Plant RNA viruses encode essential viral proteins that depend on the host translation machinery for their expression. However, genomic RNAs of most plant RNA viruses lack the classical characteristics of eukaryotic cellular mRNAs, such as mono-cistron, 5′ cap structure, and 3′ polyadenylation. To adapt and utilize the eukaryotic translation machinery, plant RNA viruses have evolved a variety of translation strategies such as cap-independent translation, translation recoding on initiation and termination sites, and post-translation processes. This review focuses on advances in cap-independent translation and translation recoding in plant viruses. Plant viruses usually encode several viral proteins essential for the important processes in the viral life cycle, such as replication, translation, movement, and virus packaging. However, translation of viral proteins totally depends on the host translation machinery, which prefers RNA templates with the same characteristics as cellular mRNA. For DNA viruses, the genomic transcripts have the same characteristics as cellular mRNA since their viral genome enters the nucleus. Translation of the viral RNA for DNA viruses is accomplished using the canonical ribosome scanning model. For RNA viruses, their viral genome does not enter the nucleus and remains the intrinsic characteristic of the virus particle. The genomic RNA of many plant RNA viruses lacks the 5′ cap and/or 3′ poly(A) as cellular mRNA, which are essential factors ensuring the effective translation of cellular mRNA. In addition, the viral RNA of some RNA viruses is multi-cistronic, which is remarkably different from mono-cistronic cellular mRNA. It is suggested that the internal open reading frame (ORF) and ORFs located at the 3’ part may be expressed by several strategy. Although most plant RNA viruses present differences in terms of the 5′ end, 3′ end, and encoding characteristic from cellular mRNA, they accomplish the expression of viral proteins through many strategies, including the synthesis of subgenomic RNA at the transcriptional level, cap-independent translation, and translation recoding at the translational level ,2,3. ThiTo study the translation of viral proteins, the characteristics of the 5′ and 3′ ends of the viral RNA are the primary factors to be considered. If viral RNA has a capped 5′ end and polyadenylated 3′ end, it can express the viral protein through the canonical ribosome scanning model as cellular mRNA. In the ribosome scanning model of eukaryotic cellular mRNA, the 7-methylguanosine cap at the 5′ end of cellular mRNA is first bound by eIF4E, part of the eIF4F complex, which recruits the 43S preinitiation complex, including the 40S small ribosomal subunit, eIF2–GTP–Met-tRNAi ternary complex, along with eIF1, eIF1A, eIF3, and eIF5. The resulting 48S preinitiation complex is then scanned from 5′ to 3′ in an ATP-dependent manner until the charged initiator Met-tRNAi is base-paired with an AUG start codon surrounding by suitable context sequences. A number of initiation factors are then displaced to allow the joining of the 60S large ribosomal subunit to form the complete 80S ribosome to initiate translation. The 3′ poly (A) can be bound by PABP, which also binds eIF4G to cyclize the cellular mRNA, greatly enhancing translation by avoiding cellular mRNA decay and cyclic utilization of ribosomal subunits [Secoviridae, two in the family Solemoviridae, 12 in the family Potyviridae of the order Patatavirales, and three in the family Luteoviridae had a viral genome-linked protein (VPg) at the 5′ end of the genomic RNA. For genera without 3′ poly(A), six in the family Bromoviridae, seven in the family Virgaviridae, and one in the family Tymoviridae had a 3′ tRNA-like structure  and 3′ cap-independent translation enhancer (3′ CITE). IRES was first reported in animal RNA viruses such as poliovirus and Encephalomyocarditis virus (EMCV), and it is mainly located at the 5′ upstream region of corresponding open reading frames (ORFs) [Cap-independent translation in plant RNA viruses is often mediated by two types of s (ORFs) ,103. 3′Cs (ORFs) ,104,105.s (ORFs) ,107,108.trans-acting factors (ITAFs). Picornavirus IRESes are classified into five types , and dicistrovirus IRESes are classified into another type [Since IRES was first reported in picornavirus RNAs ,103, it her type ,116,117.her type ,123,124.her type . IRES acher type ,131,132.Potyviridae, such as tobacco etch virus (TEV), turnip mosaic virus (TuMV), potato virus Y (PVY), triticum mosaic virus (TriMV), and wheat yellow mosaic virus (WYMV) [Potyviridae are similar to those in the family Picornaviridae. They all have VPg at the 5’ end and poly (A) at the 3’ end. They all encode a single polyprotein to produce functional proteins via the cleavage of proteinases. However, the 5’UTR of the family Potyviridae is relatively shorter than that of the family Picornaviridae (about 150 nt in Potyviridae and 600–1200 nt in Picornaviridae), and the structure of the 5’UTR in the family Potyviridae is simpler than that in the family Picornaviridae. In addition, the VPg of the family Potyviridae is relatively larger than that in the family Picornaviridae  [Calicivirus, VPg- eIF4E interaction is required for translation [Picornaviridae is dispensable in the process of translation regulation [Picornaviridae can be released from viral RNA though “unlinkase” activity via TDP2 enzyme [Studies on IRESes in plant RNA viruses have mainly focused on members of the family s (WYMV) ,135,136.viridae) . VPg canviridae) ,139,140.viridae) . In the nslation . Howevergulation . TheVPg 2 enzyme . Due to Potyviridae [TEV is a model virus used to study the translation regulation of the family yviridae ,146. Earyviridae ,147, andyviridae . The 5’ yviridae . In addiyviridae . When thyviridae . When a yviridae ,150,151.Insertion of the 5’UTR (184 nt) of PVY into the intergenic region of the bi-cistronic reporter vector can promote the expression of the second gene, which indicates that the 5’UTR of PVY has IRES activity . On the trans competition experiment, while the identical complementary sequences located at reporter gene increased translation [The 5’UTR of TuMV (130 nt) can promote translation in vivo and in vitro, but the exact mechanism is still unclear . When a nslation . It is sPotyvirus, its 5’UTR with 739 nt is very long and its opening reading frame starts from the 13th initiation codon [TriMV is a newly discovered virus that infects wheat. Compared with other members of the genus on codon ,154. Theon codon . IRES acon codon . The 5’Uon codon . In addion codon . Potyvirus, the 5’UTR (161 nt) without remarkable structure characteristic played a key role in the translation of viral RNA stimulated by VPg and ribosomal protein P0 [In PVA, another member of the genus otein P0 . It is i80U in the 5′UTR and A7574G in the 3′UTR [cis-element for IRES activity from the 5′UTR [114UUUCC [55, C66, C105, and C108) in the hairpins H1 and H2 and the guanines  in LR1 form discontinuous base pairing to maintain a dynamic equilibrium state. Dynamic base pairs between C55 and C66 in H1 and guanines  in LR1 have positive effects on IRES activity, while dynamic base pairs between C105 and C108 in H2 and guanines  in LR1 negatively regulate the IRES activity [55, C66, C105, and C108) in H1/H2 and guanines  in LR1 maintain a tertiary equilibrium state to ensure that the IRES activity of the RNA1 5’UTR is at a suitable level, which is suggested to be the evolution target of WYMV RNA1 [Recently, a novel IRES element was found in the 5′UTR (162 nt) of RNA1 of WYMV . The corhe 3′UTR . Structuhe 5′UTR . The IRE114UUUCC . In addiactivity . DynamicYMV RNA1 .Potyviridae, it has been reported in other types of plant RNA viruses. The upstream coat protein (CP) ORF in TCV contains an IRES, which can regulate the expression of CP protein [Tombusviridae, such as HCRSV and PFBV [Nepovirus. This IRES did not present a remarkable secondary structure, but it did contain multiple segments of an 8–10 nt sequence motif essential for IRES activity, which can complement the position of the 1113–1123 nt region of 18S rRNA [Nepovirus. It is speculated that these IRESes may directly recruit 40S subunit, because 18s rRNA is part of the 40S subunit [cis-elements include a conserved AUG codon and adjacent inverse symmetric motif (GGAGAGAGAGG) [In addition to IRES found in species of the family  protein . The low protein . IRES wi protein . Similarand PFBV ,160. Theand PFBV ,159,160.18S rRNA . Subsequ subunit . IRES haAGAGAGG) .55, C66, C105, and C108) in two hairpins and guanines  in the linker region. In addition to types I and II, there are several IRESes whose structural characteristics are unclear. The IRES in TuMV/PVA/PLRV has been classified as type III. Although there are three type of IRESes based on their structural characteristics, IRESes in plant RNA viruses appear to have simpler structure than that in animal RNA viruses. Similarly, IRESes of mammalian cellular mRNA are also less structured than that in animal RNA viruses [To date, IRESes of plant RNA viruses have presented multifarious structural characteristics and can be roughly divided into three types according to their structural characteristics . Type I  viruses ,164. In  viruses . With th viruses . A subse viruses . However viruses . It has cis-elements shows remarkable inhibition on translation [cis-elements in IRESes, the precise interaction sites between IRESes and host translation factors or ribosomes can be a future research direction, which will provide insight into the design of small-molecule blocking agents.In addition to the different structural characteristics, IRESes in plant RNA viruses present different mechanisms to recruit translation factors or ribosomes. Some IRESes such as TCV and TEV can bind eIF4G, while others such as WYMV can bind eIF4E. In addition, some IRESes, such as BRV, TEV and TriMV, can directly bind 18S rRNA. Although the genomic RNA of these plant RNA viruses does not contain the 5′cap, they can recruit the translation initiation complex by binding to specific components, such as eIF4E, eIF4G, and/or 18S rRNA. To date, IRESes of plant RNA viruses have appeared to function without the assistance of ITAF, while some IRESes in animal RNA viruses and cellular mRNA required ITAF ,167,168.nslation ,135, whinslation ,173,174,The primary function of IRES is the regulation of cap-independent translation, and different types of IRESes have been identified in some plant RNA viruses, which recruit translational initiation factors in different manners . In addiThe 3’CITE was firstly reported in sTNV  and subsTED was discovered in the 3′UTR (619 nt) of sTNV, a parasitic subviral agent, and it enhances translation in vitro and in vivo . Its strSimilar TED elements have been experimentally verified for other related viruses. Three carmoviruses including pelargonium line pattern virus (PLPV), pelargonium chlorotic ring pattern virus, and pelargonium ring spot virus have been shown to contain a TED-like element, which has sequences in its apical loops putatively forming a kissing-loop interaction with a 5′ proximal hairpin . The corLuteovirus, as well as in some species of the genera Necrovirus, Umbravirus, and Dianthovirus [CCUGGNRNACAGG, the underlined base pair; N is any base and R is a purine) and a stable stem-loop SL-IIII pairing with the 5′UTR (140 nt) [BTE was first reported in BYDV and subsequently found in all species of the genus thovirus ,202. BTE(140 nt) ,203. Thi(140 nt) . eIF3 ca(140 nt) . BTE of (140 nt) . The thr(140 nt) .Umbravirus and seven additional BTEs from species of the family Tombusviridae and Luteoviridae have additional structural and sequence similarities, including the distance between SL1 and SL2, conserved sequences located downstream of SL2 and SL3 [BTE-like elements have also been reported in tobacco bushy top virus (TBTV) . A study and SL3 .Carmovirus and Panicovirus, pea enation mosaic virus RNA 2 (PEMV2) of the genus Umbravirus, and pothos latent virus of the genus Aureusvirus [PTE is present in several species of the genera eusvirus . The PTEeusvirus . The 5′ eusvirus ,188. MCMeusvirus . Howevereusvirus .Carmovirus [TSS was first discovered in the turnip crinkle virus (TCV) of the genus rmovirus . The TSSrmovirus . The TSSrmovirus . In addirmovirus ,211.Carmovirus. The 3′UTR of PEMV2 of the genus Umbravirus contains two functional TSSs. One is termed kl-TSS, located 9 nt upstream of the PTE, and the other is termed 3′TSS, located near the 3′ end of the genomic RNA, which is predicted to fold into structures similar to tRNAs [Umbravirus  and also contained BTE, another type of 3′CITE [A similar TSS structure has been proposed for the related cardamine chlorotic fleck virus of the genus to tRNAs ,192. In f 3′CITE .Tombusviridae such as maize necrotic spot virus of the genus Tombusvirus and melon necrotic spot virus (MNSV) of the genus Carmovirus [ISS, the shortest 3′CITE, has been found in the different genera of the family rmovirus ,212. Thermovirus ,195,212.Tombusvirus are predicted to have a conserved YSS at the 3′ end [Nearly all members of the genus e 3′ end ,99,196. e 3′ end .A small 3′CITE termed CXTE was identified from the 3′UTR of the MNSV-N isolate, which can overcome eIF4E-mediated resistance due to the insertion of 55 nt sequences from CABYV . These 5Umbravirus contain multiple 3′CITEs. BTE, not TSS, in OPMV plays a role in cap-independent translation [cis-elements regulating viral replication, which is another important biological process in viral life cycle. 