The accurate exclusion of introns by RNA splicing is critical for the production of mature mRNA. U2AF1 binds specifically to the 3´ splice site, which includes an essential AG dinucleotide. Even a single amino acid mutation of U2AF1 can cause serious disease such as certain cancers or myelodysplastic syndromes. Here, we describe the first crystal structures of wild-type and pathogenic mutant U2AF1 complexed with target RNA, revealing the mechanism of 3´ splice site selection, and how aberrant splicing results from clinically important mutations. Unexpected features of this mechanism may assist the future development of new treatments against diseases caused by splicing errors. U2AF1 binds to the 3’ splice site of introns and its mutation lead to abnormal splicing. Here the authors solve the crystal structures of wild type and pathogenic mutant U2AF1 bound to target RNA, showing that different target sequence is preferred by pathogenic mutant. The selection of the boundary between coding sequence (exon) and the intron is a crucial step for this regulation, and its misregulation underlies many human diseases7. U2AF (U2 snRNP auxiliary factor) was first identified as the protein complex that recruits U2 snRNP to the conserved branch region8.Noncoding sequences known as introns are removed from precursor mRNA in the maturation process of mRNA. This reaction, RNA splicing, is well-controlled for gene regulation and for generating proteomic diversity9. U2AF consists of large and small subunits9. U2AF large subunit, U2AF2, interacts both with the polypyrimidine tract in the intron and to SF3B1, a component of U2 snRNP, to form the A complex of the spliceosome11. On the other hand, U2AF small subunit, U2AF1, binds to the 3′ side of the boundary sequence between the exon and intron, known as the 3′ splice site . Furthermore, very recently, Fei et al. and Esfahani et al. elucidated by genomic analysis and iCLIP-RNA sequencing that the S34F mutant of U2AF1 causes aberrant alternative splicing in lung adenocarcinomas21. In spite of its importance, the molecular mechanism of sequence-specific RNA recognition by U2AF1 has been poorly understood, especially from a structural point of view. Previously, we reported that U2AF1 could bind to the RNA molecule on its own through the specific recognition of the AG dinucleotides and solved the ternary structure of the RNA-free form of U2AF122. In this study, we solved the crystal structures of wild-type U2AF1 and pathogenic S34Y mutant U2AF1 complexed with RNA containing a 3′SS sequence, in order to clarify how U2AF1 recognizes target RNA accurately and how disease-related mutant of U2AF1 recognizes aberrant 3′SS.U2AF binds to the region around the 3′ end of the intron and the following coding sequence (exon)23, structural and biochemical experiments were carried out with a complex of Schizosaccharomyces pombe U2AF1 with the short fragment of U2AF2 spanning residues 93–161 (the U2AF1 complex), as previously reported22. U2AF1 consists of conserved three domains, an N-terminal zinc finger (ZF1), a U2AF homology motif (UHM), and a C-terminal zinc finger (ZF2)24. In our previous crystal structure of the U2AF1 complex without RNA, the ZFs lie against the β-sheet of the UHM and contact each other, consistent with mutational experiments that suggested RNA might interact with both ZFs22. In order to clarify where and how U2AF1 binds to RNA, we solved the crystal structure of U2AF1 complex with RNA containing 3′SS sequence, 5′-UAGGU. The overall structure of the RNA-free protein is conserved in the RNA-bound U2AF1 complex22, as shown in Fig. The amino-acid sequence of U2AF1 is highly conserved between human and fission yeast with 60% identity, except for RS domain  can be modeled in the RNA-bound form. The side chains of Glu12 and Lys15 interact with the 2′-hydroxyl group of the sugar portion of the guanine residue at −1 position (−1G) and the phosphate group between the uridine residue at −3 position (−3U) and the adenine residue at −2 position (−A), respectively. The Leu5–Tyr9 segment forms no contacts with the RNA, but the N-terminal region is stabilized in some cases by interaction with neighboring molecules in the crystal packing. In the present crystal structure, the first four bases of the 5′-UAGGU sequence (from −3U to the guanine at +1 position (+1 G)) are held by the two ZF domains Fig. . The car22, and the RNA-bound form of canonical zinc fingers  interacts with the guanine bases at positions −1 and +1 through perpendicular and parallel π–π stacking, respectively Figs. . The aro28. One of the hot spot for such mutations is Ser34 in U2AF1; replacement of Ser34 with Tyr or Phe residues induces aberrant splicing29. Usually, the −3 position of 3′SS is occupied by pyrimidine30, and SELEX confirms that the U2AF complex prefers a pyrimidine base at this position12. However, whole-exome sequence analysis by Ilagan et al., Kim et al., and Okeyo-Owuor et al. showed that A or C are found much more frequently at the −3 position of the 3′SS ((A/C)AG) recently, if Ser34 is replaced by Phe or Tyr in hematological malignancies19. In addition, Fei et al. and Esfahani et al. reported that in lung adenocarcinomas, the U2AF1 S34F mutant preferentially binds to CAG at 3′SS, unlike wild-type U2AF121. These results suggested that while the wild-type protein requires −3U to function efficiently, these pathogenic mutants of U2AF1 can accept A or C at this position. In order to confirm the sequence preference at −3 position, we measured the binding affinities of U2AF1 to several RNA molecules with a variety of nucleotides at −3 position by isothermal titration calorimetry (ITC). We observed a Kd value of 0.47 μM for six-nucleotide RNA, 5′-UUAGGU . This mutant was chosen because its solubility is higher than that of S34F mutant, making it more likely to find suitable crystallization conditions. Although the 5′-AAGGU and 5′-CAGGU complexes did not crystallize, the crystal structure of the complex between the S34Y mutant and 5′-UAGGU was determined. In the complex, O4-carbonyl oxygen of −3U maintains a hydrogen bond with the amide proton of the mutated residue (Tyr34), despite a small but distinct position shift of the uridine base compared to that in wild-type U2AF1 Fig. . Along wATR minigene  for the fidelity of the recognition of the bases at −1 and +1 positions.Another mutation hot spot in human U2AF1 is found at Q157, which corresponds to yeast Q151  on the CCCH domains . Based on overlays of these previously determined complex structures 34.Basically, most CCCH-type ZF domains have the pocket B formed by conserved Phe or Tyr residues at the (vi) position and Arg or Lys residues at the (i) position, and have the pocket C formed by Lys, Arg or aromatic residues at the (iv) position and the aromatic amino-acid residue at the (vi) position  and (vi) positions is rare in the zf-CCCH1 family and appeared in the U2AF1 paralogs and PARP12 ZFs. In Group III, it is considered that the D position establishes the RNA alignment by accepting the nucleotide at the 3′-end. Taken together, current evidence suggests that pockets A and D play an important role in the disposition of the RNA bases on ZF domains.On the other hand, ZF5 of Nab2 protein and CPSF40 ZF2 and 3, in Group III, have aromatic amino-acid residues at the (ii) and (vi) positions .22. For co-crystallization of U2AF1 with RNA, protein–RNA complex was produced by the addition of RNA to concentrated protein in a stoichiometric molar ratio of 1:1.5. Crystals were obtained by the hanging-drop vapor-diffusion technique. In total, 20 mg/ml of protein–RNA complex in 20 mM Tris-HCl (pH 8.0), 100 mM NaCl, and 1 mM TCEP was mixed with an equal amount of reservoir solution 10% (v/v) PEG35000, 0.1 M sodium citrate (pH 6.0) and equilibrated against reservoir solution at 4 or 20 °C. Cryo-protection was achieved in several steps by in-well buffer exchange with increased ethylene glycol concentration from 0 to 20%. Cryo-protected crystals were flash-frozen in liquid nitrogen for data collection.Expression and purification of yeast U2AF1 complexed with the short fragment of U2AF2 (93–161) were performed as previously described57. The space group was found to be P21, with nine molecules in the asymmetric unit. The structures were solved by molecular replacement using Molrep56, with the U2AF23 structure (Protein Data Bank entry 4YH8)22 as the search model. The map was of good quality, allowing RNA of the model to be traced readily . Protein samples were dialyzed against the buffer containing 20 mM HEPES (pH 7.0) and 100 mM NaCl. The sample cell was filled with a 50 μM solution of RNA, and the injection syringe was filled with 500 μM titrating U2AF complex wild type or mutants. All experiments typically consisted of a preliminary 0.4-μL injection followed by 18 subsequent 2-μL injections every 150 s. All of the experiments were performed at 25 °C. Data for the preliminary injection, which were affected by diffusion of the solution from and into the injection syringe during the initial equilibration period, were discarded. Binding isotherms were generated by plotting heats of reaction normalized by the moles of injected protein versus the ratio of the total injected one to the total RNA per injection. The heat of infections was corrected by subtracting the heat of dilution of the protein into the substrate-free buffer. The data were analyzed using Origin software with a single site-binding model. The dissociation constant values are summarized in Table ATR genomic locus  with a single mutation at −3 position of the 3′ splice site were chemically synthesized by Fasmac  and were cloned into pcDNA vector. The coding sequence of human U2AF1 was amplified by PCR using cDNA and was cloned into pcDNA3 vector with mCherry tag. The single mutation for S34F and S34Y of human U2AF1 was generated by PCR. Both minigene and U2AF1 expression plasmid vectors were injected into HEK293 cells, and infected cells were selected and collected by FACSAria II (BD Bioscience). After lysis of cells, spliced minigene was checked by RT-PCR using primers, 5′-AAGCTTCCACCATGGTCTTAAAG-3′ and 5´-GTCGCTGCTCAATGTCAAGA-3′. For quantitative analysis, the gel image was acquired using ImageQuant LAS 4000  and quantified using Multi Gauge software . Two replicas were performed for each experiment.Inserts containing the Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Anulavirus genus, leaving no doubt that both are two isolates of the same viral species. A circular RNA originating from the RNA2 was found, for which an alternative silencing suppressor role is hypothesized. Further investigation is needed to determine this possibility and also the host range and pathological significance of the virus.Grapevine line pattern virus (GLPV) was first described 30 years ago in Hungary. The lack of its genomic sequences and of an available antiserum made its detection impossible in other parts of the world. Three different high-throughput sequencing (HTS) protocols applied on a GLPV-infected vine allowed the construction of the full genome sequence of this virus. It includes three RNA segments, encoding four proteins: methyltransferase-helicase (1a), RNA-dependent RNA polymerase (2a), movement protein (3a) and coat protein (3b). The obtained sequences were used to design specific primers for its detection by RT-PCR and Northern blot hybridization, respectively. These diagnostic methods were used to test the presence of GLPV in graft-inoculated plants and in 220 grapevine accessions of different Mediterranean origins. The three RNAs-encoding proteins of GLPV shared a very high amino acid identity with those of hop yellow virus, a tentative member of the  Although GLPV is included among the viruses that infect the grapevine ([The number of grapevine-infecting viruses (over 80) has increased drastically in recent years , mainly i Oliver . Infecteizoaceae . Based oapevine ,5,6), it,6, itcvsVitis spp.: grapevine angular mosaic virus (GAMV) in Greece [Since its first discovery, two other ilarviruses have been reported from n Greece , which hAlfamovirus and an agent of the yellow mottle disease, with a multipartite genome and different particle shapes [Serological tests have also excluded the probable correlation of GLPV with alfalfa mosaic virus (AMV), a species belonging to the genus e shapes ,4. Idaeovirus, a genus with several common characteristics with ilarviruses , whose presence has been found in line pattern-diseased vines in Slovenia, Serbia and Hungary [Idaeovirus, blackcurrant leaf chlorosis-associated virus, suggesting the possible coexistence in these species of linear and circular viral RNAs [Raspberry bushy dwarf virus is another grapevine-infecting virus belonging to  Hungary ,9,10. In Hungary , which wral RNAs .Bromoviridae is currently composed of six different viral genera  characterized by spherical to bacilliform viral particles, with a multipartite genome, approximately 8 kb long, consisting of three linear, positive sense ssRNAs with 5′-terminal cap structures [Bromoviridae, members of the genus Anulavirus are characterized by having an RNA3 slightly larger than RNA2 and a smaller 2a protein (78.9 kDa), and, differently to the genome of cucumoviruses and some ilarviruses, the protein 2b, encoding a viral silencing suppressor (VSR) of RNAi, is missing [The family ructures . Each ge missing . Anulavirus, i.e., pelargonium zonate spot virus (PZSV), which is the type member [Currently, only two