The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused severe damage to the world. With the support of classic evolutionary theories and population genetics principles, many studies on the origin of SARS-CoV-2 have revealed encouraging results but meanwhile some are still under debate. We are concerned with the validity of applying classic evolutionary theories and formula to the evolution of RNA viruses. We have raised several confounding factors like the RNA replication feature and the RNA modification systems of the hosts, which might jeopardize the validity of the application of classic methods to analyze the SARS-CoV-2 data. The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused severe damage to China, especially the Hubei province . Recentlet al. [The emergence of papers on the evolution of SARS-CoV-2 is as fast as the spread of the virus itself. Based on genome sequencing followed by sequence alignment and sequence similarity analysis, researchers have characterized the evolutionary patterns of SARS-CoV-2 and postulated its origins. Theories of bat origin  and panget al.  has takeet al.  also empAs far as we know, the classic theories and principles of evolutionary biology, especially population genetics, are based on the central dogma, where DNA should be first transcribed to RNA and then produce proteins, and meanwhile the DNA replicates itself under a certain error rate. The validity of many formula/software is also based on multiple hidden hypotheses such as random mating, bi-allelic DNA, bi-sexual gender and infinite population size.However, SARS-CoV-2 is a positive-strand RNA virus. It reproduces its own RNA by RNA replication. We doubt the validity of applying classic evolutionary theories and formula to the evolution of RNA viruses. In this article, we would raise and discuss several concerns regarding how the confounding factors would jeopardize the validity of the application of classic methods to analyze the SARS-CoV-2 data. We should emphasize that we neither criticize any studies, nor prove any ideas wrong. Instead, we aim to raise some questions and wish that these concerns could be further discussed by the broad community. We hope our concerns would contribute to the accurate identification of the origins of SARS-CoV-2.We have stated that SARS-CoV-2 is an RNA virus. The classic theories, principles and formula of evolutionary biology are based on the central dogma, which assumes the DNA-to-RNA-to-protein chain. The basic notion is that the mutations on DNA could be inherited rather than the modifications on RNA. For example, despite the numerous types of RNA modifications in higher eukaryotes, these organisms do not suffer from extraordinarily high mutation rates because the modified RNAs could not be transmitted to the next generation. However, for RNA viruses, their RNA is actually their genetic information. Whether the evolutionary principles could be applied to RNA viruses should be seriously debated. The host cells have multiple RNA modification systems/enzymes. The changes in viral RNA (by host cells) would permanently change its genetic information and be transmitted to the next ‘generation’, which is similar to genetic mutations in higher organisms. Technically, one could not distinguish genetic mutations and RNA modifications from the RNA-sequencing data of RNA viruses. So, what is the point of detecting positive/negative selection based on the mutations in the virus population? These mutations are possibly conferred by the host cell’s RNA modification systems. How could the randomly occurring RNA modification events have preference on missense or synonymous sites?et al. [The recent study by Tang et al.  claimed More importantly, the single nucleotide polymorphism and modified RNAs are technically indistinguishable. The software and algorithms only align the sequences but do not tell you whether the observed mismatch is a single nucleotide polymorphism or RNA modification site. This is a biological problem rather than technical problem, and could not be solved by adjusting or improving the alignment parameters or filtering criteria.One may argue that some studies have analyzed RNA modifications by using classic evolutionary theory, but note that the viral RNA is modified by the host cell rather than by the virus itself, and their equivalence (modified by the host or modified by itself) should be formally proven before conducting any analyses.Indeed, the coronaviruses isolated from the hosts  are only compared with SARS-CoV-2. Therefore, RNA virus sequence is compared with the SARS2 RNA, and hence, the used strategy is almost sound. So, these studies compared virus to virus or RNA to RNA and conclude the potential host or carrier based on the highest percent of identity or potential concluded recombination events. However, as we have stated, the sequence similarity could be largely and even randomly skewed by the hosts' RNA modification systems. Therefore, aligning RNA with RNA is fine, but the concern is how to distinguish whether the observed divergence (or mismatch sites) really reflects the phylogeny of the viruses. It could simply be shaped by the arbitrary modification of the host’s enzymes.The next concern caused by RNA modification system is the ‘batch effect’. In population genetics, DNA mutations take place randomly among different individuals. But when RNA viruses are modified by host cells, the modification enzymes are likely to modify multiple sites at a time. Since the genes of an RNA virus (like the 12 genes of SARS-CoV-2) are linked, they are prone to be modified ‘in a batch’. In contrast, in higher organisms, it is not possible to see numerous individual-specific mutations linked within an entire haplotype unless it is driven by selective sweep. This reality again challenges the application of traditional theories to RNA viruses.In our opinion, the RNA viruses should obey a different evolutionary theory. So far, the functional experiments are more important and reliable than the pure evolutionary analyses in this case of RNA virus. When traditional evolutionary principles are jeopardized by additional mutation forces, the functional experiments work well as they did in the past.Apart from being modified by the host RNA modification systems, there are other concerns about whether the evolutionary theories could be applied to the RNA viruses like SARS-CoV-2.et al. [de novo’ RNA mutation is not mentioned by the authors at all, let alone the mutations introduced during the RNA replication process. At least, the authors could briefly introduce the reproduction mode of SARS-CoV-2 rather than ‘mechanically’ apply the formula to an organism which they are not familiar with.First, for cellular organisms, the DNA mutations are majorly introduced during the DNA replication process. The mutation rate is largely connected with the fidelity of DNA replication. The next step is the natural selection force acting on these mutations, after which the deleterious mutations are purged and those beneficial mutations are maintained. However, RNA viruses either undergo the reverse-transcription process (like HIV) or the RNA replication process (like SARS-CoV-2). For RNA viruses, every newly transcribed RNA molecule is a potential offspring of the original virus. The mismatches introduced during reverse transcription or RNA replication would be maintained and kept in the offspring. Before applying the evolutionary formula to RNA viruses, one should state whether RNA replication has similar mismatching rates as DNA replication. Intuitively, DNA–DNA pairing (DNA replication), DNA–RNA pairing (transcription) and RNA–RNA pairing (such as RNA replication) should have different mismatching rates. Thus, when applying theories to SARS-CoV-2, should the authors consider the potentially different mutation rates during the reverse transcription or RNA replication processes? Take the paper by Tang et al.  for instN RNA molecules, and a mutation takes place when N/2 RNA molecules have been transcribed, then only part of the offspring would have this mutation. All these random processes could not be predicted by any algorithms. How could theories on DNA mutations be applied to a transiently existing DNA intermediate or negative-strand RNA?Second, the DNA generated from the reversetranscription is only an intermediate, and could not be packaged into the envelope protein. The same goes for the negative-strand RNA generated by the positive-strand RNA during the RNA replication. So that the DNA/negative-strand RNA and any changes on it could not be directly transferred to the next host cell. However, if a DNA intermediate could transcribe These factors may shed concerns on the accuracy and validity of the results of previous works. However, we do not claim any studies to be wrong since we have neither better methods nor enough evidence. Hopefully, our opinions could be seen and discussed by other researchers and benefit the studies on the evolution and origin of SARS-CoV-2.We are concerned with the validity of applying classic evolutionary theories and formula to the evolution of RNA viruses. We have raised several confounding factors like the RNA replication process and the RNA modification systems of the hosts, which might jeopardize the validity of the application of classic methods to analyze the SARS-CoV-2 data. However, we neither criticize any studies nor prove any ideas wrong. We hope our concerns could be considered by the broad community and could contribute to the accurate identification of the origins of SARS-CoV-2.We anticipate and speculate that the field of virus evolution could be incorporated with more novel evolutionary theories that distinguish cellular organisms, DNA viruses and RNA viruses, due to their distinct features of nucleotide components, mutation rates, and reproductive patterns.The recent evolutionary studies on SARS-CoV-2 have revealed encouraging results as well as debatable questions.The problem of RNA modification system in host cells: RNA modification system in the host cells could act on viral RNAs, which jeopardizes the validity of many hidden hypotheses behind the evolutionary theories.Problems raised from the RNA replication process: the traditional evolutionary theories did not mention the RNA replication process at all, while SARS-CoV-2 exactly uses this approach to replicate itself.


