adaptation in The paper is generally interesting to read and certainly attractive to a wider audience. There are however some aspects – including some critical control experiments – that need to be addressed.act-3 expression in the gut is a very clear and powerful phenotype. The normalization necessary for qPCR experiments does not adequately account for global RNA levels changes which can be reasonably expected because many of the factors investigated are related to RNA stability. An independent validation seems necessary for at least some factors. The gut-miss-expression phenotype of act-3 seems ideal to validate some of the RNAi clones that prevent transcriptional adaptation.1) Any particular reasons why the strains used in Figure 2 were not used to validate some of the identified factors in Table 1? Especially the C. elegans. Publicly available mutant alleles need to be used to confirm a role for these pathways in transcriptional activation. The worry is that RNAi knockdown induces partial knockdowns, is differentially effective in different tissues, can trigger off-targets silencing, and might trigger indirect and pleiotropic defects due to titration of the RNAi machinery. For example it is noted that smg-2/upf1 knockdown didn't suppress NMD of the unc-89 ptc allele. SMG-2/UPF1 is an obligatory component of the NMD machinery and, therefore, a failure to block NMD after SMG-2/Upf1 RNAi is likely a consequence of partial kd- and not differential requirements for SMG-2/Upf1. This concern is fairly easy to remedy. The authors should ask if animals harboring mutations in NMD and nuclear RNAi factors fail to undergo transcriptional adaptation. qRT-PCR to measure RNA levels of act-3 or sax-3 +/- NMD/nuclear RNAi null mutations would be proper. Monitoring act-5::gfp and act-3::gfp +/- NMD/nuclear RNAi would also be proper. Finally, the authors state that act-5(ptc) and unc-89(ptc) animals do not show their expected loss-of-function phenotypes… presumably because of transcriptional upregulation of homologous genes. Therefore, loss of the adaptation machinery (NMD/nuclear RNAi) in act-5(ptc) and unc-89(ptc) animals would be expected to uncover the act-5(ptc) and unc-89(ptc) lof phenotypes.2) The authors use RNAi to implicate the NMD and nuclear RNAi RNA surveillance pathways in transcriptional activation in 3) The data shown in Figure 4 may not be sufficient to support the author's claims that small RNAs drive transcriptional adaptation in mammals. The paper does not absolutely need this data in order to be published. Hence, one obvious option is to just remove the data from the paper. Another option would be to soften conclusions drawn from the data. Should the data stay as is, the authors should clarify the model further in the text as well as provide additional experimental support for the model. Clarification; the authors claim that the various AGO/Dicer knockdowns do not affect expression of Rela, but the data say otherwise. All four kds appear to change Rela expression and 2-3 of these changes are statistically significant . Experimental support; given how AGO-1/2/3 are thought to function, I don't understand why kd of each of the three AGOs should block transcriptional adaptation. Is the idea that all AGOs act sequentially in a linear pathway to direct adaptation? Because of this perplexing result, the authors would need to provide additional data supporting the idea that mammalian AGOs drive adaptation. The authors could show that AGO depletion using an independent approach (maybe auxin/degron or Ago1/3 knockout MEFs) also blocks transcriptional adaptation. Probably easier to just edit text or remove the data.There are three additional items that it would be nice for the authors to address, but which are not absolutely necessary for publication. These experiments are mentioned because they are all fairly straightforward and their inclusion would make the paper much stronger.act-3/unc-89 pre-mRNA levels. If the effect is transcriptional, intron containing nascent RNAs should change predictably.1) It would be fairly simple to provide data suggesting that up-regulation of homologous genes during "transcriptional activation" is actually due to changes in transcription by using the RNA samples  to conduct qRT-PCR looking at act-5/unc-89 ptc alleles should be extremely specific; i.e. limited to just homologs . An RNA-seq experiment would be an elegant way to show that this is indeed the case.2) If the model is correct, then changes in gene expression seen in animals harboring act-3::gfp CRISPR line were used in lieu of a transgene. Or, RNA FISH showing upregulation of the act-3 mRNA in the intestine in act-5 ptc animals would also be more convincing than the current data.3) CRISPR/Cas9-based gfp tagging of genes is a better and more accurate way to readout gene expression than repetitive arrays integrated into random sites in the genome. Figure 2 would be more convincing if an  The paper is generally interesting to read and certainly attractive to a wider audience. There are however some aspects – including some critical control experiments – that need to be addressed.1) Any particular reasons why the strains used in Figure 2 were not used to validate some of the identified factors in Table 1? Especially the act-3 expression in the gut is a very clear and powerful phenotype. The normalization necessary for qPCR experiments does not adequately account for global RNA levels changes which can be reasonably expected because many of the factors investigated are related to RNA stability. An independent validation seems necessary for at least some factors. The gut-miss-expression phenotype of act-3 seems ideal to validate some of the RNAi clones that prevent transcriptional adaptation.act-3p::rfp extrachromosomal reporter in the gut of act-5(ptc) mutants is a strong phenotype and appears to be an attractive tool that could be used to confirm the factors identified in the RNAi screen. However, we observed transgenerational expression of this extrachromosomal reporter. When we outcrossed act-5(ptc); Ex[act-3p::rfp] animals to transfer the extrachromosomal reporter to a wild-type background, we observed that the WT; Ex[act-3p::rfp] animals still expressed RFP in their gut for several generations. Similarly, when we tested some of the RNAi clones with act-5(ptc); Ex[act-3p::rfp] animals, most worms still exhibited RFP expression in their gut, although some at a clearly reduced level. Thus, the results were not conclusive. In summary, although the act-5(ptc); Ex[act-3p::rfp] animals are useful to illustrate transcriptional adaptation, they cannot be used in a typical screen for genes regulating this process (RNAi or genetic).Indeed, the expression of the C. elegans, requires further investigation in the context of transcriptional adaptation.The transgenerational inheritance phenomenon observed here, which has been previously described in C. elegans. Publicly available mutant alleles need to be used to confirm a role for these pathways in transcriptional activation. The worry is that RNAi knockdown induces partial knockdowns, is differentially effective in different tissues, can trigger off-targets silencing, and might trigger indirect and pleiotropic defects due to titration of the RNAi machinery. For example it is noted that smg-2/upf1 knockdown didn't suppress NMD of the unc-89 ptc allele. SMG-2/UPF1 is an obligatory component of the NMD machinery and, therefore, a failure to block NMD after SMG-2/Upf1 RNAi is likely a consequence of partial kd- and not differential requirements for SMG-2/Upf1. This concern is fairly easy to remedy. The authors should ask if animals harboring mutations in NMD and nuclear RNAi factors fail to undergo transcriptional adaptation. qRT-PCR to measure RNA levels of act-3 or sax-3 +/- NMD/nuclear RNAi null mutations would be proper. Monitoring act-5::gfp and act-3::gfp +/- NMD/nuclear RNAi would also be proper. Finally, the authors state that act-5(ptc) and unc-89(ptc) animals do not show their expected loss-of-function phenotypes… presumably because of transcriptional upregulation of homologous genes. Therefore, loss of the adaptation machinery (NMD/nuclear RNAi) in act-5(ptc) and unc-89(ptc) animals would be expected to uncover the act-5(ptc) and unc-89(ptc) lof phenotypes.2) The authors use RNAi to implicate the NMD and nuclear RNAi RNA surveillance pathways in transcriptional activation in act-5 and unc-89 deletion alleles , further illustrating the physiological relevance of transcriptional adaptation.We fully agree with the reviewers on these points and had been generating double mutant data to incorporate into the paper. We focused on mRNA decay and sRNA biogenesis genes and the data are shown in Table 2 and Table 2—source data 1. In general, we observed effects similar to those using RNAi. In addition, we observed that double mutants that failed to undergo transcriptional adaptation phenocopied the 3) The data shown in Figure 4 may not be sufficient to support the author's claims that small RNAs drive transcriptional adaptation in mammals. The paper does not absolutely need this data in order to be published. Hence, one obvious option is to just remove the data from the paper. Another option would be to soften conclusions drawn from the data. Should the data stay as