viral species are officially recognized as members of the genus e member ,15 and Ae member . Anothere member .Anulavirus.In this paper, we describe the molecular features of GLPV, whose complete genome sequence was obtained through HTS and Sanger sequencing of RT-PCR amplicons, and which was found to be a putative member of the genus Since its original description in the eighties, GLPV has been maintained on two vines of an interspecific hybrid (Baco 22A) in a grapevine virus repository at Kecskemét-Katonatelep. In 2015, cuttings from one of the two Baco 22A vines were collected, sprouted, and RNA was extracted from their leaves, flowers, tendrils and shot tips using CTAB-based RNA purification . ExtractThe presence of GLPV was investigated in 220 grapevine accessions of different Mediterranean origins. Total nucleic acids (TNA) for that assay were extracted from leaf vein tissues according to Foissac et al. .For small RNA (sRNA) sequencing, RNA extracts originated from different organs were pooled and a sRNA fraction was purified from polyacrylamide gel. sRNA sequencing libraries were prepared from this purified fraction using TruSeq Small RNA Library Preparation Kit, following the manufacturers’ instructions , with some modifications . SamplesFor ribodepleted RNA seq, RNA extracted from the shoot tip was used. The ribosomal RNA (rRNA) was removed using the Ribo-Zero™ Plant Leaf Kit  and the library was prepared using the TruSeq Stranded Total RNA Library Prep Kit . The samples were sequenced on the Illumina Nextseq 500 platform with paired sequencing of 2 × 150 nt at the GIGA facilities of Liège University . Fastq files of the RNA seq can be accessed at SRA with the accession number PRJNA623589.Tissues from leaves (20 gr) were used for viral dsRNA template extraction using the cellulose CC-41  as described by Elbeaino et al. . DsRNA wThe CLC Genomics Workbench  was used for bioinformatics analysis. After trimming and quality control, reads were used for de novo assembly to build longer contigs . The annhttps://www.geneious.com) was used for sequence analysis. A total of 9,503,900 paired reads (2 × 150 nt) were obtained. Paired reads merged using BBMerge and duplicated reads were eliminated by Dedup embedded in Geneious prime. Deduplicated reads were used for de novo assembly by SPAdes assembler software (version 3.10.0) using the default parameters of the Geneious plugin. The annotation of de novo contigs performed using both Geneious’s BLASTX and BLASTN modules was based on a custom database created from the NCBI’s downloaded viral RefSeq database (available at 03.07.2019). The deduplicated unique reads were mapped to the reference genomes of the obtained virus hits using the Geneious mapper (The reads were trimmed for adapters and sorted by sample using Basespace (Illumina) . The Gens mapper . −6) and BLASTP.The raw reads obtained were filtered, reduced to unique reads and assembled de novo into larger contigs using Velvet software  Table S. Assemblwww.geneious.com). The complete sequences of viral RNA segments of GLPV were rechecked by sequencing RT-PCR amplicons obtained from the use of sets of sense and antisense-specific primers designed on assembled genomic RNA sequences  using “Geneious Prime” software , and used as a template in RT-PCR using GLPV-specific primers designed on the CP gene sequence , according to the manufacturers’ instructions. The generated cDNA was used as template for PCR reactions using Q5 DNA Polymerase (New England Biolabs) and primers, which were designed based on the sequenced reads . PCR prosequence .32-labelled DNA probes were prepared using the DecaLabel DNA Labelling Kit (Thermo Fischer Scientific). PCR-amplified and purified products of the cloned regions from all three RNAs were used as a template. Two membranes were prepared and hybridized with RNA2 and RNA3-specific probes. After exposure, the membrane hybridized with the RNA2-specific probe was stripped and rehybridized with the RNA1-specific probe.For Northern blot analyses, 3 µg of total RNA were separated on a denaturing-formaldehyde 1.5% agarose gel and blotted to Amersham Hybond-NX membrane  by the capillary method using 20× SSC . Hybridization was carried out at 65 °C in Church buffer  overnight with the appropriate radioactive probe, washed for 5 min in 2× SSC, 0.1% SDS and for 15 min in 0.5× SSC, 0.1% SDS at hybridization temperature and exposed to an X-ray film. Virus-specific, PThe presence and the nature of a circular RNA (derived from the RNA2), identified in the HTS-generated contigs of the analyzed sequences, were ascertained by RT-PCR assay using two pairs of sense and antisense primers designed at a common position on the circular RNA sequence , which eSecondary structure prediction of the circular RNA was done using MFOLD . In 2016, the buds of GLPV-infected Baco 22A accession were grafted by the chip budding method onto four varieties, i.e., Harslevelu, Jubileum 75, Irsai Oliver and Kekfrankos, with three repetitions for each variety. In the following years (2017–2019), all grafted plants were tested for the presence of GLPV by Northern blot (2017 and 2018) and RT-PCR (2019) assays.Two Baco 22A vines, used for maintaining GLPV, were sampled and used for HTS. They showed spots, and yellow circle-like motifs, which were described as typical symptoms in the chronic phase of GLPV infection . The HTS-library analyses of sRNA and ribodepleted RNA seq revealed the presence of viral sequences belonging to grapevine Pinot gris virus (GPGV), grapevine red globe virus (GRGV), grapevine rupestris stem pitting-associated virus (GRSPaV) and of viroidal sequences, i.e., hop stunt viroid (HSVd) and grapevine yellow speckle viroid 1 (GYSPVd-1) see , but theFrom the de novo assembled contigs of the dsRNA HTS  .Anulavirus   and HYV-Nb  , are reported in GenBank, infecting hop (Humulus lupulus L.) and Thunberg fritillary (Fritillaria thunbergii Miq.), respectively.RNA1, 3160 nt in length, contains a single open reading frame (ORF1) of 2847 nt that encodes a polypeptide of 948 amino acids (aa), with a predicted molecular weight (Mw) of 107 kDa, denoted as domain 1a . ORF1 initiates with a start codon (AUG) at nt position 73 and terminates with an ochre stop codon (UAA) at position 2919. The untranslated regions (UTR) at both 5′ and 3′ terminal sequences are 73 and 241 nt in size, respectively . The 1a ulavirus . BLAST sRNA2 of GLPV, 2493 nt in length, contains ORF2 of 2040 nt, whose translation starts at nt position 73 with an AUG and ends at position 2112 with an UAA stop codon . The seqRNA3, 2529 nt in length, contains two ORFs that encode two proteins, denoted 3a  and 3b . The translation of the protein 3a initiates at nt position 382 and terminates at position 1278; the encoded protein of 298 aa has a predicted Mw of 32 kDa. The protein 3b starts at nt position 1537 and terminates at position 2154, encompassing 205 aa with a predicted Mw of 22 kDa. Similarly to GLPV RNA1- and RNA2-encoded proteins, the amino acid identity matrix of RNA3 showed again that the MP (RNA3a) and the CP (RNA3b) of GLPV shares the highest identity with their homologues of anulaviruses, and in particular with the two isolates of HYV  and the lowest with PZSV (45% and 28%) . The 3′UAnulavirus, allocating it in one cluster together with the anulaviruses and close to HYV  reported in the GenBank .In RT-PCR, all primers designed on nucleotide sequences of RNA1, 2 and 3 showed to be specific and efficient to detect GLPV in the Baco 22A accession .When used in Northern blot, all three riboprobes were able to hybridize their homologue of RNA1, 2 and 3 and sgRNA3 of GLPV, confirming the presence of the GLPV RNA segments only in Baco 22A accession but not in healthy plant material .After the full genome sequence completion of GLPV, the HTS-contigs were again mapped to the GLPV genome in order to check for the presence of additional GLPV isolates with sequence variations within the library. All GLPV-contigs mapped were identical, with the exception of a contig of 167 nt long that shared high sequence identity with RNA2 of GLPV. When further analyzed for its secondary structure, this sequence showed to encompass a circular RNA conformity different from the homologue region of RNA2 of GLPV. To verify that this finding was not an artefact of the assembler and that this circular RNA really exists in the Baco 22A vine, sense and antisense primers a,b, bothThe circular conformity of this RNA2-derivate sequence was proven through two different sets of primers that allow its amplification at two different starting points a,b enablThe availability of the full genome sequence of GLPV allowed us to study the presence and features of GLPV-derived sRNAs, which are the hallmarks of the plant’s immune response, indicating that a virus is actively replicating in them. SRNAs in both directions were generated by all three RNAs of GLPV in high number: 21.091; 26.828 and 168.456 reads (counted with redundancy) with no mismatch a. Their As expected, most of the sRNA reads were derived from the structural RNA3 (6600 reads/1000 nt), which can be explained by the strong antiviral silencing-inducing activity of the abundant coat protein coding sgRNA. Several sRNA reads (1403 reads/1000 nt) were also generated from the circular RNA, as confirmed by the prediction analysis of their secondary structure, according to which most of them were produced by regions with extreme stem-loop structures a, furtheAnulaviruses do not encode a VSR on their RNA2; however, the presence of the circular RNA originating from RNA2 might suggest a possible alternative mechanism to block the host’s defence reaction. The sRNAs analysis showed that reads produced by the circular RNAs (1403 read/100 nt) were more abundant than those produced by any other part of the RNA2 (1076 read/100 nt) . It is pThe Northern blot assay, used to test the virus distribution in different organs of the plant, showed that GLPV was present in all organs examined , but only from those of forced cuttings . Tests cIn an attempt to search for GLPV in grapevine accessions from different Mediterranean countries , 220 grapevine vines, maintained under screenhouses in the premises of the Istituto Agronomico Mediterraneo of Bari, CIHEAM-IAMB , were assayed by RT-PCR using GLPV-specific primers designed on the sequence of the CP gene . In RT-PAnulavirus. Accordingly, it would be the fourth species of this genus, which currently comprises only two officially recognized members: PZSV and ALiMMV, and a tentative member: CIBV. The molecular information now gained on GLPV’s genome, together with those acquired in the eighties, i.e., disease characterization, shape of virus particle (polymorphic), possible member of the family Bromoviridae (confirmed in this study) and its ancient nomination as among the viruses that infect the grapevine [In this work we have determined the whole genome sequence of GLPV, almost 30 years after its first discovery. The characteristics of its genome  and the high nucleotide identity with the genome of other anulaviruses, confirmed that GLPV is a putative member of the genus rapevine , are allThe molecular analysis conducted on its genome revealed and leaves no doubt that GLPV and HYV are two isolates of the same viral species. The sequences of two isolates of HYV, detected from hop and Thunberg fritillary plants, are reported in GenBank, but, apart from the genome sequence, no other information is currently available for them. Further investigation is needed to determine whether they infect the same plant hosts in nature or by artificial inoculation, how they are transmitted in nature, what their geographical distribution is, in order to conclude whether HYV should be considered as a distinct strain of GLPV or simply a GLPV isolate.The absence of GLPV in several vines of Mediterranean origin seems to exclude its possible origin from that area and support the hypothesis that it may originate from areas with temperate/continental climates. This hypothesis seems to be substantiated by the detection of HYV (a GLPV isolate/strain) in China from hops, another typical crop of northern countries. However, further investigation is needed to confirm it.Idaeovirus, that are also characterized—like anulaviruses—by a multipartite genome. The cRNA of RNA2 origin found in our study might also recall defective RNA or DNA associated with the geminiviruses and multipartite RNA viruses [Furthermore, a circular RNA originating from the RNA2 was identified. The possible biogenesis of a circular RNA from a linear viral genome was long unknown, until it was first reported in viruses of genus  viruses ,28, whic


In 2012, a novel coronavirus, initially named as human coronavirus EMC (HCoV-EMC) but recently renamed as Middle East respiratory syndrome human coronavirus (MERS-CoV), was identified in patients who suffered severe acute respiratory infection and subsequent renal failure that resulted in death. Ongoing epidemiological investigations together with retrospective studies have found 61 laboratory-confirmed cases of infection with this novel coronavirus, including 34 deaths to date. This novel coronavirus is culturable and two complete genome sequences are now available. Furthermore, molecular detection and indirect immunofluorescence assay have been developed. The present paper summarises the limited recent advances of this novel human coronavirus, including its discovery, genomic characterisation and detection.