Transposase-assisted RNA/DNA hybrids Co-tagmEntation (termed ‘TRACE-seq’) are compared to traditional RNA-seq methods in terms of detected gene number, gene body coverage, gene expression measurement, library complexity, and differential expression analysis. At the meantime, TRACE-seq enables a cost-effective one-tube library construction protocol and hence is more rapid (within 6 hr) and convenient. We expect this tagmentation activity on RNA/DNA hybrids to have broad potentials on RNA biology and chromatin research.Tn5-mediated transposition of double-strand DNA has been widely utilized in various high-throughput sequencing applications. Here, we report that the Tn5 transposase is also capable of direct tagmentation of RNA/DNA hybrids in vitro. As a proof-of-concept application, we utilized this activity to replace the traditional library construction procedure of RNA sequencing, which contains many laborious and time-consuming processes. Results of  E. coli can bind to synthetic 19 bp mosaic end-recognition sequences appended to Illumina sequencing adapters (termed ‘Tn5 transposome’) (Transposase-assisted RNA/DNA hybrids Co-tagmEntation (TRACE-seq) to achieve rapid and low-cost RNA sequencing starting from total RNA extracted from 10,000 to 100 cells. We find that TRACE-seq performs well when compared with conventional RNA-seq methods in terms of detected gene number, gene expression measurement, library complexity, GC content and differential expression analysis, although TRACE-seq shows bias in gene body coverage and is not strand-specific. At the same time, it avoids many laborious and time-consuming steps in traditional RNA-seq experiments. Such Tn5-assisted tagmentation of RNA/DNA hybrids could have broad applications in RNA biology and chromatin research.Transposases exist in both prokaryotes and eukaryotes and catalyze the movement of defined DNA elements (transposon) to another part of the genome in a ‘cut and paste’ mechanism . Taking posome’)  and has posome’) . In addiposome’) . While Tposome’) . Given tposome’) , in addiTo test whether Tn5 transposase has tagmentation activity on RNA/DNA hybrids, we prepared RNA/DNA duplexes by performing mRNA reverse transcription. We first validated the efficiency of reverse transcription and the presence of RNA/DNA duplexes using a model mRNA sequence  as template . We thenWe next asked whether RNA/DNA hybrids are tagged by Tn5 and performed quantitative polymerase chain reaction (qPCR) quantification for the three samples. We observed that cycle threshold (Ct) value of the Tn5 transposome sample is about eight cycles smaller than the heat inactivated Tn5 sample or the control sample, indicating approximately 256 times more amplifiable products . We alsoTo compare Tn5 tagmentation efficiency between RNA/DNA hybrids and dsDNA, we performed tagmentation and qPCR on equal amount of mRNA RT products and genomic DNA (gDNA). Average Ct value of the hybrids samples was about four cycles more than gDNA samples, indicating the efficiency of Tn5 toward hybrids is about 1/16 of that of dsDNA . It is kAs reverse transcriptase could produce dsDNA from RNA/DNA hybrids, we next designed an experiment by eliminating the RT component and directly assess tagmentation activity using annealed RNA/DNA hybrids where no dsDNA is possible. We annealed in vitro transcribed and purified ssRNA  with chemically synthesized complementary ssDNA. We confirmed the successful production and purity of the RNA/DNA hybrids by dot-blot assay and native-PAGE . A 8-cycHaving demonstrated the tagmentation activity of Tn5 on RNA/DNA hybrids, we then thought about its potential applications. RNA/DNA duplexes can be found in many in vivo scenarios, including but not limited to R-loop and chromatin-bound lncRNAs . Under iWe then compared the library quality between TRACE-seq and NEBNext Ultra II RNA library prep kit, a commonly used kit for RNA-seq library construction. In addition, we conducted a comparison to Smart-seq2, which is a similar method in its use of oligo(dT) primed cDNA synthesis and Tn5 tagmentation. The HEK293T RNA used in these libraries was all from the same batch of cells. We found that TRACE-seq libraries exhibited similar percentage of reads mapped to annotated transcripts, rRNA contamination and gene numbers to NEBNext data when mRNA was used as input, but a higher rRNA contamination when total RNA was used as input ~9%, . In addiOne of the most important goals of RNA-seq is to detect differentially expressed genes among different samples. Having assessed the library quality of TRACE-seq, we next compared the performance of TRACE-seq in detecting differentially expressed genes between undifferentiated and differentiated mESCs to NEBNext Ultra II RNA library prep kit. As shown in Previous studies found that Tn5 exhibits a slight insertion bias on dsDNA substrates . To furtBased on substrate diversity and the conserved catalytic domain of the retroviral integrase superfamily including the Tn5 transposase, we envision in this study that Tn5 may be able to directly tagment RNA/DNA hybrid duplexes, in addition to its canonical dsDNA substrates. Having validated such in vitro tagmentation activity, we developed TRACE-seq, which enables one-tube, low-input and low-cost library construction for RNA-seq experiments and demonstrates excellent performance in DE analysis. Compared to conventional RNA-seq methods, TRACE-seq does not need to pre-extract mRNA and synthesize a second DNA chain after mRNA reverse transcription. Therefore, TRACE-seq bypasses laborious and time-consuming processes, is compatible with low input, and reduces reagent cost . During Despite its unique advantages, there is room to further improve TRACE-seq. For instance, the libraries generated by TRACE-seq in its current form are not strand-specific, which is a significant drawback for RNA-Seq experiments. Yet, TRACE-seq should be able to be converted to 5’ RNA-seq or 3’ RNA-seq, which can directionally preserve the 5’ or 3’ end information of transcripts . In addiCVCL_1926) used in this study were daily maintained in DMEM medium (GIBCO) supplemented with 10% FBS (GIBCO) and 1% penicillin/streptomycin (GIBCO) at 37°C with 5% CO2. We have confirmed no mycoplasma contamination using TransDetect PCR Mycoplasma Detection Kit (TransGen).HEK293T cells (RRID:25 dynabeads (Invitrogen). Genomic DNA (gDNA) from HEK293T cells was purified using genomic DNA purification kit (Qiagen) according to the manufacturer’s instructions.Total RNA was extracted from cells with TRIzol (Invitrogen), according to the manufacturer’s instructions. The resulting total RNA was treated with DNase I (NEB) to avoid genomic DNA contamination. Phenol/chloroform extraction and ethanol precipitation were then performed to purify and concentrate total RNA. For mRNA isolation, two successive rounds of poly(A)+ selection were performed using oligo(dT)Assessment of RNA integrity was performed with RNA 6000 Pico kits (Agilent Technologies). HEK293T total RNA sample was analyzed by Agilent 2100 Bioanalyzer (Agilent Technologies), and RIN was calculated using the supplied 2100 software.20 primer, oligo d(T)23VN primer (NEB) was annealed to template RNA; 2) Instead of SS IV buffer, SS III buffer supplemented with 7.5% PEG8000 was added to the reaction mixture; 3) The reaction was incubated at 55°C for 2 hr. To test the presence of RNA/DNA hyrids, IRF9 RT products were treated by DNase I (NEB) and RNase H (NEB) respectively according to the manufacturer’s instructions followed by urea-PAGE analysis.A model mRNA  was in vitro transcribed from PCR products and purified by urea-PAGE. The model mRNA, HEK293T total RNA and mRNA were reverse transcribed into RNA/DNA hybrids by SuperScript IV reverse transcriptase (Invitrogen), according to the manufacturer’s protocol, with several modifications: 1) Instead of oligo d(T)TTAGCTTCACAGGAAGTTGGAACTGTGTTTGGTGGATCAGGTTCGTAAGGACAGTCCTGGCAATGAACAGTGGCGCAGTAGACTAATGCAACGGCAAGAATTAAGGTCTTCATGGTGGCGGATCCGAGCTCGGTACCAAGCTTGGGTCTC-3’) was first amplified by PCR from CLuc Control plasmid (NEB) with forward primer (5’-TAATACGACTCACTATAGGG-3’) and reverse primer (5’-TTAGCTTCACAGGAAGTTGG-3’). RNA was produced from CLuc DNA template using in vitro transcription reaction by MAXIscript T7 Transcription Kit (Invitrogen). The resulting 150 nt RNA was treated by DNase I (NEB) and further purified by 6% urea-PAGE. Annealing between the purified in-vitro transcribed RNA and the synthesized complementary CLuc ssDNA sequence was conducted under two different conditions. 400 ng and 240 ng RNA was annealed with 200 ng DNA in group 1 and 2 respectively in the annealing buffer . The samples were first incubated for 5 min at 94°C and then cooled down slowly (1°C per minute) to room temperature. The annealed products were then purified using 2.2X Agencourt RNAClean XP beads (Beckman Coulter).To generate the 150 bp RNA/DNA hybrid, the CLuc DNA template used for in vitro transcription  for 1 hr at room temperature, followed by washing three times with 1X TBST. Lastly, the membrane was incubated with HRP linked anti-mouse secondary antibody  for 1 hr at room temperature. Signals were detected with ECL Plus Chemiluminescent reagent (Thermo Pierce).The presence of RNA/DNA hybrids in the CLuc annealed products were confirmed by dot blot assay. Nitrocellulose membrane  was marked and spotted with mRNA RT products, 150 bp CLuc annealed products and 150 bp dsDNA (negative control). The membrane was air dried for 5 min before UV-crosslink . After crosslinking, the membrane was blocked by 5% non-fat milk in 1X TBST at room temperature for 1 hr. Then the membrane was incubated with anti-hybrid S9.6 antibody  glycerol, 80 mM HEPES-KOH (pH 7.9), 100 mM KCl, 2 mM magnesium acetate) and electrophoresed in 0.5 X TBE buffer at 180 V for 1.5 hr.gDNA contamination detection qPCR experiments were performed to assess potential gDNA contamination. After DNase treatment, RNA samples were subjected to reverse transcription (RT). Two other groups (without RT enzyme and without RNA) were set as negative controls. These groups were subjected to qPCR with three pairs of primers respectively, using the method described above. The qPCR primers were designed within exons near the 3' end of three representative housekeeping genes:GCATCCTGGGCTACACTGAG-3’;GAPDH-qFWD: 5’-AAAGTGGTCGTTGAGGGCAA-3’;GAPDH-qRVS: 5’-AGTCATTCCAAATATGAGATGCGTT-3’;ACTB-qFWD: 5’-TGCTATCACCTCCCCTGTGT-3’;ACTB-qRVS: 5’-CACCATAAAGCGGCACAAGT-3’;CYC1-qFWD: 5’-CAGGATGGCAAGCAGACACT-3’.CYC1-qRVS: 5’-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG-3’) and Tn5ME-B oligonucleotides (5’-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG-3’) with equal amounts of mosaic-end oligonucleotides (5’-CTGTCTCTTATACACATCT-3’) in annealing buffer . Samples were incubated for 5 min at 94°C and then cooled down slowly (1°C per minute) to 10°C. Assembly of Tn5  with equimolar mixture of annealed Adaptor A and B was performed according to the manufacturer’s protocol (Vazyme). The resulting assembled Tn5 was stored at −20°C until use.Partial double-stranded adaptor A and B were obtained by separately annealing 10 μM Tn5ME-A oligonucleotides  or gDNA, 12 ng/μl assembled Tn5 and 1 U/μl SUPERase-In RNase Inhibitor (Invitrogen) to the reaction buffer containing 10 mM Tris-HCl, pH = 7.5, 5 mM MgClThe concentrations of RNA/DNA hybrids and dsDNA were first determined by PicoGreen quantification kit (Invitrogen). For testing tagmentation activity of Tn5 on RNA/DNA hybrids, reactions were carried out as above, with mRNA derived RT products or CLuc annealed products as substrate. The tagmentation products were then purified using 1.8X Agencourt RNAClean XP beads (Beckman Coulter) to remove Tn5 and excess free adaptors and eluted in 6 μl nuclease-free water. The size distribution of RNA/DNA hybrids after tagmentation was assessed by a Fragment Analyzer Automated CE System with DNF-474 High Sensitivity NGS Fragment Analysis Kit (AATI).AATGATACGGCGACCACCGAGATCTACACTCGTCGGCAGCGTC-3’; 5’-CAAGCAGAAGACGGCATACGAGATGTCTCGTGGGCTCGG-3’), qPCR was performed in a LightCycler (Roche) with a 5 min pre-incubation at 95°C followed by 40 cycles of 10 s at 95°C and 40 s at 60°C. For testing the effect of different buffers on tagmentation activity of Tn5 on RNA/DNA hybrids, buffers used were as follows: 1) Tagment buffer L (Vazyme); 2) Buffer with 8% PEG8000 ; 3) Buffer with 10% DMF ; 4) Buffer with 5% PEG200% and 8% PEG8000 .For testing tagmentation activity of Tn5 on RNA/DNA hybrids by quantitative polymerase chain reaction (qPCR), tagmentation products purified as above (100X-diluted) was firstly strand-extended with 0.32 U/μl Bst 3.0 DNA Polymerase (NEB) and 1X AceQ Universal SYBR qPCR Master Mix (Vazyme) at 72°C for 15 min, and then Bst 3.0 Polymerase was inactivated at 95°C for 5 min. After adding 0.2 μM qPCR primers (5’-The PCR products following RNA/DNA hybrid tagmentation and strand extension were ligated to a blunt-end cloning vector using pEASY-Blunt Zero Cloning Kit (TransGen), followed by chemical transformation. Then, several single colonies were picked and sequenced with the forward primers of T7 and T3 promoters.For TRACE-seq library preparation, all reactions were performed in one tube. Reverse transcription and tagmentation reactions were carried out as above. Strand extension reaction was performed by directly adding 0.32 U/μl Bst 3.0 DNA Polymerase and 1X NEBNext Q5 Hot Start HiFi PCR Master Mix (NEB) to tagmentation products and incubating at 72°C for 10 min, followed by Bst 3.0 DNA Polymerase inactivation at 95°C for 5 min. Next, 0.2 μM indexed primers were added to perform enrichment PCR as follows: 30 s at 98°C, and then n cycles of 10 s at 98°C, 75 s at 65°C, followed by the last 10 min extension at 65°C. The PCR cycles ‘n’ depends on the amount of purified total RNA input . After enrichment, the library was purified twice using 1X Agencourt AMPure XP beads (Beckman Coulter) and eluted in 10 μl nuclease-free water. The concentration of resulting libraries was determined by Qubit 2.0 fluorometer with the Qubit dsDNA HS Assay kit (Invitrogen) and the size distribution of libraries was assessed by a Fragment Analyzer Automated CE System with DNF-474 High Sensitivity NGS Fragment Analysis Kit (AATI). Finally, libraries were sequenced on the Illumina Hiseq X10 platform which generated 2 × 150 bp of paired-end raw reads.NEBNext Ultra II RNA libraries were constructed using NEBNext Ultra II RNA Library Prep Kit for Illumina  according to the manufacturer’s instructions. Smart-seq2 libraries were performed according to the previously published protocol .SCR_011847)  for quality control and adaptor trimming. The minimal threshold of quality was 20, and the minimal length of reads to remain was set as 20 nt. In terms of differential gene expression analysis, we down-sampled reads per library to 60 million. Otherwise, we down-sampled reads per library to 30 million. Then reads were mapped to human genome (hg19) and transcriptome using STAR  (SCR_005476) (SCR_002105) (SCR_014597) (SCR_018665) (SCR_005275) (SCR_006525) (http://broadinstitute.github.io/picard/). Library complexity was calculated by Preseq  (SCR_010236) (https://weblogo.berkeley.edu/). Reads Coverage was visualized using the IGV genome browser  (SCR_015687) (SCR_005514) (SCR_000432) (https://rstudio.com/).Raw reads from sequencing were firstly subjected to Trim Galore  , and the_005476) . Perform_002105) . The FPK_014597) , and gen_014597)  were plo_018665) . Reads d_005275) , and med_018664) . The seq_011793) . Differe_015687)  with gen_005514) . And all In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:Your revised manuscript addresses the reviewers' prior concerns. We anticipate your new TRACE-Seq method will be of interest to readers as an efficient, lower cost alternative to traditional library construction methods for RNA-Seq.Decision letter after peer review:eLife. Your article is being evaluated by three peer reviewers, and the evaluation is being overseen by a Reviewing Editor and Kevin Struhl as the Senior Editor.Thank you for sending your article entitled "Transposase assisted tagmentation of RNA/DNA hybrid duplexes" for peer review at As noted in our prior communications about the competing study that has now been published in PNAS, please be sure to mention that published study appropriately in your revised manuscript and to cite it in the main text.Also, with regard to the name of your method, I agree with reviewer #1 that ATRAC-Seq does not make sense as an abbreviation and may be confused with ATAC-Seq, and recommend naming it something else.Reviewer #1:In Lu et al. the authors describe a strategy for producing RNA-seq libraries by the direct tagmentation of RNA-DNA hybrids. This method "ATRAC-seq" is very similar to "SHERRY" recently published in PNAS ("RNA sequencing by direct tagmentation of RNA/DNA hybrids") relying on what appears to be transposition activity of the Tn5 transposase into RNA/DNA hybrids. Overall the paper does a good job characterizing the RNA-seq libraries; however, like the PNAS publication, the authors do not have any experiments that explicitly test the RNA/DNA transposition efficiency. Neither the published work or the manuscript presented here take into account the various efficiencies of RT enzymes / mixes to produce dsDNA, varying based on the RNase H efficiency. It is worth noting that this is irrelevant for producing a simplified assay – it does not matter if the Tn5 is inserting into dsDNA product after the first strand synthesis or to the RNA/DNA hybrids, as both produce a simplified workflow for producing RNA-seq libraries. The issue is that any publication claiming this phenomenon without direct evidence in a controlled setting could result in misguided assumptions to the field. A properly controlled test would eliminate the RT component and directly assess hybrid constructs where no dsDNA is possible. It may be that the efficiency is high, which drives this result and not the dsDNA after RT; however, it needs to be directly demonstrated.Other than the RNA-DNA transposition assumptions, the rest of the manuscript is a test of the RNA-seq libraries that were generated when compared to standard techniques, which are fairly standard and properly assessed.Reviewer #2:The manuscript "Transposase assisted tagmentation of RNA/DNA hybrid duplexes" by Lu et al. describes a new approach involving direct tagmentation of RNA/DNA heteroduplexes for a "one tube" mRNA-seq library preparation protocol called ATRAC-seq. Involving fewer steps, this workflow is allowing the generation of transcriptomics data with a seemingly similar quality as a conventional RNA-seq workflow and is reportedly faster and cheaper.Indeed, as a novel approach, direct tagmentation of RNA/DNA hybrids looks very interesting and can potentially provide new grounds for improving a number of existing RNA-seq protocols allowing to bypass the second strand synthesis step.The major concern, however, is the novelty of this work. A paper describing very similar results and a comparable transcriptomics approach have just been published recently as a peer-review article  and last November 2019 as a preprint. Importantly, some authors from the current Lu et al. work seem to be affiliated with the same departments as the co-authors on Da et al., namely the Tsinghua-Peking Center for Life Sciences and College of Chemistry and Molecular Engineering, Peking University. This might be considered as merely an unlucky coincidence, but the overall similarity of the two works is truly puzzling and thus suggests this might not be the case. It involves obvious parallels in the overall flow of the manuscript and its structure: 1) rationale for attempting the tagmentation of hybrids with Tn5; 2) experimental approach; 3) workflow for mRNA-seq benchmarking; 4) figure layouts look . The actual RNA-seq method ATRAC-seq described by the authors is apparently identical to SHERRY from Da et al., with slight variations such as the enzyme  and tagmentation buffer composition (9% PEG8000 vs 8% PEG8000). In brief, one may think that a number of merely esthetical changes were introduced in the work of Lu et al. to make it appear distinct from Da et al., 2020. That being said, the work of Da et al. also provides more details and mechanistic insights concerning tagmentation of hybrids.Finally, the benchmarking is rather meager, as at a minimum, differential gene expression should be included as well as other parameters as for example detailed in Levin et al., Nat Meth, 2010; Alpern et al., Genome Biology, 2019; Pallares et al., 2020.Other comments:• How does the 256-fold increase in number of amplifiable fragments after tagmentation with active Tn5 vs inactive with RNA/DNA hybrids compare when dsDNA is used as a substrate? In this regard, what the authors may have addressed is the basis of tagmentation efficiency of RNA/DNA hybrids and dsDNA. It would be interesting to know what drives the preference of the Tn5 for tagmenting one substrate over another.• The RNA samples might be contaminated with gDNA, which will presumable serve as a better substrate for Tn5, did the authors check this possibility experimentally or by checking the resulting sequencing reads?• What was the reason of using Bst polymerase? Have the authors compared this to the results obtained with the conventional tagmentation protocol involving PCR amplification as described in the protocol of Picceli et al., 2014? This also relates to the shallow benchmarking already mentioned above.Reviewer #3:General Assessment:This manuscript presents a new method termed "ATRAC-seq," which uses Tn5 to fragment RNA/cDNA hybrids to streamline RNA-Seq library construction. This is an interesting advancement, though the standard methods are not that difficult or time-consuming (contrary to the authors' statements). For this method to be widely adopted, the authors would need to show more data about quality and address issues such as Tn5 sequence specificity and 3' coverage bias. Note that essentially the same method has been published on January 27, 2020 as "SHERRY" -- https://www.pnas.org/content/early/2020/01/24/1919800117.Numbered summary of any substantive concerns.1) One key problem with the manuscript is that the authors do not use a standard sample for which the expression values are known, so that the comparison with the NEBNext Ultra II RNA library prep kit is inconclusive. It's not possible to know whether there is "comparable performance" as written about Figure 2E without a known standard or another control. The authors should add a new series of experiments with standard samples, such as "the well-characterized reference RNA samples A  and B (Human Brain Reference RNA) from the MAQC consortium, adding spike-ins of synthetic RNA from the External RNA Control Consortium (ERCC)" as published by the SEQC/MAQC-III Consortium in Nature Biotechnology 32:903-914 (2014). In that paper, the authors compare to qRT-PCR data as well as RNA-Seq. Moreover, Figure 2E shows R=0.6970 between the NEB and ATRAC-seq libraries – that is not particularly good correlation.2) In addition, it would be interesting to see a comparison to Smart-seq2, which is a similar method in its use of oligo(dT) primed cDNA synthesis and Tn5 tagmentation. This method is much closer to ATRAC-seq than the NEB kit.3) The authors need to more explicitly address 3' end bias , as it relates to sequence coverage of genes based on their length. Analysis could be presented as in Figure 1 of Ramsköld et al. Nature Biotechnology 30:777-782 (2012). The 3' end bias was also observed in Di et al. PNAS . How will this affect expression level measurements and downstream analysis? One possible solution is to use rRNA depletion together with random-primed cDNA synthesis?4) Other analyses that should be considered are evenness of coverage along a transcript (coefficient of variation) and the ability to identify differentially