Trypanosoma brucei, an expanded family of PPR proteins localize to the parasite’s single mitochondrion, where they are believed to perform important roles in both RNA processing and translation. We studied the RNA binding specificity of the simplest T. brucei PPR protein (KRIPP11) using electrophoretic mobility shift assays, fluorescence anisotropy, circular dichroism spectroscopy, and in vitro selection. We found KRIPP11 to be an RNA binding protein with specificity for sequences of four or more consecutive guanosine residues (G-tracts). Such G-tracts are dramatically enriched in T. brucei mitochondrial transcripts that are destined for extensive uridine insertion/deletion editing but are not present in mRNAs following editing. We further found that the quadruplex oligoguanosine RNA conformation is preferentially recognized by KRIPP11 over other conformational forms, and is bound without disruption of the quadruplex structure. In combination with prior data demonstrating association of KRIPP11 with the small ribosomal subunit, these results suggest possible roles for KRIPP11 in bridging mRNA maturation and translation or in facilitating translation of unusual dual-coded open reading frames.Pentatricopeptide repeat (PPR) proteins, a helical repeat family of organellar RNA binding proteins, play essential roles in post-transcriptional RNA processing. In  Trypanosoma brucei, are characterized by a single, large mitochondrion (kinetoplast) containing a disc-shaped DNA genome, itself made from a concatenated network of large DNA maxicircles and small DNA minicircles2. This unusual mitochondrion is central to the life cycle and pathogenesis of kinetoplastid parasites. In T. brucei, modulation of mitochondrial activity facilitates parasite adaptation from the sugar-deficient tsetse fly gut, where it depends on oxidative phosphorylation, to the sugar-rich environment in human blood, where it depends on glycolysis for energy4. In these parasites, both nuclear and mitochondrial genes are polycistronic and most regulation of gene expression occurs at the RNA level9. Strikingly, 12 of the 18 protein coding genes in trypanosome mitochondrial DNA are composed of incomplete open reading frames (ORFs) which are post-transcriptionally converted into translatable mRNAs by a process of systematic uridine insertion and/or deletion called RNA editing10. In fact, the primary (pre-edited) transcripts of nine of the T. brucei mitochondrial mRNA genes undergo such massive editing (pan-editing) that approximately 50% of the sequence of mature mRNA consists of externally inserted uridines11. RNA editing by nucleotide insertion and deletion is unique to trypanosomes12, and thus serves as a potential target for pharmacological intervention.Trypanosomes, including the causative agent of human African trypanosomiasis (HAT) 17. Deciphering the RNA binding characteristics of these important proteins is therefore critical to our understanding of the relationship between specific RNA targeting and biological function. Among trypanosome mitochondrial RNA binding proteins, the pentatricopeptide repeat (PPR) family of sequence-specific RNA binding proteins has proven to be particularly important. First discovered in Arabidopsis thaliana in 2000, PPR proteins are characterized by tandem repeats of 35 amino acids, with each motif folding into a pair of antiparallel alpha-helices similar to the peptide-binding tetratricopeptide (34 amino acid) repeat (TPR) motif19. Over the last decade, these proteins have been linked to a wide variety of stages of post-transcriptional RNA processing in chloroplasts and plant mitochondria24. Typically, plant genomes code for hundreds of PPR proteins whereas non-plant eukaryotes contain fewer than ten25. An exception is found in trypanosomes, where approximately 40 PPR proteins have been reported in T. brucei27. These proteins vary dramatically both in the number of PPR repeats and in the presence and nature of accessory non-PPR domains. PPR proteins are highly conserved across trypanosomatids and RNAi knockdowns cause parasite growth retardation, growth arrest, and death, consistent with functional essentiality28. Underlying the severe phenotypes is deterioration in oxidative phosphorylation and thus in mitochondrial function29.RNA editing and other post-transcriptional RNA processing events in trypanosome mitochondria are executed by a variety of RNA binding proteins whose roles and mechanisms of action are only now being characterizedT. brucei PPR proteins. Most T. brucei PPR proteins co-purify with polyadenylation complexes and/or mitochondrial ribosomal subunits, suggesting a role in their respective functions32. For PPR proteins in which the effect of RNAi on mRNA processing has been reported, namely, KPAF1, KRIPP1 and KRIPP8, compromised poly(A/U) synthesis and translation of mitochondrial mRNA has been observed32. However, knockdown of different PPR proteins often affects specific post-transcriptional processes and specific gene transcripts32, suggesting their cognate RNA sequences are unique.Proteomic and genetic analyses have provided some insights into the functions of 33 have limited such studies to a restricted subset of plant PPR proteins. These studies have shown that PPR proteins exhibit high sequence specificity in RNA recognition. For example, maize PPR10 protects and defines both the 5′ and 3′ termini of transcripts from two different loci (atpH and psaJ) by binding to a highly conserved RNA motif located in the intergenic regions downstream of each gene35. Another PPR protein, CRR4 from Arabidopsis thaliana, specifies the site of RNA editing in the chloroplast ndhD gene by recognizing a specific motif surrounding the editing site36. In maize, PPR103 protects the 5′-terminus of processed rpl16 transcripts from exonucleolytic degradation37. Numerous examples of this type have led to a general picture of plant PPR proteins as sequence-specific effectors and modulators of specialized organellar RNA metabolism38.Identifying the specific RNA ligands for PPR proteins is crucial to elucidating their mechanism(s) of RNA binding. Unfortunately, poor protein solubility and difficulty in heterologous expression39 and iterative alignment of residues at each position in the PPR motif with bases in the cognate RNA footprint have suggested a common code of RNA binding in which each PPR repeat recognizes a single nucleotide via RNA contacts from amino acids at positions 1, 3 and 642. Experimental studies using engineered PPR proteins have provided strong support for this mechanism of single-stranded RNA recognition43. Crystal structures of two plant-derived PPR proteins in complex with RNA targets  confirmed the recognition of individual nucleotides of single-stranded RNA by individual PPR repeats and elucidated the basis for many aspects of the emerging recognition code46. These correspondences have been more finely mapped by a set of four crystal structures of designed PPR proteins (dPPRs) in complex with their predicted RNA targets47.For the plant PPR proteins whose specific RNA ligands are known, progress has been made in elucidating their RNA binding mechanisms via biochemical studies with truncated PPR proteins, computational modeling, and x-ray crystallography. Biochemical studies have shown retention of RNA binding in severely truncated proteins, suggesting that the RNA binding activity resides in the PPR modules. Computational studies by phylogenetic analysis of residue conservation across numerous PPR motifsT. brucei PPR proteins have hardly been elucidated, hindering progress in their mechanistic studies and subsequent biotechnological applications. Trypanosomal PPR proteins vary greatly in the number of PPR repeats and in the number and nature of accessory domains. In the initial work reported here, we focused on the 27 kDa T. brucei PPR protein KRIPP11 , which is one of the smallest and simplest members of the protein family. The four PPR repeats originally identified in this protein26, together with two additional 35-residue regions predicted to carry strong helical content, yield a probable total of six tandem PPR repeats in 239 amino acids and no identifiable accessory domains  and equilibrium fluorescence anisotropy and in vitro selection of protein ligands to derive significant insight into the binding specificity and function of this protein. We find that KRIPP11 shows a strong preference for sequences containing G-tracts of four to six residues or more, such as are extensively found in the subset of kinetoplastid pre-mRNAs destined to undergo extensive uridine insertion/deletion editing. Preliminary in vitro evidence suggests targeting of G-tracts in quadruplex RNA form.In contrast to plants, the specific RNA sequences recognized by individual ins Fig. . Though 6 fusion protein was used for the binding assays and selections. Separately expressed MBP-His6  to promote yield and solubility. Using the constructs in Fig. is6 Fig.  was usedPreliminary insights into the sequence- and chemical specificity of KRIPP11’s nucleic acid ligand were obtained by assessing the protein’s affinity for homooligomeric and simple heterooligomeric RNAs and DNA. Among 12-nucleotide homooligomers, EMSA showed an upward shift in the mobility of 12-nucleotide ssRNA for only poly(G) for protein concentrations up to 12 μM Fig. .Figure 212- with an excess of C12-RNA to form double-stranded (G.C)12 abolishes the KRIPP11-induced upward shift in poly(G) mobility . Of the sequences tested, intense shifted bands on increasing KRIPP11 concentration only appeared with the G9 homooligomer  µM was obtained for G12, increasing to (1.88 ± 0.13) μM for the corresponding deoxy sequence  of total G residues. The contrast between anisotropy data and EMSA results may be explained by the nature of EMSA as a non-equilibrium assay, which makes it poorly suited to the detection of interactions with a fast ligand dissociation rate. On the other hand, FA is an equilibrium assay with greater dynamic range of analysis for binding affinity than EMSA49. The quantitative results in Table By contrast, poly(G) sequences as short as Gin vitro selection to isolate RNA sequences with high affinity to the protein from a pool of over 1018 RNA