R-loops are stable nucleic acid structures that have important physiological functions, but which also pose a significant threat to genomic stability. Increased R-loops cause replication stress and chromosome fragility and have been associated with diseases such as neurodegeneration and cancer. Although excessive R-loops are a feature of cells that are defective in RNA processing, what causes them to form is unclear. Here, we demonstrate that DHX9 (RNA helicase A) promotes the formation of pathological and non-pathological R-loops. In the absence of splicing factors, formation of R-loops correlates with the prolonged association of DHX9 with RNA Polymerase II (RNA Pol II). This leads to the production of DNA–RNA hybrid, which traps RNA Pol II on chromatin with the potential to block DNA replication. Our data provide a molecular mechanism for the formation of R-loops that is relevant to neurodegenerative diseases and cancers in which deregulated RNA processing is a feature. Unresolved R-loops can represent a threat to genome stability. Here the authors reveal that DHX9 helicase can promote R-loop formation in the absence of splicing factors SFPQ and SF3B3. R-loops are found in a broad range of organisms where they function in a variety of cellular processes, including replication of mitochondrial genomes and bacterial plasmids, regulation of chromosome segregation2, and immunoglobulin class-switch recombination3. In mammalian cells R-loops are widespread, occupying as much as 5% of the genome and are enriched at promoter and terminator regions of polyA-dependent genes, suggesting that they might play a role in the regulation of gene expression5. R-loops are also found in rDNA and tRNA genes suggesting that they form during transcription involving RNA Polymerases I, II, or III6.R-loops are generated during transcription when nascent RNA exits RNA polymerase and pairs with its complementary DNA template to form a region of RNA–DNA hybrid and displaced single-stranded DNA (ssDNA)8. Firstly, the displaced single-stranded DNA in R-loops is vulnerable to attack from the APOBEC family of cytosine deaminases which, upon further processing by enzymes of the base excision repair pathway, may lead to the generation of single-stranded DNA breaks9. Secondly, regions of transition from single-strand DNA to double-stranded DNA at the extremities of R-loops can be cleaved by proteins of the nucleotide excision repair pathway, generating double-stranded DNA breaks (dsb)10. Lastly, by impeding the progression of RNA polymerase on DNA, R-loops increase the potential for transcription–replication conflicts (TRC)14. This can lead to stalling and collapse of replication forks and the production of one-ended dsb that are substrates for chromosome translocations16. In humans, increased R-loops are found in a variety of diseases that exhibit genomic instability, including myelodysplastic syndromes17, neurodegenerative diseases19, and cancers such as Ewing’s sarcoma20.However, R-loops can pose a significant threat to genomic stability in a variety of ways22. In both yeast and human cells, defects in these proteins leads to the accumulation of R-loops and increased DNA damage.Given the potential of R-loops to cause genomic instability, the accumulation of these structures in cells must be tightly regulated. Indeed, a variety of proteins have been identified that prevent R-loops from forming. The majority of these are proteins involved in ribonucleoprotein (RNP) biogenesis and pre-mRNA processing, including several splicing factors and components of the THO/TREX complex that couples the maturation and export of pre-mRNA23. Alternatively, helicases including SETX (Sen1 in yeast) and AQR, disassemble R-loops by unwinding RNA–DNA hybrid26. Interestingly, the DNA repair protein BRCA2 also suppresses R-loops by promoting release of RNA Pol II that is paused at a promoter region28. However, it is unclear how these different factors regulate the balance between formation and removal of R-loops to prevent the pathological potential of these stable nucleic acid structures in cells.Several other proteins facilitate the removal of R-loops. RNaseH1, for example, removes R-loops by specifically degrading RNA–DNA hybridAlthough R-loops have been shown to play specific roles in normal physiological processes and to accumulate in cells that are defective in RNA metabolism, it is still unclear what causes R-loops to form and whether this requires the activities of specific proteins. We investigated the role of splicing factors in R-loop-induced replication stress and identified the RNA helicase, DHX9, as a key factor in the generation of R-loops by RNA Polymerase II. Our data shed new light on the mechanism through which R-loops are formed and the important role played by splicing factors to prevent R-loop induced replication stress and genomic instability.29. Among these are members of the Drosophila Behavior and Human Splicing (DBHS) family of proteins, which are found in subnuclear bodies called paraspeckles30. Although DBHS proteins are required for the retention and processing of hyper-edited RNAs, some also play a role in the repair of dsb by homologous recombination and non-homologous end-joining32. We focused on one of these, SFPQ (splicing factor proline and glutamine rich), and found that it promotes genomic stability by preventing the formation of R-loops.An increasing number of proteins that function in RNA metabolism have also been shown to contribute to the maintenance of genomic stabilitySfpq in mice is embryonically lethal33. Accordingly siRNA-mediated knockdown of SFPQ in U2OS cells  RNA–DNA hybrids in vitro38 and hypothesized that if it also unwinds RNA–DNA hybrid in vivo, knockdown of DHX9 should lead to increased R-loop formation. However, when DHX9 was depleted in U2OS cells, we observed no increase in R-loops  analysis at the cus Fig. . This cocus Fig. . Moreoveite Fig. . Hence, ite Fig. , which mΒ-actin locus in control cells. These too were diminished after knockdown of DHX9  and a helicase/ATPase-dead mutant of DHX9 (GFP-DHX9dead) into cells knocked down for the endogenous DHX9 and SFPQ genes. Whereas expression of GFP-DHX9 rescued R-loop formation in siSFPQsiDHX9 double-knockdown cells  