expressed genes .5) The authors should explain further the "per-position" analysis  as it is not clear what is being shown or how it was calculated.6) There are experimental and computational details missing from this manuscript. The authors should add the following:a) Were the ATRAC-seq and NEB libraries prepared from the same RNA?b) What was the RIN score of RNA used in each experiment?c) How was the NEB library constructed? This is not mentioned in the Materials and methods section.d) How is the annealing done for Tn5 oligos ?e) What is the full name and catalog # for the Tn5 purchased from Vazyme?f) How many reads are there for each library? Analyses should be done with the same number of raw reads per library by down-sampling.g) Accession #'s for human rRNA should be listed.eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Kevin Struhl as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Bart Deplancke (Reviewer #2).Thank you for submitting your article "Transposase assisted tagmentation of RNA/DNA hybrid duplexes" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.eLife but that some conclusions require a modest amount of additional new data, as they do with your paper, we are asking that the manuscript be revised to either limit claims to those supported by data in hand, or to explicitly state that the relevant conclusions require additional supporting data.We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, when editors judge that a submitted work as a whole belongs in eLife, either of which would be linked to the original paper.Our expectation is that the authors will eventually carry out the additional experiments and report on how they affect the relevant conclusions either in a preprint on bioRxiv or medRxiv, or if appropriate, as a Research Advance in Summary:The revisions have addressed most of the concerns raised previously by the reviewers. Some additional revisions need to be carried out before the manuscript is acceptable for publication.Revisions expected in follow-up work:1) See comment by reviewer #1 regarding a missing positive control and comparisons of efficiency for DNA/RNA hybrids versus dsDNA.2) A number of concerns made by reviewer #3 regarding the presentation in the manuscript. None of these concerns require additional experiments.Reviewer #1:I appreciate that the authors went to a good deal of work to test the synthetic constructs that they describe. They note Ct values of 24 (active Tn5), 28 (inactivated Tn5), and 29 (negative control); however, they neglect to include a positive control. I am surprised, as this would be an easy addition – annealing a ssDNA to the other ssDNA template as opposed to RNA. As it stands, the ct of 24 seems very late for transposed product. Comparing to dsDNA will give a sense of the difference in efficiency between DNA/RNA hybrids and dsDNA. The other edits are fine, this is the last component I believe needs to be addressed.Reviewer #2:The authors have adequately addressed our major concerns. No further comments.Reviewer #3:General Assessment:The revised manuscript is much improved. It was good to see the addition of the Smart-seq2 and rRNA depletion with TRACE-seq experiments. It is understandable that the authors could not add an experiment with a standard reference sample or spike-ins due to the COVID-19 outbreak. There are still issues remaining with respect to analysis, presentation, and conclusions.Numbered summary of any substantive concerns.1) The authors' use of housekeeping genes to assess correlation in gene expression measurements between different methods is acceptable, but these issues should be addressed.a) The use of a set of housekeeping genes should be clearly identified in the Results section and the figure legendsb) The actual names of the housekeeping genes used should be listed in a Supplementary table rather than "list from Eisenberg and Levanon, 2013)" as in the Materials and methods section.c) They should also present the analysis with all the genes – noting that one example is shown in the authors' response to reviewers' comments.2) In several places, the authors minimize the underperformance of their TRACE-seq method. In each place, the authors should modify the text and include the actual numbers for the readers in the text. Finally, the text should be modified from "are comparable", "demonstrates comparable performance", and "shows comparable performance" to something more measured that lists the advantages and disadvantages.a) Coefficient of Variation is actually much worse  not "slightly higher coefficient of variation".b) 5' to 3' bias. This issue is not apparent here because of the use of high quality RNA (RIN 9.5), but with lower quality "real world" samples, the bias becomes more of an issue and the gene expression measurements will be affected. This should be noted in relation to the statement "In spite of the gene body coverage bias, the gene expression measurement .… [is] unnoticeably affected."c) rRNA-aligned reads is actually ~100x worse for 200ng total RNA than for 10ng mRNA. That is not "slightly higher but acceptable". It is probably acceptable, but that's a judgement for the reader to make.d) Strandedness. The authors now do mention this, but this is actually a significant drawback for RNA-Seq experiments.3) The authors' explanation of the "per-position" analysis  as still not clear about what is being shown or how it was calculated.4) The cost comparison between NEBnext and TRACE-seq is good, but the Smart-seq2 should be included and it is likely less expensive than either method ($10-15/library). Reviewer #1:In Lu et al. the authors describe a strategy for producing RNA-seq libraries by the direct tagmentation of RNA-DNA hybrids. This method "ATRAC-seq" is very similar to "SHERRY" recently published in PNAS ("RNA sequencing by direct tagmentation of RNA/DNA hybrids") relying on what appears to be transposition activity of the Tn5 transposase into RNA/DNA hybrids. Overall the paper does a good job characterizing the RNA-seq libraries; however, like the PNAS publication, the authors do not have any experiments that explicitly test the RNA/DNA transposition efficiency. Neither the published work or the manuscript presented here take into account the various efficiencies of RT enzymes / mixes to produce dsDNA, varying based on the RNase H efficiency. It is worth noting that this is irrelevant for producing a simplified assay – it does not matter if the Tn5 is inserting into dsDNA product after the first strand synthesis or to the RNA/DNA hybrids, as both produce a simplified workflow for producing RNA-seq libraries. The issue is that any publication claiming this phenomenon without direct evidence in a controlled setting could result in misguided assumptions to the field. A properly controlled test would eliminate the RT component and directly assess hybrid constructs where no dsDNA is possible. It may be that the efficiency is high, which drives this result and not the dsDNA after RT; however, it needs to be directly demonstrated.We thank this reviewer for the suggestion. To address this question, we directly tested Tn5 tagmentation activity on RNA/DNA hybrids produced independently of reverse transcription reaction. Between homopolymers  and base-diversified hybrids, we chose the latter since it is a better mimic of real substrates for RNA-seq experiments. Because the limit of ssDNA length produced by commercially available solid-state chemical synthesis is about 150 nt, we aimed to produce 150 bp RNA/DNA hybrids independently of reverse transcription. We first produced ssRNA model sequence  by in vitro transcription reaction from PCR products. Then we annealed the IVT ssRNA with a 150 nt synthesized complementary ssDNA to produce a RNA/DNA hybrid. We confirmed the successful production of annealed CLuc RNA/DNA hybrids by dot-blot assay and the purity of the resulting hybrids was further examined by native-PAGE . We then subjected the prepared RNA/DNA hybrids to Tn5 transposome, heat-inactivated Tn5 transposome and a blank control (without Tn5) followed by qPCR quantification. We observed that cycle threshold (Ct) value of the Tn5 transposome sample (Ct=24.86) is about 4 cycles smaller than the heat inactivated Tn5 sample (Ct=28.89) or the control sample (Ct=29.25), indicating that Tn5 has direct tagmentation activity towards RNA/DNA hybrids . We have incorporated all the above results into the revised manuscript .Other than the RNA-DNA transposition assumptions, the rest of the manuscript is a test of the RNA-seq libraries that were generated when compared to standard techniques, which are fairly standard and properly assessed.We thank the reviewer for the positive comment.Reviewer #2:The manuscript "Transposase assisted tagmentation of RNA/DNA hybrid duplexes" by Lu et al. describes a new approach involving direct tagmentation of RNA/DNA heteroduplexes for a "one tube" mRNA-seq library preparation protocol called ATRAC-seq. Involving fewer steps, this workflow is allowing the generation of transcriptomics data with a seemingly similar quality as a conventional RNA-seq workflow and is reportedly faster and cheaper.Indeed, as a novel approach, direct tagmentation of RNA/DNA hybrids looks very interesting and can potentially provide new grounds for improving a number of existing RNA-seq protocols allowing to bypass the second strand synthesis step.The major concern, however, is the novelty of this work. A paper describing very similar results and a comparable transcriptomics approach have just been published recently as a peer-review article  and last November 2019 as a preprint. Importantly, some authors from the current Lu et al. work seem to be affiliated with the same departments as the co-authors on Da et al., namely the Tsinghua-Peking Center for Life Sciences and College of Chemistry and Molecular Engineering, Peking University. This might be considered as merely an unlucky coincidence, but the overall similarity of the two works is truly puzzling and thus suggests this might not be the case. It involves obvious parallels in the overall flow of the manuscript and its structure: 1) rationale for attempting the tagmentation of hybrids with Tn5; 2) experimental approach; 3) workflow for mRNA-seq benchmarking; 4) figure layouts look . The actual RNA-seq method ATRAC-seq described by the authors is apparently identical to SHERRY from Da et al., with slight variations such as the enzyme  and tagmentation buffer composition (9% PEG8000 vs 8% PEG8000). In brief, one may think that a number of merely esthetical changes were introduced in the work of Lu et al. to make it appear distinct from Da et al., 2020. That being said, the work of Da et al. also provides more details and mechanistic insights concerning tagmentation of hybrids.eLife. Thus, since the initial submission of our work, we aimed to make all the information we have as transparent as possible to the editorial office and reviewers. Now that their work published in PNAS, we have properly cited the study in the Discussion section of our revised manuscript.We thank this reviewer for pointing out the competing study. We did not know about it when we designed our project; despite the fact that some the authors of PNAS are our colleagues, we did not talk about the projects throughout the entire study and the two studies are independently performed. When we were about to submit our work at the end of 2019, we did then notice their paper posted on bioRxiv. To expedite our study, we quickly prepared our manuscript and also indicated the competing study in our initial cover letter to With regard to the similarity of figure layout and experimental details of our method (renamed to “TRACE-seq” per the request of reviewer #1) with SHERRY: we acknowledge that the two methods have similar concept and thus similar reagents that are key to the success of the tagmentation activity on RNA/DNA hybrids. This could be further magnified by the simplified library