Chromatin-enriched RNAs (cheRNAs) are a unique class of lncRNAs that are tightly bound to chromatin and putatively function to locally cis-activate gene transcription. CheRNAs can be identified by biochemical fractionation of nuclear RNA followed by RNA sequencing, but until now, a rigorous analytic pipeline for nuclear RNA-seq has been lacking. In this study, we survey four computational strategies for nuclear RNA-seq data analysis and develop a new pipeline, Tuxedo-ch, which outperforms other approaches. Tuxedo-ch assembles a more complete transcriptome and identifies cheRNA with higher accuracy than other approaches. We used Tuxedo-ch to analyze benchmark datasets of K562 cells and further characterize the genomic features of intergenic cheRNA (icheRNA) and their similarity to enhancer RNAs (eRNAs). We quantify the transcriptional correlation of icheRNA and adjacent genes and show that icheRNA is more positively associated with neighboring gene expression than eRNA or cap analysis of gene expression (CAGE) signals. We also explore two novel genomic associations of cheRNA, which indicate that cheRNAs may function to promote or repress gene expression in a context-dependent manner. IcheRNA loci with significant levels of H3K9me3 modifications are associated with active enhancers, consistent with the hypothesis that enhancers are derived from ancient mobile elements. In contrast, antisense cheRNA (as-cheRNA) may play a role in local gene repression, possibly through local RNA:DNA:DNA triple-helix formation.Long noncoding RNAs  class of gene regulatory non-coding RNAs was identified. The computational framework presented here provides a reliable approach to identifying cheRNAs from nuclear RNA-seq, and for studying cell-type specific gene regulation. We find that intergenic cheRNA, including transcripts mapped to regions with high levels of classically repressive H3K9me3-marks, may act as a transcriptional activator. In contrast, antisense cheRNA, which originates from the DNA strand complementary to the candidate target protein-coding gene may interact with diverse chromatin modulators to repress local transcription. Our new pipeline allows the identification of a more complete set of cheRNAs than other approaches. A future challenge will be to refine the functional mechanisms of cheRNAs by exploring their regulatory roles, which are involved in diverse molecular and cellular processes in humans and other organisms. Many nulncRNA) , 3. Amonry roles –7. In oury roles , 7. HowepolyA+) RNA may miss transcripts that are not polyadenylated and include many lncRNAs. Total-RNA sequencing detects a higher proportion of lncRNA, but is more expensive and less efficient in quantifying coding-gene expression [Improvements in the bioinformatic analysis of nuclear RNA-seq are required because the distinctions between mRNA-seq and nuclear RNA-seq are substantial. The differences in library construction have significant consequences for the interpretation and analysis of the sequencing data . For inspression .cis-regulatory RNAs, which may be a type of enhancer RNA (eRNA).In this study, we compare one published and three new analytic pipelines for nuclear RNA-seq data analysis. A newly developed pipeline, Tuxedo-ch, outperforms the other pipelines with respect to transcriptome completeness, accuracy of cheRNA identification, and enrichment of enhancer-hallmarks at cheRNA loci. Based on the GENCODE annotation (v25) , we veriWe explore the association of identified cheRNA with chromatin marks and unveil possible regulatory functions of intergenic cheRNAs transcribed from locations adjacent to condensed chromatin (marked by H3K9me3) and of cheRNA transcripts antisense to coding genes. Surprisingly, our data indicate that cheRNA-marked eRNAs are located in regions surrounded by high H3K9me3, which is primarily associated with transcript repression. Given that H3K9me3 is associated with the silencing of mobile elements , 12, ourFig 1A). For example, the numbers of detected transcripts differ when nuclear or total RNA is sequenced, with 30.0% (7.0 k out of 23.3 k) of the transcripts detected only by total RNA sequencing, and 15.9% only by nuclear . This difference is unlikely to be simply due to sequencing depth—the median depth was 49M for four pooled total RNA samples and 33M for 22 nuclear RNA samples; the latter includes the 9 Chromatin Pellet Extract (CPE) and 9 Soluble Nuclear Extract (SNE) samples reanalyzed in this study (S1 Table). Markers of transcriptional regulation including RNA polymerase II (Pol II) sites, transcription factor binding sites, cis-regulatory RNA structures, histone deacetylase, and histone enhancer hallmarks are common in the DNA corresponding to the 3700 RNAs detectable only by nuclear RNA-seq (S2 Table). This observation agrees with previous suggestions that nuclear-retained lncRNA may interact with chromatin regulatory proteins and recruit them to cis-regulatory elements in order to influence gene transcription [Nuclear RNA-seq library construction differs from other RNA-seq protocols Fig A. For exet al. [de novo transcripts originating from the CPE because it applies reference-guided de novo assembly (which can discover novel transcripts) to the CPE but not to the SNE fractions. 2) Werner removes transcripts shorter than 1000 bases from the analysis. LncRNA transcripts are typically shorter than (median length 592 bases) protein-coding transcripts (median 2.4k bases), and 26.8% of GENCODE-annotated lncRNAs (whose biotypes are not ‘protein-coding’) are longer than 200 but shorter than 1000 bases [XIST was categorized as “HiDATA” and excluded from differential expression analysis by Cuffdiff. In addition, it has been shown that discarding genes that are not expressed at a biologically meaningful level in any condition (prefiltering) can increase the power for detecting differential gene expression [Conventional RNA-seq pipelines would not work for the identification of cheRNA that consists of both annotated and novel transcripts. After the isolation of RNA and generation of sequencing libraries, a typical RNA-seq analytic workflow involves sequencing hundreds of millions of reads, alignment of reads to a reference genome or transcriptome, and downstream statistical analysis of expression. In the original method, developed by Werner et al. , 5, whic00 bases . Removinpression , but WerThere is a critical need for a rigorous and effective protocol to analyze nuclear RNA-seq, different from the classic schemes used for mRNA-Seq or total RNA-seq datasets. We have developed new pipelines considering two principles. First, there is no one-size-fits-all pipeline for data analysis; therefore, an empirical approach is recommended for noise removal. Second, biological conclusions need to be data-driven; therefore, both the CPE and SNE samples are analyzed using the same strategy. Specifically, the inclusion of relatively shorter (<1000 bases) lncRNAs allows for greater systematic discovery.Fig 1C). Detailed discussion of the theoretical aspects of the four nuclear RNA-seq analytic pipelines is given in the S2 File. The Tuxedo-ch pipeline makes two key computational improvements: 1) Tuxedo-ch assembles the complete transcriptome in an unbiased way, covering both highly-expressed transcripts and lncRNA shorter than 1,000 bases. 2) Tuxedo-ch employs an empirical threshold to distinguish low but informative lncRNA transcription from noise. As a result, for the first time, we report a correlation between the expression of icheRNA and adjacent genes, facilitating the prioritization of potentially cis-acting cheRNA for further experimental evaluation. The strategies used in the Tuxedo-ch pipeline are not restricted to cheRNA identification and could be beneficial to nuclear RNA-seq data analyses testing broader biological hypotheses, such as to the relationship between enhancer marks  and differentially expressed nuclear RNA.We developed three new pipelines  to analyze these datasets; each with four major analytic steps . To determine the reasons for assembly inconsistency, we compared the assembly results for annotated transcripts  and novel transcripts  separately. The annotated transcripts assembled by Tuxedo-ch, Concatenating and Werner pipelines were almost identical, and correspond to the set of annotated transcripts in GENCODE (v25). Taco only assembled 26.2% of annotated transcripts. This is because the Taco pipeline uses TACO instead of Cufflinks as the assembly tool. TACO only includes a small fraction of annotated transcripts that have significant expression, while Cufflinks keeps all annotated transcripts when building the transcriptome. Among the unannotated transcripts assembled by Tuxedo-ch and Concatenating, 96.8% were the same. Taco also assembled the smallest number of unannotated transcripts. In summary, Tuxedo-ch and Concatenating assembled more novel transcripts than Werner and Taco.To evaluate the transcriptomes assembled by the four pipelines, we used the assembly results of K562 cell data as a reference. We first compared the completeness of the transcriptomes. Transcriptomes assembled by the Tuxedo-ch and Concatenating assemblies were very concordant. 99.8% of transcripts were the same. 84.4% of transcripts assembled by both Tuxedo-ch and Concatenating were also assembled by Werner. This number decreased to 27.0% for Taco (S2 File). The length distribution of transcripts assembled by Tuxedo-ch and Concatenating, but not by Werner, showed that the majority of such transcripts are shorter than 1000 bases . Transcripts assembled by Werner are mostly longer than 1000 bases since this pipeline removed shorter transcripts from CPE samples. Transcripts assembled by Taco were much shorter compared to the other pipelines . The TACO assembler employs an algorithm based on change-point detection via binary segmentation to predict transcript structure [We next investigated the length of all assembled transcripts (tructure  but may tructure . In summCPM) ≥ 1 in at least half of the samples were defined as ‘expressed’ for downstream analysis. This filter resulted in an approximately log-normal distribution of expression levels and about 14 k measured transcripts per sample . Only 1.4% (156) of the 11k Tuxedo-specifically assembled novel transcripts passed this filter; the longer (>10k bases) transcripts often had higher expression values ( average Fragments Per Kilobase of transcript per Million mapped reads (FPKM) ≥5). The observation that almost all filtered novel transcripts are shorter than 1k bases is reminiscent of a previous work where transcripts shorter than 1k bases were discarded under the assumption that shorter transcripts are more likely to represent spurious transcription [Given that lowly expressed transcripts are likely to be experimental noise , we adoply 1.4% 16 of the S3 Table). We refer to these four novel transcripts as BONO , CLAYTON , MULLENJR , and EDGE . One validated transcript, EDGE, is relatively short (3k bases) with a low expression level (average FPKM = 4.5). We conclude that Tuxedo-ch can construct a comprehensive transcriptome including those novel lncRNAs.We validated the transcription of these Tuxedo-ch discovered novel transcripts. Reliable detection by RT-qPCR supports that the RNAs targeted by specific primers are indeed transcribed. The RT-qPCR evaluation of four biological replicates from chromatin-pellet extract and soluble nuclear extract of K562 cells confirmed the transcription and nuclear localization patterns of four RNAs randomly selected from all 156 novel transcripts (GRO-seq) (S1 Table). Expressed transcripts were defined as those having CPM ≥ 1. The expressed transcripts assembled by Tuxedo-ch showed the highest proportion of overlap with peaks representing both ongoing transcription by Pol II and peaks representing nascent transcription by GRO-seq , demonstrating that expressed transcripts assembled by Tuxedo-ch are more concordant with the active transcription signals indicated by other