is enriched at promoter regions and diminishes towards the 3′ end of the genes, while serine 7 phosphorylation (S7P) remains high throughout transcription. On the other hand, phosphorylation on serine 2 of the CTD (S2P) is low at promoter regions and increases progressively toward the 3′ end of genes44.In cells, binding of splicing factors to pre-mRNA and the removal of introns occurs concurrently with transcription and is coordinated through interactions between the splicing machinery and the carboxy-terminal domain (CTD) of RNA Pol IIWe immunoprecipitated different phosphorylated forms of RNA Pol II and looked for co-precipitation of DHX9. In control cells, DHX9 co-purified primarily with S5P Fig. a and to Β-actin locus confirmed that, in the absence of SFPQ, both DHX9  of DHX9 and RNA Pol II at the HX9 Fig.  and RNA HX9 Fig.  were higHX9 Fig. . These d46. Furthermore, while some R-loops elicit a pathological response in cells, others do not, suggesting that only a subset of R-loops are harmful to cells. The reason for this is not clear.Although defects in pre-mRNA processing leads to the generation of extensive tracts of RNA–DNA hybrids, recent evidence suggests that R-loops, by themselves, do not necessarily cause genomic instabilityΒ-actin coding sequence but also caused RNA Pol II to accumulate at the polyA site of the gene. We speculated that the formation of an extended region of RNA–DNA hybrid might impede the dissociation of RNA Pol II from DNA upon termination. This might also increase the potential for TRC and lead to replication fork collapse and increased DNA breaks.Our experiments revealed that knockdown of SFPQ not only promoted the formation of R-loops across the entire To test this idea, we prepared nuclear extracts from wild-type cells and from cells depleted for SFPQ and SF3B3 and examined the presence of RNA Pol II S2P and DHX9 in the soluble nuclear and insoluble chromatin fractions. Western blot confirmed that in extracts prepared from wild-type cells, RNA Pol II S2P and DHX9 were present in the soluble nuclear fraction Fig. . HoweverInterestingly, R-loops formed upon knockdown of XRN2, which do not impair DNA replication, did not cause retention of RNA Pol II on chromatin Fig. . We suspWe inferred that R-loops formed as a consequence of impaired RNA splicing may involve extensive regions of RNA–DNA hybrids that cause RNA Pol II to be tethered to chromatin where it can block replication and cause genomic instability. R-loops, such as those formed in cells that are depleted of XRN2, which may involve less extensive regions of RNA–DNA hybrid, do not cause retention of RNA Pol II on chromatin and might not lead to the pathological inhibition of DNA replication. Therefore, although pathological and non-pathological R-loops can be formed through a common mechanism involving DHX9, their impact on DNA replication and on genomic instability is probably context-dependent and might also be influenced by other factors.3. Our work has now identified DHX9 as a key protein that is required for the formation of, at least, some R-loops and revealed how components of the splicing machinery prevent R-loops from forming by modulating the activity of DHX9 during transcription.Although R-loops are required for normal physiological processes, very little is known about how and why they are generated. The demonstration by others that proteins involved in RNA splicing and biogenesis of RNP can suppress R-loop formation established an important link between the generation of R-loops and co-transcriptional processing of pre-mRNAWe have shown that DHX9 is required for the formation of R-loops in cells that are defective in splicing factors SF3B3 and SFPQ as well as those treated with the spliceosome inhibitor Pla-B. In the absence of DHX9, the generation of R-loops in these cells is almost entirely suppressed, restoring DNA synthesis and cell growth. This confirms the potential of some R-loops to cause profound replication stress and, more importantly, establishes DHX9 as an important driver of R-loop formation and genomic instability in cells.8. Although, we did not address the impact of DHX9 on R-loops globally, we found that the low level of RNA–DNA hybrids that form at the Β-actin locus in unperturbed cells are also suppressed by knockdown of DHX9. Furthermore, we demonstrated that R-loops generated in centromeric DNA, which regulate segregation of chromosomes during mitosis, are also dependent on DHX9 for their formation. Together these data strongly argue that, at least some, pathological and non-pathological R-loops are formed through a common mechanism involving DHX9.In addition to the R-loops that arise as a consequence of perturbed RNA processing, non-pathological R-loops are found throughout the genomes of normal cells47. Paradoxically, this study, like our own, reported that siRNA-mediated knockdown of DHX9 caused a global reduction in RNA–DNA hybrids when measured by immunofluorescence and slot blot47, supporting our conclusion that DHX9 promotes rather than prevents the formation of R-loops. The reasons for this difference are not clear but it is possible that R-loops induced upon treatment with CPT are generated through a different mechanism to those formed as a consequence of impaired RNA processing.Interestingly, DHX9 was recently identified as a component of a RNA–DNA hybrid interactome and shown to suppress R-loops at transcription termination regions and also prevent R-loop associated-DNA damage in cells treated with camptothecin (CPT)38, suggesting that it could function in the removal of R-loops, we have established that, in cells, DHX9 is required for the formation of some R-loops. Since DHX9 also unwinds RNA secondary structures in vitro, including stable guanine quadruplexes, we suggest that it is its ability of DHX9 to unwind RNA that best explains its role in R-loop formation. This is supported by several pieces of evidence. Firstly, DHX9 resolves RNA secondary structures in cells to prevent Alu-mediated backsplicing36. Secondly, R-loop formation requires a free RNA end to promote invasion and pairing of the nascent RNA with its complementary duplex DNA43. This might be facilitated by DHX9-mediated unwinding of RNA secondary structures to