3′CITE and replication-associated cis-elements located at the 3′end of virus genome may induce reciprocal actions or effects due to the local tertiary structure [cis-elements may also play an essential role in the viral life cycle, because the 3′ end could undergo a structural change upon binding to RdRp, the core component of viral replication [To date, the detailed characteristics of 3′CITE have been mainly identified in plant RNA viruses. Different 3′CITEs present different structural characteristics and regulate translation in a different manner recruiting host translation machinery . Some plnslation . Howevernslation . PTE andnslation . In addinslation ,178,179,tructure ,211, whilication .cis-elements that mediate the cap-independent translation of viral RNA without the 5′ cap. According to information from previous studies and this review, IRES and 3′CITE in plant RNA viruses appear to present different structural characteristics. IRESes in plant RNA viruses present one of three characteristics: unstructured, structured, or unclear structure  of CP ORF, in which the leaky ratio was about 50% [According to the genome organization of plant RNA viruses, leaky scanning can occur at eight genera in the family oviridae . Leaky sbout 50% . The p39bout 50% . βc protbout 50% . Rice tubout 50% . In potabout 50% . In the bout 50% . Translabout 50% .Tombuviridae, and species of the family Panicovirus [The leaky scanning mechanism implies the importance of the context of initiation codon AUG, which can also be confirmed by another translation recoding mechanism termed non-AUG initiation. No AUG initiation was first discovered in the sendai virus in 1988, and translation can be initiated from the ACG codon . In the icovirus ,233,234.cis-elements: a “slippery site” composed of seven nucleotides with the characteristic XXXYYYZ  [During the special translation process, ribosomes show an abnormal shift of non-three codons on the RNA template, which changes the reading frame of the ORF. This phenomenon is termed ribosomal frameshift . The ribs not G) ,242,243;s not G) ,245,246;s not G) ,248,249.Amalgaviridae, one genus of the family Aspiviridae, four genera of the family Closteroviridae, four genera of the family Luteoviridae, and two genera of the family Solemoviridae ) [Tombusviridae and Virgaviridae are expressed via read-through; the ratio of read-through is about 5–10% and is regulated by several cis-elements [In plant RNA viruses, ribosomal read-through can occur in the genus sviridae  and is ucription . The CP cription . Tobaccocription . The famn (RTD)) . The rean (RTD)) ,281,282.elements . During cis-elements and various viral or host trans-factors, the expression of translation recoding products at the suitable level is the common point for different RNA viruses. The suitable ratio of translation recoding is essential for fitness of corresponding RNA viruses, suggesting that small molecules interfering with the suitable ratio of translation recoding in plant RNA viruses can be effective agents for the management of virus diseases. The design of this type of small molecule relies on the detailed characterization of cis-elements or trans-factors involved in the different translation recoding processes, which is also a future research direction in translation recoding.Although different types of translation recoding in plant RNA viruses present different mechanisms involving different cis-elements was few. All these information gap will be future direction.IRESes and 3’CITEes in plant RNA viruses presented different structure characteristic in different viruses and recruited host translation machinery through eIF4E, eIF4G or 18s rRNA. However, detailed information about interaction between cap-independent translation elements and translation machinery was rough, which require further identification in future. Both ribosomal frameshift and ribosomal read through in plant RNA viruses were involved in several levels of cis-elements, but detailed characterization on structure of these core cis-elements was few and rough. In addition, potential relationship between the ratio of translation recoding and virus fitness was unclear. During translation regulation of plant RNA viruses, different RNA cis-element may undergo structure shift on the interaction with other cis- or- trans- element and/or factors. However, the study on the structure shift of Translation of viral proteins is a vital process during the life cycle of viruses. Comprehensive and persistent identification of different translation strategies in plant RNA viruses will provide new insights into translation regulation and new mechanisms in virus evolution, which will result in new strategies, target sites, and agents for the management of viral diseases of plants.


Background: RNA modifications have emerged as important posttranscriptional changes in multiple tumor cellular processes and tumorigenesis, including hepatocellular carcinoma (HCC). However, the potential roles and the interaction between regulators of RNA modifications and the tumor microenvironment (TME) are unclear in HCC.Methods: The gene expression profiles of 26 RNA modification “writers” were investigated in the TCGA cohort. The unsupervised clustering approach was used to class these RNA modification regulators. The characteristics of immune cell infiltration from TME for each cluster was tested by the CIBERSORT method. Additionally, we established a scoring model to evaluate the RNA modification characteristics of individual tumors. The associations between the scoring model and genetic as well as clinical characteristics, drug sensitivity, and response to immunotherapy were also analyzed.Results: We mapped the somatic mutations and somatic copy number variation of the RNA modification regulators. The expression of all selected regulators was detected, and two modification patterns were identified that featured distinct immune cell infiltration characteristics. Subsequently, we developed a score model (termed as WM-Score model). Furthermore, the survival analysis showed that the WM-Score value was associated with HCC patient prognosis. The results of the ROC curves analysis and multivariate analysis all confirmed that the WM-Score value was strongly associated with anti-cancer drug resistance and therapeutic efficacy of immunotherapy, thus could be used as an independent risk factor in HCC.Conclusion: Our research identified two RNA modification patterns characterized by distinct TME, and the WM-Score model was developed that might serve as reliable prognostic and immunotherapeutic effect predictor of HCC. In 2018, hepatocellular carcinoma (HCC) was predicted to be the sixth most prevalent cancer worldwide , with a 6-methyladenosine (m6A) that regulates multiple aspects of RNA metabolism, such as RNA processing, RNA translation, and nuclear export (6A-binding proteins or “readers” (they recognize and bind modified nucleotides). The RNA modification is a dynamic process, and the interaction between each type of methylation modification has not yet been fully elucidated , including cancer cells, locally infiltrating immune cells, stromal cells, and active medium, in tumor cell proliferation, invasion, and metastasis . Non-mal6A, alternative polyadenylation (APA), m1A, and A-to-I RNA editing. Furthermore, we comprehensively analyzed the correlation between various types of RNA modification regulators and cell-infiltrating characteristics of TIME by integrating the genomic and transcriptomic alterations of samples from The Cancer Genome Atlas - Liver Hepatocellular Carcinoma (TCGA-LIHC) databases. Two distinct modification patterns with different immune cell characteristics were identified. In addition, we developed the WM-Score model to quantify the efficacy of “writers” in modifying individual tumors and to predict the prognosis and immunotherapeutic response of HCC patients.In this study, we focused on the most heavily modified RNA types, including mhttp://cancergenome.nih.gov/). Data cohorts with missing information were removed. A total of 356 cases of TCGA-LIHC were used for further analysis. The R Bioconductor package and R (version 3.6.2) were employed for data analysis.The gene expression profiles and clinical annotations were downloaded from the Cancer Genome Atlas (TCGA) portal (www.cancerRxgene.org) (Drug sensitivity data were collected from The Genomics of Drug Sensitivity in Cancer (GDSC) database (ene.org) . Spearmahttp://research-pub.gene.com. The data were analyzed using the IMvigor210CoreBiologies R package.The immunotherapy dataset IMvigor210 cohort was used to explore the immunotherapy response and prognosis of HCC patients with different WM-Score values. The standardized RNA-sequencing data of 1111 HCC patients with detailed clinicopathological data were downloaded from 6A modification enzymes , 12 APA modification enzymes , four m1A modification enzymes , and three A-I modification enzymes  were analyzed. An NMF-based consistent clustering algorithm was used to determine RNA modification patterns based on the mRNA expression of analyzed regulators. Unsupervised cluster analysis was performed by The Consensus Cluster Plus package as previously described  (CIBERSORT is a method that can accurately estimate the fraction of diverse cell subsets in gene expression profiles from complex tissues (ord.edu) . To predFirstly, the RNA modification-related differentially expressed genes (DEGs) among distinct RNA modification clusters were collected using “limma” package of R software. Next, we performed univariate cox regression model to analyze the correlation of each gene with overall survival, and the significant prognosis DEGs were used for further analysis. Subsequently, distinct genomic subtypes were determined by unsupervised clustering analyses. In addition, the prognostic analysis was performed for each genomic subtype and extract principal component 1 and 2 as the signature scores. Finally, the RNA modification score was defined using a method similar to that used in analyzing gene-gene interactions (GGIs): WM-Score = Σ (PC1i + PC2i), which is defined as the expression of final RNA modification phenotype-related genes .p < 0.05 was considered as statistically significant.A Wilcoxon rank-sum test was utilized