sequences randomized at 20 continuous positions. In vitro selection of aptamer sequences from fully randomized pools such as this provides an unbiased view of consensus RNA binding preferences for proteins and other molecules51. During 11 rounds of in vitro selection, the RNA pool was progressively enriched with KRIPP11-binding activity as measured by the partitioning of fluorescent RNA into the protein-bound pool . Taken together with the homopolymer binding data above, the selection results establish KRIPP11 as a G-tract specific RNA binding protein.To delineate the binding specificity of KRIPP11 in a more unbiased fashion, we applied the technology of ool Fig. . Sequencool Fig. . Little ool Fig. . Assay oT. brucei mitochondrial genome for open reading frames coding for G-rich pre-mRNAs. Interestingly, a strong pattern of preferential enrichment of G-tracts in some transcripts was observed, particularly with respect to the U-insertion/deletion editing state of the transcripts. Specifically, we divided pre-edited transcripts into nine that undergo extensive editing, with more than 50% of the final sequence consisting of inserted uridines (“pan-edited” henceforth); three that undergo editing events to a much less dramatic extent and exclusively to the 5′ end (Cyb and Murf II) or correction of an internal frameshift (COII) (“limited” editing); and the six mitochondrial transcripts that undergo no insertion/deletion editing (“never-edited”). The final versions of the twelve pan- and limited-editing transcripts after all editing events are complete are denoted “post-editing”. Of these four classes, as well as mitochondrial rRNA transcripts, the pan-edited transcripts were specifically and dramatically enriched in G-tracts of at least four consecutive guanosines. Indeed, all but one of the pan-edited transcripts contained at least one, and usually several, G-tracts of six or more consecutive guanosines, a pattern with zero occurrences in the other transcript classes . When RNA previously thermally denatured at 95 °C followed by snap cooling on ice was used in binding assays, the increase in anisotropy with KRIPP11 concentration was greatly diminished relative to native RNA and the binding isotherm did not saturate, consistent with weakened or less-specific binding  band of G12 RNA diminished, likely due to transformation into more stable dimeric quadruplexes with concomitant quenching of fluorescein, similar to the non-thermally exposed RNA.Interestingly, the intensity of native GRNA Fig. . It is lIn short, KRIPP11 binds RNA with high affinity according to fluorescence polarization assays only if that RNA has a thermal history, specifically preparation under native conditions, that shows CD spectra and native-gel behavior consistent with a significant degree of G-quadruplex formation, suggesting that KRIPP11 binding is specific to quadruplex structures.63. To examine the state of KRIPP11-bound RNA, we applied fluorescence resonance energy transfer (FRET) analysis. We prepared a mixture of G12 RNA oligomers containing either a 5′-fluorescein (FLUO) or 3′-TAMRA fluorescent label. A strong FRET affect will be observed only if an intermolecular interaction such as G-quadruplex formation brings the fluorescein donor and TAMRA acceptor within the Förster radius (approximately 55 Å for this donor-acceptor pair), allowing efficient nonradiative donor-acceptor energy transfer. If KRIPP11 were to unfold the RNA quadruplexes, therefore, any FRET signal arising from the intermolecular quadruplex would reduce with KRIPP11 concentration. Here, we found that when annealed to 5′-FLUO-G12, the intensity of G12-TAM-3′ emission increases at least 3-fold relative to G12-TAMRA-3′ alone  and no FLUO emission signal was observed, consistent with a FRET effect. Since the fluorescence donors and acceptors reside on different RNA chains, FRET arises unambiguously from the formation of intermolecular interactions, presumably in the form of G-quadruplex structures  are very stable with melting points above 95 °C64. Thus, only a relatively small fraction of the RNA is unfolded and available to anneal to new partners.Some proteins are known to remodel nucleic acid quadruplex structures upon bindingone Fig.  followin12-TAM-3′ in the 5′-FLUO-G12/G12-TAMRA-3′ FRET combination  not only was not reduced but indeed increased , this data suggests the possibility that G-tracts bind to KRIPP11 in quadruplex form. Given that all but one pan-edited transcript contain multiple long G-tracts  sequences. KRIPP11 binds sequences of four to six or more Gs with high affinity, displays strong discrimination against other homooligomers and related sequences as well as double-stranded RNA, and shows modest specificity for RNA over identical sequences of single-stranded DNA. Bioinformatic analyses of T. brucei mitochondrial RNAs indicate a dramatic selective enrichment of G-tracts with at least four consecutive guanosines only in pre-edited transcripts of extensively edited mRNA genes  have evolved a variety of RNA binding specificities and/or accessory domains to play distinct roles within the organelle. As one of the smallest and simplest PPR proteins in nes Fig. –S7.68. Proteomic analyses of trypanosome mitochondrial ribosomes, however, indicate that KRIPP11 is associated with the small ribosomal subunit31. Indeed, a total of 20 PPR proteins have been identified as components of either the large or small subunit of the mitochondrial ribosome. Although many of these PPRs are presumed to play a structural role, some have been shown to be involved in translational activation of the mitochondrial mRNAs.The simplest explanation of the above results would be that KRIPP11 interacts with transcripts destined for extensive editing and protects, sequesters, and/or targets the transcripts to the editing apparatus. Such functions are familiar roles for PPR proteins in other organisms32 are possible. KRIPP11 binding could bridge mRNA maturation and translation, either by upregulating the substrates for the ribosome by stabilizing polycistronic precursors and pre-edited transcripts or by directly bringing the small ribosomal subunit into contact with mRNA. Alternatively, KRIPP11’s differential affinity for G-tracts of different sizes could specify the residence time of some RNA processing enzymes on their sites of action, which in the case of RNA processing nucleases could prevent stray RNA damage. By masking potential sites of spurious translation initiation, KRIPP11 could prevent premature assembly of the complete translational machinery on unedited mRNA. Evidence from plants71, humans74, yeast75, and even trypanosomes28, among others, shows that PPR proteins are capable of executing any of these functions. A more speculative function for KRIPP11 may be suggested by the existence of an alternatively-edited product of cytochrome oxidase subunit III (COIII). In this transcript, a proposed alternative editing event brings an open reading frame (ORF) found in the pre-edited 5′ end into frame with the ORF generated by editing of the 3′ end of COIII. The resulting alternatively-edited mRNA codes for the AEP-1 protein, which is essential for mitochondrial DNA maintenance77. A substantial portion of the translation-competent AEP-1 mRNA therefore contains G-tracts that are potential binding sites for KRIPP11. Similar alternative editing and dual coding events are widespread in kinetoplastid mitochondria79, and KRIPP11 may participate in stabilization or translational activation of such nonstandard mRNAs via their retained G-tracts. Further insight into the precise mechanistic role of KRIPP11 in organellar RNA metabolism will be obtained from knockdown and in vivo RNA-protein crosslinking studies, now in progress.The low affinity of KRIPP11 for U-rich and A-rich RNA suggests that direct recognition of rRNA or fully-edited, translation-competent mRNA by this protein is not likely. A variety of functions for a precursor/pre-edited RNA binding protein associated with the small ribosomal subunit82. Quadruplex-containing structures have also been found in selected aptamers targeting biologically relevant proteins83. Thus, G-quadruplex recognition has the ability to modulate biological function in a variety of contexts. G-tracts in T. brucei pre-edited mRNAs have been shown to form G-quadruplex structures84, consistent with the analysis of KRIPP11 specificity shown here. If KRIPP11 does indeed bind G-tracts in their quadruplex form, one interesting unanswered question is how the structural mode of binding of PPR proteins, which in other contexts recognize non-quadruplex sequences in extended conformation47, is adapted to the very different overall shape of quadruplex RNA.In the RNA binding assays, KRIPP11 preferentially interacted with G-tracts prepared under conditions favoring the quadruplex conformation over those in random coil states, raising the possibility that quadruplex forms may be the native target of the protein in its biological context. In recent years, it has become increasingly clear that G-quadruplex structures play important functional roles in both DNA and RNA, with specific protein targeting of RNA quadruplexes with concomitant stabilization or destabilization of the quadruplex often a key factor2O. 5′-FLUO labeled dG12 ssDNA was obtained from Integrated DNA Technologies . The pMalTEV-E30 plasmid vector was a kind gift of Dr. Alice Barkan (University of Oregon).RNA oligos labeled with FLUO (fluorescein) at the 5′ end or TAMRA (tetramethylrhodamine) at the 3′ end were synthesized by Thermo Scientific’s Dharmacon RNA Technologies  and deprotected according to the manufacturer’s instructions. Dry RNA was dissolved in MQ-H85 using the BamH1 and SalI restriction sites  was expressed from a construct created by inserting His6 at the C-terminus of MBP just before the TEV protease cleavage site  in a pMalTEV-E30 plasmid vectores Table . The pMaP11 Fig.  to aid tite Fig.  followedE. coli. Recombinant colonies were inoculated into 10 ml LB broth and grown overnight at 37 °C and 250 rpm. 20 ml of this seed culture was then added to 980 ml of LB broth, grown at 37 °C, 250 rpm to an OD600 of about 0.7, induced with 0.1 mM isopropyl-β,D-thiogalactopyranoside (IPTG), and maintained at 22 °C for 6 hours. Cultures were harvested by centrifugation at 4 °C followed by protein purification under native conditions. Bacteria were resuspended in lysis buffer , lysed by a microtip sonicator and clarified by centrifugation. The supernatant was loaded onto a Ni-NTA column and MB-KRIPP11-His6 was eluted by 50 mM NaH2PO4, pH 8.0, 300 mM NaCl, 200 mM imidazole, 5 mM β-ME. Ni-NTA eluates were immediately repurified using an amylose column. Amylose eluates were then dialyzed against at least 40 volumes of 10 mM Tris-HCl, pH 7.5, 50 mM NaCl at 4 °C for at least 12 hours with a 7 K MWCO SnakeSkin® tubing . Dithiothreitol (DTT) was then added to the dialysates to 1 mM followed by concentration using 10 K MWCO centrifugal filters. Protein purity was assessed by 5–12% SDS-PAGE and nucleic acid contamination was monitored by the A260:A280 ratio.Protein was expressed in BL21(DE3) 6. Briefly, MBP-KRIPP11 was purified by tandem Ni-NTA and amylose as above. Dilute protein was then concentrated to 0.7 mg/ml followed by TEV protease cleavage in the presence of 50 mM Tris-HCl, 0.5 mM EDTA, 1.0 mM DTT, plus or minus 0.05% (w/v) DDM. The reaction was performed at 8 °C for 13 hours. 