preparation procedure, which now contain greatly reduced steps comparing to traditional library preparation procedure. This is especially the case in terms of some key reagents. For example, PEG8000 is a known crowding agent that effectively increased the efficiency of tagmentation reaction . Nevertheless, these independently developed conditions and chosen reagents demonstrate that Tn5-mediated tagmentation activity is reproducible and robust.In order to provide more details and mechanistic insights concerning tagmentation of hybrids, we have performed multiple experiments during the revision. For instance, we have provided evidence that Tn5 has direct tagmentation activity towards RNA/DNA hybrids . This is achieved by assessing Tn5-mediated tagmentation activity on RNA/DNA hybrids obtained without reverse transcriptase, which could produce dsDNA from RNA/DNA hybrids. We designed an experiment by eliminating the RT component and directly assess annealed RNA/DNA hybrid constructs where no dsDNA is possible. We confirmed the successful production and purity of annealed RNA/DNA hybrids by dot-blot assay and native-PAGE , and observed activity of Tn5 on such RNA/DNA hybrids substrate. Secondly, during revision we discovered a new component that greatly improves Tn5 tagmentation efficiency towards RNA/DNA hybrids . The addition of PEG200 in the tagmentation condition, which we believe enables the RNA/DNA hybrids to favor B-form conformation , makes hybrids a better substrate of Tn5 and thus significantly improves the tagmentation reaction and quality of libraries. With this key invention, the current correlation between NEB and TRACE-seq  is much better than the data in the original manuscript. Third, we have performed additional differential gene expression analysis using differentiated and undifferentiated mESCs. All of these results are unique to this study and have been incorporated into the revised manuscript .Finally, the benchmarking is rather meager, as at a minimum, differential gene expression should be included as well as other parameters as for example detailed in Levin et al., Nat Meth, 2010; Alpern et al., Genome Biology, 2019; Pallares et al., 2020.We thank the reviewer for the suggestion and pointing out these references. Because it is well known that there are many differentially expressed genes between undifferentiated and differentiated mESCs , during revision, we chose them as inputs for differential gene expression analysis using TRACE-seq procedure and the traditional NEB procedure, respectively.As shown in Figure 3A, TRACE-seq successfully detected 4,577 differentially expressed genes , while NEB detected 4,452 differentially expressed genes . The overlapping gene number is 4,071 , showing very high consistency between methods. Besides, the fold change of the 4,071 overlapping genes is highly correlated between methods . Therefore, TRACE-seq shows excellent performance in differential gene expression analysis.We also assessed the performance of TRACE-seq in terms of library complexity and evenness of coverage as mentioned in previous work . TRACE-seq (using random RT primer) library has high complexity, which is highly consistent with NEB library. What’s more, TRACE-seq library complexity maintains at high level with a small input material . As for evenness of coverage, compared to NEB and Smart-Seq2 libraries, TRACE-seq libraries show a slightly higher coefficient of variation of gene coverage . These results have been incorporated into the revised manuscript .Other comments:• How does the 256-fold increase in number of amplifiable fragments after tagmentation with active Tn5 vs inactive with RNA/DNA hybrids compare when dsDNA is used as a substrate? In this regard, what the authors may have addressed is the basis of tagmentation efficiency of RNA/DNA hybrids and dsDNA. It would be interesting to know what drives the preference of the Tn5 for tagmenting one substrate over another.We thank this reviewer for the question. To answer this question, we performed tagmentation experiment on equal amount of gDNA and mRNA RT products (quantified by PicoGreen assay) followed by qPCR experiment to quantify amplifiable fragments. We found that average Ct value (Ct=25.23) of the hybrids samples was about 4 cycles more than gDNA samples , indicating the efficiency of Tn5 towards hybrids is about 1/16 of that of dsDNA.It is known that natural RNA/DNA hybrids favor A-form conformation. Interestingly, in the presence of PEG200, hybrids were found to favor B-form conformation , which we expected to make the hybrids a better substrate of Tn5. Indeed, addition of PEG200 diminishes this difference by greatly improving the Tn5 tagmentation efficiency towards hybrids (Ct=21.94), while having no influence on dsDNA (Ct=21.15). This result indicates that the conformation of substrates certainly affects the preference of Tn5. In addition, this finding also significantly improves the tagmentation reaction and provides a condition that greatly improves the quality of libraries. These results have been incorporated into the revised manuscript .• The RNA samples might be contaminated with gDNA, which will presumable serve as a better substrate for Tn5, did the authors check this possibility experimentally or by checking the resulting sequencing reads?We appreciate the reviewer’s thoroughness. During revision, we have performed qPCR experiments to assess potential gDNA contamination. After DNase treatment, RNA samples were subjected to reverse transcription (RT). Two other groups (without RT enzyme and without RNA) were set as negative controls. Then we utilized primer pairs within an exon of three represented housekeeping genes to perform qPCR for these groups, respectively. In this way, potential gDNA contamination in the RNA sample and the cDNA generated by RT can be amplified simultaneously.We found that for all the three genes, the RT groups have small Ct numbers, while the two negative control groups have very large (>35) or even not detectable (N.D.) Ct numbers, similar with qPCR result of blank control (water) . Therefore, it is the newly generated cDNA via RT that is detected by qPCR, and we found no sign of gDNA contamination.Meanwhile, we have also performed bioinformatic analysis of the reads distributions. One would expect to observe many reads from intron if the library were prepared from potential gDNA contamination. On the contrary, as shown in Figure 2H, TRACE-seq libraries starting from purified mRNA showed high exon distribution rates  and low intron distribution rates (4.88% and 2.91%). We thus conclude that the library is constructed from RNA/DNA hybrids after RT, not potential gDNA contamination. These results have been incorporated into the revised manuscript .• What was the reason of using Bst polymerase? Have the authors compared this to the results obtained with the conventional tagmentation protocol involving PCR amplification as described in the protocol of Picceli et al., 2014? This also relates to the shallow benchmarking already mentioned above.Per you request, we have constructed libraries using Bst 3.0 DNA polymerase and SS IV reverse transcriptase respectively and analyzed the sequencing data, so as to compare the strand extension catalytic performance of the enzymes. We found that the Bst 3.0 DNA polymerase showed higher mapping ratio (Supplementary file 1); we thus think Bst 3.0 may be a better choice for strand extension in TRACE-seq.We have also constructed libraries using Q5 DNA polymerase and KAPA DNA polymerase  respectively to compare their PCR amplification performance. The mapping ratio of Q5 DNA polymerase library was significantly higher than KAPA DNA polymerase library. The results showed that Q5 DNA polymerase performed better than KAPA DNA polymerase during amplification of TRACE-seq (Supplementary file 1). In addition, due to addition of both PEG200 and DMF to tagmentation reaction, the mapping ratios of these libraries were overall lower than that of libraries tagmented without DMF. Thus, we choose to only add PEG200 to conventional tagmentation buffer in the final recipe to achieve greatly improved tagmentation efficiency.Further benchmarking has been conducted during revision, including differential gene expression analysis, assessment of library complexity and evenness of coverage, which are incorporated into the revised manuscript .Reviewer #3:General Assessment:This manuscript presents a new method termed "ATRAC-seq," which uses Tn5 to fragment RNA/cDNA hybrids to streamline RNA-Seq library construction. This is an interesting advancement, though the standard methods are not that difficult or time-consuming (contrary to the authors' statements). For this method to be widely adopted, the authors would need to show more data about quality and address issues such as Tn5 sequence specificity and 3' coverage bias. Note that essentially the same method has been published on January 27, 2020 as "SHERRY" -- https://www.pnas.org/content/early/2020/01/24/1919800117.Numbered summary of any substantive concerns.1) One key problem with the manuscript is that the authors do not use a standard sample for which the expression values are known, so that the comparison with the NEBNext Ultra II RNA library prep kit is inconclusive. It's not possible to know whether there is "comparable performance" as written about Figure 2E without a known standard or another control. The authors should add a new series of experiments with standard samples, such as "the well-characterized reference RNA samples A  and B (Human Brain Reference RNA) from the MAQC consortium, adding spike-ins of synthetic RNA from the External RNA Control Consortium (ERCC)" as published by the SEQC/MAQC-III Consortium in Nature Biotechnology 32:903-914 (2014). In that paper, the authors compare to qRT-PCR data as well as RNA-Seq. Moreover, Figure 2E shows R=0.6970 between the NEB and ATRAC-seq libraries – that is not particularly good correlation.We agree with the reviewer that a more standard sample would give us more accurate information about the performance of TRACE-seq. Unfortunately, due to the outbreak of COVID-19, neither Universal Human Reference RNA, Human Brain Reference RNA nor ERCC was available at the moment. Instead of external spike-in RNA, internal control genes were also frequently used to normalize gene expression data . Thus, we chose a series of endogenous control genes, i.e. housekeeping genes ), to compare the performance of TRACE-seq and NEB kit in terms of gene expression measurement, and found a high correlation between NEB and TRACE-seq for endogenous control genes (R=0.9447). Thus, we believe TRACE-seq demonstrates comparable performance to the NEB kit. These results have been incorporated into the revised manuscript .In the meanwhile, we have significantly optimized the tagmentation condition during revision. Now, as shown below, the correlation between NEB and TRACE-seq  is much better than the data in the original manuscript. This is due to the addition of PEG200 in the tagmentation condition, which we believe enables the RNA/DNA hybrids to favor B-form conformation and thus a better substrate of Tn5 . This finding significantly improves the tagmentation efficiency and provides a condition that greatly improves the quality of libraries. These results have been incorporated into the revised manuscript .2) In addition, it would be interesting to see a comparison to Smart-seq2, which is a similar method in its use of oligo(dT) primed cDNA synthesis and Tn5 tagmentation. This method is much closer to ATRAC-seq than the NEB kit.We thank the reviewer for the suggestion. During revision, we have performed additional RNA-seq library construction by both TRACE-seq and Smart-seq2, and then compared their performance in terms of gene number, gene expression analysis, gene body coverage, evenness of coverage, library complexity, etc. in the revised manuscript. Most of the genes (~93%) detected by TRACE-seq overlap