to compare differences between two groups, and Kruskal-Wallis test was used for comparisons of multiple groups. The discrimination accuracy of the WM-Score model was described by receiver operating characteristic (ROC) analysis. Kaplan-Meier method estimate curves were generated for prognostic analysis, and the differences between groups were evaluated by a log-rank test. Univariate and multivariate analyses were further carried out to assess independent risk factors. All data were analyzed by the R 4.0.1 software. A two-tailed 6A modification “writers”, three A-I modification “writers”, 12 APA modification “writers”, and four m1A modification “writers” .Our results above demonstrated the important role of RNA modification in TME formation and patient prognosis, while these findings were based on RNA modification patterns and could not accurately evaluate the capacity of the RNA modification as a prognostic predictor in individual HCC patients. The underlying genetic alterations in these two RNA modification patterns were still unclear. Based on these queries, we examined the transcriptional expression change between the two patterns. A total of 273 DEGs related to RNA modification patterns were identified, and the further enrichment analysis showed that these DEGs were enriched in many essential biological processes, including DNA-binding transcription activator activity, signaling receptor activator activity, and multicellular organismal response to stress . SubsequFurthermore, we developed a score model based on the DEGs between gene clusters. As described in the Methods section, a scoring model named writers of RNA modification-score (WM-Score) was constructed. We discovered that cluster 1 had a higher WM-Score value than cluster 2 . ConsistAfter confirming the efficacy of the WM-Score model in predicting patient prognosis, we investigated whether this model could be applied to determine the tumorigenesis, progression, invasion and metastasis of HCC. The prognostic efficiency of the scoring model was explored through classifying patients into low and high score groups the using “survminer” package. As expected, patients with high score demonstrated a poorer prognosis than those with low score in the TCGA-LIHC cohort . We usedFor several years, sorafenib has been approved a treatment option for advanced HCC patients, while efficacy of sorafenib is limited by drug resistance . Aiming In recent years, immune checkpoint inhibitors (ICIs) have made breakthroughs in the treatment of advanced HCC, while biomarkers that could effectively predict the efficacy of immunotherapy are still lacking. Herein, we explored whether the WM-Score model could predict therapeutic response to ICI therapy in HCC patients. For the IMvigor210 cohort, the therapeutic efficacy was significantly better in patients with low WM-Score value compared to those with high WM-Score value . The freA growing pool of evidence indicates that RNA modifications play a key role in gene expression, whose disruption impacts the pathogenesis of human disease, including cancer . Althoug6A) is an RNA methylation that is the most abundant form of internal mRNA modification. Yang et al. reported the involvement of the m6A modification in the 3′-UTR of oncogene CDCP1 mRNA in bladder cancer cell growth and progression   . Chong erization . Three mc cancer , lung adc cancer , pancreac cancer , and glic cancer . Similarc cancer . Shen etc cancer . PreviouIn addition, the RNA modification pattern with higher WM-Score value tended to correlate with immune cell suppression in the tumor microenvironment, while the pattern with lower WM-Score value was usually associated with immune activation. In the IMvigor210 cohort, WM-Scores model was found to be linked with immune cell infiltration in TME as well as response to anti-PD-1/L1 immunotherapy, suggesting the application potential of WM-Score model for predicting HCC anti-PD-1/L1 immunotherapy.In the present work, the RNA modification regulators were comprehensively analyzed, and the correlation was demonstrated between RNA modification patterns and cell-infiltrating characteristics in the TME. The systematic evaluation of individual tumor RNA modification pattern might serve as a useful predictor of prognosis for HCC patients and act as a valuable tool for developing more effective immunotherapy strategies.


The COVID-19 pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The SARS-CoV-2 genome is replicated and transcribed by its RNA-dependent RNA polymerase (RdRp), which is the target for antivirals such as remdesivir. We use a combination of approaches to show that backtracking (backward motion of the RdRp on the template RNA) is a feature of SARS-CoV-2 replication/transcription. Backtracking may play a critical role in proofreading, a crucial process for SARS-CoV-2 resistance against many antivirals. Backtracking, the reverse motion of the transcriptase enzyme on the nucleic acid template, is a universal regulatory feature of transcription in cellular organisms but its role in viruses is not established. Here we present evidence that backtracking extends into the viral realm, where backtracking by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA-dependent RNA polymerase (RdRp) may aid viral transcription and replication. Structures of SARS-CoV-2 RdRp bound to the essential nsp13 helicase and RNA suggested the helicase facilitates backtracking. We use cryo-electron microscopy, RNA–protein cross-linking, and unbiased molecular dynamics simulations to characterize SARS-CoV-2 RdRp backtracking. The results establish that the single-stranded 3′ segment of the product RNA generated by backtracking extrudes through the RdRp nucleoside triphosphate (NTP) entry tunnel, that a mismatched nucleotide at the product RNA 3′ end frays and enters the NTP entry tunnel to initiate backtracking, and that nsp13 stimulates RdRp backtracking. Backtracking may aid proofreading, a crucial process for SARS-CoV-2 resistance against antivirals. The ov1523Backtracking by the cellular DdRps plays important roles in transcription regulation, including the control of DdRp pausing during transcription elongation, termination, DNA repair, and transcription fidelity . In back2327Although evolutionarily unrelated to the DdRps, a secondary channel, formed by the RdRp motif F β-hairpin loop and proposed to serve as an NTP entry tunnel, branches off from the main SARS-CoV-2 RdRp active-site channel . This NT3 and BTC5 scaffolds; Previously, DdRp backtracked complexes (BTCs) were generated for structural studies by direct incubation of the DdRp with DNA–RNA scaffolds containing mismatched nucleotides at the RNA 3′ end , 28, 30;2/nsp12) bound the RTC scaffold as observed previously .Native electrophoretic mobility shift assays revealed that although the holo-RdRp (nsp7/nsp83) and holo-RdRp with the BTC5 scaffold (5) and analyzed the samples by single-particle cryo-EM. The sample comprised two major classes: nsp131-BTC5  and nsp132-BTC5 . Analysis of the two refined structures revealed that the RdRp portion of each structure was essentially identical , while the disposition of the common nsp13 protomer (nsp13.1) was divergent . To eliminate structural heterogeneity in the nsp13 subunits and obtain a higher-resolution view of the BTC, the particles from both classes were combined and locally refined inside a mask applied around the holo-RdRp and RNA (excluding the nsp13 subunits), leading to the BTC5 combined map .Modeling suggested that about five nucleotides of backtracked single-stranded RNA at the p-RNA 3′ end would be sufficient to traverse the RdRp NTP entry tunnel. Therefore, to determine the structural organization of the SARS-CoV-2 BTC, we assembled nsp13 was disordered and not modeled.In the nsp13resolved A, allowiresolved A, 5′CCCA5 scaffold extruding into the RdRp NTP entry tunnel , including a “track” of conserved positively charged Arg and Lys residues of motif F . Conserved residues of RdRp motifs C and E complete the active-site/NTP entry tunnel environment surrounding the backtracked RNA .The RdRp NTP entry tunnel provides a steric and electrostatic environment conducive to channeling the backtracked RNA out of the active site without specific polar protein–RNA interactions that could hinder the RNA movement C and 4. 5 scaffold p-RNA . Nsp12-D760 is a conserved residue of the RdRp motif C that chelates a crucial Mg2+ ion in catalytic complexes . RTCs assembled with wild-type nsp12 and the RTC(4-thio-U) scaffold gave weak nsp12-RNA cross-linking upon UV exposure . These conditions favor a posttranslocated RTC . Under these conditions, we propose that the translocation activity of nsp13 backtracked a fraction of the complexes, freeing the 4-thio-U from the RNA–RNA hybrid for cross-linking to nsp12. Cross-linking in the presence of nsp13 but in the absence of ATP reduced nsp12 cross-linking , supporting the proposal that nsp13 translocation activity facilitates backtracking. Replacing wild-type nsp12 with nsp12-D760A , which is more prone to backtracking , showed the same trends but with increased UV-dependent nsp12-RNA cross-linking, with the maximal cross-linking occurring under the conditions expected to favor backtracking the most . These results affirm the view that nsp13 facilitates backtracking of the SARS-CoV-2 RdRp.To generate the SARS-CoV-2 BTCs for structural studies, we used the BTCA 3′ end A. To stuated RTC , 36, 37 2-BTC5 structure, the −1C was mutated to U, and the +2 to +4 Cs were removed. The resulting pretranslocated p-RNA had a matched −1U and a mismatched +1C .The SARS-CoV-2 RTC is a highly processive and rapid replicase/transcriptase, capable of replicating a ∼1-kb RNA template at an average rate of ∼170 nt/s . However415 scaffold t-RNA . We note that in bacteria the UvrD helicase has been shown to induce DdRp backtracking, suggesting that a role for helicases in backtracking may be widespread , facilitating translocation and subsequent NTP addition and thus rapid elongation . However, upon misincorporation, the pretranslocated, mismatched nucleotide at the p-RNA 3′ end spends more than half the time frayed from the t-RNA and toward or in the NTP entry tunnel .Our results are consistent with the view that a matched nucleotide at the pretranslocated p-RNA 3′ end remains base paired to the t-RNA (y tunnel C, a confy tunnel  and 4 may tunnel A, allowiOur findings have implications for the processes of subgenomic transcription and proofreading in SARS-CoV-2 . GeneratNucleotide analogs that function by being incorporated into product RNA by viral RdRps are important antiviral therapeutics . NotablySI Appendix.Detailed descriptions of SARS-CoV-2 nsp12, 7, 8, and 13 protein purification, assembly of the RTC complexes, native electrophoretic mobility shift assays, native mass spectrometry, cross-linking, specimen preparation for cryo-EM, cryo-EM data acquisition and processing, model building and refinement, and molecular dynamics simulations are provided in Supplementary FileSupplementary File