methods. In summary, we introduce the computational pipeline, Tuxedo-ch, for analyzing nuclear RNA-seq data containing both high and low lncRNA expression.Additionally, we compared the transcriptional activity of the expressed transcripts assembled by the four pipelines using two independent measurements: Pol II ChIP-seq and global run-on sequencing (ROC)-evaluation. With the sets of 731 common cheRNA predictions and 3.6k Soluble Nuclear Extract RNA (sneRNA) predictions, Tuxedo-ch and Concatenating outperformed Werner and Taco in the identification of both cheRNA and sneRNA . To further check the accuracy we examined sixteen loci of known cheRNA, sneRNA, or chromatin-independent RNA  that were previously validated in specific cell types [PPV) of 0.88 (S4 Table). This PPV analysis, although possibly susceptible to threshold effects, makes up for the shortage of a ROC-analysis due to the lack of a true gold standard. Both analyses suggest that Tuxedo-ch and Concatenating are better than Werner and Taco.To evaluate the performance of the four pipelines in cheRNA identification, we used a set of transcripts identified by all methods as a proxy gold standard to perform Receiver Operating Characteristic , which is defined as cheRNA without coordinate overlap with known coding genes, is similar to eRNA [Fig 3C). In this analysis, we used the broad Chromatin state segmentation by Hidden Markov Model (ChromHMM)-predicted eRNA  and non-enhancer RNA ( black) as positive and negative controls [Fig 3C, purple) compared to the TSS of ChromHMM predicted non-enhancer RNA , while the levels at icheRNA of repressive marks was significantly lower. At TSSs, we observed that cheRNA identified by all four pipelines has higher H3K27ac and EP300 signals than random non-enhancer RNA, but not H3K4me1 marks. These observations connect cheRNA TSSs to active transcription regulation; while the ENCODE H3K4me1 data may lack antibody specificity or be also associated with inactive enhancers [Fig 3D). In summary, icheRNAs identified in nuclear RNA transcripts are associated with eRNAs with higher H3K27ac and EP300 occupancies. Among the four nuclear RNA-seq analytic pipelines, Tuxedo-ch achieves the strongest enrichment of enhancer hallmarks at icheRNA.Because intergenic cheRNA , and those that overlap with mRNAs in the sense orientation . S3 Fig shows the workflow used to categorize the three RNA groups). A large fraction (66%) of the 5,680 identified cheRNAs were transcribed from noncoding regions ( pink bar). In contrast, approximately 90% of the identified 5,672 sneRNAs were mRNAs . Additionally, K562-cell data show that icheRNA exhibited lower coding potential  score [isneRNA), and intergenic RNA transcribed from ChromHMM-predicted enhancer regions or FANTOM5-predicted eRNAs that mostly overlap with genes by cap analysis gene expression (CAGE) [Fig 4B). The coding potential of icheRNA is therefore more similar to that of ChromHMM-predicted intergenic eRNA, while that of isneRNA is more similar to that of mRNA.Werner 2) score ) than con (CAGE)  Fig 4C). Additionally, over half (69% of 445) of the antisense cheRNAs were unannotated, in contrast to only 2% of 163 antisense sneRNAs. This biased annotation of noncoding RNA suggests that previously detected noncoding RNAs primarily correspond to chromatin-depleted noncoding RNA , and that identifying chromatin-enriched RNAs from nuclear extracts can give a more holistic picture of the overall noncoding RNA population.81% (2.7 k) of the identified 3.3 k icheRNAs were previously unannotated transcripts, in contrast to only 6% (27) of the 459 isneRNAs,  between the expression of icheRNA and neighboring protein-coding genes and compared it to the simulated PCC between the expression levels of icheRNA and randomly selected protein-coding genes. Similarly, we calculated these two types of PCCs for isneRNA, ChromHMM predicted eRNA, and FANTOM5 predicted eRNA, respectively.RT-PCR experiments have shown that several expressed eRNAs are intergenic icheRNA . Werner cription , 5. HoweFigs 4D and  red line shows relative density > 1 when correlation coefficient > 0.5). The same calculation for FANTOM-predicted eRNAs or ChromHMM predicted intergenic eRNAs, which are believed to have cis-regulatory enhancer effects, and adjacent genes in the same cell types, showed similar but weaker positive correlations. In contrast, pairs of isneRNA and neighboring genes (blue line) showed a negative correlation . Specifically, with a significance cutoff of correlation coefficient = 0.8, 23% of the identified icheRNA transcripts, in contrast to only 11% of the isneRNA were positively correlated with proximal genes. This observation, for the first time, gives quantitative evidence for a potential cis-regulatory effect of icheRNA on adjacent genes. It also suggests that icheRNA identification as a new approach to predict cis-activating lncRNA, comparable to the conventional approaches using the ChromHMM or FANTOM5 databases.We found that the expression of icheRNAs is more positively correlated with the expression of neighboring genes than with randomly selected genes  of intergenic cheRNAs in a nuclear Poly(A)+ RNA-seq library and nuclear total RNA-seq libraries using published datasets for K562 cells (S1 Table). We observed  higher expression of icheRNA in the nuclear total-RNA library and lower relative abundance in the nuclear Poly(A)+ RNA-seq library, supporting the conclusion that icheRNA are relatively weakly polyadenylated. A similar, but weaker, preference for the total-RNA-seq library was also observed for antisense cheRNAs . In contrast, all protein-coding mRNAs had equivalent expression levels in two libraries, which is consistent with the role of polyadenylation in producing mRNA in the eukaryotic cell nucleus [S5 Fig). The patterns of polyadenylation indicate that icheRNA and isneRNA are differentially polyadenylated. With respect to polyadenylation, icheRNA appears to be more similar to eRNA than is sneRNA, since the majority of icheRNA are depleted in the Poly(A)+ RNA-seq library.Most eRNAs have been reported to be unspliced and non-polyadenylated –27. To t nucleus . Chromatet al. previously observed peaks of H3K27ac near the transcriptional start sites (TSS) of icheRNA, however, unlike prototypical eRNA, these regions did not show abundant H3K4me1 modification [RPM) of RNA polymerase II (POLII), H3K27ac, H3K4me3, H3K4me1, and H3K27me3 marks on the flanking 1 kb sequences around TSSs of icheRNA, isneRNA, mRNA and unexpressed mRNA (RNAs annotated in GENCODE(v25) but not transcribed in K562) . IcheRNA showed low levels of marks associated with active transcription (POLII and H3K4me3), similar to the levels of unexpressed mRNA, and lower than those of isneRNA and mRNA . In contrast to unexpressed mRNA, icheRNA TSS flanking regions showed low levels of repressive (H3K27me3) and poised enhancer (H3K4me1) marks ( red and purple box), and were enriched in active enhancer (H3K27ac and EP300) marks ( red and purple box). In addition to being enriched at enhancer regions, H3K27ac and EP300 marks were also pervasively found near TSS of actively transcribed regions. IcheRNA TSS thus have a chromatin profile that is distinct from those of mRNA, isneRNA, and unexpressed mRNA, suggesting that significantly different modes of regulation may be controlling icheRNA expression.Histone 3 lysine 4 monomethylation (H3K4me1) and histone 3 lysine 27 acetylation (H3K27ac) have been identified as key histone modification features that mark enhancers. H3K4me1 is present at both poised and active enhancers , while HIn summary, icheRNA and isneRNA differ in many respects. In addition to the enrichment of specific epigenetic marks near the TSS, icheRNA has lower coding probability, appear to lack polyadenylation, and icheRNA expression is more positively correlated with that of neighboring coding genes. Overall icheRNA is more similar to eRNA, while isneRNA is more similar to mRNA. The similarity of icheRNA to eRNA, as defined by ChromHMM and FANTOM5 predictions, suggests that icheRNA identification may provide a useful independent approach to predicting eRNA.Fig 5A1) was calculated. Interestingly, we found that the levels of H3K9me3 near (100–1000 bases away from) actively transcribed icheRNA and mRNA TSS  were much higher than that near transcriptionally silenced TSS (DNA regions near to unexpressed mRNA) . In addition, H3K9me3 profiles at actively transcribed regions were quite different from those at transcriptionally silent regions. Specifically, H3K9me3 was high on either side of the TSS of transcribed RNA , but the signal drops precipitously at the TSS . In contrast, H3K9me3 was flat around the TSS of unexpressed mRNA . It has been suggested, for coding transcripts, that H3K9me3 at the promoter is repressive, whereas H3K9me3 across the mRNA gene body is activating [Histone 3 lysine 9 trimethylation (H3K9me3) is associated with constitutive heterochromatin and has been shown to mark transcriptionally repressed regions that are mutually exclusive with H3K27me3 marked repressive regions –34. We etivating , consiste.g., mRNA and isneRNA) . Comparing the average ChIP RPM across RNAs  to that around TSSs , the H3K9me3 values from icheRNA (red) and random mRNA (green) were substantially different, indicating a coincidence of H3K9me3 appearance alongside icheRNA transcripts. To further investigate the effect of H3K9me3 on icheRNA transcription, we separated DNA regions of icheRNA into high H3K9me3 (at least one peak of H3K9me3 mark near the transcribed icheRNA) and low H3K9me3 (no H3K9me3 mark near the transcribed icheRNA) groups. As expected, DNA regions in the “icheRNA with high H3K9me3” had significantly higher levels of H3K9me3 modification than those in the “icheRNA with low H3K9me3” group . The statistical significance of high H3K9me3 ChIP signal at regions peripheral to the TSS of the ‘high H3K9me3” group was true in two other groups of cheRNA, those overlapping with coding-genes on the same strand  or on the opposite strand . Interestingly, chromatin signatures associated with active transcription   were strikingly elevated in the “icheRNA with high H3K9me3” group compared to the “icheRNA with low H3K9me3” group around the TSS. This pattern was reproducible in the two other groups of cheRNA .We also noted that H3K9me3 levels within the DNA region of icheRNA were substantially higher than levels at other transcribed RNA . The levels of icheRNA in the soluble nuclear fraction (the three blue boxes of icheRNAs in the middle), although significantly lower than that in the chromatin pellet fraction (each corresponding yellow box on the left), were also evaluated in the “icheRNA with high H3K9me3” group compared to the “icheRNA with low H3K9me3” group (P<0.01). The normalized expression level of the icheRNA with high H3K9me3 was similar to that of random RNA, suggesting an overall higher nuclear RNA transcription associated with local H3K9me3 occupancy. These observations reinforce the finding that regions with abundant H3K9me3 modification surrounding, but not at the TSS, can be actively transcribed. We conclude that icheRNA are more actively transcribed within regions with high surrounding H3K9me3 levels than those outside H3K9me3-marked regions.We next checked the expression levels of transcripts in the chromatin pellet fraction and soluble nuclear fraction of which we had identified the cheRNAs and sneRNAs respectively . We found that levels of active enhancer marks (H3K27ac and EP300) around TSS of “icheRNA with high H3K9me3” were significantly higher than at the TSS of “icheRNA with low H3K9me3”  and TSS of isneRNA . Moreover, we recaptured the higher levels of active enhancer marks around TSS of “coding-gene overlapped cheRNA with high H3K9me3” , as well of “cheRNA antisense to coding-gene with high H3K9me3” . We measured the H3K9me3 levels across canonical icheRNA transcribed regions and found that three previously identified icheRNAs  with validated positive cis-regulatory