is, the authors should clarify the model further in the text as well as provide additional experimental support for the model. Clarification; the authors claim that the various AGO/Dicer knockdowns do not affect expression of Rela, but the data say otherwise. All four kds appear to change Rela expression and 2-3 of these changes are statistically significant . Experimental support; given how AGO-1/2/3 are thought to function, I don't understand why kd of each of the three AGOs should block transcriptional adaptation. Is the idea that all AGOs act sequentially in a linear pathway to direct adaptation? Because of this perplexing result, the authors would need to provide additional data supporting the idea that mammalian AGOs drive adaptation. The authors could show that AGO depletion using an independent approach (maybe auxin/degron or Ago1/3 knockout MEFs) also blocks transcriptional adaptation. Probably easier to just edit text or remove the data.We agree with the reviewers that more work needs to be done to confirm the data shown in the original Figure 4; for this reason, we have now removed these data from the manuscript.There are three additional items that it would be nice for the authors to address, but which are not absolutely necessary for publication. These experiments are mentioned because they are all fairly straightforward and their inclusion would make the paper much stronger.1) It would be fairly simple to provide data suggesting that up-regulation of homologous genes during "transcriptional activation" is actually due to changes in transcription by using the RNA samples  to conduct qRT-PCR looking at act-3/unc-89 pre-mRNA levels. If the effect is transcriptional, intron containing nascent RNAs should change predictably.act-5(ptc) and unc-89(ptc) mutants compared to WT, suggesting that increased transcription is causing the increase in mRNA levels.We have now performed qPCR experiments and found higher pre-mRNA levels of the adapting genes in 2) If the model is correct, then changes in gene expression seen in animals harboring act-5/unc-89 ptc alleles should be extremely specific; i.e. limited to just homologs . An RNA-seq experiment would be an elegant way to show that this is indeed the case.act-3 and sax-3) are the only genes whose expression is changed in act-5(ptc) and unc-89(ptc) mutants, respectively. To test specificity for this study, we measured unc-89 and sax-3 mRNA levels in act-5(ptc) mutants, as well as act-5 and act-3 expression levels in unc-89(ptc) mutants. We did not observe any significant difference , indicating that the expression changes are not genome wide.In our published transcriptome analyses of wild type versus mutant mouse cell lines , we observed the differential expression of hundreds of genes. As discussed in the paper, these gene expression changes can be grouped into at least three categories: (1) those that are a direct or indirect result of protein function loss, or forms of compensation other than transcriptional adaptation, (2) those that are a result of transcriptional adaptation, and (3) those that are an indirect result of transcriptional adaptation. Thus, it is unlikely that the adapting genes we analyzed (3) CRISPR/Cas9-based gfp tagging of genes is a better and more accurate way to readout gene expression than repetitive arrays integrated into random sites in the genome. Figure 2 would be more convincing if an act-3::gfp CRISPR line were used in lieu of a transgene. Or, RNA FISH showing upregulation of the act-3 mRNA in the intestine in act-5 ptc animals would also be more convincing than the current data.act-3 lines from Craig Mello, but so far have not observed GFP expression in the gut when crossed into the act-5(ptc) mutant background. This discrepancy could be due to differences in expression levels of the transgene vs. the endogenous gene  background). Given the relatively high autofluorescence of the intestine, a relatively minor increase of the endogenous gene in the GFP-tagged act-3 lines may not be visible over background. It is also possible that the insertion of GFP in the act-3 locus interferes with the transcriptional adaptation response. Thus, further work is required to obtain the optimal reagent to pursue this question.We obtained several GFP-tagged act-3 with other actin genes makes it challenging to design enough act-3-specific probes required for the experiment.We agree that RNA FISH would be a better approach. However, the high level of sequence similarity of


Our study identifies that APOBEC3-mediated RNA editing occurs in breast cancer tumors and is positively associated with elevated immune activity and improved survival.APOBEC3 enzymes contribute significantly to DNA mutagenesis in cancer. These enzymes are also capable of converting C bases at specific positions of RNAs to U. However, the prevalence and significance of this C-to-U RNA editing in any cancer is currently unknown. We developed a bioinformatics workflow to determine RNA editing levels at known APOBEC3-mediated RNA editing sites using exome and mRNA sequencing data of 1040 breast cancer tumors. Although reliable editing determinations were limited due to sequencing depth, editing was observed in both tumor and adjacent normal tissues. For 440 sites (411 genes), editing was determinable for ≥5 tumors, with editing occurring in 0.6%–100% of tumors  at an average level of 0.6%–20% . Compared to tumors with low RNA editing, editing-high tumors had enriched expression of immune-related gene sets, and higher T cell and M1 macrophage infiltration, B and T cell receptor diversity, and immune cytolytic activity. Concordant with this, patients with increased RNA editing in tumors had better disease- and progression-free survivals (hazard ratio = 1.67–1.75,  APOBEC1, 2, 3A–D, 3F–H, and 4) and mice have four (APOBEC1–4) APOBEC genes. Expression of APOBEC1, APOBEC2, and APOBEC4 genes is largely restricted to intestine, muscle, and gonad tissues, respectively, whereas APOBEC3 genes are expressed the most in cells of the immune system )Our study, the first examination of APOBEC3-mediated C-to-U RNA editing in cancer, identifies that this phenomenon occurs in breast cancer tumors. Transcriptome and exome sequencing data were examined for this. Stringent criteria were used in the study to identify such editing in order to reduce false positivity because of sequence variations arising from inherited DNA polymorphisms, DNA mutations, sequencing errors, and read sequence alignment artifacts. Strictness of the criteria was limited by the depth of coverage in the aligned sequencing data that was available to us. With the criteria that were used, approximately 97% of editing estimations were indeterminable because of shallow coverage . ConsideWe devised an editing score to simplify further examination of the multi-dimensional RNA editing determinations. RNA editing across multiple sites of a sample was summarized into the editing score for the sample. The score was simply the fraction of sites for which editing was observed in the sample. We chose not to use the mean of editing levels among the sample′s sites because the precision of editing level calculations was not high due to limitations of depth of sequencing coverage. The approach of targeted sequencing with a focus on known editing sites, which permits much deeper coverage, should be considered in future studies for accurate determination of RNA editing levels.APOBEC3 genes compared to tumors with a score of 0  had higher expression of multiple ore of 0 a. This aic sites . Interesignature  were pooBecause of the constrained site-specific editing determinability, determination being possible for an average of only 11 sites among tumors, we did not examine the biological or clinical relevance of editing of individual RNAs. In examinations using the editing score as an overall marker of APOBEC3-mediated RNA editing, numerous insights were obtained. Tumors with increased RNA editing had more cancer-related changes such as aneuploidy and copy number aberrations in their genomes c. Whethe+ and CD8+, were higher among these tumors  and RNA sequencing data was obtained from National Institutes of Health, Bethesda, MD, USA, under study accession phs000178 of Database of Genotypes and Phenotypes (dbGaP). The data, in BAM format, was downloaded in early 2018 from the Genomic Data Commons (GDC) portal of National Cancer Institute, Bethesda, MD, USA, using the gdc-client GDC data transfer tool (version 1.3). Data in GDC were processed for all TCGA samples in a harmonized and uniform manner, using the GRCh38.p0 human genome reference . BrieflyN) was poor (<10), or if the reference base count (R) suggested the presence of DNA polymorphism, either homozygous  or heterozygous , or if variant base count (V) was 1. For V = 0, editing level was estimated as 0 if R was > 3× mean of R/V ratios of all samples with V > 0; otherwise, editing was considered indeterminable. For V ≥ 2, editing was indeterminable if DNA sequencing coverage was <10, or if the p-value in the comparison of R and V values of RNA and DNA data with one-sided Barnard′s test (Boschloo method) was >0.05. Otherwise, editing level was estimated as the V/(R + V) fraction if V was 0 for DNA data or V/(R + V) of RNA data was ≥10× that of DNA data, and, if V was > 2, there