help assemble RNA processing proteins on the nascent RNA strand. Thirdly, the role of splicing factors and other RNA-binding proteins in preventing R-loop formation is most easily explained if they bind to and stabilize the nascent RNA strand, minimizing its potential to invade DNA duplex. This last point is supported by our experimental evidence showing that DHX9 is required for the binding of splicing factors to nascent RNA as part of the elongating transcription complex.Although DHX9 unwinds RNA–DNA hybrids in vitro41, this would alleviate the requirement for DHX9 as transcription progresses. Conversely, in the absence of splicing factors, DHX9 remains associated with the transcription complex where it binds to RNA secondary structures that form in the nascent strand and unwinds them during transcription elongation. The disadvantage of this activity is that, in the absence of splicing factors or components of RNP, the free “unstructured” RNA end generated by DHX9 is available to invade DNA duplex where it can form RNA–DNA hybrid and displaced ssDNA. As transcription progresses, RNA–DNA strand exchange might extend the region of RNA–DNA hybrid to generate an R-loop along an entire coding region as we observed at the Β-actin locus. This model, described in Fig. 17. Interestingly, a recent study using a conditional deletion of murine SFPQ proposed that SFPQ, together with CDK9, facilitates transcriptional elongation as well as activating RNA processing and stabilizing pre-mRNA33.We have also established that the formation of R-loops caused by impaired splicing correlates with the prolonged association of DHX9 with RNA Pol II during transcription. Whereas in normal cells, DHX9 associates with RNA polymerase II in the early phases of transcription, it is absent from RNA Pol II at later stages of elongation. Importantly, the dissociation of DHX9 from RNA Pol II is dependent on the availability of the splicing factors SF3B3 and SFPQ. We hypothesize that these proteins stabilize the unwound nascent RNA strand, preventing it from forming further secondary structures. Since DHX9 does not bind single-stranded RNA46. We found that depletion of XRN2 in human cells also induces R-loops but does not cause replication stress. This raised the question, why do some R-loops cause replication stress and genomic instability and others do not? Our data suggest that R-loop formation can cause RNA polymerase to become tethered to chromatin through RNA–DNA hybrid, where it has the potential to block DNA replication. In contrast, R-loops generated upon depletion of XRN2 do not trap RNA Polymerase II on chromatin and these cells do not exhibit replication stress. This supports a model in which it is the retention of RNA Polymerase on chromatin and the concomitant increased transcription–replication collisions that are responsible for pathological replication stress, rather than the generation of R-loops per se.In another study, mutations in yeast histones were shown to promote the formation of R-loops without inducing DNA damage, indicating that R-loops, per se, do not cause genome instability48. Since R-loops can also be generated during transcription by RNA polymerases I and III6, there must be other mechanisms through which R-loops form. It will be interesting to determine whether R-loops generated during transcription by these by other polymerases also require the activity of helicases, equivalent to DHX9, that unwind nascent RNA.It is important to note that DHX9 contributes to the processing of genes transcribed by RNA Pol IIIn summary, our work identifies DHX9 as a pivotal factor in the formation of R-loops in cells with perturbed RNA splicing. Our data also provide an explanation for the role of splicing factors in the suppression of R-loops, by facilitating the dissociation of DHX9 from RNA Pol II. In the absence of these stabilizing factors, the generation of R-loops causes trapping of RNA Pol II on chromatin creating a physical block to DNA replication and increasing genome instability. Our work reveals detailed new insights into the important interplay between transcription, mRNA splicing, and DNA replication that might be relevant to those neurodegenerative diseases and cancers that are impaired in processing of pre-mRNAs.2. All cell lines were obtained from ATCC.HeLa and U2OS cell lines were cultured in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum and appropriate antibiotics and grown at 37 °C and 5% COPrimary antibodies used in this study: mouse anti-RPA32  used at a dilution of 1:500 for immunofluorescence experiments (IF) and 1:1000 dilution in western blot (WB); rabbit polyclonal anti-SFPQ , mouse monoclonal anti-SFPQ antibody , mouse monoclonal anti-GAPDH antibody , rabbit polyclonal anti-RNA polymerase II antibody phospho-ser2 , rabbit Polyclonal anti-RNA polymerase II antibody phospho-ser5 , rabbit polyclonal anti-Chk1 [p Ser345] , rabbit Polyclonal anti-Phospho RPA32 (S4/S8) Antibody , rabbit polyclonal anti-RNA polymerase II antibody phospho-ser7 , rabbit polyclonal anti-SF3B3 antibody , mouse monoclonal anti-γH2AX , rabbit polyclonal anti-53BP1 Antibody , rabbit polyclonal anti-RNA Helicase A antibody , rabbit polyclonal anti-XRN2 Antibody , mouse monoclonal anti-RNase H1 antibody  and rabbit polyclonal anti-nucleolin antibody , rabbit monoclonal anti-SC35 (SRSF1) antibody . For detecting DNA–RNA hybrid, mouse anti-DNA–RNA Hybrid [S9.6]  was used and mouse anti-DNA, single stranded  to detect total ssDNA. Secondary antibodies: goat anti-mouse Alexa Fluor-488 (Molecular Probes) was used at 1:200 dilution, and goat anti-rabbit alexa fluor 647 (Molecular Probes) was used at 1:200 dilution. EdU incorporation was measured by using the Click-iT EdU Alexa Fluor 647 flow cytometry kit (Life Technologies) according to the manufacturer’s instructions. Hydroxyurea (H8627) and Actinomycin D (A1410) were supplied by Sigma-Aldrich and Pladienolide B (CAS 445493-23-2) was purchased from Santa-Cruz Biotechnology.49. pCMV-DHX9-GFPSPARK is designated pGFP-DHX9 and was purchased from Stratech . pGFP-DHX9dead contains D511A and E512A mutations made by site-directed mutagenesis of pGFP-DHX9 using Q5 Site Directed Mutagenesis system (New England Biolabs) according to the