activation function showed relatively higher H3K9me3 levels sounding their TSSs than the only icheRNA with a known repressive role (XIST) . These examples reinforce the hypothesis that DNA regions transcribing icheRNA with high levels of surrounding H3K9me3 modification may act as enhancers.Our previous analysis showed that icheRNA possesses features similar to eRNA. However, the TSS of icheRNA showed only moderately higher levels of enhancer marks compared to negative controls (annotated mRNAs unexpressed in the K562 cells) and lower levels than TSS of isneRNA. We measured the levels of enhancer marks  around TSS of “icheRNA with high H3K9me3” (asRNA) complementary to protein-coding transcript(s) has been shown to interfere with transcription of mRNA on the opposite strand [Fig 4A), indicating a significant enrichment of asRNA in the chromatin pellet . Moreover, we noticed that about one third of the chromatin-enriched asRNAs  were unannotated while 98% of chromatin-depleted asRNAs  were annotated, suggesting that many as-cheRNA are completely novel.Antisense RNA , to its corresponding sense mRNA to induce histone methylation and gene repression [S7A Fig), using the Rfam database [Fig 6B, two or more folds). In particular, the overrepresentation of the antisense structure group among as-cheRNA suggests that the function of as-cheRNA, rather than that of as-sneRNA, is likely to be structure-based.Regulatory mechanisms involving asRNA range from simple transcriptional interference by competing for RNA Pol II  to regulpression , 40. Inspression . Therefodatabase . Among fFig 6C), suggesting a negative correlation between the transcription of sense and antisense RNA. Even though both as-cheRNA-colocalized mRNA and as-sneRNA-colocalized mRNA were shown to be repressed at similar levels, the chromatin features and histone patterns around the TSS of the two mRNA groups were significantly different. The TSS of as-cheRNA-colocalized mRNA  were significantly less open , had fewer active transcription marks , but had more repressive marks (H3K27me3), and showed higher PRC2 complex binding (EZH2 but not SUZ12) compared with random mRNA . This pattern was not observed in as-sneRNA-colocalized mRNAs . Altogether, this raises the possibility that as-cheRNA and as-sneRNA may cis-repress local gene transcription through different mechanisms.We then measured the transcription level in CPE and SNE of mRNA that antisense overlaps with as-cheRNA and as-sneRNA. We found that the transcription of both as-cheRNA-colocalized mRNA and as-sneRNA-colocalized mRNA were relatively low compared to that of random mRNA  [TDF) analysis [S2 File, S8 Fig). Interestingly, 58 as-cheRNAs had predicted triple-helix formations, presenting a co-enrichment of as-cheRNA and predicted triple-helix formation in asRNAs expressed in K562 cells . This enrichment suggests that as-cheRNA represses transcription of adjacent mRNAs on the opposite strand, possibly by triple-helix formation.We further propose a molecular mechanism for the S2 File) . Among tanalysis  predictecis-regulatory elements. Operationally, cheRNA are defined by their statistically significant enrichment in the chromatin pellet fraction after biochemical fractionation of nuclei. With our improved computational strategy, we have examined the molecular characteristics of cheRNAs in greater detail than has heretofore been possible. We find that, first, cheRNAs are more likely to be transcribed from noncoding regions, while sneRNAs are mostly transcribed from protein-coding regions. Second, icheRNA have a lower transcription level and are largely unannotated, in contrast with isneRNA which are more highly transcribed and more frequently annotated. Traditional transcriptome profiling of non-coding RNA, using techniques such as total RNA-seq, yields the broadest survey of transcripts, but has limited ability to detect low expression transcripts such as icheRNA. Thus, previous analyses of noncoding RNA primarily focused on noncoding RNA with relatively high transcription levels . In contrast, isolating and sequencing chromatin-enriched RNAs in a nuclear extract more sensitively identifies low expression noncoding RNAs that previously have been ignored by conventional sequencing and analysis methods. Third, we have shown that icheRNA, in contrast to isneRNA, is mostly non-coding, non-polyadenylated, and positively correlated with the expression of neighboring coding genes . Notwithstanding the similarity of these features to those of eRNA, icheRNA has several unique molecular characteristics that distinguish it. For example, icheRNA is generally longer than eRNA . Moreover, some icheRNAs  are known to be repressive regulators rather than activators. Combining all this evidence, we conclude that icheRNA more comprehensively defines chromatin-localized regulatory lncRNAs than cis-activating eRNA.Detailed analysis of nuclear RNA-seq from lncRNA that are shorter than 1,000 bases or transcribed at a low level sheds new light on 0 bases, ) and ichIcheRNA transcripts mapped to regions with high levels of H3K9me3-marks in the transcript body, but not at the TSS, are more actively transcribed and are more highly associated with elevated levels of enhancer marks than icheRNA transcribed from regions with low levels of H3K9me3. This observation indicates that paradoxically, the repressive H3K9me3 mark may be higher surrounding potential enhancer regions. The widespread presence of H3K9me3 at enhancer flanking regions has been previously observed . RegulatFig 5A1). In metazoan cell nuclei, hundreds of large chromatin domains, termed Lamina-Associated Domains (LADs), are enriched in histones H3K9me2 and H3K9me3 modifications that are typical of heterochromatin [et al. that transposable element may provide an evolutionary origin to chromatin-enriched RNAs [TEs). Together, these observations suggest that icheRNA may represent a group of RNAs transcribed from condensed chromatin domains derived from mobile elements [Both icheRNA and transcribed mRNA show a substantial drop in the H3K9me3 signal at the TSS, although the degree to which the H3K9me3 signal is decreased at the TSS is much greater for mRNA than icheRNA  has been shown to have a cis-activators, of which eRNAs are a sub-group. In contrast, as-cheRNA may interact with diverse chromatin modulators to cis-repress transcription. With the Tuxedo-ch pipeline, the future challenge will be to refine the functional mechanisms of these noncoding RNA classes by exploring their regulatory roles, which are involved in diverse molecular and cellular processes in human and other organisms.Nuclear fractionation coupled with RNA-seq provides a powerful way to profile the nuclear transcriptional landscape, especially the noncoding transcriptome. The computational pipeline presented here provides researchers with a reliable approach to identifying cheRNA, and for studying cell-type specific gene regulators. Although the cheRNA is unlikely to be monolithic in function, icheRNA, including icheRNA with high H3K9me3, may act as transcriptional  list all publically available datasets analyzed in this study.Fig 1C). Computational strategies in the latter three steps varied in four different pipelines (S2 File). Source file for the Tuxedo-ch pipeline is provided in the S1 File.We compared three pipelines with the original cheRNA-identification pipeline . Each piPCC) between the intergenic RNA and protein-coding gene. We tested five types of intergenic RNA-gene groups: the icheRNA with random protein-coding gene pairs; the icheRNA with neighbor protein-coding gene pairs (icheRNA:neighborCoding); the broad Chromatin state segmentation by Hidden Markov Model (ChromHMM)-predicted eRNAs with neighbor protein-coding genes pairs (ChromHMM-neighborCoding), FANTOM5-predicted eRNAs with neighbor protein-coding genes pairs (FANTOM-neighborCoding) and the isneRNA with neighbor protein-coding gene pairs (isneRNA:neighborCoding).We calculated the pairwise Pearson correlation coefficient (e.g. icheRNA:neighborCoding) is calculated in the way of dividing the kernel density estimates of indicated intergenic RNA and neighboring protein-coding gene pairs group (e.g. icheRNA:neighborCoding) by the kernel density of icheRNA and randomly selected coding gene pairs group.The PCC of each intergenic RNA-gene pair was calculated based on their expression levels across all CPE and SNE samples of three cell types . To pair an intergenic RNA with its neighbor protein-coding gene out of its nearest upstream and downstream genes on the same strand, the one with the highest absolute PCC value is selected. A significant cutoff of PCC values was set at -0.8 or 0.8, respectively for the negative or positive correlation. Kernel density is estimated for each intergenic RNA-gene pair group. Relative density for each intergenic RNA and neighboring protein-coding gene pairs group , much shorter than the ncRNAs in the assembled transcriptome. Therefore, we could annotate each asRNA as belonging to an Rfam family if it fully covered an Rfam family motif.RNA structural analysis based on the Rfam annotations  was conducted for each Rfam-family, by dividing its frequency within an ncRNA set (icheRNA or isneRNA) versus the frequency in all assembled RNAs. Each Rfam family is represented by a multiple-sequence alignment, a consensus secondary structure, and a covariance model ; and we r), a) the fraction of the asRNA set (t) annotated to this Rfam family (observed fraction); b) the fraction of all assembled RNA annotated to this Rfam family (background fraction); and c) the ratio of the observed and background fractions -overrepresented RNA structural family.Therefore, an RR-score above 1 indicates an asRNA set (ERCC) spike-in RNA standards to the CPE and SNE prior to TRIzol RNA extraction. 1 μg of RNA from each extract was used for reverse transcription with MMLV HP Reverse Transcriptase (Lucigen). A qPCR melt curve analysis was also performed to ensure the specificity of each primer set used in the experiment. Cycle quantification (Cq) values from qPCR with PowerUp SYBR Green (Applied Biosystems) were normalized to the ERCC spike-in RNA standard #42 (ΔCq = Cq−Cqspike−in) per replicate [A = 2(−ΔCq)) of the novel and two control RNAs .The K562 cell line was the kind gift of C. David Allis and subsequently authenticated by the American Type Culture Collection (ATCC). Four independent replicates of 10 million K562 cells were grown in Roswell Park Memorial Institute 1640 Medium (Gibco), supplemented with 2mM Glutamine and 10% Fetal Bovine Serum. Nuclear fractionation of the four replicates followed the previously published protocol [eplicate . The norS2 File). The coding probability of RNA transcripts was calculated using Coding Potential Calculator 2 (CPC2) [Other statistical analyses were performed using R (2 (CPC2) . AUC was2 (CPC2) .S1 FigS2 Table lists the data resources.Transcriptomic (Trans) loci were defined by the presence of ENCODE ChIP-seq peaks or similarity to annotated Rfam families (lncRNA). Peaks of epigenetic marks and transcription factor-occupancy show ChIP-seq results downloaded from ENCODE. Mark of interest (peaks), were compared with each transcriptome and assigned as occurring in both, only one, or neither . The assignment is indicated by the bar color Hallmarks are ordered according to the percentages of peaks overlapping with only the nuclear RNA transcriptome (darkest bar). CPE: Chromatin Pellet Extract; SNE: Soluble Nuclear Extract. (EPS)Click here for additional data file.S2 Figa, The width distribution of all transcripts built in the four pipelines showing Taco assembles relatively shorter transcripts, with 83% of Taco-assembled RNAs are shorter than 1k bases. b, The width distribution of all transcripts built in the four pipelines showing Taco assembles relatively shorter transcripts, with 83% of Taco-assembled RNAs are shorter than 1kbp.(EPS)Click here for additional data file.S3 Fig(EPS)Click here for additional data file.S4 FigBesides the four types of pairing presented in the (EPS)Click here for additional data file.S5 FigIdentified chromatin-enriched (top),—depleted (middle), and -independent (bottom) loci were respectively isolated into three subclasses and plotted. (EPS)Click here for additional data file.S6 Figa, d) H3K9me3  POL II and H3K4me3 profiles, or H3K27ad and EP300 profiles  at promoters (±1kb centered at TSS) of two subclasses of cheRNAs compared to unexpressed RNAs (decoded in colors). The cheRNAs overlapping with coding genes on the same strand on top, while antisense to coding genes at the bottom. P-values calculated by two-sided Wilcoxon rank sum test, NS p>0.05, * p<0.01, ** p<1e-10, **** p<2.2e-16.Average ChIP-seq read density versus input in K562 cells of ((EPS)Click here for additional data file.S7 Figa, Pi plot showing the proportion in RNA structural motifs per group; b, histogram of RNA structural motif widths compared to nuclear RNA-seq transcriptome (Tuxedo-ch). Color decoding the fourteen major RNA structural groups.(EPS)Click here for additional data file.S8 FigThe majority (>80%) of those 30 TDF-failed asRNAs were extremely long RNAs (length>50k bases). In contrast, there were approximately 20% extremely long RNAs among the overall asRNAs or among the identified as-cheRNAs.(EPS)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(PDF)Click here for additional data file.S1 File(TXT)Click here for additional data file.S2 Filehttps://github.com/xyang2uchicago/Tuxedo-ch).The identifications of Tuxedo-ch in three cell types are accessible on GitHub ((DOCX)Click here for additional data file.