was no strong (>8×) or significant (Fisher exact test p ≤ 0.01) RNA sequencing strand bias of variant compared to reference bases. Strand bias was not tested for V = 2. Editing was considered indeterminable for all other cases. Aligned DNA and RNA sequencing data were examined and compared to determine editing levels in 1040 tumor and 93 adjacent normal tissues. DNA and RNA data were from the same portion of TCGA tissue samples as determined from their biospecimen data identifiers. The data were analyzed with samtools (version 1.3) to generate pileups of base calls of phred33 quality ≥20 for each examined genome position. Pileups were then parsed with custom scripts in awk and R languages to count base calls (A/C/G/T) and to determine editing level from the count data, as outlined in For 24 C-to-U RNA editing events that were identified in four tumor samples, the RNA editing levels were redetermined after realigning RNA sequencing data. For realignment, samtools fastq utility was used to extract read data from the aligned data that had been generated by GDC. Only paired read sequences with concordant mapping were extracted. The sequences were then realigned using Subread [Tumor histologic scores for mitotic counts, nuclear pleomorphism, and tubular formation as per the Nottingham system were collected through manual examination of pathology reports with the aid of data and the search engine in the Text Information Extraction System (TIES) Cancer Research Network , a federScores for intratumoral clonal heterogeneity, as well as tumor aneuploidy, copy number changes, homologous recombination deficiency, and neoantigen load were collated from a TCGA Pan-Cancer Atlas study . To coun2-transformation, TPM values were padded with 0.05.Gene-level counts of mapped RNA sequencing reads were obtained from the GDC portal with the TCGAbiolinks (version 2.5.9) Bioconductor package  in mid-22-transformed TPM values were used. To identify genes that were differentially expressed between two groups, the empirical Bayes-moderated t-test in limma (version 3.38.2) Bioconductor package [p-value and absolute fold change value. To determine the enrichment of expression of the 50 gene sets of the Molecular Signatures Database (MSigDB) Hallmark collection (version 6.2), the gene set variation analysis (GSVA) method implemented in the GSVA Bioconductor package (version 1.30.0) was used [t-test. To control false discovery in multi-testings of both differential gene expression and GSVA analyses, the Benjamini–Hochberg method was used to adjust raw p-values.Log package  was usedwas used . Two-groPRF1) and granzyme A (GZMA) gene expression values as the CYT score [https://cibersort.stanford.edu (jar version 1.06) was used with LM22 signatures and 100 permutations [p-value was ≥0.05 (about 10% of cases) were excluded from analysis. Other immune-related measurements of tumors such as B and T cell receptor diversities were from the study of Thorsson et al. [Immune cytolytic activity in tumors was quantified from perforin 1  and R (version 3.5+). The survival package (version 2.44) for R was used for survival analyses with Cox regression and log-rank tests for the determination of HR and p-values. Statistical overrepresentation tests of gene lists with Fisher′s exact test and false discovery calculation were conducted online at https://pantherdb.org with the complete GO biological process annotation dataset of PANTHER [Unless noted otherwise, default option values were used for all software, group comparisons of continuous and categorical variables were with standard  PANTHER  database


The coupling of transcription and translation is more than mere translation of an mRNA that is still being transcribed. The discovery of physical interactions between RNA polymerase and ribosomes has spurred renewed interest into this long-standing paradigm of bacterial molecular biology. Here, we provide a concise presentation of recent insights gained from super-resolution microscopy, biochemical, and structural work, including cryo-EM studies. Based on the presented data, we put forward a dynamic model for the interaction between RNA polymerase and ribosomes, in which the interactions are repeatedly formed and broken. Furthermore, we propose that long intervening nascent RNA will loop out and away during the forming the interactions between the RNA polymerase and ribosomes. By comparing the effect of the direct interactions between RNA polymerase and ribosomes with those that transcription factors NusG and RfaH mediate, we submit that two distinct modes of coupling exist: Factor-free and factor-mediated coupling. Finally, we provide a possible framework for transcription-translation coupling and elude to some open questions in the field. In bacterial cells, the lack of a physical barrier allows transcription and translation machineries to mingle, thus enabling concurrent translation of an mRNA while it is being transcribed, in a process known as transcription-translation coupling ,2. Due tIn transcription polarity, a premature stop codon curtails not only the expression of the mutated gene, but also that of all genes on the same polycistronic operon downstream of the mutation. The premature translation termination causes the ribosome to dissociate from the nascent mRNA, allowing the transcription termination factor, Rho, to proceed along the nascent RNA all the way to the RNAP. At the RNAP, the Rho factor induces transcription termination, halting transcription of the downstream genes on the operon ,7,8 Figa. Premattrp operon. Starvation for tryptophan induces stalling of the first ribosome translating the leader sequence of the operon. The stalled ribosome prevents the formation of a transcription termination signal on the nascent RNA, allowing the RNAP to continue to transcribe downstream genes on the trp operon ..73].The 30S subunit of all three reconstructed 30S•RNAP particles adopts the same conformation, in which the diameter of the mRNA exit site is widened. This widening of the 30S subunit’s mRNA exit site may allow the nascent RNA to better access the mRNA path on the 30S subunit during translation initiation . Please In the reconstruction of the expressome, the RNAP docks to the mRNA entry site of the ribosome, allowing the nascent RNA exiting the RNAP to immediately enter the ribosome. The binding interface on the RNAP consists of regions close to the nascent RNA exit site from all subunits, and on the ribosome it includes ribosomal proteins uS2, uS3, uS4, uS5, and uS10, and helix 16 of the 30S subunit’s ribosomal RNA  Figure c,e. In aAlthough the RNAP positions in both structures are distinct, they may be part of a single, overarching cycle of transcription-translation coupling. We propose that similar to the translation initiation of a structured mRNA, during which the 3’ end is repositioned on the 30S subunit from the mRNA exit to the mRNA entry site ,76, the In both structures, the NusG- and RfaH-binding sites on the RNAP and the ribosome are too far apart to allow NusG or RfaH to bridge both macromolecules. Therefore, another spatial arrangement between the RNAP and the ribosome must exist that complements already captured and visualized arrangements.The structure of the expressome suggests a continuous, static physical connection between the RNAP and the ribosome during coupling. Such a close connection provides a simple explanation for the effects the coupling of translation exerts on transcription. However, the length of the intervening nascent RNA between the RNAP and the ribosome is constantly fluctuating. Because the ribosome steps three nucleotides at a time along the nascent RNA, the ribosome must wait for the RNAP to add three nucleotides, one by one, before taking a step. This causes the length of the intervening RNA to fluctuate between one, two, three, and no extra nucleotides between the RNAP and the ribosome. Such small variations in the length of the nascent RNA may be scrunched in between the RNAP and the ribosome without breaking the interface.Larger variations are more difficult to reconcile with a static model of the RNAP-ribosome arrangement of the expressome. The transcription and translation rates are dependent on the cellular concentration of different metabolites, i.e., nucleotides and amino acids, respectively. Therefore, these rates will respond differently to concentration fluctuations of these metabolites. These independent responses of transcription and translation will result in varying lengths of intervening nascent RNA. The rate differences are further aggravated by the apparent independent distribution of transcription and translation regulatory elements along genes. . We sugWe can discern two possible modes of transcription-translation coupling, factor-free and factor-mediated coupling; a distinction also eluded to by others, e.g., .In factor-free coupling, the RNAP is initially recruited to the mRNA exit site of the 30S subunit . During Factor-mediated coupling is most apparent for coupling mediated by the RfaH. Here, the coupling also affects the translation of the nascent RNA, in particular, its initiation . This thNusG-mediated coupling appears to be a hybrid of factor-mediated and factor-free coupling. Unlike RfaH, NusG is not recruited at a defined point during the transcription