1.6 µl of 10x blue native Tris-glycine (BNTG) sample buffer  sucrose, 5% (w/v) brilliant blue-G) was then added to 14.4 µl of TEV protease cleavage mixture and run on a 6–12% polyacrylamide gradient resolving gel with a 3.5% polyacrylamide stacking gel at 150 V constant voltage, 4 °C, for one hour. 25 mM Tris, 250 mM glycine was used as running buffer. Native TEV protease (27 kDa), thioredoxin-His6 (17 kDa), MBP (45 kDa), MBP-KRIPP11 (69 kDa), and factor Xa protease (43 kDa) were the size markers.After detachment of MBP by TEV protease, free KRIPP11 aggregated upon purification even in the presence of detergents and glycerol. To establish the oligomeric state of KRIPP11, we therefore performed blue native PAGE on the TEV protease cleavage mixture of MBP-KRIPP11-His12, U12, A12, G12, G9, G6, G6C2U2A2, G4, G4C2U3A3 and (GGU)4), and double stranded (G.C)12. Double-stranded (G.C)12 was prepared by heating a mixture of G12 ssRNA, a three-fold excess of C12 ssRNA, and a 5x annealing buffer  on boiling water for two minutes followed by slow cooling at room temperature for one hour. Agarose rather than polyacrylamide gels were used for electrophoresis because the latter were associated with strong well retention of the RNA as the protein concentration rose. Due to the thickness of the agarose gels and the propensity of poly(G) to quench fluorescein, 150 nM RNA/DNA was required in the reaction for optimal signal in the gel images. The RNA binding reaction consisted of 2.5 µl of RNA/DNA, 7.5 µl of protein (MBP-KRIPP11-His6 or MBP-His6 control as labeled), and 2.5 µl of a 5x RNA binding buffer adapted from Stuart and coworkers 86. 25 mM Tris, 250 mM glycine was used as running buffer. Gels were scanned using a VersaDoc™ MP 4000 fluorescence imager (Bio-Rad Laboratories).5′-FLUO labeled RNA and DNA oligonucleotides were used, namely, single stranded C6, 45 µl of a 10x binding buffer , and 50 µl of 180 nM RNA/DNA. After at least 15 minutes of equilibration at room temperature, the intensities of vertically- and horizontally polarized fluorescence emission (Ivv and Ivh respectively) following vertically polarized excitation were obtained at 25 °C using a 5 mm microsquare quartz sample cell in a QuantaMaster spectrofluorometer . Noise from Raman scattering was removed by subtracting the fluorescence emission of KRIPP11 dialysis buffer from data. For all assays, the instrument grating factor (G) was about 1.5. Excitation was at 450 nm with a 2.0 mm slit with emission measured at 520 nm with a 3.8 mm slit. Fluorescence anisotropy was computed from:The anisotropy of 20 nM 5′-FLUO labeled ssRNA or ssDNA was assessed in the presence of increasing KRIPP11 concentration. A 450 µl reaction for each protein concentration was prepared from dialysis buffer, MBP-KRIPP11-Hisd by nonlinear fitting with IGOR Pro 6 according ton is an overall scaling factor.The mean anisotropies of at least three data sets were then normalized and used to determine the KPreliminary experiments indicated stronger and more reproducible interactions of KRIPP11 with slowly thawed G-tract RNA than with either rapidly thawed or thermally annealed RNA  by 11 rounds of in vitro selection using immobilized MBP-KRIPP11-His6 on Ni-NTA magnetic beads using procedures based on published methods87. RNA was synthesized by T7 RNA polymerase from a DNA template containing a variable region of 20 nucleotides surrounded by primer binding sites followed by treatment with DNase and purification. Negative selection to remove sequences with affinity to the fusion partner was performed in every second round of selection using MBP-His6 as a decoy. At each round, the RNA pool in binding buffer  was incubated with MBP-His6 beads (if performed) at 4 °C for 20 minutes. The flow-through from the latter was then incubated with MBP-KRIPP11-His6 for 20 minutes. Binding stringency was increased across the course of the selection by decreasing protein and  RNA concentration . The cDNA from the 11th round RNA was cloned into a TOPO® TA plasmid and sequenced by dideoxynucleotide chain termination. Sequences were then aligned with MEME89 and WebLogo90 to identify conserved elements.RNA aptamers for KRIPP11 were isolated from a pool of 2.4 × 10on Table . After dT. brucei maxicircle DNA sequence (GenBank accession # M94286.1). Edited mRNA sequences were obtained from Hong and Simpson91. A census of nonoverlapping dodecanucleotides containing at least one homopolymeric stretch of four or more Gs in each RNA was then made. Next, a count of each Gn homopolymer  in each transcript category was made.Sequences of all the kinetoplast pre-mRNA and rRNA genes were decoded from the 2O were thawed slowly on ice-cold water. For G12, the concentrations of RNA used were 4.1 µM in MQ-H2O and 3.7 µM in RNA binding buffer . For G4, the concentrations of RNA used were 7.5 µM in MQ-H2O and 6.8 µM in RNA binding buffer. An average of three spectra was obtained per sample. Before CD spectroscopy, the G12 RNA was desalted by dialysis against two1000-fold volumes of MQ-H2O at 12 hour intervals for 24 hours at 4 °C using a 3.5 K Slide-A-Lyzer® cassette (Thermo Scientific). G4 was used in undialyzed form due to lack of retention by the molecular-weight filters used.The native conformation of G-tract RNA ligands was investigated by CD spectroscopy. CD spectra were collected using a Chirascan CD spectrometer  and a 0.1 mm path length cuvette. To assure native conformation, frozen RNA samples in MQ-H12 RNA with varying thermal history. One RNA sample was not exposed to elevated temperature, and represented the native RNA. The second RNA sample was heated at 95 °C for 10 minutes, then one of several different 10X RNA binding buffers  was loaded as marker for monomeric G12 RNA.To further understand the basis for better KRIPP11 binding to native G-tracts than thermally exposed ones, we investigated the gel mobility of four samples of 5′-FLUO-G12 and 3′-TAMRA labeled G12 (G12-TAM-3′) ssRNAs were desalted by dialysis against 200-fold volume of MQ-H2O at 4 °C overnight using a 2.0 K MWCO Spectra/Por® dialysis membrane . To anneal the 5′-FLUO-G12 and G12-TAM-3′, a mixture of 350 µl of each RNA at 3.0 µM monomeric concentration was heated at 95 °C for 10 minutes, then 245 µl of MQ-H2O and 105 µl of 10X RNA binding buffer were added, diluting the RNA to 2.0 µM monomeric concentration. Tubes containing the RNA mixture were then transferred to 95 °C water in a plastic dish and allowed to slowly cool to room temperature on the bench for 4 hours. Finally, the RNA was stored at 4 °C for at least five days to allow further renaturation before FRET assays. The intensities of fluorescence emission of 50 nM monomeric concentrations of 5′-FLUO-G12 alone, G12-TAM-3′ alone, and of the annealed FLUO-G12/G12-TAM mixture in the absence and presence of various KRIPP11 concentrations were then collected at 25 °C following excitation at 490 nm as described above. Three datasets were used to compute average spectra.FRET was used to determine whether KRIPP11 binding perturbs the native conformation of G-tract RNA. Separately labeled 5′-FLUO-GSupplementary Information


RHAMMB promoted liver metastasis. It was unknown whether RHAMMB is upregulated in pancreatic cancer or contributes to its progression. In this study, we found that RHAMM protein was frequently upregulated in human PNETs. We investigated alternative splicing isoforms, RHAMMA and RHAMMB, by RNA-Seq analysis of primary PNETs and liver metastases. RHAMMB, but not RHAMMA, was significantly upregulated in liver metastases. RHAMMB was crucial for in vivo metastatic capacity of mouse and human PNETs. RHAMMA, carrying an extra 15-amino acid-stretch, did not promote metastasis in spontaneous and experimental metastasis mouse models. Moreover, RHAMMB was substantially higher than RHAMMA in pancreatic ductal adenocarcinoma (PDAC). RHAMMB, but not RHAMMA, correlated with both higher EGFR expression and poorer survival of PDAC patients. Knockdown of EGFR abolished RHAMMB-driven PNET metastasis. Altogether, our findings suggest a clinically relevant function of RHAMMB, but not RHAMMA, in promoting PNET metastasis in part through EGFR signaling. RHAMMB can thus serve as a prognostic factor for pancreatic cancer.The receptor for hyaluronic acid-mediated motility (RHAMM) is upregulated in various cancers. We previously screened genes upregulated in human hepatocellular carcinomas for their metastatic function in a mouse model of pancreatic neuroendocrine tumor (PNET) and identified that human The online version of this article (10.1186/s12943-019-1018-y) contains supplementary material, which is available to authorized users. RIP-Tag; RIP-tva to identify metastatic factors [B), significantly promotes liver metastasis of pancreatic neuroendocrine tumors (PNET) in RIP-Tag; RIP-tva mouse models [RHAMM encodes 18 exons and alternative splicing generates different isoforms. RHAMMA includes all 18 exons and RHAMMB lacks exon 4 , RHAMMA levels in metastatic tumors were not significantly higher than those in normal islets (p = 