with that of Smart-seq2, with slightly more genes detected by TRACE-seq. In addition, TRACE-seq showed comparable performance to Smart-seq2 in terms of gene expression measurement. When the gene body coverage across all transcripts is concerned, TRACE-seq showed a slightly more 3’ end bias than Smart-seq2, consistent with the observation that TRACE-seq shows a slightly higher coefficient of variation of gene coverage. Nevertheless, TRACE-seq library complexity is similarly high when compared to NEB and Smart-seq2 library.3) The authors need to more explicitly address 3' end bias , as it relates to sequence coverage of genes based on their length. Analysis could be presented as in Figure 1 of Ramsköld et al. Nature Biotechnology 30:777-782 (2012). The 3' end bias was also observed in Di et al. PNAS . How will this affect expression level measurements and downstream analysis? One possible solution is to use rRNA depletion together with random-primed cDNA synthesis?Per the request of the reviewer, transcripts were grouped according to annotated lengths and the gene body coverage was analyzed separately. As shown in Figure 2 —figure supplement 1F, the gene body coverage was comparable among TRACE-seq, NEB kit and Smart-seq2 libraries for transcripts shorter than 1kb. For transcripts with length between 1kb and 4kb, a 3’ end bias was observed in TRACE-seq libraries (using oligo dT RT primer); for transcripts with length between 4kb and 15kb, the central regions of transcripts were less covered by TRACE-seq (using oligo dT RT primer), which is also a known phenomenon in Smart-seq2 libraries . We also performed TRACE-seq by using rRNA depletion together with random-primed cDNA synthesis. While this indeed solved the 3’ end bias of TRACE-seq, we appear to observe a 5’ end bias. Nevertheless, this library shows a higher correlation with NEB kit (R=0.9447). In spite of these gene body coverage bias, the gene expression measurement and differential gene expression analysis is almost unaffected, as shown in Figure 2E and Figure 3.4) Other analyses that should be considered are evenness of coverage along a transcript (coefficient of variation) and the ability to identify differentially expressed genes .We thank the reviewer for the suggestion. We have calculated the median coefficient of variation of coverage over the 1000 most highly expressed transcripts by Picard Tools in the revised manuscript. Compared to NEB and Smart-seq2 libraries, TRACE-seq libraries show a slightly high coefficient of variation of coverage .In addition, comparison of the performance in terms of differential gene expression analysis between NEB and TRACE-seq libraries have been conducted in the revised manuscript. Because it is well known that there are many differentially expressed genes between undifferentiated and differentiated mESCs , during revision we performed DE analysis using TRACE-seq procedure and the traditional NEB procedure, respectively.As shown in Figure 3A, TRACE-seq successfully detected 4,577 differentially expressed genes , while NEB detected 4,452 differentially expressed genes . The overlapping gene number is 4,071 , showing very high consistency between methods. Besides, the fold change of the 4,071 overlapping genes is highly correlated between methods . Therefore, TRACE-seq shows excellent performance in differential gene expression analysis.5) The authors should explain further the "per-position" analysis  as it is not clear what is being shown or how it was calculated.We apologize for not making this clear in the original main text. In the revised manuscript, we calculated nucleotide composition of the first 30 bases of each sequencing read per library by QoRTs to characterize the potential insertion bias of Tn5 . The detailed description can be found in the Results section.6) There are experimental and computational details missing from this manuscript. The authors should add the following:a) Were the ATRAC-seq and NEB libraries prepared from the same RNA?Yes, we extracted RNA from cultured HEK293T cells and then used it in parallel to construct NEB, TRACE-seq and Smart-seq2 library. The newly updated results are shown in Figure 2 and Figure 2—figure supplement 1.b) What was the RIN score of RNA used in each experiment?We have performed experiment to assess the RIN score. The HEK293T RNA samples used in experiments are from the same batch. The RIN score of the batch is high as shown in Figure 2—figure supplement 1E, so the RNA integrity is assured.c) How was the NEB library constructed? This is not mentioned in the Materials and methods section.The NEB library was constructed according to the manufacturer’s instructions (NEB #E7770S). We have added several sentences in the revised manuscript .d) How is the annealing done for Tn5 oligos ?10μM synthetic Tn5ME-A adapter or 10μM Tn5ME-B adapter were mixed with equal amount of Tn5ME-Rev oligos in annealing buffer . The two samples were both incubated in a PCR block starting at 95°C for 5min followed by decreasing gradient of 1°C per minute until 10°C. We have added several sentences in our revised manuscript .e) What is the full name and catalog # for the Tn5 purchased from Vazyme?The full name of Vazyme Tn5 is “TruePrep Tagment Enzyme” and the catalog number is #S601-01 .f) How many reads are there for each library? Analyses should be done with the same number of raw reads per library by down-sampling.Indeed, our analyses were done with the same number of reads per library. In terms of differential gene expression analysis, we down-sampled reads per library to 60 million. Otherwise, we down-sampled reads per library to 30 million.g) Accession #'s for human rRNA should be listed.We apologize for the missing information. The accession numbers for human rRNA we used are NR_003286.2, NR_003287.2, NR_003285.2, and X71802.1.Reviewer #1:I appreciate that the authors went to a good deal of work to test the synthetic constructs that they describe. They note Ct values of 24 (active Tn5), 28 (inactivated Tn5), and 29 (negative control); however, they neglect to include a positive control. I am surprised, as this would be an easy addition – annealing a ssDNA to the other ssDNA template as opposed to RNA. As it stands, the ct of 24 seems very late for transposed product. Comparing to dsDNA will give a sense of the difference in efficiency between DNA/RNA hybrids and dsDNA. The other edits are fine, this is the last component I believe needs to be addressed.We thank this reviewer for the suggestion. Per your request, we bought commercially available 150nt ssDNA strands and produced dsDNA by annealing the two strands. The 150 bp-hybrid was prepared as previously mentioned. We then subjected the prepared RNA/DNA hybrids and dsDNA to Tn5 transposome, and a blank control (without Tn5) followed by qPCR quantification. We observed that cycle threshold (Ct) value of the hybrid sample with Tn5 transposome treatment (Ct=22.68) is about 8 cycles smaller than the control sample (Ct=30.4), indicating that Tn5 has direct tagmentation activity towards RNA/DNA hybrids. We also observed that cycle threshold (Ct) value of the dsDNA sample with Tn5 transposome treatment (Ct=18.08) is about 4 cycles smaller than the hybrid sample with Tn5 transposome treatment (Ct=22.68), indicating that the efficiency of Tn5 towards hybrids is about 1/16 of that of dsDNA . It should be noted that we previously conducted qPCR assay with templates diluted 1:600, which might be over-diluted and led to the previously observed Ct value (24.86). Now we are conducting the assay with templates diluted 1:100. We have incorporated all the above results into the revised manuscript .Reviewer #3:General Assessment:The revised manuscript is much improved. It was good to see the addition of the Smart-seq2 and rRNA depletion with TRACE-seq experiments. It is understandable that the authors could not add an experiment with a standard reference sample or spike-ins due to the COVID-19 outbreak. There are still issues remaining with respect to analysis, presentation, and conclusions.Numbered summary of any substantive concerns.1) The authors' use of housekeeping genes to assess correlation in gene expression measurements between different methods is acceptable, but these issues should be addressed.a) The use of a set of housekeeping genes should be clearly identified in the Results section and the figure legendsWe have included the words “a set of housekeeping genes” in the Results section and the figure legends in the revised manuscript.b) The actual names of the housekeeping genes used should be listed in a Supplementary table rather than "list from Eisenberg and Levanon, 2013)" as in the Materials and methods section.We have listed the names of the housekeeping genes in the Supplementary file 6.c) They should also present the analysis with all the genes – noting that one example is shown in the authors' response to reviewers' comments.We have presented the scatterplots with all genes as Figure 2—figure supplement 1C in the revised manuscript.2) In several places, the authors minimize the underperformance of their TRACE-seq method. In each place, the authors should modify the text and include the actual numbers for the readers in the text. Finally, the text should be modified from "are comparable", "demonstrates comparable performance", and "shows comparable performance" to something more measured that lists the advantages and disadvantages.We have modified the corresponding text to avoid the vague descriptions in the revised manuscript.a) Coefficient of Variation is actually much worse  not "slightly higher coefficient of variation".We have modified the text and included the actual numbers of coefficient of variation in the revised manuscript.b) 5' to 3' bias. This issue is not apparent here because of the use of high quality RNA (RIN 9.5), but with lower quality "real world" samples, the bias becomes more of an issue and the gene expression measurements will be affected. This should be noted in relation to the statement "In spite of the gene body coverage bias, the gene expression measurement .… [is] unnoticeably affected.".We have modified the text and reminded the readers to pay attention to the quality of RNA in the revised manuscript.c) rRNA-aligned reads is actually ~100x worse for 200ng total RNA than for 10ng mRNA. That is not "slightly higher but acceptable". It is probably acceptable, but that's a judgement for the reader to make.We have modified the text and included the actual percentage of rRNA contamination in the revised manuscript.d) Strandedness. The authors now do mention this, but this is actually a significant drawback for RNA-Seq experiments.We have modified the text to explicitly point out this drawback in the current version of TRACE-seq. We also discussed a potential approach to preserve the strand information.3) The authors' explanation of the "per-position" analysis  as still not clear about what is being shown or how it was calculated.We apologize for the missing information. We have included more detailed information in the figure legend of Figure 2—figure supplement 1J in the revised manuscript.4) The cost comparison between NEBnext and TRACE-seq is good, but the Smart-seq2 should be included and it is likely less expensive than either method ($10-15/library).Firstly, we apologize for a mistake in the cost calculation of TRACE-seq in our previous manuscript. The cost of Tn5 per reaction of TRACE-seq should be $5.43 instead of $27.16. We previously divided the total price of Tn5 by the wrong number of rxn. The actual total cost of TRACE-seq should be $12.68 per reaction. Secondly, we found that the cost of Smart-seq2 in our lab should be $29.12, based on the commercially available reagents in China. This price is close to the cost ($35) previously reported : 1096-1098.). Overall, TRACE-seq is more cost-effective than NEBNext kit and Smart-seq2. We have included the cost of Smart-seq2 in the revised Supplementary file 4.