of a gene, but is recruited after the RNAP has cleared a promoter proximal pausing site . This imThe discovery of direct physical interactions between the RNAP and the ribosomes hints that individual transcription events can immediately be relayed to the ribosome, affecting its translational activity. Conversely, individual translation events can be relayed to the RNAP, thus affecting its transcriptional activity. The mutual influence of transcription and translation on coupling raises the tantalizing prospective of a novel mechanism of regulation. Any mechanism of the mutual regulation will have to specify: (1) The phases of transcription and translation that are coupled, (2) the functional states of the RNAP and the ribosome that interact, and (3) the effect this regulation exerts on the coupled processes.Most of our current understanding of transcription-translation coupling was gained from work with a narrow set of model genes and operons under a few conditions. A comprehensive list of genes that support or require coupling for expression remains elusive. Modern genome-wide approaches may overcome this shortcoming in the foreseeable future. It will be interesting to see how this list of genes depends on the presence of NusG or varies with environmental and growth conditions.Although we focused this review on transcription-translation coupling alone, it is important to realize transcription and translation couples with other critical cellular processes. For example, transcription couples to DNA repair ,86 and t


The formation of these structures is the result of conformational changes that occur in the duplex, which allow the binding of a third strand within the major groove of the helix. Formation of these noncanonical forms by introducing synthetic triplex-forming oligonucleotides (TFOs) into the cell may have applications in molecular biology, diagnostics and therapy. This study focused on the formation of RNA triplexes as well as their thermal stability and biological potential in the HeLa cell line. Thermodynamics studies revealed that the incorporation of multiple locked nucleic acid (LNA) and 2-thiouridine (2-thioU) residues increased the stability of RNA triplexes. These data suggest that the number and position of the modified nucleotides within TFOs significantly stabilize the formed structures. Moreover, specificity of the interactions between the modified TFOs and the RNA hairpin was characterized using electrophoretic mobility-shift assay (EMSA), and triplex dissociation constants have been also determined. Finally, through quantitative analysis of GFP expression, the triplex structures were shown to regulate GFP gene silencing. Together, our data provide a first glimpse into the thermodynamic, structural and biological properties of LNA- and 2-thioU modified RNA triplexes.The occurrence of triplexes  The biological functions of nucleic acids are determined by the conformational alterations from one structure to another. The polymorphic nature of DNA and RNA allows them to adopt a variety of structures depending on the sequences, the presence of ions and other biomolecules and the local environment. The formation of noncanonical DNA and RNA forms has been well documented and three-stranded nucleic acids are examples of these unusual structures.et al. and occur when a triplex-forming oligonucleotide (TFO) binds specifically in the major groove of DNA or RNA duplexes1. These structures are classified into two main categories depending on the TFO base composition and binding orientation relative to its target site in the helix. The purine-rich strand of the duplex is recognized by a purine TFO through reverse Hoogsteen hydrogen bonds to form an antiparallel triplex . In the pyrimidine motif, a TFO consisting of cytosine and thymine residues binds parallel to a purine-rich strand of helical DNA or RNA via Hoogsteen hydrogen bonds. Pyrimidine oligonucleotides require base protonation and form triplexes largely in a pH-dependent manner. Because the recognition of DNA or RNA duplexes through an unmodified third strand is typically limited to the presence and length of homopurine-homopyrimidine tracts and low pH conditions, it is important to enhance the biological stability of the triplexes and increase TFO binding affinity toward the complementary strand of the duplex. Therefore, various chemically modified oligonucleotides have been developed to improve the properties of a triple-helical structure and its potential as a molecular tool for applications under physiological conditions. The examples of modifications that stabilize triplexes are LNAs2, 2′-O-methyl-RNAs3, peptide nucleic acids (PNAs)4, 2-thiouridine3 and 5-methylcytidine5.Triplexes were first observed by Felsenfeld 8. Thermal stability studies have shown that LNA residues enhance the thermodynamic stability and kinetic properties when introduced into duplexes12 and highly ordered structures . Recently, Zain’s group has confirmed that the number and position of LNA substitutions in TFOs influence the DNA triplex formation, by TFOs conformational pre-organization for major groove binding16. Furthermore, it has been reported that incorporation of LNA can shift the pK value of cytidine in TFO17. The beneficial influence on the stability, kinetics, resistance to nucleases and cellular uptake make LNAs interesting tools in triplex-based approaches18. Moreover, Chen and co-workers have reported that also 2-thioU in TFO is effective in terms of stabilization of RNA triplexes3.LNA is a conformationally constrained nucleotide analogue, allowing to increase the binding affinity, in comparison with DNA and RNAin vitro and in vivo20, whereas few studies have shown triplex formation by targeting RNA duplex regions. However, it has been found that RNA triplexes are formed mainly in functionally important RNAs, including telomerase RNA21, group I and II introns23, long noncoding RNAs24 and ribosomal RNAs25. Furthermore, it is known that endogenous mirror repeat DNA sequences form intramolecular triplexes, called the H-DNA structure, and play an important role in vivo19. Thus, triplexes of DNA and RNA have a great potential for applications in molecular biology, diagnostics and therapy27. Interaction between the TFO and DNA duplex could be a basis for antigene therapy, where a single oligonucleotide downregulates the target gene expression28. Moreover, the DNA triplex has been used in replication pausing, gene-targeted mutagenesis or genomic DNA mapping29. Interactions between noncoding RNA and genomic DNA are important in the biologically active RNA-dsDNA triplex20. However, some limitations of triplex approaches include the TFO base composition, specificity of TFO-duplex interactions and its pH-dependence.A number of reports concern DNA or mixed RNA-DNA triplex structures formed under various conditions HeLa cell line was studied. LNA and 2-thioU residues cause an essential increase in triplex thermodynamic stability, however, the CD spectra show that these modifications do not change the overall structure of RNA triplexes. In addition, the TFO specificity and hairpin interaction studies indicated that LNA and 2-thioU residues are beneficial for triplex formation under the conditions similar to physiological ones. Notably, data from HeLa cells experiments revealed that TFOs containing LNAs and 2-thioUs can be alternative chemical tools for the regulation of gene expression in various triplex-based strategies.In this paper, we present the triplex-forming thermodynamics and structural properties, binding affinity and cellular activity of RNA TFOs containing simultaneously LNA and 2-thioU modifications, for the first time. We have performed the thermodynamic analysis of the influence of multiple substitutions of LNA and 2-thioU derivatives on triplex thermal stability. The model RNA triplexes were characterized by a UV/VIS melting method and circular dichroism (CD) spectroscopy. In addition, the influence of modified nucleotides on the specificity of TFO-RNA hairpin interactions was determined. Lastly, the biological effect of RNA triplexes in a 32. TFOs constitute potential tools for downregulating gene expression, mediating gene-targeted mutagenesis and mapping genomic DNA29. Therefore, it is crucial to increase the thermodynamic stability of the triplexes under physiological conditions. LNAs appeared to be useful chemical tools to modulate the thermal stability of triple-helical structures33. Moreover, the incorporation of 2-thiouridine into the TFO strand has been shown to stabilize triplex formation with RNA and DNA duplex regions3. Although many studies have reported the functional properties of LNA and 2-thioU modified oligonucleotides in duplex and triplex17, the contributions of both modifications to triplex formation remains unknown. We expected that the multiple and simultaneous substitutions of LNA and 2-thioU within the TFO will induce its conformational changes, improve nuclease resistance and form more favorable binding of TFO to the RNA hairpin under neutral conditions16. Therefore, the studies of the effect of multiple LNA and 2-thioU substitutions on RNA triplex formation, followed by examination in GFP gene expression system in HeLa cells, were performed.Some papers concerning triplex-based strategies revealed