Lung metastasis of malignant tumor signifies worse prognosis and immensely deteriorates patients' life quality. Spatholobi Caulis (SC) has been reported to reduce lung metastasis, but the mechanism remains elusive. P value <0.05. Network of SC-active components-intersection targets-KEGG pathway was accomplished with Cytoscape. Molecular docking between hub targets and active components was performed, analyzed, and visualized by AutoDockTools, AutoDock Vina, PLIP Web tool, and PYMOL.  The active components and corresponding targets of SC were obtained from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP) database and the SwissTargetPrediction database. The disease targets were acquired from DisGeNET and GeneCards databases. Venn map was composed to figure out intersection targets by using R. The PPI network was constructed through STRING and Cytoscape, and MCODE plug-in was used to sift hub targets. Gene Ontology (GO)-Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was carried out by utilizing clusterProfiler package (R3.6.1) with adjusted  24 active components and 123 corresponding targets were screened, and the number of disease targets and intersection targets was 1074 and 47, respectively. RELA, JUN, MAPK1, MAPK14, STAT3, IL-4, ESR1, and TP53 were the 8 hub targets. GO analysis and KEGG analysis elucidated that SC could ameliorate lung metastasis mainly by intervening oxidative stress, AGE-RAGE signaling pathway, and microRNAs in cancer. All 8 hub targets were proven to combine successfully with active components of SC.  Inflammation is the core factor that integrates all these targets, biological process, and signaling pathways, which indicates that SC prevents or reduces lung metastasis mainly by dispelling inflammation. It is estimated that the number of worldwide new cancer cases and cancer deaths has exceeded 19 million and 10 million, respectively, in 2020 . Since tThe question of why metastatic cancer cells manifest the feature of organotropism has brought about extensive discussions. Paget put forward the “seed and soil” hypothesis that prometastatic tumor cells (the “seed”) colonize in specific organ sites (the “soil”) where the microenvironment is favorable for metastasis , 8. In 2Spatholobus suberectus Dunn., is a typical kind of traditional Chinese medicine that possesses functions of invigorating blood circulation and eliminating stasis. It has been proven that 80% ethanol extracts of SC significantly reduced the pulmonary metastasis and prolonged the life span of Balb/c mice, which had been injected with 4T1-luc cells [Spatholobi Caulis (SC), the vine stem of uc cells . The undhttps://tcmsp-e.com/) [http://new.swisstargetprediction.ch/) [https://pubchem.ncbi.nlm.nih.gov/) [http://www.uniprot.org/uniprot/) [With the thresholds of oral bioavailability (OB) ≥30% and drug-likeness (DL) ≥0.18, the active components of SC and its corresponding targets were obtained from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP) (-e.com/) . To thosion.ch/)  was utilih.gov/) . To ensuniprot/) .http://www.disgenet.org) [https://www.genecards.org/) [Homo sapiens,” only those targets that appear in both databases simultaneously were chosen as targets relevant to lung metastasis of malignant tumor.The academic name of lung metastasis “secondary malignant neoplasm of lung” was searched in the DisGeNET database (net.org)  and Geneds.org/) . With thR (v3.6.1) software , we created two files in “csv” format to store the targets of the active components of SC and targets relevant to lung metastasis of malignant tumor, respectively. The two files were read by R (v3.6.1) software, and the VennDiagram package was employed to get the intersection targets between SC and lung metastasis.Before using Setting minimum required interaction score as 0.9, the intersection targets were imported into STRING 11.0  to gain P value <0.05 [Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of intersection targets were conducted to show the top 15 items by using clusterProfiler package (R3.6.1) with adjusted ue <0.05 .This network was constructed by Cytoscape 3.7.2 to visualize mechanisms of SC treating lung metastasis.Homo sapiens”; (ii) the original 3D structures should possess at least one eutectic ligands; and (iii) only the 3D structures with the least “resolution” value would be chosen. The selected 3D structures of the hub targets were downloaded from the PDB database (http://www.rcsb.org/) [https://pubchem.ncbi.nlm.nih.gov/) [https://plip-tool.biotec.tu-dresden.de/plip-web/plip/index) [We followed three key principles to select the most suitable 3D structures of the hub targets: (i) the source organism should be “sb.org/) , and remih.gov/)  and werep/index)  to analyAccording to the criterion, 24 active components were recorded, and 123 targets of the active components were identified. The basic information of 24 active components is listed in R software  for further process, shown in p. adjust ＜0.05, 1846 items of biological process (BP) were acquired, and the top 15 items are illustrated in With Taking the advantage of Cytoscape, we created the network of SC, 24 active components, 47 intersection targets, and top 5 signaling pathways, containing 77 nodes and 248 edges shown in . The sizα-L-arabinosylluteolin, MAPK1-Calycosin, MAPK14-Catechin, STAT3-Medicago, IL-4-Vestitol, ESR1-Catechin, and TP53-Hederagenin. After analyzing noncovalent interactions, details including affinity, hydrogen bonds, hydrophobic interactions, π-stacking, π-cation interactions, and relative amino acid residues are exhibited in Supplementary π-stacking and π-cation interactions were present by red and purple dotted line, respectively.In consideration of affinity and hydrogen bonds, we ultimately chose the most practical conformation for each hub target, which were RELA-Aloe-emodin, JUN-8-C-α-L-arabinosylluteolin was supported by 7 hydrogen bonds, which is the most among all 8 conformations. Hydrophobic interaction is the force that reduces the free energy and stabilizes the contact between two nonpolar regions. Except for STAT3-Medicago, at least 1 hydrophobic interaction formed in the remaining 7 conformations, and there were 7 hydrophobic interactions formed between ESR1 and catechin, ranking 1st in our research. MAPK14-Catechin was the only conformation that contains π-stacking and π-cation interactions, which made a great contribution for the stable combination.Affinity is the concept that measure binding force between ligand and macromolecular protein, and it is widely acknowledged that the spontaneous combination is likely to occur when the affinity is smaller than −5 kcal/mol. In our research, affinity of all 8 conformations was smaller than −5 kcal/mol and MAPK14-Catechin exhibited the strongest binding force with affinity reaching −8.9 kcal/mol. The formation of hydrogen bonds mainly results from electrostatic force, which stems from charge transfer between donor and acceptor. In our research, at least 2 hydrogen bonds took shape, which offered powerful electrostatic force to form stable conformation, and JUN-8-C-Compared with primary tumor, the colonies of lung metastasis often mean worse prognosis and less effectiveness of therapeutic plans. Therefore, preventing or reducing lung metastasis of malignant tumor will extend life expectancy and mitigate the distress of patients with advanced stages of tumor.β-Sitosterol is a bioactive phytosterol compound that is naturally present in the plant cell membrane, and it was proven to decrease lung metastasis in PC-3 and 4T1 cells in vivo and in vitro experiments [β-sitosterol for 7 days, the number of metastatic colonies in the lungs of B16BL6 melanoma cells was prominently less than that of the control group, which might be the result of enhanced immune surveillance activity evidenced by the increase of NK cells and immune response cytokines such as IL-12 and IL-18. Aloe-emodin is a natural anthraquinone derivative of many Chinese herbs, and it is reported that the administration of aloe-emodin dampened the burden of lung metastasis through the inhibitory effect on capabilities of invasion and migration of MDA-MB-231 cells [16H12O4) has a promising anticancer effect through influencing a variety of mechanisms, which pertains to a class of 7-hydroisoflavones [β-catenin expression [μM) of luteolin remarkably inhibited VEGF secretion in MDA-MB-231 (4175) LM2 cells, thereby suppressing the occurrence of pulmonary metastasis [In this study, 24 active components were screened in the aggregate, among which many components have been confirmed to suppress lung metastasis with convincing proof. eriments . Imanakaeriments  discover31 cells , 29. Witflavones . Zhou etflavones . Luteoliflavones . A previpression . The restastasis .In all, there were 47 intersection targets obtained between SC and secondary malignant neoplasm of lung and 8 of them were regarded as hub targets after utilizing MCODE plug-in unit of Cytoscape, namely RELA, JUN, MAPK1, MAPK14, STAT3, IL-4, ESR1, and TP53.κB), participates in cancer development and metastasis by forming chronic inflammation. Upon the phosphorylation of S276 amino acid residue mediated by TNF (tumor necrosis factor), RELA leads to the promoter-specific methylation and transcriptional repression of tumor metastasis suppressor gene BRMS1 (breast cancer metastasis suppressor 1) via direct recruitment of DNMT-1 (DNA (cytosine-5)-methyltransferase 1) to chromatin [P < 0.05) and decrease the ability of MDA-MB-231 cells to adhere in vivo and in vitro, demonstrating that RELA can induce lung metastasis by suppressing BRMS1 [κB p65 protein [RELA (transcription factor p65), which is the p65 subunit of nuclear factor NF-kappa-B  and MAPK14 both belong to MAPK, which plays a vital role in the switch from extracellular signals to intracellular responses . Gagliartastases . The ext [α MAPK .JUN (transcription factor AP-1), a downstream factor of ERK pathway, is involved in gene reprogramming in many tumorigenic processes . The bloUpregulated in approximately 50% of all human tumors, STAT3  is a key signaling protein engaged by a multitude of growth factors and cytokines to elicit diverse biological outcomes including cellular growth, differentiation, and survival . AccordiSimilar to STAT3, IL-4 (interleukin-4) assists lung metastasis mainly through M2 polarization of macrophages , which rα (hypoxia-inducible factor 2α). It has been revealed that pretreatment of luteolin reversed oxidative stress induced by H2O2 in a dose-dependent manner [The GO.BP enrichment analysis spotlights the fundamental position of response to oxidative stress in SC treating lung metastasis of malignant tumor. Lung colonies of B16F10 cells increased apparently caused by oxidative stress, assessed by p22phox and SOD mRNA levels and the NRF2 protein level . In addit manner .Among the top 15 results of KEGG pathway enrichment analysis, the AGE-RAGE signaling pathway and microRNAs in cancer are the most relevant to lung metastasis of malignant tumor.Synthesized during chronic hyperglycemic conditions or aging, AGEs (advanced glycation end products) are the products of a nonenzymatic reaction between the free reducing sugars and proteins, lipids, or nucleic acids . The comMicroRNAs (miRNAs) are small noncoding regulatory RNAs with sizes of 17–25 nucleotides and can be transported to distant organs by cancer-secreted exosomes to regulate local microenvironment for engraftment and colonization of circulating tumor cells . miR-25-According to the results above, we found that the majority of hub targets and biological process including RELA, MAPK1, MAPK14, STAT3, IL-4, and oxidative stress are directly associated with inflammation, which is a key feature of premetastatic niche . As the Last but not least, limitations are also clear that further experiments are necessary to verify the results, and the studies cited in this paper are mainly based on animal or cell experiments, indicating deficiency of clinical research as proof. In addition, data of SC and lung metastasis could be more comprehensive by retrieving more literature and databases.Integrating network pharmacology with molecular docking, our research elaborated that SC could prevent or reduce lung metastasis of malignant tumor to some extent by its active components through targeting RELA, JUN, MAPK1, MAPK14, STAT3, IL-4, ESR1, and TP53. Oxidative stress, AGE-RAGE signaling pathway, and microRNAs in cancer also play important roles in lung metastasis of malignant tumor, which are likely to be reversed by SC, laying the foundation for further experiments. Moreover, inflammation is the core factor that integrates all these targets, biological process, and signaling pathways together, which indicates that SC prevents or reduces lung metastasis mainly by dispelling inflammation.