manufacturer’s instructions.pSFPQ-myc is described in Rosonina et al.The siRNAs were purchased from Dharmacon-ON-TARGETplus. Non-targeting siRNA D-001810-01-05; SFPQ-J-006455-06 J-006455-08 J-006455-09; SFPQ utr DUPLEX STD CTM-64991; SF3B3-J-20085-08; DHX9-J-009950-06 DHX9utr CTM-310164; RNASEH1-J-012595-09; XRN2- J-017622-12Β-actin locus are described in Kaneko et al.39.Primers used for qPCR analysis of the Region A: (fwd) cccacctgacaacctctcat, (rev) cccttcttgctgcctgttPromoter: (fwd) ctcaatctcgctctcgctct, (rev) ctcgagccataaaaggcaacRegion B: (fwd) caactgggacgacatggagaaa, (rev) gagtcctacggaaaacggcagaRegion C: (fwd) gcgcacagtaggtctgaaca, (rev) agaggcgtacagggatagcaPoly(A): (fwd) tgtacactgacttgagaccagt, (rev) aagcaggaacagagacctgaccRegion D: (fwd) taggcttaggagaggccgcaat, (rev) gtccaggagcctgggtatctccRegion E: (fwd) gaggcctggactctcaactg, (rev) ggtccttgtccaggtcatctRegion F: (fwd) caaccagatgtgttccgtgt, (rev) ctacacctgcaagaccaccaRegion G: (fwd) actgctgacattggtgatgc, (rev) agtaggtggtggcagcagacRegion H: (fwd) tgtctcagaggcatggattg, (rev) ccgctacagtcaccttccag2.Primers used for DRIP at the centromeric region of Chromosome 1 are described in Kabeche et al.c1 centro (fwd) tcattcccacaaatgcgttg, (rev) tccaacgaatgggaaaggagtcc1 pericentro (fwd) catcgaatggaaatgaaaggagtc, (rev) accattggatgattgcagtcaasnrpn (fwd) gccaaatgagtgaggatggt, (rev) tcctctctgcctgactccat6 HeLa cells per condition were collected and suspended in 250 µl of buffer A  and incubated for 5 min on ice. The soluble cytoplasmic fraction (S1) was separated from the nuclei (P2) by centrifugation for 4 min at 2000 × g at 4 °C. The nuclear fraction P2 was washed twice with 500 µl buffer A and suspended in 200 µl buffer B  and incubated at 4 °C for 30 min. The insoluble chromatin fraction (P3) was separated from nuclear soluble proteins (S3) by centrifugation for 4 min at 1700 × g at 4 °C. S1 was cleared from insoluble proteins by centrifugation at 16,000 × g in a benchtop micro-centrifuge for 30 min at 4 °C and the supernatant (S2) was kept for analysis. Cell fractions were subsequently analyzed by the Novex transfer system (Invitrogen) and western blotting.Briefly, 3 × 10BamHI, NcoI, PvuII, ApaLI, NheI, XbaI, XmnI, and DraI. The supernatant was cleared by centrifugation at 16,000 × g for 15 min and extracts were left untreated or treated with RNaseA (10 mg/ml).Prior to immunoprecipitation, primary antibody was incubated with Dynabeads protein G beads  for 2–4 h at 4 °C. Nuclei were prepared as described above. For immunoprecipitation of DHX9, nuclei were lysed using Lysis Buffer  supplemented with protease and phosphatase inhibitor cocktails (Thermoscientific). Extracts were passed through 23G needle for 10 min, and incubated with rocking at 4 °C for 30 min. Extracts were centrifuged at 16,000 × g for 15 min in a microfuge and the supernatant was collected. For immunoprecipitation of RNA Pol II (phospho-ser-2), nuclei were lysed in Nuclear Lysis buffer . DNA in the extract was digested overnight by the addition of 50 units each of Extract was added to the antibody-Dynabead complex and then incubated with rotation for 4 h to overnight at 4 °C. Immunocomplexes were separated using a magnet, washed three times in lysis buffer, boiled in sample buffer, and loaded on a 4–12% Bis-Tris polyacrylamide gel (Invitrogen). Proteins were transferred to PVDF membrane using a Novex transfer system (Invitrogen) and immunoblotted using the indicated antibodies.2, 300 mM sucrose, and 0.5% Triton X-100, after which they were fixed using 4% formaldehyde (w/v) in PBS for 15 min. Cells were then washed three times in PBS and permeabilized for 10 min in 0.5% Triton X-100/PBS. Three additional PBS washes were performed, after which cells were blocked using 1–3% bovine serum albumin (BSA)/PBS for 30 min. Cells were incubated with primary antibody (as indicated above), followed by the addition of Alexa Fluor-488 or -594 conjugated secondary antibodies (1:1000). To visualize nuclei, cells were also stained with 0.5 μg/ml DAPI (Molecular Probes). Slides were mounted using Prolong gold anti-fade reagent (Invitrogen) and images were acquired using a Deltavision DV4 wide-field deconvolution microscope with a ×100 objective.For EdU incorporation, U2OS cells were seeded onto coverslips and transfected with the indicated siRNA and grown up to 96 h. At the indicated times 10 μm EdU was added and incubation continued for a further 1 h before cells were harvested. Coverslips containing fixed cells were washed with phosphate-buffered saline (PBS) and stained using the Click-iT EdU Alexa Fluor 647 Flow cytometry kit (Life Technologies) according to the manufacturer’s instructions. For detection of nuclear foci, cells were pre-extracted for 5 min on ice in 25 mM Hepes pH 7.4, 50 mM NaCl, 1 mM EDTA, 3 mM MgCl27. Cells were co-stained with antibody against nucleolin, which was used to mask nucleolar regions for quantification of S9.6 staining. The nuclear S9.6 signal was determined subtracting the S9.6 staining intensity of the region co-stained with nucleolin from the total nuclear S9.6 stain. Images were analyzed using a DeltaVision microscope and quantified using image J software.To detect DNA–RNA hybrid, cells were stained with S9.6 antibody as describedU2OS cells were transfected with siRNA for 48 h and 50,000 cells were seeded into a six-well plate (time 0). At the indicated times, cells were recovered from the monolayer using trypsin and counted using the Casey Cell Counter. Growth curves were plotted using data from three independent biological replicates.2B4O7. Cells were blocked using PBS/1% BSA/0.5% Tween-20 and incubated with mouse anti-BrdU primary antibody  followed by goat anti-mouse FITC-conjugated secondary antibody (DAKO). Cells were suspended in 1 ml of PBS containing 5 μg/ml propidium iodide and 5 μl RNAse (25 mg/ml), incubated at room temperature for 30 min, and analyzed by FACS. Cell-cycle distribution was measured by flow cytometry in a Fortessa flow cytometer (Becton Dickinson) and analyzed using FlowJo software (FlowJo).Cells were grown for 1 h in medium supplemented with 10 μm BrdU. Cells were fixed using ethanol and the DNA was denatured using 1 ml of 2 N HCl/Triton X-100 and then neutralized with 500 μl 0.1 M NaApoptotic cell death was analyzed