Poor self-rated health (SRH) is a strong predictor of premature mortality in older adults. Trajectories of poor SRH are associated with multimorbidity and unhealthy behaviours. Whether trajectories of SRH are associated with deviating physiological markers is unclear. This study identified trajectories of SRH and investigated the associations of trajectory membership with chronic diseases, health risk behaviours and physiological markers in community-dwelling older adults.Prospective general population cohort.Trajectories of SRH over 5 years were identified using data of 11 600 participants aged 65 years and older of the Lifelines Cohort Study.Trajectories of SRH were the main outcome. Covariates included demographics , chronic diseases, health-risk behaviour  and physiological markers .Four stable trajectories were identified, including excellent , good , moderate  and poor SRH . Being women , low education , one  or multiple chronic diseases , smoking , physical inactivity , alcohol abstinence  and deviating physiological markers  increase the odds for a higher probability of poor SRH trajectory membership compared with excellent SRH trajectory membership.SRH of community-dwelling older adults is stable over time with the majority (65%) having moderate SRH. Older adults with higher probabilities of poor SRH often have unfavourable health status. This study concerns the evaluation of physiological markers as a determinant of self-rated health trajectories.The study results are representative for Dutch community-dwelling adults aged 65 years and older.Reverse causation could not be eliminated.The number of chronic conditions were based on self-report; this could have caused non-differential misclassification bias.Self-rated health (SRH) is known as an inclusive measure of global health and is often used as a supplement to objective clinical measures of physical health such as presence of disease and disability.The aim of this study is to identify classes of SRH over 5 years in community-dwelling older adults and to investigate whether group membership of SRH trajectories is associated with self-reported chronic diseases, health risk behaviours and physiological markers.A subsample of the adult Lifelines Cohort Study was used, including participants aged 65 years or older at baseline n=12 685). A detailed description of the complete Lifelines cohort profile is described elsewhere. 685. A dRepeated measures of SRH were assessed at baseline, 1.5 years, 3 years and 5 years after baseline measurement by means of a self-reported question ‘how would you rate your health in general? ’.age, sex and education level  based on a participant’s baseline report on presence of the most burdensome chronic diseases as forecasted for the next decades by RIVM,physical activity , alcohol consumption  and a sum score of abnormal physiological markers were used in the analyses .Physiological markers included body mass index (BMI) as a marker of body composition10.1136/bmjopen-2019-035012.supp1Supplementary dataBaseline characteristics of all participants and classified by SRH trajectory groups were expressed in median and IQR for continuous variables and proportions and percentages for categorical variables. To identify distinct trajectories of SRH over 5 years, latent class analyses were performed using group-based trajectory modelling.Step 1: The basic model was build by including the four repeated measures of SRH using a censored normal model. Two to six trajectories were considered after which the optimal number of trajectories was selected using highest Bayesian information criterion (BIC),Step 2: Multivariable multinomial logistic regression analyses were performed to estimate associations between the probability of SRH trajectory group assignment (result of step 1) and covariates. Three theoretical models were investigated. Model 1: chronic diseases and health behaviours; Model 2: model 1 plus physiological markers; Model 3: model 1 plus the sum score of abnormal physiological markers. For all determinants, multicollinearity was checked using Pearson’s correlations. Baseline age, sex and level of education were included in all models. Model selection was based on lowest BIC, and Akaike’s information criterion (AIC).Step 3: Trajectories of SRH were re-estimated by including the covariates of the selected model out of step 2. This last step allows to evaluate the influence of one covariate on the probability of belonging to each trajectory taking into account the uncertainty of posterior group membership probability that is introduced by trajectory analysis. Wald statistics were applied for testing the differences between covariates across trajectory groups.Data of participants with missing data of SRH at all time points were excluded from all analyses (n=1085 (9%)). Participants with missing SRH data at three or less time points were handled using maximum likelihood estimation. Maximum likelihood estimation uses all available information from observed data for constructing the likely values for missing data.Sensitivity analyses were performed by: (1) rerunning basic trajectory analysis accounting for non-random attrition , and (2) using a composite score for chronic diseases without anxiety and mood disorders. For all analyses Stata Statistical Software release 14 was used (StataCorp. 2015) with the traj plug-in.Of all 11 600 participants, median age at baseline was 69 years (range 65–93), and 47% were men. Of this sample, 34% reported one chronic disease at baseline, 13% reported multimorbidity (≥2 chronic diseases), 57% had one or two abnormal physiological markers, and 38% had three or more abnormal physiological markers . Over 5 Of all evaluated models, four trajectories of SRH with different intercepts, and all slopes close to zero showed the best fit  would be more undesirable than type I error (an overfit model). Therefore the covariates included in model 3 were used for the final model see , model 3The final trajectory model was modelled by jointly estimating the basic model and the covariates age, sex, educational level, self-reported chronic diseases, physical activity behaviour, smoking behaviour, alcohol consumption and the sum score of affected physiological markers as risk factors. The final model assigned 471 (5.5%), 1716 (20.0%), 5637 (65.6%) and 766 (8.9%) people to the excellent, good, moderate and poor SRH trajectories. The final model including covariates showed best fit statistics of posterior probability of group assignment . The basic model over-represented the proportion of participants with highest probability of poor and moderate SRH trajectory membership, and under-represented the proportion of people with highest probability of excellent and good trajectory membership, compared with the final model that took into account the effect of covariates .Wald tests implied that all trajectory groups were distinguished by the number of self-reported chronic diseases, alcohol consumption and the sum score of affected physiological markers . However, the results presented in Sensitivity analysis including alteration of the composite measure for multimorbidity without anxiety and depressive disorders did not alter trajectory group sizes, shapes and OR (results not shown). Dual trajectory modelling accounting for non-random attrition showed constant annual attrition probabilities between 10% (good SRH) and 17% (poor SRH) for all trajectory groups . PosteriIn this sample of an ongoing large cohort study of Dutch community-dwelling older adults, four stable trajectories of SRH over 5 years were identified. The majority (65.3%) of the participants were classified into the moderate SRH category, followed by good (18.8%), poor (10.2%) and excellent (5.6%) SRH. The results of this study confirmed our a priori hypothesis that the probability of poor SRH trajectory membership was associated with multimorbidity, health risk behaviours and abnormalities in physiological markers. The number of chronic diseases seems to be one of the key factors that determine someone’s probability of SRH trajectory membership, as this was the only covariate under consideration that was significantly associated in all SRH trajectories. In addition, the probability of poor SRH trajectory membership was associated with being women, a low education level, health risk behaviours and presence of three or more affected physiological markers.Contrary to previous studies investigating trajectories of SRH, this study identified only stable trajectories of SRH of older community-dwelling adults during 5 years.Consistent with other studies investigating trajectories of SRH, we found strong associations between increasing numbers of baseline self-reported chronic diseases and the probability of poor SRH trajectory membership.Strengths of this study are the large sample size and short measurement intervals for SRH that contribute to the robustness of the findings. In addition, the use of physiological markers next to self-reported data was, to the best of our knowledge, not previously investigated in combination with trajectory analyses. There were limitations as well. First, although we found a strong association between self-reported diseases and higher probability of poor SRH trajectory membership, we cannot rule out reverse causation. The presented ORs only measure relative change on group level and are not suited to generalise to individual probability of group membership. It is therefore hard to translate these results into concrete clinical implications, as there will always be people having multimorbidity combined with excellent SRH. Second, in this older population, the use of self-reported measurements used for measuring the number of chronic diseases may have led to an over/under-estimation of the prevalence of diseases due to non-differential misclassification bias. Finally, attrition may have threatened the generalisability of our results.This study identified four stable trajectories of SRH over 5 years in Dutch community-dwelling, older adults where the majority of the sample had moderate SRH. Being women, lower levels of education, health risk behaviours  and presence of three or more abnormal physiological markers were associated with higher probability of poor SRH trajectory membership. The identified modifiable determinants may provide a basis for future preventive strategies.