Sw neuroblastoma, a cell model of familial Alzheimer's disease, were crosslinked and sequences of linked peptides identified. We constructed a normalized “contactome” comprising 11 subnetworks, centered on 24 high‐connectivity hubs. Remarkably, all 24 are nucleic acid‐binding proteins. This led us to isolate and sequence RNA and DNA from Alzheimer's and control aggregates. RNA fragments were mapped to the human genome by RNA‐seq and DNA by ChIP‐seq. Nearly all aggregate RNA sequences mapped to specific genes, whereas DNA fragments were predominantly intergenic. These nucleic acid mappings are all significantly nonrandom, making an artifactual origin extremely unlikely. RNA (mostly cytoplasmic) exceeded DNA (chiefly nuclear) by twofold to fivefold. RNA fragments recovered from AD tissue were ~1.5‐to 2.5‐fold more abundant than those recovered from control tissue, similar to the increase in protein. Aggregate abundances of specific RNA sequences were strikingly differential between cultured SY5Y‐APPSw glioblastoma cells expressing APOE3 vs. APOE4, consistent with APOE4 competition for E‐box/CLEAR motifs. We identified many G‐quadruplex and viral sequences within RNA and DNA of aggregates, suggesting that sequestration of viral genomes may have driven the evolution of disordered nucleic acid‐binding proteins. After RNA‐interference knockdown of the translational‐procession factor EEF2 to suppress translation in SY5Y‐APPSw cells, the RNA content of aggregates declined by >90%, while reducing protein content by only 30% and altering DNA content by ≤10%. This implies that cotranslational misfolding of nascent proteins may ensnare polysomes into aggregates, accounting for most of their RNA content.All neurodegenerative diseases feature aggregates, which usually contain disease‐specific diagnostic proteins; non‐protein constituents, however, have rarely been explored. Aggregates from SY5Y‐APP after aggregating.Nucleic acid‐binding proteins are shown attaching to RNA and DNA, and then undergoing oxidation, thermal denaturation (reversible or irreversible), or other PTMs that destabilize their secondary structure sufficiently to allow aggregation to occur, an essentially irreversible process. Nascent polypeptides as they are synthesized by ribosomes provide another source of transiently misfolded proteins that can aggregate without oxidation or other trigger for denaturation. The sequence shown is not obligatory, in that disordered proteins could also bind nucleic acids  ADAlzheimer's diseaseAMCage‐matched controlsAPOEAPOE, apolipoprotein E 1–42AβAmyloid beta (residues 1–42)ChIP‐seqChromatin ImmunoPrecipitation ‐ sequencingCLEARCoordinated Lysosomal Expression and Regulation, a binding motifDNAdeoxyribonucleic acidEEF2EEF2, eukaryotic elongation factor 2 G4BPG‐quadruplex binding proteinMAP1Amicrotubule‐associated protein 1ANAnucleic acidsNSnot significant (referring to a difference between groups)OEoverexpressingPTMpost‐translational modificationRNAribonucleic acidTFtranscription factor1Protein aggregation increases inexorably with aging in all animal species and in all tissues examined , or bind DNA , or both (N = 2). This supports and extends our earlier observation that nucleic acid‐binding proteins are especially susceptible to aggregation , fell into 11 clusters comprising 24 “central hubs” , regardless of the methods used for separation and quantitation . For AD samples, nucleic acid recoveries were higher and more variable, with roughly twice as much RNA as DNA  and confirmed by histopathological markers, and from age‐matched controls (AMC) without dementia or AD‐diagnostic markers (amyloid deposits or hyperphosphorylated tau). From equal initial weights of hippocampus, quantified recoveries of nucleic acids increased in AD aggregates, over those in controls, by 1.5‐ to 2‐fold for DNA, and ~twofold for RNA Figure . These eA Figure .APOE) gene alleles are the leading genetic risk factors for AD, with at least fourfold increased AD risk for each APOE ε4 allele , and increased severity of aggregate‐associated neuropathology for AD carriers of APOE4 alleles , whereas their RNA content declined a little  with the APOE4 allele overexpressed.Apolipoprotein E , and their sequences determined . DNA fragments were analyzed using a ChIP‐seq protocol, suited to detection of site specificity, and were then mapped to the human genome. RNA fragments underwent a dual screening, comprising a test of peak significance (similar to ChIP‐seq) followed by RNA‐seq analysis of differential abundance, and mapping to the human genome.To assess whether DNA and RNA fragments in aggregates are a random sampling from the genome and transcriptome, respectively, these nucleic acids were separately extracted from pooled aggregate preparations from either AD or age‐matched control (AMC) individuals , 25 reached that threshold in AD vs. 28 in AMC tissue, and 26 in T98G cells carrying APOE3 vs. 30 in APOE4 cells  distribution, these data provide decisive evidence that aggregate DNA fragments are not random, but most likely reflect specific binding sites for proteins that ensnared them into aggregates. Only 5 of these 38 DNA peaks (13%) mapped to known genes or ORFs: RP5‐857K21.4, LINC00486, DUX4L26, MAMDC2‐AS1, and ROCK1P1. The other 33 peaks mapped to intergenic regions. Of the 24 chromosomes represented, Y had the most DNA reads (47‒98 reads in each of 6 peaks), followed by chromosomes 4 (3 peaks of 48‒53 reads), 1 (2 peaks of 57‒65 reads), 10 (2 peaks of 35‒45 reads), 16 (2 peaks of 26‒35 reads), 17 (2 peaks of 24‒37 reads), and 21 (4 peaks of 9‒17 reads). Neither the numbers of DNA peaks or reads differed significantly between the groups compared , with the sole exception of a Y‐chromosome peak mapping at 26,638,004‒ 26,638,595, which yielded only 5 reads in aggregates from AD, but 59 for AMC (Chi2p < 0.005) and a range of 52‒63 reads for the 3 non‐AD samples.Of the 38 loci that showed significant DNA read peaks in at least one pool (each p < 0.001 (2‐tailed Fisher exact tests), vs. 1 of 38 (2.6%) for DNA. It is noteworthy that 30 significantly differential genes were more abundant in AD, while only 9 (23%) were relatively enriched in AMC. This 3:1 bias is on top of the ~1.8‐fold higher abundance of RNA in AD aggregates  include two uncharacterized transcripts on chromosome 21, enriched 17‐fold and 9‐fold beyond other RNAs in AD; ribosomal protein/RPS29, 4.6‐fold; RNAse‐P/RPPH1_2, 3.7‐fold; nucleolar RNA/SNORD3A and long noncoding RNA/LINC00486, enriched 3.5‐ and 3.4‐fold; signal‐recognition‐particle RNAs (SRP_138 and RN7SK), 3.2‐ and 2.7‐fold; mitochondrial RNAse P1/RMRP1, 2.6‐fold; karyopherin/KPNA4, 2.3‐fold; amyloid precursor protein/APP, 2.1‐fold, and SERCA2/ATP2A2, 1.9‐fold  cells, relative to isogenic cells overexpressing APOE4. For 53 of the 59 genes that were confidently identified within fragment alignment peaks, the read count in APOE4‐OE cells differed significantly from APOE3‐OE cells at Fisher exact p < 10‒4, with E3/E4 ratios ranging from 1.7‒13.9. Only one gene appeared to be more abundant in the presence of excess APOE4, a long noncoding RNA for which there were too few reads to attain significance. This bias is consistent with evidence that APOE4 protein competes with transcription factor TFEB for the ~400 DNA binding sites containing the CLEAR motif, most of which drive expression of proteins involved in autophagy/lysosome functions  and comprise an interesting set. Examples include α‐enolase (E3/E4 = 1.85), MHC‐II YBX1 (3.8), scaRNA2 (2.3), histones H2B (2.8) and H1 (6.7), HSP60 (1.6), HSP90‐A1 (1.8) and ‐B1 (1.9), HSP‐A8 (2.0) and HSP‐B1 (3.4), IGF‐BP3 (5.4) and ‐BP5 (2.0), NCL (2.0), prothymosin α (3.2), SPARC (2.4), nucleophosmin (2.5), RACK1 (3.0), 7SK small nuclear RNA (6.2), EEF1‐A1 (2.2), β‐actin (3.2), peptidylprolyl isomerase A (2.6), collagen 1A2 (4.1), vimentin (4.2), CD44 (2.7), cofilin 1 (3.6), GAPDH (2.9), α tubulin (2.9), RNAse P component H1 (9.2), ribosomal proteins RPS2 (4.2) and RPS29 (13.9), 7SL RNA 2 (8.7), β2‐microglobulin (4.1), annexin A2 (3.4), pyruvate kinase M (2.4), profilin 1 (3.7), γ‐actin (3.4), APOE (3.6), ferritin light chain 1 (3.0), galectin 1 (5.0), and filamin A (2.1). With lesser significance, we find synapsin 3 , sequestosome_1/SQSTM1  and vimentin antisense .Differential RNA‐fragment abundances in glioblastoma aggregates, in which only the APOE allele differs between cell lines, tend to be highly significant  of the chromosome 21 short arm  revealed highly significant enrichment for specific groups of RNAs. Focusing on genes with RNA reads that map to significant peaks and are differentially abundant in T98G/E3 vs. T98G/E4 glioblastoma cells, DAVID meta‐analysis revealed highly significant enrichment clusters for gene annotations relating to , [Ubl conjugation + cadherin binding + cell‐cell adherens junction], [glycoprotein binding + protein stabilization], and [myelin sheath + unfolded protein response + protein refolding + stress response + chaperone]  RNA binding + acetylation], [extracellular matrix +chaperone + ATPase activity], [nucleoplasm +nucleus], and [myelin sheath +unfolded protein binding +chaperone] , in the course of replication and transcription can adopt as wide a range of single‐stranded structures as RNA. Affinity for nucleic acids, as well as the protein constituents of multimeric RNA‐ and DNA‐binding complexes, may require protein structures that are at least partially disordered , signal recognition particles, and proteins involved in the processing and functions of noncoding RNAs Figure  Castell. There aG‐quadruplex binding proteins (G4BPs) could be responsible for the presence of certain DNA and RNA segments in aggregates. Of the 39 DNA loci listed in Table 1, 13 (33%) had predicted G‐quadruplex‐forming sequences at >100‐fold higher likelihood than predicted at random, whereas 18 (46%) were <20‐fold above random expectation , relative to the 1.6‐fold AD enrichment of aggregate proteins ; Human Adenovirus 54 ; and Human Papillomavirus 72 . Most of the remaining viruses were more highly represented in DNA than RNA, signifying that they were transcriptionally inactive. The consistently greater RNA/DNA ratios in AD tissue than in AMC is intrinsically “corrected” for relative viral and aggregate abundance, and strongly implies greater transcription and/or aggregation of RNA in AD hippocampus relative to AMC.For 5 of the 10 viruses shown in Table 2.7As noted above, RNA reads