interesting and exceptional properties of these structures in therapeutic contexts11. Next, thermodynamic studies of the model RNA triplexes were conducted using the UV/VIS melting method. The thermodynamic data demonstrate that the simultaneous presence of LNA and 2-thioU modifications within the TFO strand has a significant influence on the thermal stabilities of T1–T8 model triplexes. The presence of LNA-cytidine and 2-thioU residues increased the melting temperatures of the RNA triplexes by 15.1 °C on average, in comparison to an unmodified counterpart  were higher for T1, T2 and T4 triplexes , in comparison to T5, T6 and T8 triplexes . The changes in melting temperatures correspond to the numbers of LNA and 2-thioU residues within the TFO strand. This observation agrees with previous findings that showed the stabilization effect of LNA on triplex formation34. In general, the incorporation of LNA nucleotides pre-organizes the structure of TFO oligonucleotides and induces a C3′-endo conformation12. As a consequence, the interactions of the third strand containing LNA residues cause favorable energetic changes during the formation of triplexes. Recently it has been shown that the introduction of 2-thioU within the TFO increased the thermodynamic stability of the triplex3. The presence of a sulfur atom may improve the specificity of TFO interactions with the RNA hairpin by increasing the base stacking and van der Waals contacts3. In addition, most likely 2-thioU modification enhances TFO binding by reducing the thermodynamic cost of dehydration. Simultaneous incorporation of LNA and 2-thioU into a TFO strand leads to significant stabilization of the triplexes.As a result, we were unable to obtain reliable thermodynamic data for the T7 triplex due to the lack of two melting transitions  was determined from the concentration of TFO that caused half of the hairpin to form a triplex39. In general, the binding affinity of TFO is strongly dependent on the pH, which is related to cytidine protonation. Based on the previous study, it is known that LNA substitution in the TFO shifts the pK of cytidine toward high values, promoting the triplex formation through Hoogsteen base pairing, at neutral pH17. In the present paper, the capacity of modified TFO to bind model RNA hairpin was investigated using the EMSA method. We have examined eight variants of the same TFO sequence, containing different number of LNA and 2-thioU substitutions. All of the studied TFOs formed triplex structures (T1–T8) at pH 7.0.To gain insight into the specificity of TFO interactions with a RNA hairpin, we conducted an electrophoretic mobility shift assay (EMSA) and determined triplex dissociation constants under the conditions comparable to physiological ones. The gel mobility shift assay is a useful technique to quantitatively analyze triplex formation. The difference in charge density between double- and triple-helical structures leads to the retardation of duplex migration due to triplex formation42. Our results revealed that the binding affinities between the modified TFO and RNA hairpin are different among the model triplexes 43. Under these conditions, Kd value was 1.2 μM, whereas under the standard conditions (100 mM sodium chloride), Kd value was 27.3 μM for T2 triplex  were searched for their modulation of reporter gene expression in the HeLa cell line because previous thermodynamic studies revealed that these structures are stable under near physiological conditions. In addition, the specificity of the studied RNA triplex interactions (EMSA experiments) allows for applying the TFOs containing LNA and 2-thioU modifications in a cellular context. The effect induced by TFOs with LNA and 2-thioU residues (eight variants) was determined using the quantitative polymerase chain reaction (qPCR) technique.Due to the pH-dependence of triplex formation, it is important to increase its stability in the natural environment of the cell , thus improving its potential for HeLa cells were conducted with pZsGreen-N1 plasmid construct, carrying RNA triplex-forming target sequence. We first examined the possibility of interactions between the TFO variants and pZsGreen-N1 plasmid with a target insert. As expected, our results show a very low (8–10%) binding affinity of the TFO and pZsGreen-N1 vector, even at hundred fold molar excess of TFO  into TFO strand is beneficial for triplex formation. The ability of modified TFOs to selectively modulate the activity of genes is a promising alternative in diagnostics and therapy.The data obtained from these studies show that all variants of TFO cause downregulation of gene expression Fig. . MoreoveIn conclusion, the results presented herein provide information about the thermodynamics, structural and biological properties of model triplexes. The obtained data demonstrate that LNA and 2-thioU modifications are beneficial for triplex formation and increase the resistance of TFOs within the cellular environment. In summary, our findings expand our knowledge of RNA triplex structures containing LNA and 2-thioU residues. The behavior of modified nucleotides makes them an alternative chemical tool for designing triplexes with improved stability under physiological conditions.49. FAM-labeled oligonucleotides were synthesized using fluorescein-labeled phosphoramidite. Thin-layer chromatography (TLC) purification of oligonucleotides of length 12 nt was performed on Merck 60 F254 TLC plates with 1-propanol/ammonia/water = 55:35:10 (v/v/v). Oligonucleotides of length 32 nt were purified by polyacrylamide gel electrophoresis. The details of deprotection and purification of oligonucleotides have been described previously50. Purified oligonucleotides were characterized using MALDI-TOF mass spectrometry.All oligonucleotides were synthesized on a MerMade12 (BioAutomation) synthesizer using standard phosphoramidite chemistry2EDTA, pH 7.0. Oligonucleotide single strand concentrations were calculated based on the absorbance measured above 80 °C and extinction coefficients, which were approximated by a nearest-neighbor model using the ribotask.com website. LNA and 2-thioU modified and unmodified RNA strands with identical sequences were assumed to have identical extinction coefficients. The samples were renatured for 3 min at 90 °C and then cooled to room temperature overnight. The measurements were performed for nine different concentrations of each triplex in the concentration range 10−4–10−6 M. Absorbance versus temperature curves were obtained by the UV melting method at 260 nm in the temperature range 4–90 °C with a heating rate of 0.5 °C/min on a Jasco V-650 spectrophotometer equipped with a thermoprogrammer. Melting curves were analyzed, and the thermodynamic parameters were determined by non-linear curve fitting with MeltWin 3.5 software. Melting temperatures calculated for 10–4 M oligonucleotide concentration are marked by Tm.Oligonucleotides were dissolved in a buffer containing 100 mM sodium chloride, 20 mM MES and 0.5 mM Na2EDTA, pH 7.0 to achieve a 20 µM sample concentration. All samples were renatured for 3 min at 90 °C and then slowly cooled to room temperature overnight before data collection. The measurements were taken at 10 °C in the 210–320 nm wavelength range with a 1 nm data interval. The CD curves were established as an average of three CD measurements. The buffer spectrum was subtracted from the sample spectra.CD spectra were recorded on a Jasco J-815 spectropolarimeter using 1.5 ml quartz cuvettes with a 5 mm path length. The oligonucleotides were dissolved in a buffer containing 100 mM sodium chloride, 20 mM MES and 0.5 mM Na2EDTA, pH 7.0 to obtain final volume of 10 µl. The samples were renatured by 3 min at 90 °C and then cooled to room temperature overnight. After folding, 2 µl of 35% glycerol solution was added. Samples were centrifuged and loaded into a 12% native polyacrylamide gel prepared in 1X TAE buffer, pH 7.0. The electrophoresis was performed at 10 W for 6.5 h at room temperature. The results obtained from three independent EMSA experiments. The data analysis was performed with Origin 8.0 software and the triplex dissociation constant (Kd) was determined from the concentration of TFO that caused half of the hairpin to form a triplex and was calculated using the least squares algorithm39.The 1 µM of FAM labeled RNA hairpin was mixed with increasing concentration of LNA and 2-thioU modified TFO. Oligonucleotides were dissolved in a buffer containing 100 mM sodium chloride, 20 mM MES and 0.5 mM NaHeLa cell experiments were performed with the use of pZsGreen-N1 expression plasmid with the GFP protein. The PCR products (carrying RNA hairpin sequence) and the pZsGreen-N1 vector were digested by EcoRI and PstI restriction enzymes, at 37 °C overnight. The products of digestion were verified by electrophoresis on agarose gel, and then purified. Next, the products were ligated by T4 DNA ligase (Thermo Scientific), at a 3:1 ratio, at 4 °C overnight. The 130-nucleotide fragment of the sequence of interest  was inserted into a pZsGreen-N1 expression plasmid, upstream of the GFP protein coding region. The recombinant plasmid was cultured in E. coli in LB medium with kanamycin, overnight at 37 °C. The pZsGreen-N1 plasmid construct was extracted with the Qiagen extraction kit (Qiagen Plasmid