We recently discovered that the OAS3/RNase L antiviral pathway is essential for restriction of CpG- and UpA-enriched viruses, in addition to the requirement for zinc finger antiviral protein (ZAP). The current study provides evidence for the specific dinucleotide and wider recognition contexts associated with virus recognition and attenuation. Previous studies have implicated both zinc finger antiviral protein (ZAP) and oligoadenylate synthetase 3 (OAS3)/RNase L in the attenuation of RNA viruses with elevated CpG and UpA dinucleotides. Mechanisms and interrelationships between these two pathways were investigated using an echovirus 7 (E7) replicon with compositionally modified sequences inserted into the 3′ untranslated region. ZAP and OAS3 immunoprecipitation (IP) assays provided complementary data on dinucleotide composition effects on binding. Elevated frequencies of alternative pyrimidine/purine (CpA and UpG) and reversed (GpC and ApU) dinucleotides showed no attenuating effect on replication or specific binding to ZAP by IP. However, the bases 3′ and 5′ of CpG motifs influenced replication and ZAP binding; UCGU enhanced CpG-mediated attenuation and ZAP binding, while A residues shielded CpGs from ZAP recognition. Attenuating effects of elevated frequencies of UpA on replication occurred independently of CpG dinucleotides and bound noncompetitively with CpG-enriched RNA, consistent with a separate recognition site from CpG. Remarkably, immunoprecipitation with OAS3 antibody reproduced the specific binding to CpG- and UpA-enriched RNA sequences. However, OAS3 and ZAP were coimmunoprecipitated in both ZAP and OAS3 IP and colocalized with E7 and stress granules (SGs) by confocal microscopy analysis of infected cells. ZAP’s association with larger cellular complexes may mediate the recruitment of OAS3/RNase L, KHNYN, and other RNA degradation pathways.IMPORTANCE We recently discovered that the OAS3/RNase L antiviral pathway is essential for restriction of CpG- and UpA-enriched viruses, in addition to the requirement for zinc finger antiviral protein (ZAP). The current study provides evidence for the specific dinucleotide and wider recognition contexts associated with virus recognition and attenuation. It further documents the association of ZAP and OAS3 and association with stress granules and a wider protein interactome that may mediate antiviral effects in different cellular compartments. The study provides a striking reconceptualization of the pathways associated with this aspect of antiviral defense. It is increasingly recognized that the nucleotide composition of the genomes of viruses has a profound influence on their subsequent interaction with the cell upon infection. Elevated frequencies of the CpG dinucleotide in RNA virus genomes or in mRNAs expressed during replication substantially modify replication kinetics and gene expression in mammalian viruses, including enteroviruses  and othe2–6–14–17–We recently obtained evidence that the attenuation of high-CpG mutants of the enterovirus echovirus 7 (E7) is further dependent on oligoadenylate synthetase 3 (OAS3) and the downstream activity of RNase L , 20. RevIn addition to the growing complexity of the antiviral pathways mediated by ZAP binding, we have additionally shown that RNA sequences with elevated frequencies of the UpA dinucleotide may additionally be targeted for ZAP binding and virus restriction . UpA-medin vitro binding assay. This assay enabled further studies of the site specificity of CpG and UpA binding to ZAP and the existence of shared or separate binding sites. Finally, through the use of cell lysates from ZAP and OAS3 KO cell lines, we were able to investigate the interdependence of ZAP and OAS3 on RNA binding and their potential cellular interactions.In the current study, we made extensive use of our recently developed E7 replicon construct  in which24–Replication kinetics of E7 replicons are largely unaffected by genome length , enablinWe additionally investigated whether the attenuation created by high-CpG and high-UpA mutants originates from the resulting increased frequency of self-complementary base pairs in viral genomic RNA or mRNAs. Two additional mutants were generated with sequences containing maximized frequencies of reversed dinucleotides (GpC and ApU). These retained native frequencies of CpG and UpA, but their altered composition would have a similar effect on RNA structure formation in the virus (or replicon) genome. Bioinformatically, increasing the frequencies of GpC and ApU dinucleotides substantially increased the minimum free energy (MFE) on folding predicted by RNAFold from −60.9 kcal/mol of the WT sequences to −72.4 and −78.5 kcal/mol of the high-ApU (ApU-H) and GpC-H mutants, respectively. These were comparable to values of −76.4 and −69.9 kcal/mol of the equivalently mutated UpA-H and CpG-H sequences.RNA from both sets of mutants was transcribed from linearized replicon cDNA clones along with previously described WT, CpG-H, and UpA-H mutants as controls . RNA was10.1128/mSphere.01138-20.3FIG S1P < 0.0001. Download FIG S1, PDF file, 0.2 MB.Replication abilities of CpG context mutants in RD cells. Replication of replicons with 3′ UTRs of different dinucleotide compositions  in RD cells compared to a WT R1 sequence. Replication was monitored by luciferase expression and normalized to WT replication. Bars represent the means for two biological replicates, each with three technical replicates; error bars show standard errors for the biological repeats. ns, no statistically significant difference from the WT 51 CpGs construct; ****, Copyright © 2021 Goonawardane et al.2021Goonawardane et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Together, these findings provide no evidence for recognition and downstream potential ZAP-mediated restriction of replication of the CpA and UpG mutants. Furthermore, increased frequencies of GpC and ApU dinucleotides on RNA configuration have no effect on their replication, and this mechanism is unlikely to account for the attenuation of the high-CpG and high-UpA mutants.n = 51) and positions (and therefore spacings) of CpG dinucleotides found in the native R1 sequence; a second set was generated in which the number of CpG dinucleotides was doubled, each in its specific 5′ and 3′ contexts.To investigate whether upstream and downstream contexts influenced CpG-mediated attenuation of the E7 replicon, two sets of modified synthetic sequences with A, C, G, or U bases surrounding each CpG dinucleotide were created. The first set contained the number (n = 51). Conversely, surrounding CpGs with A residues prevented any attenuation even of the high-CpG mutant (n = 102). A similar but even more extreme context effect on attenuation was observed in RD cells  and >40 for amplification of 107 copies of the UpA-H R1 template with CpG-H-specific primers (B). Download FIG S2, PDF file, 0.1 MB.Specificity of amplification of CpG-H and UpA-H R1 RNA sequences. Amplification efficiency of CpG-H and UpA-H R1 transcripts by specific primers used for transcript quantitation in the competition assay . AmplifiCopyright © 2021 Goonawardane et al.2021Goonawardane et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the To investigate the roles of ZAP and OAS3 in the varied attenuation phenotypes of these mutants, the transfections were repeated in B8 (ZAP KO) and B1 (OAS3 KO) cells . For botThe effects of sequence context on CpG-mediated attenuation were similarly apparent when replication was assayed by immunofluorescent detection of dsRNA in infected cells . The repin vivo binding assay for ZAP . However, binding of ZAP was comparable to that of the zero-CpG, low-UpA, and combined zero-CpG/low-UpA sequences  and short (S) isoforms of ZAP  and GAPDH in uninfected cell lysates detected by immunostaining with anti-ZAP polyclonal antibody or GAPDH polyclonal antibody. The lower panel shows a WB for immunoprecipitated ZAP. Download FIG S3, PDF file, 0.1 MB.Western blot analysis for the experiment whose results are shown in Copyright © 2021 Goonawardane et al.2021Goonawardane et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mSphere.01138-20.6FIG S4FIG S4, PDF file, 0.1 MB.Western blot analysis for the experiment whose results are shown in Copyright © 2021 Goonawardane et al.2021Goonawardane et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the The binding of the CpG-H replicon was unaffected by coincubation with differing concentrations of the UpA-H replicon, even if in 10-fold molar excess. Similarly, the binding of the UpA-H replicon was unaffected by coincubation with the CpG-H replicon over the same range of relative concentrations. These findings are most consistent with the existence of separate binding sites for CpG and UpA dinucleotides in ZAP or associated, coimmunoprecipitated proteins.Previous investigations of ZAP and UpA-mediated effects on E7 replication and that of other viruses have not considered whether both efficient binding and ZAP-mediated attenuation of replication requires the copresence of both CpG and UpA dinucleotides in the same RNA sequence. The observation of the potential existence of separate recognition sites does not rule out this possibility. To investigate this, we constructed a pair of replicon mutants in which the inserted 3′ UTR sequence was constructed to contain either zero CpG dinucleotides and maximized numbers of UpAs or vice versa . The repex vivo immunoprecipitation (IP) assay to pull out OAS3 using an anti-OAS3 specific antibody and investigated its binding to E7 R1 RNA sequences of different compositions  cell line , where bex vivo conditions used in the IP assay indicates that apparent binding of high-CpG or high-UpA RNA in the OAS IP assay  mutants of E7. OAS3, while seemingly necessary for attenuation, seems unlikely to be able to bind and discriminate between single-stranded RNA (ssRNA) sequences of different dinucleotide compositions, primarily because of its binding specificity to long dsRNA sequences . HoweverIndeed, the findings in the current study provided evidence for a cooperative interaction between the two proteins, through their close physical association through their coprecipitation , the depThis study provides further evidence for the attenuating effects of elevated frequencies of the UpA dinucleotide on E7 replication and binding in ZAP and OAS3 IP assays , and 7. There are undoubtedly vast complexities in the cellular response to RNA sequences of different compositions and configurations. For example, ZAP binding may directly or indirectly activate OAS3 independently of RNase L; this might represent a complementary or additional effector pathway to KHNYN, perhaps targeting RNA in the different cellular compartments of E7 in replication complexes and HIV-1 sequences expressed as mRNAs. The use of a range of different viral models with their different replication strategies is clearly essential to fully understand the nature and purpose of CpG- and UpA-mediated restriction of virus replication in mammalian cells.Cells were maintained in Dulbecco’s modified Eagle medium (DMEM) (Life Technologies) supplemented with 10% heat-inactivated fetal calf serum (FCS) (Gibco), 100 U/ml penicillin, and 