0.8928). The mRNAs of RHAMMA and RHAMMB were readily detectable in additional primary PNETs and metastases by RT-qPCR using isoform-specific primers  PNETs exhibited cytoplasmic staining using an antibody that recognizes common region in RHAMM isoforms Fig. b. BecausA to RHAMMB in RIP-Tag; RIP-tva models of spontaneous metastasis and tail vein assays [B, RHAMMA did not promote spontaneous metastasis . N134 is a cell line derived from a PNET of RIP-Tag; RIP-tva mouse [A than RHAMMB for unknown reasons . Knockdown of RHAMM by shRNA was confirmed  datasets. Both RHAMMA and RHAMMB were expressed at significantly higher levels in PDAC than in normal pancreatic tissues, and RHAMMB was substantially higher than RHAMMA  as well as a control shRNA targeting LacZ (shLacZ). shEGFR(S7 and S9) decreased the levels of both EGFR and p-ERK1/2, a downstream target of EGFR signaling, with S7 exhibiting a better knockdown efficiency than S9  and N134-RHAMMB-shEGFR(S9) cells did not develop metastases 5 weeks post-injection  still did not develop metastases 7 weeks post-injection, and only a mean of 0.5 liver macrometastases appeared in mice injected with N134-RHAMMB-shEGFR(S9) at this time point  and 2 developed liver metastases (25%)  and RHAMMB (B) in 9 primary human PNETs and 3 metastatic PNETs from the livers. Figure S2. Unlike RHAMMB, RHAMMA did not promote liver metastasis of mouse PNET N134 cell line in a tail vein experimental metastasis assay. (A) The number of liver macrometastases was recorded. (B) Immunohistochemical staining of synaptophysin in the liver sections to reveal the presence of metastatic PNETs. Arrows indicate micrometastases. Original magnification: 10X. Scale bar, 200 μm. Figure S3. Correlation between EGFR expression and RHAMMA (A) or RHAMMB (B) expression in TCGA PDAC dataset (RNA-Seq V2). (PPTX 3371 kb)Additional file 2:Table S1. Impact of genes on lymph node and liver metastasis of PNETs in RIP-Tag; RIP-tva mice. (DOCX 37 kb)Additional file 3:Supplementary materials and methods. (DOCX 37 kb)


Exosomes and microvesicles are two major categories of extracellular vesicles (EVs) released by almost all cell types and are highly abundant in biological fluids. Both the molecular composition of EVs and their release are thought to be strictly regulated by external stimuli. Multiple studies have consistently demonstrated that EVs transfer proteins, lipids and RNA between various cell types, thus mediating intercellular communication, and signaling. Importantly, small non-coding RNAs within EVs are thought to be major contributors to the molecular events occurring in the recipient cell. Furthermore, RNA cargo in exosomes and microvesicles could hold tremendous potential as non-invasive biomarkers for multiple disorders, including pathologies of the immune system. This mini-review is aimed to provide the state-of-the-art in the EVs-associated RNA transcriptome field, as well as the comprehensive analysis of previous studies characterizing RNA content within EVs released by various cells using next-generation sequencing. Finally, we highlight the technical challenges associated with obtaining pure EVs and deep sequencing of the EV-associated RNAs. The “Extracellular Vesicles (EVs)” is a general term used to describe various types of spheroid structures, encircled by a lipid membrane bilayer, which are secreted by mammalian cells either passively or upon certain stimuli . Since tThere are three distinct types of EVs (as classified by their origin and biogenesis)—apoptotic bodies (ABs), microvesicles , and exosomes . The ABsImportantly, multiple research reports have demonstrated that various RNA species  entrapped within EVs can be transferred from donor to acceptor cells and interfere in gene expression in the latter , 14. ThiThe techniques widely used so far for isolating EVs include ultracentrifugation, density gradient flotation, ultrafiltration, chromatography, polymer-based precipitation, and immunoprecipitation . DiffereWhile each of the above-mentioned approaches harnesses certain differences in biophysical or molecular properties of EVs , neither method can recover a pure material and allows only an enrichment for certain subpopulations of EVs in a sample , 25. As Finally, certain cell types  exhibit a membrane polarity . TherefoThe presence of mRNAs, miRNAs, and lncRNAs within exosomes and MVs have been consistently shown with microarrays and RT-qPCR techniques in multiple early , 30–36 aIn a pioneering work, Nolte-'t Hoen et al. characterized small RNA content in EVs released by the immune cells in culture using deep sequencing. Interestingly, the majority of total RNA isolated from EVs consisted of small RNAs (<200 nt), with minor amounts of 18S and 28S rRNA. Those short RNA fragments were primarily mapped to protein-coding regions and genomic repeats including SINE, LINE, and LTR sequences . On the The sequencing of total  RNAs in the EVs was reported by Jenjaroenpun et al.  and MiraR = 0.91), MVs and exosomes (R = 0.86), as well as MVs and parental cells (R = 0.86). While a less strong correlation was found between ABs and exosomes (R = 0.79) and exosomes and cells (R = 0.75). Despite the fact that EVs subsets were different only to a minor degree from the aspect of their miRNA cargo, a significant number of miRNAs were detected only in exosomes and were absent in both ABs and MVs, supporting the concept of specific RNA loading into exosomes. It has to be mentioned that other ncRNA species were not only significantly more abundant as compared to miRNA but also selectively enriched in different EVs subtypes released by melanoma cells, which adds another level of complexity to investigating extracellular vesicle RNA cargo and its function  8 signaling, which induces cytokine secretion, presumably by mimicking viral RNA . The TLRMassive parallel sequencing has enabled characterization of the whole spectrum of nucleic acids in a given sample, and was consistently applied to demonstrate the presence of the complex RNA cargo within EVs populations released by various cells. Interestingly, the intravesicular miRNAs (which were well-documented previously using microarray and qPCR-based methods) represented only a very marginal proportion as compared to other RNA species including various small non-coding RNAs, lncRNAs, and mRNA fragments. A putative biological impact of the EVs-associated transcriptomes remains to be validated; however, multiple studies indicated that, at least, exosomal miRNA could mediate communication among various cell types including the immune cells. In addition, EVs-encapsulated miRNAs have been shown to serve as highly specific biomarkers for various pathological conditions and correlate with the presence of malignant tumors. Indeed, exosomes carrying a tumor-specific miRNA repertoire have been consistently detected in the venous blood of cancer patients and mouse models. The collective finding that non-miRNA species are in fact much more abundant in the isolated EVs populations, suggests that they could serve as even more promising non-invasive biomarkers for cancer and/or other disorders.ATo and ATu conceived the study. ATu prepared the tables and figures and wrote the manuscript. ATo and OD participated in final manuscript design, and provided experts' opinion on the content and critical revision.ATu is affiliated with the company SciBerg e.Kfm. ATo is affiliated with the company SRC BioClinicum. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Arabidopsis thaliana (Arabidopsis) and later also found in humans  is a crucial posttranscriptional mechanism of gene expression which promotes transcriptome and proteome diversity. At the molecular level, splicing and AS involves recognition and elimination of intronic regions of a precursor messenger RNA (pre-mRNA) and joining of exonic regions to generate the mature mRNA. AS generates more than one mRNA transcript (transcripts) differing in coding and/or untranslated regions (UTRs). AS can be classified into four major types including the exon skipping (ES), intron retention (IR), alternative donor (AD), and alternative acceptor (AA), of which IR is the most prevalent event in plants , results in multiple transcripts (SVP1 and SVP3), which encode proteins with altered interaction domains  gene, but only when subjected to drought and heat stress, and results in the production of an alternative transcript which encodes the full-length functional protein that confers tolerance to the stresses  against Tobacco mosaic virus (TMV) is alternatively spliced, resulting in production of two forms—a short and a long transcript . The PTC-containing transcripts are often targeted to degradation by a conserved cytoplasmic RNA degradation mechanism called NMD (non-sense-mediated mRNA decay). NMD mechanisms ensure that there is a balance or homeostasis in the functional vs. non-functional transcripts  and long read (Pacific Biosciences and Oxford Nanopore) sequencing technologies have revolutionized the field of DNA and RNA sequencing. Specifically, short read (<300 bp) RNA-sequencing (ShR RNA-seq), which integrates qualitative (gene discovery) and quantitative (gene quantification) assays, became a popular tool for genome-wide AS identification in plants as well as in other organisms. Because ShR RNA-seq provides high sequencing depth, a low error rate (<1%) and relatively-lower cost, it has been extensively used to characterize and quantify spliced transcripts in well-annotated plant genomes such as Despite the advances in ShR RNA-seq for AS discovery, this technology has limited scope in polyploids plant species  without reference genomes or those lacking comprehensive transcript-level annotations. To overcome this limitation, long read RNA-sequencing (LoR RNA-seq) technologies such as Pacific Biosciences (SMRT sequencing) and Oxford Nanopore (MinION) which has the ability to sequence full-length transcripts and direct RNA sequencing, have been used to study complex AS landscapes in polyploids , cloning and Sanger-based sequencing are widely used approaches to confirm the presence and the sequence of the alternatively spliced transcripts  using stable or transient plant transformations, followed by evaluation of the trait of