Midi Kit 25), and the construct was then confirmed through sequencing.HeLa cells were passaged to 24-well plates and cultured in a standard RPMI 1640 medium containing 10% FBS (Invitrogen), 1x Antibiotic-Antimycotic solution (Sigma Aldrich) and 1x MEM vitamins solution (Sigma Aldrich). When the confluence reached ca. 90% per well, co-transfection of the pZsGreen-N1 plasmid constructs of 1 μg and TFOs at concentrations of 150 nM was carried out with Lipofectamine 2000 (Invitrogen) in medium without antibiotics. After 24 h incubation, cells were washed with phosphate-buffered saline (PBS) and then total RNA was extracted. Each transfection experiment (using various TFOs) was repeated at least three times. For quantitative analysis of silencing, total RNA from cells was isolated using the TRIzol method51. Next, 0.5 μg of RNA was subjected to DNase I (Life Technologies) treatment. RNA quality was controlled by separation on 1.5% agarose gels. cDNA, which was the template for qPCR, was obtained from a reverse transcription reaction using iScript cDNA Synthesis Kit (Bio-rad). qPCR was performed on a CFX96 real-time PCR system (Bio-Rad) using iTaq SYBR Green Supermix (Bio-rad) and 96-well clear plates. The level of GFP mRNA was quantified with the use of target gene primers which are listed in Supplementary Materials. Statistical analysis of the qPCR results was performed with Bio-Rad CFX Manager 3.0 and OriginLab 8.0 software. The results from the biological replicates for particular samples were gathered to determine the mean relative expression and its standard deviation (Bio-Rad CFX Manager 3.0). Next, the normalized expression of the GFP gene was compared using a significance level of 0.05 for the particular analyzed TFOs.One day before transfection, Supplementary Materials


An artificially evolved ribozyme can catalyse the synthesis of RNA by using trinucleotide triphosphates as building blocks. Related research article Attwater J, Raguram A, Morgunov AS, Gianni E, Holliger P. 2018. Ribozyme-catalysed RNA synthesis using triplet building blocks. eLife7:e35255. doi: 10.7554/eLife.35255If you could travel three to four billion years back in time, you would find yourself in a world inhabited by the first primitive cells. But what if you went even further? According to the ‘RNA World’ hypothesis, biological evolution was preceded by chemical evolution: an era in which the tasks that are currently performed by DNA (the storage of genetic information) and proteins  are performed by RNA molecules . MoreoveAlthough it may have taken many millions of years for self-replicating nucleic acids to emerge, we can speed up the process in the laboratory by employing a high-throughput technique called in vitro evolution . First, Techniques such as these have been employed to evolve RNA enzymes known as ribozymes, which are capable of connecting multiple pieces of RNA to generate a longer strand or using single building blocks  to assemble a new strand from an RNA template . To do tThe researchers used trinucleotide triphosphates  as building blocks, rather than the more typical mononucleotide triphosphate building blocks. When fed to the active ribozyme, the triplets worked together to unravel those folded RNA structures that would otherwise have prevented the replication process . Unlike Remarkably, the new ribozyme was able to copy a wide range of complex RNA sequences, including its own catalytic domain. Structural analyses also revealed that it had an unusual heterodimeric structure that comprised of a catalytic portion and a non-catalytic RNA co-factor. Although this kind of dimerization has been seen before in RNA evolution, the spontaneous emergence of two distinct and cooperative RNA molecules had not previously been observed in an active ribozyme .The use of triplet building blocks had other advantages: it was possible to copy RNA sequences in both directions , and copying could be initiated anywhere along a template, sometimes even without the use of a primer . AccordiMany challenges will have to be overcome to demonstrate that RNA, by itself, could have supported an evolving genetic system. If RNA were to have existed as a sole genetic biopolymer, it would have needed to be able to replicate itself efficiently, completely, and without the help of proteins. Although evidence for an RNA-copying machinery is likely to be found within a small ribosomal subunit, an ancient ribozyme with intact RNA replication activity has yet to be discovered . Ribozym


Sclerotinia sclerotiorum. However, recent progresses in RNAi or dsRNA-based pest control requires more detailed characterization of the RNA silencing pathways in S. sclerotiorum to investigate the utility of dsRNA-based strategy for white mold control. This study elucidates the roles of argonaute enzymes, agl-2 and agl-4, in small RNA metabolism in S. sclerotiorum. Gene disruption mutants of agl-2 and agl-4 were compared for changes in phenotype, virulence, viral susceptibility, and small RNA profiles. The Δagl-2 mutant but not the Δagl-4 mutant had significantly slower growth and virulence prior to virus infection. Similarly, the Δagl-2 mutant but not the Δagl-4 mutant, showed greater debilitation under virus infection compared to uninfected strains. The responses were confirmed in complementation studies and revealed the antiviral role of agl-2. Gene disruption mutants of agl-2, agl-4, Dicer-like (dcl)-1, and dcl-2 did not change the stability of the most abundant endogenous small RNAs, which suggests the existence of alternative enzymes/pathways for small RNA biogenesis in S. sclerotiorum. Furthermore, in vitro synthesized dsRNA targeting agl-2 showed a significantly reduced average lesion diameter (P < 0.05) on canola leaves with agl-2 down-regulated compared to controls. This is the first report describing the effectiveness of RNA pesticides targeting S. sclerotiorum RNA silencing pathway for the control of the economically important pathogen.RNA silencing or RNA interference (RNAi) is an essential mechanism in animals, fungi, and plants that functions in gene regulation and defense against foreign nucleic acids. In fungi, RNA silencing has been shown to function primarily in defense against invasive nucleic acids. We previously determined that mycoviruses are triggers and targets of RNA silencing in  Neurospora crassa and other filamentous fungi have revealed diverse small RNA biogenesis pathways, suggesting that fungi adapt RNAi silencing pathways for several cellular processes with some of the RNA silencing genes playing dual roles , it is intriguing whether corresponding argonaute genes affect S. sclerotiorum virulence and whether it could add to the tool box of disease control with other novel strategies.of crops . Recent rotiorum . The virame time . A similgenicity . TherefoThe Argonaute protein family constitutes four domains, N-terminal domain, Mid domain, and RNA-binding domains known as PAZ domains, and slicer domains known as PIWI domains . ArgonauMucor circinelloides, has three argonaute genes while Cryphonectria parasitica has four argonaute genes and Colletotrichum higginsianum has two  has been characterized, and N. crassa RNA silencing components not involved in quelling have been shown to be involved in this pathway  and compared the changes in morphology and pathogenicity. Gene displacement mutants revealed that only agl-2 is important in vegetative growth, as well as antiviral defense, whereas the biological function of agl-4 remains unknown. We further established the application of dsRNA externally targeting agl-2 as an RNA pesticide to slow the infection in a dose-dependent manner.The goals of this study were to determine the function of argonaute genes in endogenous small RNA processing and defending virus infection in S. sclerotiorum was grown on potato dextrose agar (PDA) (Sigma) at 20–22Δ. The gene displaced mutants of Δagl-2 and Δagl-4 strains were grown on PDA amended with hygromycin B (Alfa Aesar) at 100 μg/mL as selection. Dicer mutants were produced in our previous study  using the split-marker homologous recombination cassettes as described before  using primers PtrpC – HY and YG – TrpC to give two amplicons (1.2 and 1.3 kb) each containing part of the hph marker gene with an overlap  cloned to express the full agl-2 gene flanked by 2.8 kb of 5′-upstream and 1.5 kb of 3′-downstream sequences to include the corresponding promoter and terminator. The agl-2 gene and flanking arms were amplified from the DNA extract of DK3 using primers F1-COMP-AGO2 and F4-COMP-AGO2 , and when significant effect was determined, Tukey’s HSD test was performed to compare all pairs of means.PCR amplification of the ere used . dsRNAs agl-2 gene in a dose-response manner using Luna Universal One-Step RT-qPCR Kit (NEB) following the manufacturer’s protocol. The comparative CT method (ΔΔCT method) was used to analyze the data. The expression levels of agl-2 and an endogenous control (actin) were evaluated with three biological replicates and four technical replicates each. The statistical significance of observed fold-difference was analyzed by ANOVA and Tukey’s test for pair-wise means separation.Only the lesions from 200 and 400 ng/20 μl were cut out to extract for total RNA using RNeasy Plant Mini Kit (Qiagen) since 800 ng/20 μl treatment