100 μg/ml streptomycin (Life Technologies). A549 ZAP knockout (KO) and A549 OAS3 KO cell lines with deletion of all three alleles were grown as described previously  and UpA (n = 62) dinucleotides as the WT R1 sequence, but the context of the CpG dinucleotides was altered. Four mutants were created where an A, C, G, or T base was placed immediately 5′ and 3′ of each CpG dinucleotide in the sequence, creating the ACGA, CCGC, GCGG, and UCGU motifs  for 4 h. pTK-Ren (Promega) expressing Renilla luciferase was cotransfected as a transfection control. PTK-Ren was linearized using XbaI. RNA transcripts were DNase treated (Thermo Fisher Scientific) and cleaned with a RNA Clean and Concentrator column (Qiagen). RNA integrity was confirmed on agarose gels, and the concentration was determined with Qubit fluorometric quantitation (Thermo Fisher Scientific).The replicon was further modified by insertion of modified sequences in the nontranslated 3′ UTR as described in 4 cells per well in 96-well plates and transfected with 50 ng of replicon and 10 ng of pTK-Ren using the transfection reagent Lipofectamine 2000 (Thermo Fisher Scientific). At the 6 h posttransfection, cells were washed with phosphate-buffered saline (PBS) and harvested in passive lysis buffer (Promega), and the luciferase activities were measured using the dual luciferase reagent kit and GloMax multidetection system (Promega). The firefly luciferase readings were normalized to the Renilla value for each sample. In some formats investigating effects of gene KO, luciferase expression was further normalized to that of the parental WT A549 cell line control.Cells were seeded at 2 × 100C. To remove any unbound primary antibody, cells were washed three times in PBS before the application of the relevant Alexa Fluor 488-, 594-, or 647-conjugated secondary antibodies (Life Technology) diluted 1:750 in 1% (wt/vol) BSA in PBS, followed by 2 h of incubation at room temperature in the dark. DAPI  staining and microscopy were performed as previously described (R) by the PSC colocalization plug-in  (R ranges between −1 (perfect negative correlation) and +1 (perfect positive correlation), with 0 corresponding to no correlation. Colocalization calculations were performed on >10 cells from at least two independent experiments.IF assays were performed as previously described , using ceJ, NIH) . R rangeTo quantify viral RNA copy numbers, total RNA was extracted from cell supernatants with an RNeasy kit (Qiagen). The amount of viral RNA for the given time point was determined against a standard curve of quantified transcript RNAs using the Quantitect RNA kit (Qiagen) and primers annealing specifically to the 5′ UTR of E7 . qPCRs wTotal cellular RNA was isolated using an RNeasy kit (Qiagen). About 40 ng RNA was used as the template for qRT-PCR using Superscript III (Invitrogen) and Fast SYBR green master mix (Applied Biosystems). The abundance of the target mRNA was normalized to that of the GAPDH housekeeping gene coamplified by qPCR  (eBioscience) stimulation (100 ng/ml) 24 h before harvesting in 15-cm dishes using radioimmunoprecipitation (RIP) lysis buffer containing protease and RNase inhibitors (Millipore). Cell lysate and RNA transcript  mixtures for each reaction were then incubated with magnetic A/G beads associated with either rabbit anti-ZAP  or normal rabbit IgG (Millipore) as described above. For RNase treatment, after washing, beads were resuspended in extraction buffer supplemented with the RNase A/T1 mix (Thermo Scientific no. EN0551) for 20 min at room temperature with shaking at 1,000 rpm. The beads were then washed four times with RIP lysis buffer, and the immune complexes were eluted by boiling in Laemmli sample buffer for 5 min at 95°C; the proteins were analyzed by Western blotting.IP in the previously used intracellular format was performed as previously described . For theFor the competitive RNA binding assay, four binding assays were conducted for each experiment. Cell lysates were incubated with CpG-H E7 transcripts at 1:0.1, 1:1, 1:10, and 1:100 molar mass ratios to UpA-H and vice versa (UpA-H E7 transcripts at the indicated molar mass ratios to CpG-H). Cell lysates were incubated for 5 h, and the samples were washed six times, with complete resuspension of beads between washes and 15 min incubation with rotation for the last two washes. After washings, the samples were resuspended in RIP wash buffer and divided into aliquots. A 100-μl aliquot of immunocomplexes was reserved for analysis of the protein fraction. After beads were immobilized, the wash media were discarded, and beads were resuspended in Laemmli sample buffer. About 10 μl of the inputs was also mixed with Laemmli buffer. All the samples were heated for 5 min at 95°C and separated by SDS-PAGE for Western blot analysis. In parallel, viral RNA were purified from another aliquot of immune complexes and inputs, using the RNA viral kit (Zymo Research). RNAs were eluted in 15 μl of RNase- and DNase-free water. The copy number of E7 present in each fraction was determined by qPCR as described above.Following separation by 4% to 15% SDS-PAGE, proteins were transferred to a nitrocellulose membrane using a semidry transfer unit (Bio-Rad). The membrane was blocked in blocking solution containing PBS with 0.1% Tween and 5% skimmed milk (Sigma) and immunoblotted with the following primary antibodies: ZCCHV (for ZAP) (Abcam no. ab154680) and anti-GAPDH (Abcam no. ab8245). Antibody binding was detected by horseradish peroxidase (HRP)-conjugated secondary antibodies followed by chemiluminescence detection by the ECL Prime Western blotting reagent .t test with Welch’s correction or an ordinary one-way analysis of variance (ANOVA) with multiple comparisons using Bonferroni's correction.Statistical significance was determined in GraphPad Prism using either Student's


They determined a structure of the polymerase bound to RNA and to the drug remdesivir. Remdesivir mimics an RNA nucleotide building block and is covalently linked to the replicating RNA, which blocks further synthesis of RNA. The structure provides a template for designing improved therapeutics against the viral polymerase.Understanding the inner workings of the virus that causes coronavirus disease 2019 (COVID-19) may help us to disrupt it. Yin Science, this issue p. 1499 Cryo-EM structures show how the drug remdesivir binds to the RNA polymerase to block RNA elongation. The pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global crisis. Replication of SARS-CoV-2 requires the viral RNA-dependent RNA polymerase (RdRp) enzyme, a target of the antiviral drug remdesivir. Here we report the cryo–electron microscopy structure of the SARS-CoV-2 RdRp, both in the apo form at 2.8-angstrom resolution and in complex with a 50-base template-primer RNA and remdesivir at 2.5-angstrom resolution. The complex structure reveals that the partial double-stranded RNA template is inserted into the central channel of the RdRp, where remdesivir is covalently incorporated into the primer strand at the first replicated base pair, and terminates chain elongation. Our structures provide insights into the mechanism of viral RNA replication and a rational template for drug design to combat the viral infection. The coronavirus disease 2019 (COVID-19) pandemic that has arisen from widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has become a humanitarian crisis, with more than 1.5 million infections and 87,000 deaths reported on 8 April 2020  . Negative-stain EM visualization of the nsp12-nsp7-nsp8 complex displayed monodispersed particles with excellent homogeneity (fig. S1I). For the apo nsp12-nsp7-nsp8 complex, we vitrified the sample in the presence of the detergent DDM. The initial attempt at image processing revealed that the particles are preferentially oriented (fig. S2A). Therefore, we collected >7400 micrograph movies of more than 5.7 million particle projections to increase the number of projections from the nonpreferential orientation. Of these, 81,494 particles were used to yield a density map of 2.8-Å resolution . Cryo-EM studies of the nsp12-nsp7-nsp8 complex bound with the template-primer RNA and RTP (termed the template-RTP RdRp complex) faced two challenges (fig. S3). First, most particles were adsorbed to cryo-EM grid bars rather than staying in the vitreous ice. Second, the RNA duplex was dissociated from the template-RTP RdRp complex, likely owing to conditions of cryo-EM specimen preparation. Eventually, we prepared the cryo-EM specimen of the template-RTP RdRp complex at 15 mg/ml, which is much higher than the normal concentrations used for EM studies of soluble protein complexes. The high concentration of the complex has a mass action effect to stabilize the RNA-protein complex and has an excess amount of the complex to escape the absorption of cryo-EM grid bars to enter the vitreous ice (fig. S3). We collected 2886 micrograph movies, which yielded a 2.5-Å resolution structure using 130,386 particle projections. Because of the relatively high resolution of our structure, the EM map is clear for key structural features across the complex .The structure of the apo RdRp complex contains one nsp12, one nsp7, and two nsp8 proteins, with an overall arrangement resembling those seen in SARS-CoV and the recently solved structure of SARS-CoV-2 . Our strThe structure of the template-RTP RdRp complex contains one nsp12, one nsp7, and one nsp8 . The secThe overall structure of the template-RTP RdRp complex is similar to the apo RdRp structure, with nsp12 in a closed conformation  and 3A. At the 3′ end of the primer strand is RMP . AdditioThe RMP position is at the center of the catalytic active site . As an aThe catalytic active site of the nsp12 RdRp consists of seven conserved motifs A to G; . Both D7Structural comparison reveals several notable differences between the apo and complex structures . Third, Besides remdesivir, several nucleotide analog drugs—including favipiravir, ribavirin, galidesivir, and EIDD-2801—efficiently inhibit SARS-CoV-2 replication in cell-based assays (The COVID-19 pandemic has inflicted emotional pain and economic burden across the globe. Enzymes that are vital for the viral life cycle are suitable antiviral drug targets because they differ from host proteins. Among viral enzymes, RdRp is the primary target of many existing nucleotide drugs. In this paper, we report the structures of the SARS-CoV-2 RdRp complex in the apo form as well as in complex with a template-primer RNA and the active form of remdesivir. The structures reveal how the template-primer RNA is recognized by the enzyme and how chain elongation is inhibited by remdesivir. Structure comparison and sequence alignment suggest that the mode of substrate RNA recognition and remdesivir inhibition of RdRp is highly conserved in diverse RNA viruses, providing a foundation for designing broad-spectrum antiviral drugs based on nucleotide analogs. Moreover, our structures provide a solid template for modeling and modifying the existing nucleotide drugs, including the highly potent EIDD-2801. Together, these observations provide a rational basis to design even more potent inhibitors to combat SARS-CoV-2 infection.