interest. Biochemical experiments to decipher the encoded protein localization, protein-protein, and protein-RNA interactions can also provide mechanistic insights into the functions of the alternatively spliced transcripts (Dinesh-Kumar and Baker, In the past few years, HTS technologies has unraveled the breadth of AS that is occurring in plants (Shen et al., RB, SI, EP, and KM designed the study and prepared the manuscript for submission. All authors have read and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Caenorhabditis elegans, environmental double-stranded RNA provided by feeding can lead to heritable changes in phenotype and gene expression. Notably, transmission efficiency differs between the male and female germline, yet the underlying mechanisms remain elusive. Here we use high-throughput sequencing of dissected gonads to quantify sex-specific endogenous piRNAs, miRNAs and siRNAs in the C. elegans germline and the somatic gonad. We identify genes with exceptionally high levels of secondary 22G RNAs that are associated with low mRNA expression, a signature compatible with silencing. We further demonstrate that contrary to the hermaphrodite germline, the male germline, but not male soma, is resistant to environmental RNAi triggers provided by feeding, in line with previous work. This sex-difference in silencing efficacy is associated with lower levels of gonadal RNAi amplification products. Moreover, this tissue- and sex-specific RNAi resistance is regulated by the germline, since mutant males with a feminized germline are RNAi sensitive. This study provides important sex- and tissue-specific expression data of miRNA, piRNA and siRNA as well as mechanistic insights into sex-differences of gene regulation in response to environmental cues.RNA interference (RNAi) related pathways are essential for germline development and fertility in metazoa and can contribute to inter- and trans-generational inheritance. In the nematode  Caenorhabditis elegans to show that the female and male germline react differently to the presence of such an environmental factor that may affect transmission to following generations. Sequencing of gonadal small RNA suggests that the underlying sex-differences affect downstream processing but not uptake. Furthermore, we describe the naturally occurring small RNA populations of female and male gonads and use genetic mutants to assign small RNAs to the two tissues of the gonad, namely the somatic gonad or the germline. These sex-and tissue-specific small RNA expression data provide an important resource for future research. In addition, this work reveals mechanistic insights into sex-differences in response to environmental cues.Environmental factors such as heat or pathogens influence living organisms, and in some cases these experiences can be passed on to the next generation. One such environmental factor is double stranded RNA that can be taken up by some animals and induce changes in gene expression via small RNA mediated silencing. Here, we use the roundworm  The environment can induce changes in phenotype and gene expression that persist across multiple generations ) called fog-3 or ‘feminized male’ for clarity) ) I/ hT2[qIs48]  (kind gift from Scott Aoki and Judith Kimble) and fem-3(q96) IV [mjIs145 [mex-5p::GFP::his-58::21UR-1sense::tbb-2 3'UTR] II ([adIs2122 [lgg-1p::GFP::lgg-1 3’UTR + rol-6(su1006)] [zuIs178 [his-72p::his-72::GFP:his-72 3’UTR] ( II ] ; Fig 4C) 3’UTR]  by PCR . him-8(egfp(RNAi) experiments were carried out with a construct targeting the full gfp coding sequence including three introns. The recoded gfp(RNAi) with SNP every 21 nucleotides targets only exons and was synthesized by Integrated DNA Technologies and cloned into the L4440 plasmid. Silencing efficiency of recoded gfp(RNAi) is slightly reduced compared to full length gfp(RNAi), which may be caused by SNPs or lacking introns.RNAi feeding plates where prepared from freshly streaked HT115 bacteria containing L4440 vector according to . Those wRNAi silencing was scored in live adults mounted on slides with reaction wells (Paul Marienfeld) using 20x or 40x objective on a Zeiss Axio Scope.A1 microscope. Worms scored as RNAi sensitive on a binary scale if GFP-sensor was absent or greatly diminished as compared to animals treated with empty vector RNAi. Differential interference contrast (DIC) and fluorescence images were acquired on a Axiocam 506 mono CCD camera and processed with Fiji software . OutlineBleach-synchronized L1 worms were grown on RNAi bacteria 48h at 20°C until L4/ young adult, then washed 5 times in 15mL M9 to remove bacteria and grown overnight at 20°C on OP50 bacteria. Prior dissection, adults were picked on empty plates and transferred in groups of 3–4 in a drop of 0.01% levamisole + sperm buffer  to wash fog-3 males (each 200) were processed as independent replicates for sequencing as follows  samples): hermaphrodites , males  and fog-3 males . Since endogenous siRNAs levels were not different from germlines treated with or without gfp(RNAi), both were used for sex-biased expression analysis.Gonads from hermphrodites (100), males or RNA was extracted with 1 ml of TRIzol according to manufactor’s protocol. Briefly, RNA was precipitated adding 1 volume of isopropanol and 20 μg glycogen (Roche). Samples forming a white precipitate at this point were cleared by addition of 500 μL isopropanol: water 50% (v/v). Samples were frozen at -80°C, thawed on ice and RNA was pelleted by centrifugation for 30 min at +4°C, 16000 g. The pellet was washed in ice cold 70% (v/v) ethanol and recovered by centrifugation for 20 min at +4°C, 16000 g and finally resuspended in 10 μL water. RNA concentration was determined by Qubit RNA BR Assay Kit (Thermo Fisher).For RNA dephosphorylation 400 ng of RNA were treated with 20 Units of 5’ polyphosphatase (Epicenter) in 20 μL reaction volume, purified using acid-phenol-chloroform, pH 4.5 (Thermo Fisher) and isopropanol precipitated using 20 μg of glycogen. Subsequently, RNA was suspended in 6 μL water and directly used for TruSeq Small RNA library kit (Illumina) following the manufacturer’s instructions with exception that 15 cycles of PCR amplification were used. The cDNA libraries were separated on 6% TBE PAGE gels (Life Technologies) and bands with 147–157 nucleotides were cut from the gel. The gel matrix was broken by centrifugation through gel breaker tubes (IST Engineering Inc.) and size-selected cDNA eluted with 400 μl of 0.3M Na-Chloride. cDNA was purified by centrifugation through Spin-X 0.22μm cellulose acetate filter columns (Costar) followed by isopropanol precipitation. Libraries were sequenced on a HiSeq 1500 Sequencer (Illumina).https://basespace.illumina.com/ as fastq files after demultiplexing. Sequencing data is available in the European Nucleotide Archive under accession number PRJEB12010 . Seventhly, the remaining reads were aligned with no mismatches to C. elegans genome cel235. Overall, we obtained ~2.3–12.8 million trimmed reads mapping to the genome (WS235) for each sex. endo-siRNAs was quantified per gene, antisense reads mapping to coding exons, which account for more than 96% of reads in this class.Small RNA sequencing results were obtained from JEB12010 . FirstlyC. elegans WS250 genome [Fastq-mcf was used to trim adapters from single-end reads . Bowtie 0 genome . Reads w0 genome . Reads m0 genome . Because0 genome   are highlighted in red  and blue . Related to A) Mean normalized miRNA reads (sense) in hermaphrodite (n = 6 replicates) and male gonads (n = 3). miRNA expression-differences with four-fold difference in abundance that were statistically different  between gonads of hermaphrodites and males as well as between hermaphrodites and (TIF)Click here for additional data file.S2 FigA) Percentage of antisense reads in hermaphrodite and male gonads classified as primary 26G RNA, secondary 22G RNA or other siRNA types. B) Normalized mean 22G RNA reads in hermaphrodite and male gonads per gene, median dotted line, mean full line. C) Mean 22G RNA reads targeting mRNAs of similar abundance in hermaphrodite (red) and male (blue) gonads. Boxes represent first and second quartile, 1.5 interquartile range: vertical line, mean: horizontal line, outliers: circles. Bonferroni corrected p-value of Wilcoxon rank sum test give the probability that samples from a continuous distribution have equal medians.(TIF)Click here for additional data file.S3 FigA) Mean normalized mRNA reads  and siRN(TIF)Click here for additional data file.S4 Figfog-3 males (n = 2), control hermaphrodites (n = 4) and control males (n = 2) raised on gfp(RNAi). Data for control hermaphrodites and control males are taken from Mean primary and secondary siRNA reads normalized to total reads in gonads from (TIF)Click here for additional data file.S5 Fig(gfp)RNAi or control RNAi. Percentage of animals with germline expression classified as: high, intermediate uniform, intermediate variable and no GFP-sensor expression (from bottom to top) for (gfp)RNAi (n = 27). 100% of animals raised on control RNAi showed high GFP-sensor expression (n = 24). B) Fluorescence microscopy images of sperm chromatin marked with a ubiquitous GFP-sensor in adult hermaphrodites, males and fem-3 hermaphrodites producing only sperm (top). Partial silencing of the GFP-sensor upon gfp(RNAi) at 24°C in control and fem-3 hermaphrodites, while control male germlines are RNAi resistant (bottom). Images were acquired with the same exposure time in control and RNAi condition, but are different between sexes due to different expression levels and physiology. For illustration purposes images are background subtracted, as explained in A) Fluorescence microscopy images of GFP-sensor expression of L4 hermaphrodite germlines ; animals fed (TIF)Click here for additional data file.S1 TableAnalyses of sex-biased miRNA, piRNA, germline siRNA, sense and antisense reads.(XLSX)Click here for additional data file.S2 TableWormExp input and output.(XLSX)Click here for additional data file.S3 TableExpression levels of 22G RNA and mRNA and classification as WAGO, WAGO-1, CSR-1, ALG-3/-4.(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 TableAccession and genotype of each replicate.(XLSX)Click here for additional data file.