substantially exceeded DNA reads by twofold to fivefold Figure . The proDuring translation, nascent proteins are at high risk for misfolding and aggregation until entire structural domains have emerged from the ribosome. From bacteria to mammals, chaperone complexes that include members of the HSP40, HSP60, and HSP90 families are closely associated with ribosomes, where they counteract misfolding of nascent polypeptides  and in cultured human cells as follows. In SY5Y‐APPSw cells, shRNA targeting EEF2 eliminated over 90% of the RNA entrapped in aggregates , in reasonable agreement with previous AD/AMC protein ratios of 1.65 and 1.66 for Aβ and tau aggregates, respectively —implying more abundant and varied protein interfaces in AD than in AMC hippocampus.We were led from the results of proteomic “contactome” studies, intended to define the molecular architecture of aggregates , to investigate the nature, extent, and specificity of nucleic acids incorporated into aggregates. In each of these three respects, the results were unexpected. We observed two‐ to fivefold more RNA than DNA in aggregates, whether isolated from AD or control hippocampus Figure . Many RNAPOE3 vs. APOE4 transgene, sequences with the most differential representation were quite consistently more abundant in APOE3‐bearing cells. We believe this very likely reflects the surprising ability of APOE4 to enter nuclei and bind competitively to the CLEAR/E‐box motifs recognized by transcription factor EB (TFEB), thereby inhibiting expression of autophagy and lysosomal genes  appears to be of viral origin, although these totals may be underestimated due to as‐yet‐uncatalogued and mutated viruses or endogenous retroposons  viral genomes have highly variable insertion sites. As a result, viral RNAs and DNAs require identification by searching a database of known virus genomes. Quantitation of viral sequences may thus be underestimated due to the many human viruses as yet unidentified, plus the high viral mutation rates impeding sequence alignment. Nevertheless, viral RNA and DNA comprise very small fractions of the nucleic acids recovered from aggregates. From an evolutionary perspective, however, they may ultimately be responsible for the perseverance in our genomes of proteins with high levels of disorder and high probability of aggregation—provided only that disorder contributes to the ability to bind viral nucleic acids and/or to sequester them in aggregates.The observed data are consistent with a scenario in which endogenous retroviruses—of which HERV K113 is the youngest and only actively transposing exemplar  “hitchhiker” or “bystander” entrapment of DNA and RNA, when they are bound by proteins that become misfolded and consequently enmeshed in aggregates; and (2) cotranslational misfolding of proteins in the midst of their translation, which might be expected to also ensnare ribosomes and the mRNAs they are translating. The first mechanism is supported by the remarkably high abundance of DNA‐ and RNA‐binding proteins in the aggregate interactome  protein, or when the RNA is in the process of translation into a nascent protein that has a high probability of transient misfolding and aggregation. Our observations imply that cotranslational aggregation is the predominant route, accounting for at least 90% of aggregate RNA.Why did Sw cells, which are subjected to chronic ER stress by continual generation of Aβ1–42, is normally insufficient to prevent cotranslational aggregation. However, even moderate alleviation of that stress appears to shift the balance back to sustainable translational proteostasis. Translational inhibition has been reported to lower chronic inflammation  that might pull them into aggregates. The number and variety of viral sequences found in aggregates suggests that there may be an evolutionary advantage  to the synthesis of nucleic acid binding proteins that readily misfold and thus sequester viral genomes in aggregates. Significant enrichment of viral sequences in AD aggregates, relative to controls, is consistent with roles for integrated viruses in AD susceptibility. The preferential enrichment of RNA over DNA in aggregates may implicate a mechanism specific to transcripts: cotranslational aggregation of polysomes during initial misfolding of nascent polypeptides. This process would likely be quite sensitive to the balance between translation rate and chaperone‐mediated refolding capacity. A critical role of cotranslational entrapment is supported by our observation that shRNA knockdown of the translation elongation factor EEF2, although only 25–35% effective, selectively eliminates at least 90% of RNA in aggregates.55.12 flasks, with culture medium comprising Dulbecco's Modified Eagles Medium (DMEM) supplemented with 10% (v/v) fetal bovine serum (FBS) at 37°C, grown in an atmosphere of air supplemented with 5% CO2. Cells were harvested and washed with phosphate buffered saline and then digested with 0.25% (w/v) trypsin (Thermo Fisher) at 37°C for 4 min or until cells detach from the surface.Cells were grown in 75‐cm5.2EEF‐2 gene knockdown, RNAi knockdown was performed with 3 distinct EEF‐2 shRNA sequences, targeting human EEF‐2 , each introduced separately into SH‐SY5Y‐APPSw cells. Cells were harvested and replated at a density sufficient to achieve ~80% confluence 72 h later. RNAiMax (Thermo Fisher) was used as the transfection reagent, following the manufacturer's protocol. MISSION shRNA universal negative controls  were transfected by the same protocol, as negative controls for the EEF‐2 knockdowns. Cells were harvested and flash frozen 72 hours after transfection.For 5.3APOE3 or T98G/APOE4 human glial cell pellets; or SY5Y‐APPSw human neuroblastoma cell pellets. Frozen tissues or cells were pulverized with a mortar and pestle (cooled on dry ice) and suspended in lysis buffer containing 20‐mM HEPES pH 7.4, 0.3‐M NaCl, 2‐mM MgCl2, 1% NP40 (w/v), supplemented with phosphatase and protease inhibitors . Tissue suspensions were lysed in a Teflon homogenizer  and sonicated . Samples were centrifuged 5 min at 600 × g to remove debris. Supernatant protein was quantified and each sample (0.6–1.0 mg) was centrifuged 15 min at 13,000 × g. Supernatants (soluble protein) were removed, and to each insoluble pellet the same lysis buffer was added plus 1% (v/v) sarkosyl, and mixed well. Samples were centrifuged 20 min at 100,000  × g; supernatants and pellets were recovered as “sarkosyl‐soluble aggregates” and “sarkosyl‐insoluble aggregates”, respectively.Aggregates were prepared from Alzheimer's Disease (AD) vs. age‐matched control (AMC) hippocampus; T98G/5.4g), protein was quantified by the Bradford protein assay. Protein was then gently mixed with magnetic beads coated with antibody to either Aβ1–42 (ab11132) or tau (ab80579) for immuno‐pulldown (IP); sarkosyl‐insoluble protein was isolated from the antibody‐bound fractions as described previously  separation of RNA and DNA fragments using a Qiagen AllPrep DNA/RNA extraction kit according to the manufacturer's protocol, with recovery assayed by absorbance at 260 nm; (2) separation of RNA and DNA fragments with the Qiagen kit, and quantitation by ethidium bromide and/or SYBR Gold after resolution by acrylamide gel electrophoresis; (3) selective enzymatic digestion with RNAse‐free DNAse  and assay by 260‐nm absorption , and (4) using TRI Reagent  to isolate RNA, DNA, and protein in a single protocol. Figure 5.7All RNA‐seq and ChIP‐seq analyses were performed by the UT Southwestern Genomics Core, analyzed using the CLC Genomics Workbench. We employed ChIP‐seq to evaluate DNA‐fragment specificity; thus, the primary analytic value is the number of significant peaks, with peak validity assessed by an E value relative to a flat distribution (peak absence). RNA‐seq was preceded by peak validation, just as for ChIP‐seq. Subsequently, valid‐peak reads that map uniquely to exons (“unique exon reads”) were summed as our expression metric, and were used to determine differential expression between groups.The nucleic acid contig assemblies were quite consistent in size, 579 ± 34 (SD) base pairs in length for DNA peaks, and 291 ± 31 (SD) for RNA‐fragment contigs. The efficiency of ChIP‐seq and RNA‐seq fragment cloning protocols, employed prior to sequencing, is quite sensitive to fragment size. Under normal ChIP‐seq protocols, they would be determined by shearing or sonication, size selection by cloning vector, and/or manual size selection. However, in the case of aggregate nucleic acid fragments, other factors may be influential—such as the size, age, and intracellular location of individual aggregates.5.8https://github.com/WGLab/VirTect/blob/master/README.md): ≥5x coverage depth, a continuous/contiguous region cutoff of ≥75, and a read count ≥50. Several protocol modifications were made for our pipeline: (1) tophat2 was replaced by hisat2; (2) code was optimized to use all available threads; (3) the internal threshold number of reads was reduced in exploratory runs for the purpose of obtaining AD/AMC read ratios, but recommended thresholds were maintained to eliminate false positives in the assignment of valid hits; (4) the modified script was rewritten in Bash, with unnecessary subroutine calls deleted to reduce run‐time. The database screened by VirTect comprises complete sequences of 757 viruses, as described  hippocampi. VirTect is a pipeline script that calls a sequence of RNA‐seq pattern‐matching routines  nondirectional tests, substituting 2‐tailed Fisher Exact tests as required to meet numerical constraints. This conservative replacement is stated in the text but is not made explicit (line by line) in tables to conserve space.Inter‐group differences were tested for significance by 2‐tailed Behrens–Fisher heteroscedastic The authors declare no competing or conflicting interests.EEF2‐shRNA knockdown experiments, and RNA and DNA recovery quantitations; RJSR wrote the manuscript with contributions from SA and MB. All authors read and approved the final manuscript.RJSR and SA designed the study; MB and SA performed aggregate cross‐linking studies; MB undertook subsequent data analysis and network modeling; MB and AG performed additional proteomics data analyses and contactome construction; JJ undertook G‐quadruplex and human‐virus searches, and checked all RNA and DNA sequencing data analyses ; RA and SA performed Fig S1‐S3Click here for additional data file.Table S1Click here for additional data file.