Escherichia coli degradosome, PNPase is involved in maintaining proper RNA levels within the bacterial cell. It plays a major role in RNA homeostasis and decay by acting as a 3′-to-5′ exoribonuclease. Furthermore, PNPase can catalyze the reverse reaction by elongating RNA molecules in 5′-to-3′ end direction which has a destabilizing effect on the prolonged RNA molecule. RNA degradation is often initiated by an endonucleolytic cleavage, followed by exoribonucleolytic decay from the new 3′ end.The polynucleotide phosphorylase (PNPase) is conserved among both Gram-positive and Gram-negative bacteria. As a core part of the Rhodobacter sphaeroides exhibits several phenotypical characteristics, including diminished adaption to low temperature, reduced resistance to organic peroxide induced stress and altered growth behavior. The transcriptome composition differs in the pnp mutant strain, resulting in a decreased abundance of most tRNAs and rRNAs. In addition, PNPase has a major influence on the half-lives of several regulatory sRNAs and can have both a stabilizing or a destabilizing effect. Moreover, we globally identified and compared differential RNA 3′ ends in RNA NGS sequencing data obtained from PNPase, RNase E and RNase III mutants for the first time in a Gram-negative organism. The genome wide RNA 3′ end analysis revealed that 885 3′ ends are degraded by PNPase. A fair percentage of these RNA 3′ ends was also identified at the same genomic position in RNase E or RNase III mutant strains.The PNPase mutant from the facultative phototrophic R. sphaeroides. This includes sRNAs, emphasizing the role of PNPase in cellular homeostasis and its importance in regulatory networks. The global 3′ end analysis indicates a sequential RNA processing: 5.9% of all RNase E-dependent and 9.7% of all RNase III-dependent RNA 3′ ends are subsequently degraded by PNPase. Moreover, we provide a modular pipeline which greatly facilitates the identification of RNA 5′/3′ ends. It is publicly available on GitHub and is distributed under ICS license.The PNPase has a major influence on RNA processing and maturation and thus modulates the transcriptome of The online version contains supplementary material available at 10.1186/s12864-021-07409-4. Prokaryotes populate nearly every imaginable habitat. In contrast to higher multicellular eukaryotes, they are directly exposed to all types of environmental stress. Since escaping is not an option, prokaryotes need mechanisms to quickly adapt to their changing surrounding. This can be achieved by modifying the transcriptome and/or the proteome. One essential mechanism in bacterial adaptation is to exchange the sigma factor, a subunit of the RNA polymerase. Alternative sigma factors target different DNA sequences and thus activate the expression of a specific set of genes. This activates transcription of genes needed for the cell to deal with the present growth condition , 2.Besides and in addition to the transcriptional initiation, posttranscriptional regulation plays a major role in bacterial adaptation . During Escherichia coli, this complex is composed of RNase E, which serves as catalytic and scaffold protein, a DEAD box RNA helicase (RhlB), an exoribonuclease  and an enolase . In conradosome  that in nditions .E. coli, each monomer consists of two RNase PH-like domains and a KH and S1 domain -ATP was obtained from Hartmann Analytic (SRP-301), the oligonucleotides used for labeling are listed in Table S2 in Additional file The hot phenol method was used to isolate total RNA . The proic SRP-30, the oliThree single colonies were used to inoculate three independent pre-cultures. Every culture was then used to inoculate three main cultures . During the exponential growth phase, all three replicates belonging to one biological pre-culture were harvested and pooled. Total RNA was extracted followed by DNase treatment.2+ at 94 °C for 3 min 15 s using the NEBNext Magnesium RNA Fragmentation Module (NEB) followed by RNA purification with the Zymo Oligo Clean & Concentrator kit. Fragmented RNA was dephosphorylated at the 3′ end, phosphorylated at the 5′ end and decapped using 10 U T4-PNK +/− 40 nmol ATP and 5 U RppH, respectively (NEB). After each enzymatic treatment RNA was purified with the Zymo Oligo Clean & Concentrator kit. The RNA fragments were ligated for cDNA synthesis to 3′ single-read (SR) adapter and 5′ SR adapter diluted 1:2 with nuclease-free water before use. PCR amplification to add Illumina adaptors and indices to the cDNA was performed for 14 cycles. Barcoded DNA Libraries were purified using magnetic MagSi-NGSPREP Plus beads (AMSBIO) at a 1.5 ratio of beads to sample volume. Libraries were quantified with the Qubit 3.0 Fluorometer (ThermoFisher) and the library quality and size distribution was checked using a 2100 Bioanalyzer with the DNA-1000 kit (Agilent). Sequencing of pooled libraries, spiked with 10% PhiX control library, was performed in single-end mode on the NextSeq 500 platform (Illumina) with the High Output Kit v2.5 (75 Cycles). Demultiplexed FASTQ files were generated with bcl2fastq2 (Illumina). The sequencing data are available at NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) under the accession number GSE156818.RNA quality was checked using a 2100 Bioanalyzer with the RNA 6000 Nano kit (Agilent Technologies). Five hundred nanograms of high quality total RNA were used for the preparation of a cDNA library with the NEBNext Multiplex Small RNA Library Prep kit for Illumina (NEB) in accordance with the manufacturers’ instructions with modifications: RNA samples were fragmented with MgRhodobacter sphaeroides 2.4.1 genome (assembly GCF_000012905.2) using READemption  lower than 0.05. All positions within a maximal distance of three nucleotides were merged to one 3′ end with BEDtools’ subcommand merge . All filtered reads were mapped to the on 0.4.3 ;) with ton 0.4.3 ;). The Don 0.4.3 ;) was uson 0.4.3 ;) with tn 2.25.0 ;), the mwindow using a window size of 1 nt while only matches on the same strand were considered for further analysis. Fisher’s exact test was calculated for all intersection files using BEDtools’ subcommand fisher.The intersection of the differential 3′ ends between different RNase mutant strains was analyzed with BEDtools https://github.com/datisp/XPEAP). The raw reads and analyzed data from all experiments are deposited on NCBI Gene Expression Omnibus: PNPase and RNase III mutant strains (NCBI GEO accession number: GSE156818) and thermosensitive RNase E mutant strain .For the 3′ elongation analysis, reads that could not be mapped in end-to-end mode with segemehl were mapped with bowtie2 (version 2.2.6) in local mode with option pnp mutant strain of Rhodobacter sphaeroides 2.4.1. The KH-S1 RNA binding domains were removed and a stop codon was introduced at the end of the remaining coding sequence of pnp resulting in a truncated enzyme lacking those domains. The knockout was confirmed via selection on agar containing gentamicin and subsequent RNA sequencing analysis , while the pnp mutant exhibited repeatedly higher pigment concentrations under phototrophic conditions. However, this difference was statistically not significant.To analyze the functionality of PNPase in vivo, we designed and cloned a c growth . MoreoveE. coli, Yersinia enterocolitica and Photorhabdus sp. PNPase plays an important role in the cold shock response due to selective degradation of mRNAs for cold shock proteins at the end of the acclimation phase to low temperature ; y-axis: COG category. Figure S3. The 3′ elongated RNA sequences are similar in the wild type and the pnp mutant strain. A) Schematic overview of the sequence extraction procedure. The lengths of all non end-to-end mapped reads (B) and of all tail sequences (C) do not differ. In both strains the first part of the tail (around 20 nt in length) is guanine rich (D). Figure S4. Full size Northern blots of the depicted images in Fig. rpsL (D) and 5′ UTR RSP_6083 (E). Red frames mark the selected sections. Figure S5. Full size Northern blots of the depicted half-life images in Fig. Figure S6. Full size Northern blots of the depicted half-life images in Fig. rpsL (B). Red frames mark the selected sections. Figure S7. Full size Northern blots of the depicted half-life images in Fig. Figure S8. A) Sequence windows of 20, 30, 40 or 50 nt upstream and downstream of every wild type enriched 3′ end were extracted. B) Every dot in the boxplots depicts the minimal folding energy (MFE) [kcal/mol] of one RNA sequence computed with RNAfold. C) The number of unstructured sequences  is increased in the group of 20 nt downstream control sequences. Figure S9. Representative RNA full coverage and 3′ end coverage profiles of two selected tRNAs in the wild type and the pnp mutant strain. The full coverage of tRNAs can exhibit characteristic 3′ ends as shown for tRNALeu (A) or 3′ ends which are detected because of minor edges and a different slope .Additional file 2: Supplementary tables of differential gene expression. Table S3. DESeq2 analysis results comparing the differential gene expression in the pnp mutant strain and the wild type. Table S4. BaySeq analysis results comparing the differential gene expression in the pnp mutant strain and the wild type.Additional file 3: Supplementary tables of all differential RNA 3′ ends. Table S4. Differential RNA 3′ ends comparing the pnp mutant strain and the wild type. Table S5. Differential RNA 3′ ends comparing the rnc mutant strain and the wild type. Table S6. Differential RNA 3′ ends comparing the rne mutant strain (32 °C) and the wild type (32 °C). Table S7. Differential RNA 3′ ends comparing the rne mutant strain (42 °C) and the wild type (42 °C).