using Annexin-V kit (ebiosciences) as described by the manufacturer and quantified using a NucleoCounter NC-3000 system (Chemomotek).6 cells that were lysed in cell lysis buffer  for 5–10 min on ice. Cells were washed with PBS, collected by centrifugation and the collected nuclei lysed in nuclei lysis buffer . Proteinase K (10 mg/ml) was added and nuclei pellet were incubated at 37 °C overnight. Nucleic acid was precipitated using ethanol and digested overnight by the addition of 50 units each of BamHI, NcoI, PvuII, ApaLI, NheI, XbaI, XmnI, and DraI. Digested nucleic acid was treated with RNaseA (10 mg/ml) and 5 M NaCl for 2 h at 37 °C to remove contaminating ssRNA. DNA:RNA hybrids were precipitated using glycogen and isopropanol. Nucleic acid was purified with phenol–chloroform and precipitated with ethanol. The DNA was rehydrated in 250 μl water and quantified with a Nanodrop spectrophotometer. Fifty microliters was stored as the “input” sample. Ten micrograms of nucleic acid was treated with 25 U RNaseH1 to digest DNA–RNA hybrid and serve as a negative control. Five micrograms of RNAseH1 treated and untreated nucleic acid was immunoprecipitated using 10 μg S9.6 antibody and 50 μl with Dynabeads Protein G and made up to 500 μl with binding buffer  and incubated overnight at 4 °C. IPs were then washed several times with wash buffer . Nucleic acid were eluted with 100 mM NaHCO3 and 1% SDS along with addition of 3 μl RNaseA for 2 h at 65 °C followed by incubation with Proteinase K (10 mg/ml). Proteins were removed from the sample by phenol–chloroform extraction and ethanol precipitation. Control IP was performed using 10 μg of anti-mouse IgG antibody. Quantitative PCR was performed using Fast SYBR™ Green Master Mix (Applied Biosystems) with the indicated primers and samples were amplified using an Applied Biosystems 7500 Real-Time PCR System. The data were expressed as fold enrichment of each primer region in the experimental sample over the negative control. The mean and s.e.m. was plotted from three independent experiments and statistical analysis was performed using one-way ANOVA. The list of primers are provided above.DRIP was performed using HeLa cells transfected with the indicated siRNAs. Briefly, each immunoprecipitation used 10 × 102). Membranes were blocked in 5% Milk with PBST and probed overnight at 4 °C with S9.6 antibody (diluted 1:1000) and anti-mouse ssDNA antibody (1:5000) and then probed with goat anti-mouse antibody secondary antibody. The membrane was washed three times with PBST and exposed to X-ray film. The image is normalized to the control sample (set to 1) and quantified using Image J software.Preparation of nucleic acids was as described for DRIP with a few modifications. Briefly, after overnight digestion with restriction enzymes half of the nucleic acid sample was treated with RnaseH1 (20 U) every 3 h. The other half of the sample was treated with denaturation buffer (0.5 N NaOH and 1.5 M NaCl) and then neutralized with 1 M NaCl and 0.5 M Tris-HCl pH 7.0. In all, 0.5, 1, and 2 μg aliquots of nucleic acids were loaded onto a nylon membrane using a Biorad slot blot manifold and then crosslinked using a Uvitech (Cambridge) Stratalinker . Lysate was digested overnight with the addition of 50 units each of BamHI, NcoI, PvuII, ApaLI, NheI, XbaI, XmnI, and DraI. The lysate was centrifuged at 15,700 rcf for 15 min in a benchtop microfuge and the supernatant collected. Twenty-five microliters of Dynabeads coupled to 4 μg anti-DHX9 antibody was added to 500 μl supernatant and incubated with rotation at 4 °C overnight. Antibody was omitted from one sample as a control. Immunocomplexes were separated using a magnet, washed three times in lysis buffer, and DNA eluted in 200 mM glycine for 5 min and then boiled for 10 min. Immunocomplexes were incubated with 30 units RNase A for 30 min at 37 °C followed by proteinase K for 45 min at 55 °C. DNA was purified with phenol–chloroform and quantified using a Nanodrop spectrophotometer (Thermo-Fisher). Quantitative PCR was performed using standard protocols in an ABI PRISM 7900 (Applied Biosystems) using Fast SYBR Green Master Mix (Applied Biosystems). Analysis was carried out using the delta Ct method (fold enrichment). The mean and s.e.m. was plotted from three independent experiments and statistical significance determined using one-way Anova.1–5 × 10t-test (*p ≤ 0.05), Mann–Whitney unpaired t-test  or one-way Anova test as indicated. All statistics were performed using Prism v6 (GraphPad Software).Values are shown with the standard deviation from three independent experiments unless indicated otherwise. Data were analyzed and, where appropriate, the significance of the differences between the mean values was determined using two-tailed Students Supplementary Information


While the paradigm of utility maximisation has formed the basis of the majority of applications in discrete choice modelling for over 40 years, its core assumptions have been questioned by work in both behavioural economics and mathematical psychology as well as more recently by developments in the RUM-oriented choice modelling community. This paper reviews the basic properties with a view to explaining the historical pre-eminence of utility maximisation and addresses the question of what departures from the paradigm may be necessary or wise in order to accommodate richer behavioural patterns. We find that many, though not all, of the behavioural traits discussed in the literature can be approximated sufficiently closely by a random utility framework, allowing analysts to retain the many advantages that such an approach possesses. Discrete choice models have established themselves as an important tool for the analysis of individual decision making across numerous fields  paradigm and how it has been used to model choice. This is followed by a discussion of behavioural ‘anomalies’ and an overview of efforts to accommodate these in choice models, looking both at extensions to RUM as well as the use of other model frameworks in this context. We highlight how some of these alternative structures actually remain close to RUM, while also questioning whether some of the extensions of RUM lead to violations of utility maximisation.The concept of