Adenosine-to-Inosine (A-to-I) RNA editing is the most prevalent post-transcriptional modification of RNA molecules. Researchers have attempted to find reliable RNA editing using next generation sequencing (NGS) data. However, most of these attempts suffered from a high rate of false positives, and they did not consider the clinical relevance of the identified RNA editing, for example, in disease progression. We devised an effective RNA-editing discovery pipeline called CREDO, which includes novel statistical filtering modules based on integration of DNA- and RNA-seq data from matched tumor-normal tissues. CREDO was compared with three other RNA-editing discovery pipelines and found to give significantly fewer false positives. Application of CREDO to breast cancer data from the Cancer Genome Atlas (TCGA) project discovered highly confident RNA editing with clinical relevance to cancer progression in terms of patient survival. RNA-editing detection using DNA- and RNA-seq data from matched tumor-normal tissues should be more routinely performed as multiple omics data are becoming commonly available from each patient sample. We believe CREDO is an effective and reliable tool for this problem. A-to-I RNA editing, i.e., conversion of adenosine (A) to inosine (I), is most prevalent events; inosine is interpreted as guanosine (G) by reverse transcription and the translational machinery, so A-to-I editing is also known as A-to-G editing. Studies have been performed to discover the pathological relationship between RNA editing and diseases. It was reported that aberrant ADAR, a family of RNA’s adenosine to inosine editing enzymes, regulation and aberrant RNA-editing profiles are associated with many diseases including neurological disorders and cancers8. It was also reported that changing a single RNA editing level can drive cancer progression3. Sagredo et al. showed that RNA editing in 3′ UTRs and exonic regions are increased in breast cancer cells compared to immortalized non-malignant cells, and high-level of ADAR1 expression was associated with worse clinical outcome and increased editing in 3′UTRs9. It is also previously shown that RNA editing and ADAR expression are significantly altered in most cancer types and increased editing activity is associated with patient survival10.Post-transcriptional modifications are essential for normal gene expression and tissue development. RNA editing, i.e., base conversion, insertion, or deletion of RNA molecules, is one of the most prevalent of such modifications; it plays crucial roles in fine-tuning gene expression and provides the diversity of the transcriptomeThus RNA-editing loci could be promising therapeutic targets. However, most of these functional studies were limited to individual RNA-editing events. Identification of RNA editing at the global transcriptomic level should broaden our insights to the post-transcriptional modification landscape and its pathological relevance to disease development. Therefore, an effective RNA-editing discovery in diseases should comprise a highly confident RNA editing identification and an investigation of pathological or clinical relevance of the spotted candidate RNA-editing events.15. Because of the high statistical noise in NGS data and the incidental and potentially mosaic RNA-editing event, i.e. occurring in a subset of cell in specific individuals, identification of RNA-editing loci at transcriptomic level is highly susceptible to numerous false positives19. Many studies have often focused on single samples, so it is unclear whether the identified editing events are individual-specific or prevalent in the general population. Furthermore, the majority of the identified editing loci were in noncoding and repetitive-element regions without obvious functional relevance.Advances of next generation sequencing (NGS) allows discovery of RNA-editing events at global transcriptomic level and several RNA editing discovery methods have been developedet al. developed an approach that can identify genomic variants reliably from RNA-seq. They identified genomic variants from RNA-seq data proposing a modified mapping procedure that can avoid misalignment of split reads and a variant filtering process that can prune spurious variants called in error-prone regions, repeated region, splice sites, homopolymer runs, etc.20. However, Hsiao et al. showed that the vast majority of RNA editing occurs co-transcriptionally prior to polyadenylation in human cells. It proposes the hypothesis that many RNA editing events may alter splicing by changing sequences on the splicing sites or by ADAR’s interaction with dsRNA structure21. They claim that the RNA editing in splice regions plays a crucial role in RNA maturation and splicing process. Hard filtering of RNA editing in splice regions can lose this important information.Piskol et al. did an impressive work on RNA editing using extensive cancer sample data from the TCGA project22. Some functional and clinical analyses were performed for the identified RNA-editing events among various cancer samples. A number of RNA-editing events showed significant functional and clinical relevance in some cancer sites. However, they only attempted to find informative RNA-editing events from previously reported editing sites (in RADAR)14 rather than to identify novel disease-specific RNA-editing events. In addition, they did not find any RNA-editing events relevant to disease progression in breast cancer.Recently, Han We developed an effective pipeline called CREDO with novel statistical modules that capture highly confident RNA-editing events in the TCGA breast-cancer samples. When compared to three other RNA-editing identification pipelines CREDO produced significantly fewer false positives as measured by the occurrence in the dbSNP database. Furthermore, CREDO discovered highly confident RNA-editing loci that were recurrent in multiple samples and clinically associated with breast-cancer patient survival.23. Raw sequencing data in FASTQ/bam format and clinical data of these patients were obtained from the TCGA data portal. The sequencing data can be downloaded from TCGA Data Portal .A total of 60 breast cancer patients that have both Exome-seq and RNA-seq from normal and tumor matched samples were chosen in the TCGA breast cancer database24, Galaxy25).CREDO RNA editing discovery pipeline is outlined in Fig. 26. Duplicate reads were marked and removed to reduce bias from library preparation, e.g., PCR artifact (Picard)27. Insertion and deletion (indels) in an individual’s genome compared against the reference genome causes many mismatches around them and may mislead variants discovery. Therefore, the reads around indels were realigned locally . Variants are identified based on base quality scores. The scores produced by the machine are distorted by various sources of systematic technical errors. So, base quality scores are adjusted before variant calling using GATK BaseRecalibrator (the dbSNP build 138 and 1000-genome gold standard indels were used). DNA variants were identified and filtered by GATK HaplotypeCaller. Confident DNA variants were called by setting “stand_call_conf” to 30.0 and “stand_emit_conf” to 10.0. Obtained variants were recalibrated through GATK variant recalibration tool . It develops a covariance model between SNP call annotations  and the probability that a SNP is a true genetic variant versus a sequencing or data processing artifact. The SNPs from Hapmap Project 3 and 1000 genome Omni 2.5 M SNP chips were used as true sites. It uses the covariance model built based on the true SNP sites and assign new variant quality scores. Only high-quality A-to-G homozygous DNA variants supported by more than 4 mapped reads and calling quality ≥50 were retained for further analyses.High quality reads were mapped to the reference genome (GRCh37) by BWA allowing 3 edit distance29, we employed two of the best performing aligners (STAR30 and TopHat31) in order to overcome the shortcomings of each aligner. Maximum 3 mismatches (STAR) and 3-base edit distance (TopHat) were allowed in the mapping. After mapping, duplicate reads were marked and removed as in the previous section. For the following process, reads marked with ‘N’ symbol were removed, and overhanging regions into the intronic regions were hard-clipped to avoid the pitfalls caused by these artifacts (GATK Split ‘N’Trim). Base quality scores were recalibrated . Mapped reads from both aligners were combined as follows. The read mapped only by an aligner on unique genomic location was retained. The best-scored read was retained when there are identical reads mapped on the same genomic location by both aligners. The highest-scored read out of the same reads mapped on different genomic loci by different aligners was retained. After combining information from the two aligners, the number of reads mapped on each genomic location was computed . Only the loci that have adenosine (A) reference base and one alternative allele (guanine (G)) were kept. The loci with more than 4 read count and moderate strand bias  were retained. For RNA-seq and DNA-seq, the read count of each site was calculated using samtools and VarScan with minimum base quality 25.Since different RNA-seq aligners may produce different mapping resultsFor each individual, high-quality DNA A-to-G variants and the RNA A-to-G loci from Exome-seq and RNA-seq analysis were acquired, respectively, in normal and tumor matched samples separately. To be a true editing event, an A-to-G locus must be specific to the RNA-seq and not in the DNA-seq data. In order to impose this specificity, the loci that were found as DNA A-to-G variants were pruned from the A-to-G loci captured in RNA-seq analysis in the same sample.n reads. Intuitively our confidence should be lower when n is small compared to when n is large. More generally, to account for possible sequencing errors, the filter must also allow for small number of alternative G alleles out of n reads (i.e. we do not impose exact zeroes). We thus define the zero-confidence score as −10*log10(U), where U is 100(1 − α)% upper-confidence bound of the probability of success based on observing x successes out of n Bernoulli trials; see Pawitan34, Section 5.8. Higher scores mean higher confidence, as typically the case if we observe zero alternative G alleles from larger number of reads. For example, using α = 0.05, if we observe zero alternative G alleles out of n = 5, 10 and 30 reads, the scores are, respectively, equal to 3.46, 5.87 and 10.22. The value α = 0.05 and zero-confidence score cutoff of 10 were applied to retain high-confidence RNA A-to-G editing candidate loci.Many DNA loci corresponding to their RNA A-to-G loci have a low number of alternative G reads simply because the total number of reads is too small. These loci will produce false-positive editing sites. The zero-confidence score measures the statistical confidence in a locus with zero alternative G alleles out of Comparison of the reads statistics from matched tumor and normal samples allows identification of tumor-specific or normal-specific editing events. Odds ratio (OR) and Fisher Exact test p-value between normal and tumor matched samples for a site in an individual were calculated from the 2 by 2 table as described in Fig. 36, highlighting the common views that they tend to be false positives. However, there are also known editing sites in dbSNP, though they are too few to affect its use as negative controls37. So, while we use dbSNP sites to assess false positive rates, for our final candidates we do not rule out dbSNP-sites, as there are possible errors in the dbSNP database38.Having RNA and DNA sequencing with very high coverage or PCR based confirmation on the same samples is desirable to estimate the reliability of the discovered editing loci. But, in practice, it is impossible to perform these kinds of validation due to unavailability of the identical samples. A priori we do not expect an editing event to occur in previously known SNPs, so we can use SNPs in