Mononegavirales, known as nonsegmented negative-sense (NNS) RNA viruses, are a class of pathogenic and sometimes deadly viruses that include rabies virus (RABV), human respiratory syncytial virus (HRSV), and Ebola virus (EBOV). Unfortunately, no effective vaccines and antiviral therapeutics against many Mononegavirales are currently available. Viral polymerases have been attractive and major antiviral therapeutic targets. Therefore, Mononegavirales polymerases have been extensively investigated for their structures and functions. Mononegavirales, known as nonsegmented negative-sense (NNS) RNA viruses, are a class of pathogenic and sometimes deadly viruses that include rabies virus (RABV), human respiratory syncytial virus (HRSV), and Ebola virus (EBOV). Unfortunately, no effective vaccines and antiviral therapeutics against many Mononegavirales are currently available. Viral polymerases have been attractive and major antiviral therapeutic targets. Therefore, Mononegavirales polymerases have been extensively investigated for their structures and functions. Mononegavirales mimic RNA synthesis of their eukaryotic counterparts by utilizing multifunctional RNA polymerases to replicate entire viral genomes and transcribe viral mRNAs from individual viral genes as well as synthesize 5′ methylated cap and 3′ poly(A) tail of the transcribed viral mRNAs. The catalytic subunit large protein (L) and cofactor phosphoprotein (P) constitute the Mononegavirales polymerases. In this review, we discuss the shared and unique features of RNA synthesis, the monomeric multifunctional enzyme L, and the oligomeric multimodular adapter P of Mononegavirales. We outline the structural analyses of the Mononegavirales polymerases since the first structure of the vesicular stomatitis virus (VSV) L protein determined in 2015 and highlight multiple high-resolution cryo-electron microscopy (cryo-EM) structures of the polymerases of Mononegavirales, namely, VSV, RABV, HRSV, human metapneumovirus (HMPV), and human parainfluenza virus (HPIV), that have been reported in recent months (2019 to 2020). We compare the structures of those polymerases grouped by virus family, illustrate the similarities and differences among those polymerases, and reveal the potential RNA synthesis mechanisms and models of highly conserved Mononegavirales. We conclude by the discussion of remaining questions, evolutionary perspectives, and future directions. Mononegavirales, known as nonsegmented negative-sense (NNS) RNA viruses, are a class of viruses infecting numerous plants, animals, and humans, and many of them cause significant diseases and deaths in humans  and human metapneumovirus (HMPV) from Pneumoviridae and human parainfluenza virus (HPIV) from Paramyxoviridae  and Marburg virus (MRAV) from Filoviridae and NIAID category C priority pathogens rabies virus (RABV) from Rhabdoviridae and Nipah virus (NiV) and Hendra virus (HeV) from Paramyxoviridae MononegavMononegavirales initiate viral infection by delivering into the host cell a virus-specific RNA synthesis machine  tocesses –.Mononegavirales transcription, the RdRP initiates de novo RNA synthesis by recognizing a single promoter within the leader (Le) region at the 3′ end of the negative-sense genome and sequentially synthesizes mRNAs of the linear array of genes. The de novo initiation of the RNA synthesis by the RdRP typically involves a priming loop (cis-acting gene-start (GS) and gene-end (GE) sequences of viral genes, respectively  region and replicates the positive-sense antigenome into its negative-sense genome  long and is larger than 240 kDa in size. The sequence of L is conserved among Mononegavirales, and the sequence alignment reveals six conserved regions (CRs), named CR I to VI  domain, CR IV to V in the cap addition (Cap) domain, and CR VI in the cap methylation (MT) domain  domain , 55, 78 ) domain .Mononegavirales L contains all the catalytic activities necessary for RNA synthesis. The enzymatic activities of L are coordinated in such a way that the nascent mRNA transcript is synthesized and modified during multiple specific stages. A 5′ cap structure is formed after the mRNA transcript reaches a certain length, and failure to make a 5′ cap for mRNA results in the premature termination of RNA synthesis , an oligomerization domain (POD), and a C-terminal domain (PCTD), connecting with a flexible linker  binding site  and delivers to N0 nascent RNA genome or antigenome during replication  P is an essential cofactor to regulate the processivity of L. As an adapter, P interacts with NC and bridge in the RNA to thread into the L active sites during transcription and replication –113.  , one for VSV , two for HRSV (PDBs: 6PZK and 6UEN), one for HMPV (PDB: 6U5O), and one for HPIV (PDB: 6V85) (–NTD (magenta), POD (red), and PCTD (orange) for P  , and it observed . Since 2reported , 127. InB: 6V85) –63. For 6U1X) was reported that enables the visualization of not only the 2,109-residue VSV L but also the bound PNTD of the 265-residue VSV P  are shown to interact with CTD, RdRp, and CD domains of L, respectively  in the Cap domain of ynthesis , 60, 125Pneumoviridae polymerases have also been reported in recent months, including a 3.2-Å (PDB: 6PZK) and a 3.67-Å (PDB: 6UEN) resolution structures of the HRSV polymerase and a 3.7-Å resolution structure of the HMPV polymerase (PDB: 6U5O) (–OD (128 to 157) and PCTD (158 to 241) of a tetramer of the 241-residue P. Interestingly, although full-length L and P were used to reconstitute the HRSV polymerases, the EM densities of MT domain and structural CD and CTD domains of the L and the PNTD are missing in 3-dimensional (3D) reconstructions  –63. Two : 6U5O) –, 63  –. The strructions , 63  shares a highly similar architecture to that of the HRSV polymerase, which contains the RdRp (8 to 902) and Cap (903 to 1380) domains of the 2,005-residue HMPV L and POD (168 to 193) and PCTD (194 to 266) of a tetramer of the 294-residue HMPV P  and 4.63-Å (PDB: 6V86) resolution structures of the HPIV polymerase at two similar stable conformations (OD (198 to 271) and PCTD , are present to interact with the HPIV L  and share a similar architecture. Indeed, the RdRp domains of Mononegavirales L share a standard right-hand thumb-palm-finger ring-like configuration of RNA and DNA polymerases. Comprehensive comparisons of the RNA/DNA polymerases and viral polymerases have been extensively reviewed elsewhere  of the RdRp domains are shown as magenta spheres , followed by the attack by a guanosine nucleotide. The motifs A to E of the Cap domain of the Mononegavirales L are shown as a ribbon diagram in blue, yellow, red, magenta, and green, respectively. Those motifs are centered around the motif D (HR) active site. The proposed priming loops (orange) are next to the motif B (yellow) but exhibit a dramatic conformational rearrangement  All five domains  of the Rhabdoviridae and Paramyxoviridae L compared with only two domains (RdRp and Cap) of the Pneumoviridae L are visible in the cryo-EM structures. (ii) P forms dimers in Rhabdoviridae but tetramers in Pneumoviridae and Paramyxoviridae. It is thought that P displays distinct structural features due to low sequence identity and different oligomerization states. Interestingly, different domains of P interact with L in the reported structures. In Rhabdoviridae, only the PNTD interacts with mostly CD and CTD and part of RdRp of L  The priming loop and the supporting helix of L (Rhabdoviridae (VSV and RABV), the priming loop together with a supporting helix in the RdRp domain project into the GDN active sites (Pneumoviridae (HRSV and HMPV), the supporting helix is  disordered, and the priming loop retracts from the RdRp active sites (Paramyxoviridae (HPIV), the supporting helix is visible (similar as Rhabdoviridae), but the priming loop with a disordered tip is projected away from the RdRp active sites (similar as Pneumoviridae)  .Mononegavirales polymerases discussed here reveal multiple distinct conformational arrangements of the L and P proteins, as shown in the cartoon diagrams  the polymerases of the Rhabdoviridae (VSV and RABV) are likely at the initiation stage of genome replication, and (ii) the polymerases of Pneumoviridae (HRSV and HMPV) and Paramyxoviridae (HPIV) are at different phases, possibly late phase and early phase, of the elongation stages of transcription, respectively.Collectively, the structures of the diagrams . The comngements –63. BaseMononegavirales polymerases, we superimposed other viral polymerase complexes in the initiation and elongation stages. For the initiation, the superimposition of the reovirus (ReoV) λ3 initiation complex reveals in the presence of the RNA template (yellow), the initiating nucleotide stacks with a Trp (W1167 in VSV L and W1180 in RABV L) residue of the priming loop, which is also similar to the Y630 in hepatitis C virus (NS5B) (Pneumoviridae (HRSV and HMPV) and Paramyxoviridae (HPIV). The superimpositions of the influenza B (FluB) elongation complexes at early and later stages reveal that the RNA transcripts (pink) have sufficient space to extend and pass through a continuous tunnel when the priming loop is entirely retracted (Paramyxoviridae (HPIV) results in a partially extruded tunnel, where the missing support helix in Pneumoviridae (HRSV and HMPV) leads to a fully open tunnel, which is ideal for highly processive transcription.To better understand the RNA synthesis mechanism by the s (NS5B) , 139 (Fis (NS5B) . For theetracted   go? How do we capture the snapshots of their intermediates? Second, the known structures of the Mononegavirales polymerases are protein only without RNA present in the complex. However, those polymerases are in different initiation and elongation-compatible stages. Why do the priming loop and the supporting helix of L adopt different conformations in the protein-only complex? Third, the tetrameric P has a large interaction surface between POD and L in Pneumoviridae and Paramyxoviridae. Given that P is a dimer in Rhabdoviridae but a tetramer in Pneumoviridae and Paramyxoviridae, is it possible that the dimeric P in Rhabdoviridae may not form a tight complex with L with large interfaces? This may explain why the HRSV, HMPV, and HPIV L need to be coexpressed in the presence of P, but not VSV L, which can be expressed and purified alone.Several interesting questions arise by comparing and analyzing the known structures of the Mononegavirales have evolved to utilize a single multifunctional enzyme to transcribe individual genes  and replicate the entire genome without capping and methylation. This may be due to reduced evolutionary pressure; typically, this multifaceted process is sensitive to cell state and signaling inputs. These viruses have evolved to drive this process efficiently forward using minimal components. In eukaryotes, RNA transcription (copying the genetic information) is a delicate and complicated process involving many molecular machines, such as DNA-dependent RNA polymerases, capping enzymes, and methyltransferases. For example, the eukaryotic counterparts of the RdRp, Cap, and MT domains of the multifunctional enzyme L are (i) RNA polymerase II and polyadenylate polymerase, (ii) RNA triphosphatase and guanylyltransferase, and (iii) RNA methyltransferase, respectively (–Mononegavirales L also mimics the replication of the entire genome by accessing the N protein-coated RNA genome, similar to eukaryotic counterparts of DNA polymerases on the histone-assembled DNA genome (–From an evolutionary perspective, ectively –167. AddA genome –170.Mononegavirales polymerases agrees with the relatively high sequence conservation. Nonetheless, the structural differences also highlight the virus- or genus-specific features. Collectively, the structures of the Mononegavirales polymerases provide significant advances into understanding the molecular architectures, interrelationship, the inhibitors, and the evolutionary implications of the Mononegavirales polymerases. Other polymerases from measles, mumps, Nipah virus, and Hendra virus in Paramyxoviridae and Ebola virus and Marburg virus in Filoviridae need to be determined for us to fully understand the similarities and differences of the polymerases in Mononegavirales. Furthermore, structures of Mononegavirales polymerases in complex with RNA templates, RNA products, or inhibitors are desired to appreciate the specific protein:RNA interactions and druggable sites.The structural similarity of the All the figures presenting the structural models were generated using PyMOL .