utility is fundamental to the standard microeconomic theory of consumer behaviour, where consumers are represented as choosing among bundles of continuously variable quantities of goods. Discrete choice might be seen as a variation on the standard theory, where consumers are represented as choosing the single alternative that, from a finite, exclusive and exhaustive set, maximises their utility, conditional on the constraints affecting the agent, in particular the budget.In practical implementations of choice modelling, it is necessary to admit that the analyst does not know all, or indeed perhaps most, of the relevant facts about the agent to be modelled, such as the agent’s preferences, attitudes, income, exact location, etc. In particular, the process by which an agent makes choices is unknown to the analyst, and a paradigm such as utility maximisation is likely to be only an approximation to the real process used. Moreover, agents’ behaviour is likely to vary, systematically and/or idiosyncratically. For these reasons, practical models based on most paradigms contain a random element, such that choice is represented as a probabilistic phenomenon. This representation acknowledges the existence of uncertainties, but nevertheless allows the development of rigorous models. Issues of identification may, however, arise, so that it is often impossible to attribute randomness between the agent and the analyst: for example, perception error by the agent may be impossible to identify separately from measurement error by the analyst.In this section, we first provide an overview of the history of random utility in choice modelling, before talking about the properties and benefits of the paradigm.M is the choice set) is given by:The idea of combining a random element with the concept of utility maximisation is intuitively appealing. Such models are generally referred to as RUM, a concept proposed by Marschak  and BlocIn some but not all paradigms, it is also admitted that agents may exhibit random behaviour. Block and Marschak saw RUM as a model of an individual agent engaged in a discrete choice task, whereby randomness arises from variations in choice behaviour across independent repetitions of that task. Prompted by the interest of economists in aggregate behaviour, McFadden re-interpreted RUM as representative of a population of decision-makers with explicitly varying tastes, each facing a single discrete choice task. McFadden  argued tThe primary motivation of Marschak and his associates was to formulate models that could help in understanding choice processes. In particular, they sought to confirm through experimental investigation the propensity of decision-makers to adhere to RUM  RUM. With regard to ordinal RUM, it is well established that for binary choice probabilities involving up to five distinct alternatives, RUM holds if and only if the so-called ‘triangle inequalities’ hold , the binary choice probabilities for any three distinct elements From these contributions, a series of tests can be derived that allow practical models to be assessed in terms of RUM compatibility and other related properties. Central among these tests is regularity Marschak , p. 192,Another test which has attracted considerable interest is transitivity, whereby if alternative A is preferred to alternative B, and B to C, then alternative A should be preferred to alternative C. Recognising that transitivity is ostensibly a deterministic property, the discrete choice literature has developed various stochastic interpretations of transitivity , which relate to the probability that alternative A is preferred to alternative B, and so on. Whilst none of these interpretations are necessary for RUM, there is a close relationship between stochastic transitivity and the triangle inequalities.Suppose that we can view an individual’s discrete choice as resulting from a complete and transitive preference structure that gives an ordering of preference of the alternatives. At any moment this ordering is clearly defined but could be the result of a random process, e.g. it may vary over successive choices by that individual. Then this preference structure is consistent with utility maximisation . In addition to these economic tests, conditions may be applied that arise from behavioural considerations. For example, sign conditions or relative value conditions may be applied to the values of estimated coefficients. Testing models in this way can make a valuable contribution to obtaining models that give good results for whatever objectives the modelling may have.In summary, by RUM we mean a model in which each alternative has a cardinal or ordinal utility, expressed in a common numéraire; utility is not known in full by the analyst but is capable of approximation with error. The model must comply with the triangle inequalities, must not exhibit preference reversal and, therefore, the utility differences of any pair of alternatives must not depend on the characteristics or existence of another alternative.The use of the RUM paradigm brings substantial benefits, so that constraining choice models to that paradigm, where possible, is often found to be beneficial, even though there may be a loss in explanatory power or in the clarity of theoretical exposition of the model. In the following section we discuss how some behaviour that is at first sight ‘non-RUM’ may be approximated by RUM, thereby retaining the benefits of the RUM approach.It is important to note that consistency with RUM does not necessarily imply that behaviour arises from individuals assessing the attributes of the alternatives they face, deriving utilities and choosing the best-performing alternative. Instead, it is postulated that behaviour that follows the rules outlined above may be characterised ‘as if’ behaviour followed RUM and the benefits of the RUM approach then follow. According to this interpretation, RUM could encompass a whole range of behavioural processes employed in practice, provided these can be reconciled in some shape or form with utility maximisation subject to constraints. Such behaviour is often described as ‘rational’,The key benefit of the RUM approach to the study of choice is the link it gives to microeconomics. Here