does not produce lesions. RT-qPCR was performed to confirm the silencing of Δdcl-1, Δdcl-2, Δagl-2, and Δagl-4 samples were sequenced. Adaptors were trimmed by BBMap tools (S. sclerotiorum and SsHV2-L genomes were computed using bowtie (MirVana miRNA Isolation kit (Thermo Fisher Scientific) was used to extract small RNAs from 4-day-old mycelia. NEBNext small RNA Library Kit  was used to construct the libraries for sequencing. The libraries were barcoded, pooled in a single lane for 50-nt single-end reads sequencing on an HiSeq4000 at the Roy J. Carver Biotechnology Center, UIUC. Three replicates of samples from SsHV2-L virus-infected DK3 as well as four replicates (two virus-infected and two virus-free mutants) each of ap tools . ShortStap tools  was usedg bowtie , and furg bowtie .hph gene. Sanger sequencing of the PCR amplicons confirmed the integration. Once a monokaryotic mutation was obtained by hyphal-tipping and confirmed by PCR that the target genes were completely deleted, further characterizations of the mutants were carried out.Argonaute-like genes were disrupted directly from wild-type strain DK3 using the same approach as described before . Disruptagl-4 and DK3 exhibited similar growth rates, whereas the Δagl-2 gene displacement mutant exhibited significantly slower growth at 24 h measured by the diameters of hyphal growth (P < 0.05)  . As show < 0.05) , no chanproduced . After m defense .S. sclerotiorum argonaute mutants was evaluated by inoculating detached leaves with agar plugs of mycelia. Lesion size data was collected at 1, 2, and 3 dpi showed that no difference in the lesion size produced by the mutant Δagl-4, but a significantly smaller lesion produced by Δagl-2 mutant compared to those produced by DK3 (P < 0.05).The virulence of d by DK3 , 5 .To examine the effect of viral infection on strains containing null-mutations of d growth , 5 , SRR8785204 (Δdcl1-2), SAMN12129781 (Δdcl1-VF1), SAMN12129782 (Δdcl1-VF2), SRR8785203 (Δdcl2-1), SRR8785202 (Δdcl2-2), SAMN12129783 (Δdcl2-VF1), SAMN12129784 (Δdcl2-VF2), SRR8785201 (Δagl2-1), SRR8785200 (Δagl2-2), SAMN12129777 (Δagl2-VF1), SAMN12129778 (Δagl2-VF2), SRR8785199 (Δagl4-1), SRR8785198 (Δagl4-2), SAMN12129779 (Δagl4-VF1), and SAMN12129780 (Δagl4-VF2). The raw sequence reads were uploaded to NCBI SRA database under accessions SRR8844548 (WT-1), SRR8844549 (WT-2), SRR8785208 (WT-3), SRR8785205 , virus-induced gene silencing (VIGS) approaches or heterologous expression of dsRNA sprays (spray-induced gene silencing) targeting agl-2 in S. sclerotiorum are expected to be effective in reducing the virulence, adding to the tool box of disease control.The results derived from this study pave the way for the development of new control strategies that exploit RNA silencing mechanisms. The external RNA pesticide developed suggests the occurrence of external uptake of RNA in AN, PM, and S-YLM conceived and designed the experiments and wrote the manuscript. PM, CF, and HS performed the experiments. AN analyzed the small RNA data.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


N6-methyladenosine (m6A) modification provides an important epitranscriptomic mechanism that critically regulates RNA metabolism and function. However, how m6A writers attain substrate specificities remains unclear. We report the 3.1 Å-resolution crystal structure of human CCHC zinc finger-containing protein ZCCHC4, a 28S rRNA-specific m6A methyltransferase, bound to S-adenosyl-L-homocysteine. The methyltransferase (MTase) domain of ZCCHC4 is packed against N-terminal GRF-type and C2H2 zinc finger domains and a C-terminal CCHC domain, creating an integrated RNA-binding surface. Strikingly, the MTase domain adopts an autoinhibitory conformation, with a self-occluded catalytic site and a fully-closed cofactor pocket. Mutational and enzymatic analyses further substantiate the molecular basis for ZCCHC4-RNA recognition and a role of the stem-loop structure within substrate in governing the substrate specificity. Overall, this study unveils unique structural and enzymatic characteristics of ZCCHC4, distinctive from what was seen with the METTL family of m6A writers, providing the mechanistic basis for ZCCHC4 modulation of m6A RNA methylation. 6A) RNA modification is an evolutionarily conserved epitranscriptomic mechanism that impacts several cellular processes. Here the authors present a structure-function analysis of the ZCCHC4, 28S RNA-specific m6A methyltransferase, shedding light on its regulation and mechanisms that ensure substrate specificity.The N6-methyladenosine (m One of the most prevalent RNA modifications is N6-methyladenosine (m6A), which is widely present in mRNA and long noncoding RNA (lncRNA)2, as well as in the ribosomal RNA (rRNA)4 and small nuclear RNA (snRNA)6. Specific methylation of these RNA molecules functions to modulate RNA structure and protein–RNA interactions, which in turn influences RNA metabolism, cell signaling, cell survival, and differentiation8. Dysregulation of m6A-based RNA modification has been associated with severe human diseases, such as cancer10.Covalent modifications of RNA molecules represent an evolutionarily conserved epitranscriptomic mechanism that critically regulates diverse cellular activities6A across the epitranscriptome is mediated by an array of distinct writer enzymes. For instance, mRNA and lncRNA are primarily methylated by the METTL3–METTL14 heterodimeric complex15, which recognizes a DRACH  consensus sequence near 3′ UTR18, whereas a subset of mRNA and snRNA sites is distinctly methylated by RNA methyltransferase METTL1619, which recognizes a UACAGAGAA motif embedded in a stem-loop structure21. In addition, m6A modification of cap adenosine at the transcription start nucleotide of mRNAs is achieved by cap-specific methyltransferase CAPAM, which then promotes translation of capped mRNAs22. Recent studies have further demonstrated that the m6A modification on the site 4220 of 28S rRNA and site 1832 of 18S rRNA is, respectively, mediated by CCHC zinc finger-containing protein ZCCHC4 and the methyltransferase METTL523. Notably, these identified RNA methyltransferases bear no sequence homology, except for a remotely related methyltransferase (MTase) domain , raising a question of the molecular basis underlying their distinct substrate specificities.The dynamic profiling of m6A RNA methyltransferase and is highly conserved in multicellular organisms23. ZCCHC4 knockout in human cells eliminates the m6A4220 methylation of 28S rRNA23, but not any other identified m6A sites23, suggesting its exclusive role in methylating 28S rRNA. ZCCHC4-mediated m6A4220 methylation in 28S rRNA promotes ribosome assembly and translation, which in turn impacts cell proliferation and tumor growth9. In addition, a previous study on K-Ras-transformed cells has identified ZCCHC4 as a potential factor required for Ras-mediated gene silencing24. However, due to the lack of structural information, the mechanism by which ZCCHC4 recognizes and methylates its RNA substrate remains unknown.ZCCHC4 is a newly identified m6A RNA methylation, we determined the crystal structure of human ZCCHC4 at 3.1 Å resolution. Distinct from what was observed for all other m6A methyltransferases, ZCCHC4 is organized into four domains, with three flanking zinc finger domains packed around the MTase domain, forming an integrated RNA-binding platform. Strikingly, the catalytic center is blocked by a linker sequence, namely regulatory loop, bridging the MTase domain and the C-terminal CCHC domain, resulting in an autoinhibitory conformation. Furthermore, the SAM-binding pocket adopts a fully closed conformation, suggesting of a mechanism by which cofactor binding is coupled with RNA substrate recognition. In addition, mutational and enzymatic analyses reveal a role of the stem-loop structure within the RNA substrate in governing the substrate specificity. Together, this work reveals the previously unappreciated molecular mechanisms that underlie activity autoregulation and substrate binding of ZCCHC4 in the modulation of cellular m6A RNA methylation.To provide mechanistic insights into the ZCCHC4-mediated m9  , which permitted crystallization and structure determination. The crystal structure of ZCCHC424-464, in complex with S-adenosyl-L-homocysteine (SAH), product of methyl donor S-adenosyl-L-methionine (SAM), was refined to 3.1 Å resolution  of one to pair in antiparallel with residues F48-V51 of the other , likely due to crystal packing effects. These two molecules also yield the highest-quality electron density map, with one of which permitting the modeling of the entire segment of residues M25-G440. We therefore chose this ZCCHC4 molecule for structural analysis. The N-terminal regions of all the other ZCCHC4 molecules are not involved in domain swapping, in line with the fact that ZCCHC4 exists as a monomer in solution, as demonstrated by our size-exclusion chromatography analysis .ZCCHC4 predictably contains a MTase domain with a DPPF catalytic motif, flanked by an N-terminal GRF (Gly–Arg–Phe)-type zinc finger domain and a C-terminal CCHC domain9 Fig. . Based o64) Fig. , encompa24-464 reveals four closely packed domains: an N-terminal GRF zinc finger domain is followed by a C2H2 zinc finger domain, an MTase domain, and a C-terminal CCHC zinc finger