the dbSNP database (build 151) as negative controls. Moreover, identified A-to-G editing loci that coincide with SNP positions are likely to be DNA variants that have been missed in the variant calling step of the DNA-seq data analysis. In practice we use the dbSNP database as negative controls: a good discovery set should have fewer editing sites within the dbSNP database. In fact dbSNP positions are normally filtered out by some RNA-editing pipelinesWe now describe the results of our analysis of the TCGA breast-cancer matched samples. In total, taken from 60 individuals, 2,967,207 candidate loci (zero-confidence score ≥ 10.0 in both matched samples), only 408,614 loci (13.7%) were still present in dbSNP. An illustration showing the effectiveness of the zero-confidence filter is given by the scatter plots in Fig. A total of 20,168 highly confident A-to-G sites  were identified from the 60 individuals; 82.5% of these loci were not in dbSNP. The number of A-to-G loci discovered from the whole analysis pipeline is shown in Fig. We next checked if the edited loci are supported by differential expression of ADAR genes which produce the RNA editing enzymes. For each identified site, samples were divided into ‘edited’ and ‘non-edited’ groups. Then, the expression difference of ADAR genes between tumor and normal samples of the ‘edited’ group was measured for each edited loci. In total 210 editing loci out of 439 highly recurrent loci Fig.  were fou36 using the defaults filters. In contrast to CREDO, they were designed to identify RNA-editing loci in single samples without matched sample, i.e., normal and tumor samples from identical individual. To make all the methods comparable to each other, CREDO was redesigned to identify RNA editing loci in single sample. For each candidate site, a 2 × 2 table of the number of reference (Adenine) and alternative (Guanine) alleles based on the RNA and DNA sequences from an individual was used to compute odds-ratio (OR) and Fisher Exact test statistics . The RNA-editing candidates with confidence-zero score on their DNA read counts at least 10.0, and OR among RNA and DNA read counts of 2.0 were judged as confident editing loci in CREDO; see the Methods and Materials section. The other steps before the confidence-zero and OR filters in Fig. False-positive pruning capability is indispensable in RNA-editing discovery because of the genome-wide high-throughput and high-noise nature that makes it susceptible to false positives. In particular, an effective RNA-editing discovery pipeline should be able to discriminate true RNA modifications, which are true positives, from those caused by DNA-level heterozygosity, which are false positives. This problem occurs because heterozygosity calls depend on sufficient reads coverage of the potential editing site in the DNA-sequence data, but inherent non-uniformities in reads coverage make this hard to achieve genome-wide. CREDO was compared with three other methodsAs summarized in Fig. 38.) These identified A-to-G editing loci reside in the genes closely related with immune systems. Table 40. NCSTN was found to be a tumor suppressor in NOTCH pathway41, and PIK3R2 participates in PI3K/AKT pathway which is most commonly dysregulated in many human cancers42. On the other hand, the loci in Table Tables Kaplan-Meier estimate (KM) was used to assess the clinical relevance of RNA editing on disease progression in terms of patient survival. First, for each editing site, an individual is categorized as ‘edited’ if the site is identified as both high-confidence and ADAR-DE; as described above, there are 210 such sites. A total of 34 confident A-to-G editing loci were found to be associated with patient survival .Figure 43; to increase confidence in the mutation calls, we remove all singleton calls, so each mutation in further analysis is recurrent in at least two individuals. There were no mutations observed in the IGKV.1 and ZNF747 genes, and only two mutations in IGKV2.30. The FN1 gene, however, is frequently mutated, seen in 413 (38%) of the cohort. Figure Since there is no comparable external data on RNA editing, we instead consider the impact of DNA mutations in these genes among 1080 subjects with breast cancer in the TCGA database. We hypothesize that DNA mutations in these genes would be associated with poor survival. Mutation calls are provided in the TCGA project based on the Mutect algorithmIdentification of reliable RNA editing events relevant to disease development is an important and difficult problem. Most of existing approaches is susceptible to high false positives due to numerous technical and biological noises in NGS library preparation, reads mapping, or the mosaic nature of RNA editing itself. We have developed CREDO, an NGS analysis pipeline with novel statistical modules, which integrate DNA- and RNA-seq data from matched normal and tumor tissues from multiple individuals to discover highly confident and reproducible disease-relevant RNA editing loci. The pipeline successfully removed vast majority of false positives, e.g. most of the candidate loci found in the dbSNP database were filtered out without using information from the database itself. CREDO outperformed three other RNA-editing identification pipelines by pruning significantly more false positives.9. An important role of ADAR1 expression and its function, and the significant association between the RNA editing in genes related to cancer-relevant pathways and clinical outcomes were also previously confirmed10. CREDO discovered A-to-G loci that are potentially related with breast cancer development. Some identified RNA-editing loci were found to be differentially expressed in ADAR genes and associated with worse survival. The top 4 editing sites comprise 27% of the subjects, so editing with potential clinical relevance is not a rare event. Because deleterious RNA-editing is biologically similar to deleterious DNA-mutations, we validated the clinical relevance of RNA editing in FN1 gene by showing that subjects with FN1-mutation have significantly worse survival compared to those with no mutation. Among the 1080 TCGA breast-cancer cases, there was little or no DNA mutations in IGKV2.30, IGKV.1 or ZNF747 genes. So, intriguingly for these genes, we might have a deleterious event at purely RNA-level. The FN1 and ZNF737 genes are relatively well-known cancer-related genes. Both were found to be overexpressed in aggressive cancer cells46. FN1 is known to be overexpressed in aggressive thyroid cancer, and silencing of FN1 expression significantly reduced proliferation, adhesion, migration, and invasion in thyroid cancer cells44. FN1 was found overexpressed also in renal cancer cells and reported as a determinant for renal cancer aggressiveness45.Basal-like subtype breast-cancer patients with high-level ADAR1 expression had been shown to have more RNA editing and worse clinical outcome47.CREDO outperformed the other approaches in RNA editing discovery with more editing events and far less false positive rates. In addition, reproducibility and clinical relevance of identified editing events was previously not assessed due to limited focus on a single normal sample. The main strengths of CREDO include the integration of DNA-seq and RNA-seq data from multiple matched tumor-normal pairs, and the use of stringent statistical filters such as zero-confidence and recurrence filters. Without the DNA-seq data from normal tissue, we cannot rule out individual/rare A-to-G SNPs explaining the RNA A-to-G variants. Most of the previous studies have focused on single samples using normal tissues. Recurrence over multiple samples greatly improves the statistical confidence in an editing event and reduces false positive events. The use of tumor tissues allows identification of tumor-specific editing events, which have higher likelihood of being clinically relevant. As the main weakness, our clinical validation results are based on a small sample size. At present, even for a large project such as the TCGA, there are still few samples with complete DNA- and RNA-seq data from the matched tumor-normal pairs. However, this problem is getting continually addressed as the value of having multiple omics from each patient sample is more recognized, so we can expect larger samples in future studiesSupplementary file


Human telomerase RNA (hTR) is transcribed as a precursor that is then posttranscriptionally modified and processed. A fraction of the transcripts is oligoadenylated by TRAMP and either processed into the mature hTR or degraded by the exosome. Here, we characterize the processing of 3′ extended forms of varying length by PARN and RRP6. We show that tertiary RNA interactions unique to the longer transcripts favor RNA degradation, whereas H/ACA RNP assembly stimulates productive processing. Interestingly, the H/ACA complex actively promotes processing in addition to protecting the mature 3′ end. Processing occurs in two steps with longer forms first being trimmed by RRP6 and shorter forms then being processed by PARN. These results reveal how RNA structure and RNP assembly affect the kinetics of processing and degradation and ultimately determine the amount of functional telomerase produced in cells. Telomerase RNA (hTR) is transcribed as a 3′-extended precursor. Here the authors examine the processing of hTR precursors of various lengths and show that processing occurs in distinct steps involving different nucleases PARN and RRP6. In addition to providing the template for telomerase repeats, TR acts as a scaffold for the assembly of protein components that are part of the holoenzyme.The catalytic protein subunit telomerase reverse transcriptase (TERT) and the RNA component telomerase RNA (TR) form the core of the telomerase enzyme. TERT reiteratively copies the template region of TR onto the chromosome ends to replenish terminal DNA repeats lost during DNA replication2. The 3′ half of hTR closely resembles a box H/ACA domain3. This structure is composed of two RNA hairpins connected by a single-stranded hinge, referred to as H box (ANANNA). The second hairpin is followed by a 3′ single-stranded tail containing the sequence motif ACA4. Like other H/ACA RNAs, the H/ACA domain of hTR is associated with the four H/ACA box proteins dyskerin, NHP2, NOP10, and GAR13. Mutations in the H/ACA domain of hTR have been identified in patients with dyskeratosis congenita, aplastic anemia, and idiopathic pulmonary fibrosis5. These have been shown to cause defects in processing and localization of RNA, resulting in accelerated telomere shortening7. Similarly, mutations in the protein components that interact with this domain also lead to a reduction in the steady-state level of hTR and are associated with the same spectrum of degenerative syndromes8.At the gross level, human telomerase RNA (hTR) can be divided into two domains. The 5′ domain folds into an evolutionarily conserved pseudoknot that harbors the template region and a triple helix structure that contributes to telomerase activity9. In contrast, hTR is transcribed as an independent gene by RNA polymerase II and is subsequently processed into the 451-nt mature form. While the promoter of hTR is well-characterized10, the mechanism of transcription termination and processing remain poorly understood. Several independent studies have demonstrated the existence of hTR transcripts extending beyond the mature end at position 45115. Some 3′-extended forms are only a few nucleotides (nts) longer than the mature hTR, whereas others exceed 1500 nts in length. Their accumulation in cells depleted of the cap-binding complex (CBC), the nuclear exosome targeting complex (NEXT), and the exosome suggests that the long forms are predominantly degraded by this pathway12. Whether a fraction of the long transcripts is converted into shorter intermediates or whether short primary transcripts are also generated has remained unclear.In vertebrates, H/ACA snoRNAs are typically encoded within introns, and mature via splicing, intron debranching, and