there is a large body of theory and empirical evidence offering methodology and tests of behaviour. Setting the modelling within such a widely accepted behavioural framework helps in gaining acceptance for the approach, by providing a well-developed discussion of its strengths and weaknesses. For example, while microeconomics provides a sound basis for welfare analysis at the level of the individual, it also draws attention to the difficulty of integrating the measures over a population and presents plausible ways in which this might be done. It also provides a theoretically acceptable basis for the estimation of willingness-to-pay measures as marginal rates of substitution between the price and other attributes of alternatives. Similarly, for forecasting, RUM offers a credible basis that justifies expectations that individuals may continue to behave in ways that have been observed to date.However, there are numerous examples in the literature of criticisms of the RUM approach, and interest in behavioural features that are not compatible with generally understood interpretations of RUM. In the following section we discuss a number of these apparent departures in detail, addressing the key issue of whether extensions or adaptations to RUM could accommodate or approximate these features, some more subtle than others. Clearly, our preference is to accommodate more behavioural realism while remaining, if possible, within the RUM framework with all its advantages.Two general extensions may be mentioned here. First, it is reasonable to use models that may be consistent with utility maximisation only within a defined region; provided that no investigations need to be made outside this region, such models can claim the advantages of RUM. This would apply, for example, to models in which the impact of variables such as price changed sign outside the defined region (as would happen with specific non-linear treatments), or where the structure of the model implied inappropriate elasticities outside the region  according to a type I extreme value (EV1) distribution, this leads to a Multinomial Logit (MNL) model, with:iid EV1 errors) or Probit models  to represent the effect in the choice modelling literature. With regard to the last point, we specifically look at the implications of such efforts on maintaining consistency with utility maximisation. We group the phenomena together according to whether or not they are theoretically consistent with RUM.Anchoring effectsAnchoring effects refer to the phenomenon that individuals’ decisions could be affected by external cues. A crucial initial investigation came in the work of Tversky and Kahneman , who dempurchase a reduction in travel time at a cost of £x/h, then this may influence his/her willingness to purchase a reduction at a cost of £year/h  in subsequent tasks. Anchors may form specifically the first time a respondent faces a given type of choice, but subsequent choices may refine the anchor. The influence of anchoring on the value of time has been considered in some depth by VandeKaa  or evolve over time (e.g. changing with each choice situation). If, in each choice situation, the choice is modelled with a RUM structure, then the actual choice is consistent with RUM, but the sequence is not consistent with a single definition of utility, as utility gets redefined over time, either just once for all choices following the initial choice, or after each choice. This is consistent with the original Block and Marschak  interpreZero cost/price effects‘Predictably Irrational’ , which was proposed by Tversky , b, posiLexicography and extreme sensitivitiesLexicography refers to the case where, typically in an experimental setting, a decision-maker evaluates the alternatives on the basis of a subset of attributes  framework  that:6\del with . With RRComplexity, simplification of choice tasks and heuristicsA number of authors have addressed the issue of choice complexity, especially in the context of stated choice surveys , then the potential for preference reversals clearly exists, as the utility functions become dependent on attributes of other alternatives. On the other hand, it is also worth noting the existence of work looking at the role of inattention (which can link to complexity) and incorporating this in an Additive Random Utility Model (ARUM) context , and this makes basic valuation calculations possible in the situation where no major changes to the choice scenario arise. However, in many cases, it is difficult or impossible to include them in forecasting, because it is far from obvious how the phenomena would translate to the do-something situation . This is of course more particularly likely to happen when there is a significant time difference between do-nothing and do-something situations. In even more cases, welfare analysis is difficult or impossible, because of the additional requirement to aggregate measures of welfare change under the do-something scenario across alternatives and individuals, leading to further non-linearities.The paradigm of utility maximisation has underpinned the vast majority of discrete choice models reported in the literature, and there are good reasons why this is so, since consistency with RUM greatly improves the applicability of models for forecasting and economic valuation at both individual and societal levels. However, there has also accumulated a comprehensive literature documenting real-world and/or experimental choice contexts that validate alternative behavioural paradigms, and where RUM seemingly offers a poor description of actual behaviour. Against this background, the present paper explored the basis on which RUM is adopted, what the alternative approaches might be and the relative advantages of the various approaches.Our main conclusion is that the RUM paradigm has served choice modelling well. If we adopt a normative perspective then RUM can in principle admit a whole range of behavioural processes employed in practice, provided these are reconcilable in some shape or form with utility maximisation subject to constraints. On this basis, RUM is rather more flexible and agile than might appear from a positivist perspective, since many of the behaviours which have been promoted