domain, folded into an integrated structural unit , highlighting their divergent cofactor-binding mechanisms.The structure of ZCCHC4nit Fig. . The MTanit Fig. . This cenit Fig. . The SAHnit Fig. . On the nit Fig. . In addinit Fig. . It is wThe tandem GRF and C2H2 domains flank one end of the central β-sheet, with the GRF domain stacking on top of the SAH-binding pocket and the C2H2 domain docked in the groove formed by helices αG and αH of the MTase domain Fig. .25 reveals that the GRF domain of ZCCHC4 is well aligned with the corresponding domain of APE2 (apurinic/apyrimidinic endonuclease 2) nuclease26 ; among the most conserved sites are those involved in the interactions of APE2 with single-stranded DNAs for 3′–5′ exonuclease processing26. The CCHC domain of ZCCHC4 bears a remote homology with the CCHC motif of the DHHC (Asp–His–His–Cys) palmitoyltransferases , which harbors a catalytic center for protein palmitoylation27. On the other hand, there is no structural homologue identified for the C2H2 domain.Structural homology search using the Dali server24-464 core fragment shows a comparable activity with full-length ZCCHC4. In contrast, deletion of the C-terminal CCHC domain (ΔCCHC) led to a dramatic reduction of enzymatic activity, while deletion of the N-terminal GRF domain, either alone (ΔGRF) or together with the C2H2 domain (ΔGRF-C2H2), completely abolished the activity of ZCCHC4, indicating the critical requirement of these domains for ZCCHC4-mediated RNA methylation. Consistently, electrophoretic mobility shift assays (EMSA) revealed that, in comparison with wild-type ZCCHC424-464, the ΔGRF, ΔGRF-C2H2, and ΔCCHC truncations all substantially impair the RNA-binding affinity of ZCCHC4 . Analysis of 1D 1H NMR spectra of these domain-truncated ZCCHC4 fragments indicate that they remain folded in solution , supporting a direct role of the flanking domains in mediating substrate binding of ZCCHC4.The close association between MTase and the flanking domains potentially creates an extended RNA-binding surface, implying a possible contribution of the flanking domains to the RNA binding of ZCCHC4 Fig. . To test6A RNA methyltransferases identified so far . Nevertheless, their structures exhibit a similar Rossmann fold, with the catalytic motif aligned next to the SAH-binding pocket  of 6.7 μM 20 . The structural model indicates that the cofactor loop is in close proximity to the RNA substrate, with loop residue Y173 flanking the adenosine ring in a fashion similar to that of residues L75 and I218 of METTL16 -long stem , which in turn reduces the activity of METTL1620. Likewise, binding of SAM or SAH to METTL3 also induces a conformational change of a loop segment at the cofactor-binding site, namely gate loop, resulting in binding-induced folding of the SAM-binding pocket 14. These observations suggest that cofactor binding-coupled conformational changes may represent a common mechanism for various m6A writers.Uniquely among all the mate Fig. . The othAC motif9. Through nucleotide complementation analysis, this study demonstrates that the stem-loop structure critically influences the methylation activity of ZCCHC4. In this regard, structural analysis of 18S rRNA reveals a discrete structural environment for site 1832, which forms a base pair with Cyt1732 at the base of helix 44 , providing an explanation for the lack of methylation activity of ZCCHC4 on this site. Through nucleotide replacement analysis, this study suggests that the stem-loop structural feature of 28S rRNA significantly contributes to the substrate specificity of ZCCHC4. Future investigation is warranted to further determine whether or not the stem region of the RNA substrate directly engages ZCCHC4 interaction or functions to stabilize the conformation of the RNA loop.Previous studies have demonstrated that ZCCHC4 shows high specificity toward 28S rRNA: it specifically methylates Ade4220 of 28S rRNA, but not Ade1832 of 18S rRNA, the other methylation site of rRNA, even though both sites are embedded in an A6A methyltransferases identified so far, except for METTL5, contain MTase-flanking domains, suggesting a flanking-module-directed regulation, as we herein show for ZCCHC4, as a widely adopted mechanism for m6A writers, ensuring both binding affinity and substrate specificity. For instance, METTL3 harbors an N-terminal CCCH zinc finger domain that specifically recognizes the RNA substrate containing the GGACU motif32, which is essential for the methylation activity of the METTL3–METTL14 complex32. The detailed mechanism by which the MTase-associated domains of ZCCHC4 regulate its activity awaits further investigation.Lastly, this study has demonstrated how various structural modules within ZCCHC4 act in synergy for mediating the binding and methylation of substrates. In particular, the GRF and CCHC modules, through direct association with the MTase domain, extend the substrate-binding surface, permitting a rather large RNA-binding platform to accommodate the substrate specificity. In fact, all the RNA m24-513: residues 24-513; ZCCHC424-464: residues 24–464; ΔCCHC: residues 24–368; ΔGRF: residues 100–464; ΔGRF-C2H2: residues 159–464) were each inserted into a modified pRSF-Duet vector, preceded by an N-terminal hexahistidine (His6)-SUMO tag and a ubiquitin-like protease 1 (ULP1) cleavage site. To promote crystallization, five surface mutations  were introduced onto the ZCCHC424-464 construct, which presumably would lead to surface entropy reduction. On the other hand, for biochemical and enzymatic characterizations, various point mutations were generated based on the wild-type ZCCHC424-513 construct. For protein expression, BL21(DE3) RIL cells harboring the expression plasmids were induced by addition of 0.4 mM isopropyl-β-D-thiogalactoside (IPTG) when the cell density reached optical density at 600 nm (A600) of 0.8, and continued to grow at 15 °C overnight. The cells were harvested and lysed in buffer containing 50 mM Tris–HCl (pH 8.0), 1 M NaCl, and 25 mM imidazole, 10% glycerol, 10 µg/mL DNase I, 10 µg/mL RNase A, and 1 mM PMSF. Subsequently, the fusion proteins were purified through a nickel column, followed by removal of His6-SUMO tag by ULP1 cleavage, ion-exchange chromatography and size-exclusion chromatography. The purified protein samples were concentrated in 20 mM Tris–HCl (pH 7.5), 100 mM NaCl, 5% glycerol, and 5 mM DTT, and stored at −80 °C freezer before use.DNAs encoding human ZCCHC4, full-length or various fragments , 11–12% PEG3350, 10% glycerol, and 5 mM TCEP (Tris (2-carboxyethyl) phosphine hydrochloride) (pH 7.0) using the sitting drop vapor-diffusion method at 12 °C. For crystal harvesting, the crystals were soaked in the well solution supplemented with 20% (v/v) ethylene glycol before flash frozen in liquid nitrogen. X-ray diffraction data were collected on beamline 5.0.2 at the Advanced Light Source (ALS), Lawrence Berkeley National Laboratory with a wavelength of 1.283 Å and processed with the HKL3000 program24-513 in buffer containing 20 mM Tris–HCl (pH 7.5), 100 mM NaCl, 5% glycerol, 1 mM DTT at 4 °C for 1 h. Five μL of the mixture was loaded and resolved in 6% TBE native gel at 4 °C under 100 V for 0.5 h. The gel image was visualized by SYBR Gold (Thermo Fisher) staining and subsequently by Coomassie blue staining.To measure the binding between ZCCHC4 and the 30-mer 28S rRNA (5′-CGGUACA CCUGUCAAACGGUAACGCAGGUG-3′), unless indicated otherwise, 0.3 μM RNA was incubated with 0, 0.3, 0.6, or 1.2 μM ZCCHC431) with modifications. Each reaction mixture contains 25 nM ZCCHC424-513, wild-type or mutants, 0.5 μM S-adenosyl-L-[3H] methionine (Perkin Elmer) and 1 μM RNA substrate in 50 mM Tris–HCl (pH 8.0), 7 mM β-ME, 5% glycerol, 100 μg/mL BSA, and 10 μM zinc acetate. The reaction mixture was incubated at 37 °C for 15–20 min, before quenched by 2 mM cold SAM. Ten μL of the reaction mixture was applied onto DEAE filtermat (Perkin Elmer), sequentially washed with 0.2 M ammonium bicarbonate (pH 8.2) twice, water once, and ethanol once. The filter paper was then air dried and soaked in ScintiVerse cocktail (Thermo fisher). The activity was measured by Beckman LS6500 scintillation counter. All the experiments were performed in three biological replicates and repeated with consistent results.The RNA methylation assays follow a previously published protocol , 100 mM NaCl, 1 mM TCEP) overnight. 1 mM SAM compound (Sigma) was dissolved in the same buffer. Titration of SAM in the syringe over ZCCHC424-513 samples was carried out at 5 °C. The time between each injection was set at 180 s. All data were processed with the MicroCal Origin software and fitted with the single-site binding mode. The Kd values and error estimates were derived from the duplicated experiments.ITC measurements were performed using a MicroCal iTC200 instrument . To measure the bindings between the ZCCHC41H NMR experiments, 0.05 mM purified mutant ZCCHC4 proteins were dissolved in 250 μL buffer containing 50 mM sodium phosphate (pH 6.7), 1–3 mM Tris–HCl, 150 mM NaCl, and 10% D2O. NMR spectra were collected on a Bruker Advance 700 MHz NMR spectrometer equipped with a TXI probe at 25 °C and processed using the Bruker TopSpin software.For Further information on research design is available in the Supplementary InformationReporting SummarySource Data