exonucleolytic processing18. Cells from patients with mutations in PARN have short telomeres and reduced levels of hTR20. Oligo-adenylated hTR that extends beyond the mature 3′ end by a few nucleotides was found to be increased in these cells19. Oligo-adenylation is predominantly mediated by PAPD5 (TRF4-2), a non-canonical poly-A polymerase that is a component of the TRAMP complex21. Oligo-adenylation of some RNAs by TRAMP stimulates degradation by the exosome23. This has led to a model in which PARN antagonizes degradation by removing oligo (A) tails from hTR. Whether PARN or another nuclease trims hTR to position 451 has remained controversial. To address this issue and to elucidate which factors determine whether an hTR precursor RNA is acted upon by PARN or the exosome, we conducted a series of experiments to examine the processing of RNAs of varying lengths. These studies establish direct roles for PARN and RRP6 in hTR processing, reveal a novel function for the H/ACA complex in promoting processing, and identify a role for a triple helix structure in competing with ribonucleoprotein complex (RNP) assembly.A key insight into hTR processing came from genetic studies linking poly(A)-specific ribonuclease (PARN) to telomere dysfunction in patients with dyskeratosis congenita20. As these length-specific phenotypes suggested the existence of functionally distinct RNA isoforms, we will henceforth refer to hTR molecules that terminate between positions 452 and 460 as the 3′-extended short (exS) form and those molecules that terminate beyond position 460 as the 3′-extended long (exL) form. Whereas RRP6 appears to primarily act on the exL forms, PARN seems to function either by antagonizing degradation of oligo-adenylated exS or by actively processing exS into the mature form.To assess the fate of 3′-extended forms of hTR, we depleted PARN, the exosome-associated nuclease RRP6, and the core exosomal component RRP40, respectively, from cultured cells  sequences were efficiently trimmed from all RNA substrates  and the exL (460) forms both terminate in two uridines. The sequences diverge only further upstream: (456-CGC-458) in exL and (451-CAG-453) in exS. To determine whether GC-rich sequence inhibits PARN, we introduced A452C, A452G, and G450A mutations into exS substrates  over oligo (U), with oligo (C) and oligo (G) being even poorer substratestes Fig.  and 2c. Although in vitro processing assays revealed pronounced effects of sequence on PARN processivity, little attenuation was observed at the position of the mature 3′ end Fig. . ClearlyAs binding of the H/ACA complex is critical for hTR stability in vivo, we next asked whether this complex was responsible for attenuating PARN at position 451 in vitro. Following incubation of mature, exS and exL in extracts on ice, all forms of wild-type but not C408G mutant hTR were recovered by immunoprecipitation with anti-DKC1 Fig. . ConsistRecombinant PARN alone failed to degrade exL oligonucleotides Fig. . Similar29. To examine the effect of H/ACA RNP assembly on exL processing, oligo-adenylated exL (nucleotides 206–461+5A) was incubated in the siRNA-control and dyskerin knockdown extracts, respectively  to C–G●C, providing an additional hydrogen bond  tails. Nevertheless, in the absence of PARN, processing of exS into mature hTR is inefficient  analysis of yeast exosome components revealed substrates only enriched in the Rrp6 data set32. For example, truncated 18s rRNA transcripts appear to be degraded in a process that involves Trf4 and Rrp6, but not the core exosome32. In the context of TR, it is tempting to speculate that exL processing may be carried out by RRP6 alone, whereas degradation involves the entire exosome. Consistent with this idea, reverse transcription quantitative polymerase chain reaction (RT-qPCR) of hTR implicated the core exosome (RRP40) and its two associated exonucleases, RRP6 and RRP44/DIS3, in the turnover of hTR extending by at least 50 nts beyond the mature 3′ end12. In one study, knockdown of RRP40 stabilized 3′ extended hTR sixfold more than knockdown of RRP6. The implication of the NEXT complex in the turnover of longer forms of hTR12 supports the idea that degradation occurs via NEXT targeting the exosome to hTR, whereas processing may involve RRP6 alone or in complex with other factors.Another area in need of further investigation is the mechanism and sites of transcription termination. Intriguingly, examination of processing intermediates that accumulate in cells after siRNA knockdowns revealed that 3′ end processing proceeds in at least two distinct steps Fig. . First, 33. They have been found in diverse functional contexts. For instance, the catalytic activity of telomerase depends on a triple helix in the pseudoknot domain of hTR34. Furthermore, a triple helix in the SAM-II riboswitch creates a binding pocket for S-adenosylmethionine35, and triple helix structures have also been implicated in protecting 3′ ends of RNAs from exonucleolytic degradation. In the case of the Kaposi’s sarcoma-associated herpes virus polyadenylated nuclear RNA, a protective triple helix involves the poly(A) tail36. In MALAT1 RNA, a triple helix structure involving the non-polyadenylated 3′ end increases RNA stability and stimulates translation38. The tertiary RNA interactions involving the 3′ end of hTR exL, the H box, and an internal loop sequence does not fit into any of these functional paradigms. Although the structure inhibits rapid nuclear RNA decay as shown for the analogous structure in MALAT1, its presence in hTR is ultimately in direct competition with canonical processing. Functionally, it appears that the structure transiently protects exL from rapid degradation and creates a window of opportunity for the H/ACA complex to bind and remove the triple helix in the process. Consistent with dyskerin binding resolving the triple helix structure, exL has a notably longer half-life in extracts from dyskerin-depleted cells than exS or the mature form  and 250 nM unlabeled hTR RNA oligo were incubated with the indicated concentrations of recombinant PARN  in a buffer containing 20 mM Tris-HCl (pH 7.5), 50 mM KCl, 2.5 mM MgCl2, 50 µg ml−1 BSA (NEB), and 40 U RNasin plus RNase inhibitor (Promega). A 10-µl reaction mixture was incubated at 37 °C for 30 min, and the reaction was stopped by the addition of 2× RNA loading dye containing 99% formamide, 0.025% xylene cyanol, 0.025% bromophenol blue, and 0.1 mM EDTA. The samples (5 µl) were separated on 20% denaturing acrylamide sequencing gels containing 7 M urea at 80 W for 3 h for long hTR RNA oligos and 1.5 h for short hTR oligos. RNA oligos used for in vitro deadenylation assays are listed in Supplementary Tables Trace amounts of 5′-32P-UTP , 1 µg DNA template, 40 U RNasin plus RNase inhibitor (Promega), and 20 units T7 RNA polymerase (Promega). Reaction mixtures (10 µl) were incubated at 37 °C for 2 h followed by the addition of an equal volume of formamide dye. Full-length RNA products were purified on 8% polyacrylamide/8 M urea gels. Primers used to generate DNA templates are listed in Supplementary Table In vitro transcription reactions were carried out in 1× transcription buffer (Promega), 0.5 mM each for ATP, CTP, and GTP, 0.1 mM UTP, 0.66 µM α-2, 50 µg ml−1 BSA (NEB), 40 U RNasin plus RNase inhibitor (Promega), 2 nM 32P-labeled hTR RNA, and either indicated amounts of recombinant PARN or 20 µg of whole cell extract, or both. Reactions were stopped by the addition of 10 µl stop buffer  and incubation at 37 °C for 20 min followed by extraction with phenol/chloroform pre-equilibrated with 50 mM NaOAc (pH 5.0), and ethanol precipitation. RNA was dissolved in 70% formamide dye and analyzed on 6% polyacrylamide (19:1) gels containing 8 M urea.In vitro hTR processing reactions (10 µl) were carried out at 37 °C in a buffer containing 20 mM Tris-HCl (pH 7.5), 50 mM KCl, 2.5 mM MgClA fragment of DNA containing 1.5 kb upstream and 2 kb downstream of the major transcription start site of hTR was cloned into pACGFP1-1 using XhoI and BamH1 sites; this plasmid was named pMG80. Mutations were introduced using QuikChange II XL Site-Directed Mutagenesis Kit (Agilent). Oligonucleotides used for site-directed mutagenesis are listed in Supplementary Table ® CCL-75.1™) were cultured in E-MEM medium  supplemented with 10% fetal bovine serum (Sigma-Aldrich) at 37 °C, 5% CO2. Cells were transfected with 12 µg of plasmids using Fugene HD (Promega) for 72 h. Plasmids used for transfection are listed in Supplementary Table 2. 293 T cells (ATCC® CRL-3216™) were cultured in DMEM medium  containing 10% fetal bovine serum (Sigma-Aldrich) at 37 °C, 5% CO2. HeLa or 293T cells were treated with 20 nM or 40 nM siRNA for 72 h using Dharmafect I (Dharmacon). siRNAs used in this study are listed in Supplementary Table WI-38 VA-13 subline 2RA cells , 0.78% β-mercaptoethanol (v/v) (J.T. Baker), and 4% SDS. Protein lysate was loaded onto a 4–12% Bis-Tris protein gel (Invitrogen) and transferred to a nitrocellulose blotting membrane , Low-fat milk (5%) in TBS buffer was used as a blocking reagent. Antibodies used in this study are listed in Supplementary Table 32P-α-dCTP) and 42 °C . Oligonucleotide sequences are listed in Supplementary Table Cells were collected in Trizol reagent  according to the manufacturer’s instructions, followed by treatment with DNase I (New England Biolabs) at 37 °C for 30 min. Total RNA was extracted once with phenol/chloroform equilibrated with 50 mM NaOAc (pH 5.0), then ethanol precipitated. RNA (10 µg) was separated on a 4% polyacrylamide gel containing 8 M urea at 15 W for 1.5 h. RNA was transferred to a hybond-N1 nylon membrane  at 400 mA for 1 h followed by crosslinking in a Stratalinker . Hybridizations were carried out in Church-Gilbert buffer at 65 °C  fragment with 12. Oligonucleotides used for the library preparation are listed in Supplementary Table Library preparation was based on a published protocol32P at the 5′ end using T4 polynucleotide kinase. hTR substrates containing a single 32P-labeled 4sU were produced by ligation of a 3′ fragment to the 3′ end of the in vitro-transcribed 5′ fragment using T4 RNA ligase 2 . A splint DNA oligonucleotide , and 1 unit µl−1 T4 RNA ligase II. The ligated products were gel-purified by electrophoresis on a 6% acrylamide sequencing gel containing 8 M urea.DNA templates for in vitro transcription were generated by PCR. BLoli6336 and BLoli6790 as listed in Supplementary Table 2, 50 µg ml−1 BSA (NEB), and 40 U RNasin plus RNase inhibitor (Promega). The reaction mixture was spread onto a piece of parafilm covering an ice-cold aluminum block. Droplets were UV-irradiated for 20 min at a distance of ~2 cm with a 365-nm UV Lamp . The crosslinking products were analyzed on a 6% acrylamide sequencing gel containing 8 M urea.The 4sU–hTR substrates (6 nM) were incubated at 37 °C for 10 min in buffer containing 20 mM Tris-HCl (pH 7.5), 50 mM KCl, 2.5 mM MgCl32P-labeled oligonucleotide BLoli1915 (ACGTCCCACAGCTCAGGGAAT) or BLoli5880 (GCATGTGTGAGCCGAGTCCTGG) and dNTPs (10 nmol) in 6.5 µl of ddH2O at 65 °C for 5 min and at 55 °C for 2 min. The reaction volume was increased to 10 µl by the addition of RNase inhibitor , dithiothreitol (5 mM), 1× first-strand buffer (Invitrogen), and Superscript III reverse transcriptase . Reaction mixtures were incubated at 55 °C for 60 min and terminated by the addition of an equal volume of formamide dye. Primer extension products were separated on 12% acrylamide sequencing gel containing 8 M urea next to a sequencing ladder as a marker. Sequencing reactions contained the same primer as used for the primer extension, pMG80 as template, and components of the SequenaseTM Version 2.0 DNA Sequencing Kit  as instructed by the manufacturer.The crosslinking products were gel-purified by electrophoresis on a 6% acrylamide sequencing gel containing 8 M urea. The crosslinking sites were mapped by primer extension. Purified RNA was incubated with Further information on experimental design is available in the Supplementary InformationSource Data