Single-cell RNA sequencing (scRNA-seq) provides new insights to address biological and medical questions, and it will benefit more from the ultralow input RNA or subcellular sequencing.Here, we present a highly sensitive library construction protocol for ultralow input RNA sequencing (ulRNA-seq). We systematically evaluate experimental conditions of this protocol, such as reverse transcriptase, template-switching oligos (TSO), and template RNA structure. It was found that Maxima H Minus reverse transcriptase and rN modified TSO, as well as all RNA templates capped with m7G improved the sequencing sensitivity and low abundance gene detection ability. RNA-seq libraries were successfully prepared from total RNA samples as low as 0.5 pg, and more than 2000 genes have been identified.The ability of low abundance gene detection and sensitivity were largely enhanced with this optimized protocol. It was also confirmed in single-cell sequencing, that more genes and cell markers were identified compared to conventional sequencing method. We expect that ulRNA-seq will sequence and transcriptome characterization for the subcellular of disease tissue, to find the corresponding treatment plan.The online version contains supplementary material available at 10.1186/s12864-021-08132-w. Single-cell RNA sequencing (scRNA-seq) technologies provide a unique opportunity to analyze the single-cell transcriptional landscape. It is a transformative technology that is rapidly deepening our understanding of biology , 2. ThisAt present, the optimization of low mRNA capture efficiency and the sensitivity of detecting low-abundance expressed genes is mainly from two aspects: scRNA-seq technology and data analysis. Previous studies have shown that droplet-based scRNA-seq methods suffer from low mRNA capture efficiency, and the low abundance transcripts detected are not representative. However, cell lysis, mRNA capture, and reversed transcription can be efficiently carried out by improving the parameters of the microfluidic system, such as fluid speed and pressure –19. In aBased on the limitations of current scRNA-seq schemes, we aim to explore a library construction scheme for high sensitivity and low abundance gene detection ability, and it is suitable for subcellular or ultralow RNA sequencing (ulRNA-seq). We have optimized and improved from three aspects: Moloney murine leukemia virus (MMLV) reverse transcriptase (RT), template-switching oligos (TSO), terminal modification and template RNA structure. Using this protocol, we have sequence well-defined dilution series of total RNAs , to comprehensively assess how mRNA capture efficiency, sensitivity, coverage uniformity, and detection of low abundance genes under different amounts of starting material, and it was verified in the single-cell micro-region obtained by glass hollow needle. Compared with the existing methods, this method can creatively apply an optimized and improved scRNA-seq to the precise analysis of spatial transcriptomes, subcellular, tissue biopsies, and rare samples such as circulating tumor cells and early developing embryonic cells, which improved the accuracy and reliability of single-cell sequencing results.Reverse transcriptase is the most important factor affecting the efficiency of reverse transcription. In this study, we compared the performance of five Moloney murine leukemia virus (MMLV) reverse transcriptase that has the necessary template-switching properties, each group had 3 technical replicates. cDNA yields are one of the most direct performance metrics of reverse transcriptase efficiency. The results showed that Template Switching showed higher cDNA yield to input 5 pg and 2 pg RNA ) and sensitivity ) at different input amounts of RNA in each reverse transcriptase. The result showed that as input decreased, precision remained robust among all five reverse transcriptases Fig. A. Compar2 ≥ 0.8), except the 0.5 pg RNA inputs from SuperScript II reverse transcriptase showing a lower level of concordance (R2 < 0.8)  Fig. . Templat.8) Fig. .Fig. 3HP < 0.05). However, at 0.5 pg RNA inputs, TSO-rN detected more genes per sample at comparable sequence depth     (in 0.5 pg RNA inputs)  of all samples. In the MDS plot, the biological replicates clustered closely of the TSO-rN and TSO-rG samples under 5 pg RNA inputs . In addition, we also examined the influence of the two libraries on the number of genes in the range of FPKM values. The figure showed that the template RNA structures didn’t effect on gene expression at 5 pg RNA input  , but there was no significant difference compared with m7G-capped RNA  and low abundance genes  and Smart-seq2 had the lowest 26%) , dropout% , dropoFor single-cell and low-input RNA library preparation, template switching-based RNA-seq is increasingly gaining popularity. However, the efficiency of reverse transcription and template switching can affect single-cell mRNA capture, thus reducing the sensitivity of single-cell sequencing results. Among them, reverse transcriptase is the most direct factor affecting the efficiency of reverse transcription . In thisMoreover, it has been reported that TSO terminal modification or mRNA templates may lead to inefficient amplification and therefore to affect the efficiency of mRNA capture –34. Due At present, our results show that the ulRNA-seq protocol has higher sensitivity at 0.5 pg total RNA input. Therefore, this protocol may be applied to ultralow input RNA samples, subcellular, or high-resolution spatial transcriptome-related research. When we obtained a single cell with spatial position, it may be not a complete cell. The preparation of tissue sections leads to the loss or degradation of RNA in a single cell, so that ultralow RNA sequencing can be performed at the RNA input level lower than single-cell levels. Liu et al. developed the DBiT-seq technology and detected 2068 genes in approximately 4 pg of total RNA . We beliIn summary, we presented a template-switching based library preparation method in the study, which obtained higher sensitivity, accuracy, and gene detection ability in ultralow input RNA sequencing. It is concluded that Maxima H Minus reverse transcriptase, rN modified TSO and 5′-capped RNA templates contributed main to the enhanced ability of low abundance gene detection and ultralow RNA input in this method. More gene numbers and cell markers were identified, and more uniform coverage was obtained in single-cell sequencing. It is suggested that ulRNA-seq will help the further development of single-cell and subcellular studies.One male C57Bl/6 J mouse (8 weeks old) was purchased from Shanghai Southern Model Biotechnology Co., Ltd. It was anesthetized with tribromoethanol (500 mg/kg) , and then was killed by cervical dislocation. This study was reviewed and approved by the Ethics Committee of Zhongda Hospital Southeast University. The brain was dissected from the skull, and then the brain sample was washed with 0.9% pre-cooled saline. The brain samples were immediately treated to isolate the RNA.Total RNA was extracted from brain tissue according to the method of Chomczynski and Sacchi . The RNAThe oligonucleotide sequences are listed in Table Whether the extracted RNA is complete or not, we add capped structure to the extracted total RNA. Capping RNA templates were performed using the Vaccinia Capping System . Briefly, 5 pg or 0.5 pg RNA, 1 × Capping Buffer, 0.5 mM GTP, 0.1 mM SAM, 2.5 units of Vaccinia Capping Enzyme were incubated for 30 min at 37 °C. Then, the cDNA library was constructed with capped RNA templates.− 1 RNAse inhibitor were at 72 °C for 3 min for denaturation, and immediately placed on ice afterward. Next, 2.5 μl 5 X first-strand buffer, 1 μl 10 μM TSO primer, 2 μl 5 M betaine, 1 μl 25 mM MgCl2, 0.5 μl 0.1 M DTT, 0.25 μl 40 U μl− 1 RNAse inhibitor, and 1 μl 200 U μl− 1 reverse transcriptase were added to each sample. Different reverse transcriptases have different template switching conditions. The reaction program of Superscript II reverse transcriptase is 42 °C, 90 min, then 10 cycles , and finally 70 °C, 15 min. The reaction program of Superscript III reverse transcriptase is 50 °C, 60 min, and 70 °C 15 min. The reaction program of Maxima H reverse transcriptase is 42 °C, 90 min, then 10 cycles , and finally 85 °C, 5 min. The reaction program of SMARTScribe reverse transcriptase is 42 °C, 90 min, and 70 °C, 10 min. The reaction program of Template Switching RT Enzyme Mix is 42 °C, 90 min, and 85 °C, 5 min. PCR pre-amplification was performed directly after reverse transcription by adding PCR mix, containing 12.5 μl 2 X KAPA HiFi HotStart Ready Mix and 0.5 μl 5 μM PCR primer. The number of PCR cycles depends on the input amount of RNA. We typically use 20 cycles for than 100 pg RNA input. The number of cycles can be increased to 25 cycles for 1 pg ~ 50 pg RNA input. We use 30 cycles for less 1 pg RNA input. PCR was cycled as follows: 3 min at 98 °C for initial denaturation, 25 cycles of 20 s at 98 °C, 15 s at 67 °C and 6 min at 72 °C. Final elongation was performed for 5 min at 72 °C. Then, we measured the cDNA concentration using the Qubit dsDNA Assay Kit (Thermo Fisher). Finally, 1 ng of cDNA was then used for the tagmentation reaction carried out with One-step DNA Lib Prep Kit for Illumina , with the addition of Tagment DNA Buffer and Tagment DNA Enzyme, in a final volume of 50 μl. The tagmentation reaction was incubated at 55 °C for 5 min and then purified with Ampure XP beads. After tagmentation, the Tn5 transposon DNA will add adaptor adapters at both ends of the RNA/DNA hybrid strand for subsequent PCR amplification for the library building. The reaction program is 72 °C, 3 min, 98 °C, 45 s, then 13 cycles , and finally 72 °C, 5 min. The Agilent 2100 High Sensitivity DNA Assay Kit was used to detect the distribution of amplified product cDNA fragments. According to the detection results, the quality of the amplified product cDNA was determined, and the subsequent cDNA library was sequenced on the Illumina HiSeq X10 PE150 platform .First, the 2 μl capped RNA templates, 0.5 μl 10uM oligo-dT primer, 1 μl 10 mM dNTP mix, and 0.25 μl 40 U μlFirstly, the raw data were filtered to generate clean data, and FastQC software (v0.11.4) was used for the quality control (QC) of the sequencing data. Then, clean data were aligned to the mouse reference sequences by Hisat2 software using default parameters. The expression levels of each transcript were normalized by quantifying FPKM.-△△CT method.To verify the efficiency of different reverse transcriptases, quantitative real-time PCR (qPCR) was used to analyze GAPDH, 18S , and HprAdditional file 1: Table S1. Summary of ulRNA-seq.Additional file 2: Figs. S1. Compared the efficiency of different reverse transcriptase. Figs. S2. The number of genes and cell marker genes detected at 1 ng RNA inputs. Figs. S3. Gene body coverage averaged over different input amounts of RNA sequenced with the different reverse transcriptase library construction. Figs. S4. Principal component analysis and correlation analysis of normalized gene expression values for all samples RNA-Seq datasets analyzed. Figs. S5. Correlation analysis for all samples RNA-Seq datasets. Figs. S6. Comparison of differentially expressed alternative splicing (DEAS) under the different terminal modification TSO for 5 pg RNA inputs. Figs. S7. Gene body coverage averaged over the different structure of mRNA templates. Figs. S8. Comparison of differentially expressed alternative splicing (DEAS) under the different structures of mRNA templates for 5 pg RNA inputs.


Our understanding of RNA structure has lagged behind that of proteins and most other biological polymers, largely because of its ability to adopt multiple, and often very different, functional conformations within a single molecule. Flexibility and multifunctionality appear to be its hallmarks. Conventional biochemical and biophysical techniques all have limitations in solving RNA structure and to address this in recent years we have seen the emergence of a wide diversity of techniques applied to RNA structural analysis and an accompanying appreciation of its ubiquity and versatility. Viral RNA is a particularly productive area to study in that this economy of function within a single molecule admirably suits the minimalist lifestyle of viruses. Here, we review the major techniques that are being used to elucidate RNA conformational flexibility and exemplify how the structure and function are, as in all biology, tightly linked. RNA is a critical, central component of the chemical processes of life, not just as an information storage mechanism but also as a spatially dynamic ligand and chaperone, and in some cases, catalytic, molecule. As is common in biology, form and function are inseparable, and the physical properties of RNA are what enables it to perform such a diverse range of roles. Viruses pack functionality into small genomes, and often use the different properties of RNA to carry out distinct parts of their lifecycle. The most familiar of the structural properties is the ability to form Watson–Crick base pairs; this facilitates the generation of RNA duplexes which are significantly stiffer and less deformable than DNA duplexes . This adBesides the classical canonical base pairing, RNA has many well-categorised non-canonical interactions that allow for structural diversity. Each base has three edges which can hydrogen bond to other bases: the Watson–Crick edge, the Hoogsteen edge, and the sugar edge. These alternative interactions include the G-U wobble base, which has similar bonding energy to an A-U pair and can fit within a Watson–Crick helix . Having With such a plethora of possible interactions, and the ability to transition between different states, it is no surprise that higher order RNA structure is incredibly diverse and is often flexible. However, an increasing amount of evidence suggests that these secondary and tertiary structures are comprised of a modular combination of conserved motifs , which causes multiple changes in the RNA structure of an expression platform, hindering translation. Remarkably, the SAM-Ioduction . Viruses2+ binding to RNA affects the stability of conformations and variations in its concentration can induce structural changes, such as the more tightly folded three helix junction present in 16s RNA being favoured at higher Mg2+ concentrations ..45].Within the HCV IRES, domain II controls, amongst other things, the progression from initiation to elongation. In the absence of ligand, it sits in a tightly bent conformation, proposed to act as a brake on the ribosome. Upon ligand binding, the domain straightens and elongates without changing its secondary structure. Such a large-scale tertiary structural change without an effect on secondary structure is proposed to be a hallmark of viral RNA structural switches substantiated by further experiments on IRES structures from a range of viruses. HCV IRES domain II has also been studied in complex with 40s ribosomal RNA using smFRET, revealing that domain II exists in two conformational states even whilst in complex, instead of the previous single conformation model . It has 2+ concentration (10 mM). Further mutational analysis then revealed that the ability of the P1 and P2 helices to bend into a close conformation, present in a four-way junction motif on the opposite side of the dumbbell structure, affected the frequency of formation of the pseudoknot [Like other flaviviruses, West Nile Virus (WNV) cyclizes its RNA before genome replication in the host and has structurally complex 5′ and 3′ UTR regions to facilitate this. One of the necessary 3′UTR cyclization signals is concealed within a metastable 3′ helix, which, in human cells, requires AUF1 p45 binding to mediate a structure switch exposing the cyclization signal. sm-FRET was used to show that this switch can also be mediated in the mosquito host, by the mosquito squid proteins p30 and p32, although less efficiently than in humans. smFRET also showed the RNA switch to be temperature sensitive, acting as a ‘thermometer’ for the virus . Such RNeudoknot .Although smFRET has most commonly been used to follow structural changes in real time, it can also be used to model tertiary RNA structures, if the secondary structure is known. This was carried out for the HIV-1 packaging signal RNA  provides a cost-effective, time-efficient method to investigate molecular structure dynamics in near-native conditions. The technology itself is not a recent development, having been used to assess tRNA structure in the 1960s ; however2+ dependent, adopting perpendicular helices or a compact arrangement of SLB and SLD, which are both proposed to be important at different stages in the replicative cycle, depending on the appropriate conditions [The ability of SAXS to detect flexibility within a molecule makes it an obvious choice to study viral RNA dynamics in their native state. Both the poliovirus and rhinovirus interactions with poly-C binding protein (PCBP) have been investigated using SAXS ,58. The nditions . In an anditions ,60. SAXSnditions . HCV enccis-acting sequence within the env open reading frame) and its interaction with Rev has also been analyzed using SAXS. Multiple Rev molecules must bind to the RRE, and this nucleoprotein structure engages the Crm1 nuclear export pathway and enables transport of partially spliced and unspliced HIV RNA out of the nucleus. Using SAXS, a structural rearrangement has been suggested to occur in the RRE as each successive Rev molecule binds, eventually exposing a cryptic Rev binding site that enables further nucleation of Rev [Long non-coding sub genomic RNAs are produced by several species of flavivirus and are of functional significance particularly in controlling host antiviral responses. SAXS analysis has shown that their structure is modular and that differences between them can be used to explain mechanistic variations . Some ofn of Rev ,63. Shern of Rev .Although SAXS, NMR, sm-FRET, SHAPE, and proximity ligation are the most commonly used techniques to study viral RNA dynamic structures, many other techniques have also been used to complement them, such as cryogenic electron microscopy (cryo-EM). Here, samples are immobilized within a carbon (or sometimes gold) nano-grid using vitrified ice and images are then captured by a transmission electron microscope before software packages combine the different orientations of the complex captured into a robust three-dimensional model. Cryo-EM has been applied to viral RNA in several studies, and usually accompanies another technique that can capture the RNA dynamics in a near-native environment (such as SAXS or sm-FRET). Limitations of cryo-EM include that is has a low resolution, with structure determinations below 100 kDa being rare , and higA field of study that high-resolution cryo-EM is particularly useful for is imaging the RNA packaging structure within the nucleocapsid of viruses. Asymmetric reconstructions of Brome mosaic virus (BMV) and MS2 bacteriophage have been completed and revealed differing levels of RNA packaging . AnalysiSmaller genomes can sometimes be structurally solved using X-ray crystallography, which showed that in tobacco mosaic virus (TMV), RNA structure inside the capsid is beautifully ordered and exhibits a high degree of symmetry but does not contain the motifs known to be necessary for viral replication, translation, or RNA transport, indicating that a genome-wide conformational change must occur when it is released into the host cell .Gel-based experimentation methods have also been used to elucidate viral RNA structural interactions via mutational analysis. The wheat yellow mosaic virus genome segment RNA1 contains a 5′ UTR IRES and a 3′-cap-independent translation element (CITE). In line cleavage analysis in the presence and absence of the 3′ CITE followed by electrophoretic mobility shift assays (EMSAs) identified a structural switch that controls translational activity , via theAn emerging technique that is particularly useful for studying long non-coding RNAs (lncRNAs) is analytical ultracentrifugation (AUC). Using the sedimentation velocity (SV) and sedimentation equilibrium (SE) modes can give information about molecule size, purity, aggregation, hydrodynamic shape, and ensemble composition whilst requiring very small sample sizes compared to other biophysical techniques . AUC is Several forms of spectroscopy are also emerging as viable techniques for determining RNA structure. Circular dichroism makes use of the differing absorbance between left and right circularly polarized light, with different biomolecules displaying different absorbance spectra signatures. Having been applied widely to DNA and proteins the technology is now beginning to be applied to RNA, thanks to advances in synchrotron capabilities allowing the spectral range to become as low as 170 nm . Down atAn interesting strategy of investigating RNA excited states (ES) using 2′-O-methyl (Nm) modification of the ribose sugar has recently been characterized. Nm modification has been known to alter the biological activities of RNA and is used endogenously by many organisms. Abou Assi et al. demonstrated that Nm achieves this by altering the conformational ensemble composition, usually by increasing the incidence of ES conformations that base pair the modified residues compared to the dominant ground state (GS) conformation . These eAlongside the wet lab techniques to study RNA structure and conformational change, computational structure prediction techniques are also applied extensively. Many such programs center around the philosophy of finding a local energy minimum, using simplified ‘coarse-grained’ molecular models and optimizing algorithms such as Ant colony or Metropolis to refine initially random arrangements into an optimized structure. The many ensuing 2D prediction programs, such as ACOfoldpath and NARES-2P ,76, are The armamentarium of techniques used to study RNA structure is growing, and with it, a greater appreciation of the extraordinarily versatility of this molecule and its ability to carry out multiple roles simply by using conformational variants of a single molecular species. The molecular environment is clearly critical and complicates interpretations of many current methods that rely on analysis in non-native conditions. As with much of molecular biology, pivotal findings in this field have been made studying viral RNA, although, paradoxically, these may represent some of the most densely compacted overlapping functional entities that exist in RNA molecules. Better in vivo techniques are emerging and alongside these is the rapidly expanding field of nucleotide modification of RNA and its effect on RNA structure and function. Enhanced methods of RNA sequencing such as nanopore are starting to make these more easily analyzable. Combined with computational advances and the emerging power of machine learning, the future of RNA structure/function analysis has an exciting but unpredictable future.