as ‘non-RUM’ in the literature can be recast as RUM-consistent or can be approximated by RUM-consistent models. That said, there remain some behaviours which are intrinsically non-RUM: these imply behavioural features such as irregularity, non-transitivity or preference reversal.First and foremost, whether or not a given phenomenon is RUM-consistent—the key violations here are certain forms of reference dependence and simplification heuristics.Second, the practicability of forecasting the phenomenon under the do-something—this is challenging for many of the phenomena because of their context specificity to the do-nothing, and the difficulty of transferring the phenomena to the do-something.Third, the challenges of forecasting follow through into welfare analysis—here they are compounded by additional difficulties associated with variations in the behavioural phenomena across alternatives and individuals.Our concluding message is that the developments in both the scientific and non-specialist literature on behavioural economics have certainly revitalised the field of choice modelling, raised a number of important issues and contributed to the development of new approaches. However, there seems to have been an exaggeration of both the ‘inability’ of RUM to accommodate these behavioural phenomena, as well as the importance of explicitly representing these phenomena (as opposed to approximating their effects). It remains for individual analysts to decide upon the relative merits of different approaches, and specifically to contrast the importance of behavioural realism with the ability to produce outputs that are of practical use, especially for policy analysis. Finally, a key point in our paper is that a model does not necessarily need to ‘represent’ a behavioural process in order for it to demonstrate good performance on data associated with that process.We illustrated the above conclusion in relation to several behavioural phenomena which have attracted particular interest in real world and experimental studies (summarised in Table


Genome packaging is a critical stage during virus replication. For viruses with segmented genomes, the genome segments need to be correctly packaged into a newly formed capsid. However, the detailed mechanism of this packaging is unclear. Here we focus on VP6, a minor viral protein of bluetongue virus, which is critical for genome packaging. We used multiple approaches, including a robust RNA-protein fingerprinting assay, to map the ssRNA binding sites of recombinant VP6 and the genomic dsRNA binding sites of capsid-associated VP6. By these means, together with virological and biochemical methods, we identify the viral RNA-packaging motif of a segmented dsRNA virus for the first time. Reoviridae, including the animal pathogen bluetongue virus (BTV), are multisegmented double-stranded RNA (dsRNA). During replication, single-stranded (ss) positive-sense RNA segments are packaged into the assembling virus capsid, triggering genomic dsRNA synthesis. However, exactly how this packaging event occurs is not clear. A minor capsid protein, VP6, unique for the orbiviruses, has been proposed to be involved in the RNA-packaging process. In this study, we sought to characterize the RNA binding activity of VP6 and its functional relevance. A novel proteomic approach was utilized to map the ssRNA/dsRNA binding sites of a purified recombinant protein and the genomic dsRNA binding sites of the capsid-associated VP6. The data revealed that each VP6 protein has multiple distinct RNA-binding regions and that only one region is shared between recombinant and capsid-associated VP6. A combination of targeted mutagenesis and reverse genetics identified the RNA-binding region that is essential for virus replication. Using an in vitro RNA-binding competition assay, a unique cell-free assembly assay, and an in vivo single-cycle replication assay, it was possible to identify a motif within the shared binding region that binds BTV ssRNA preferentially in a manner consistent with specific RNA recruitment during capsid assembly. These data highlight the critical roles that this unique protein plays in orbivirus genome packaging and replication.The genomes of the IMPORTANCE Genome packaging is a critical stage during virus replication. For viruses with segmented genomes, the genome segments need to be correctly packaged into a newly formed capsid. However, the detailed mechanism of this packaging is unclear. Here we focus on VP6, a minor viral protein of bluetongue virus, which is critical for genome packaging. We used multiple approaches, including a robust RNA-protein fingerprinting assay, to map the ssRNA binding sites of recombinant VP6 and the genomic dsRNA binding sites of capsid-associated VP6. By these means, together with virological and biochemical methods, we identify the viral RNA-packaging motif of a segmented dsRNA virus for the first time. Orbivirus, which belongs to the Reoviridae family. The BTV particle has two capsids, an outer capsid and an inner capsid, the latter of which is also called the core. The outer capsid contains proteins VP2 and VP5 to facilitate virus entry through the cellular membrane and the release of the core into the cytoplasm. The icosahedral core is principally composed of two proteins, VP7 and VP3, which are arranged in two layers. VP3 encloses the viral genome of 10 double-stranded RNA (dsRNA) segments (S1 to S10). In addition, the core contains three minor proteins: the polymerase (VP1), the capping enzyme (VP4), and VP6, an essential structural protein of 36 kDa with RNA binding and ATP binding activity. VP6 is unique to the Orbivirus genus within the Reoviridae family.Bluetongue virus (BTV) is an important animal pathogen and the prototype of the genus Upon entry, core particles become transcriptionally active, producing and extruding single-stranded positive-sense RNAs (ssRNAs) through the local channels at the 5-fold axis, without further disassembly. These ssRNAs then act both as mRNAs for viral protein synthesis and as templates for nascent genomic RNA synthesis. Our current understanding is that the 10 newly synthesized ssRNA segments are first combined via specific intersegment RNA-RNA interactions to form RNA complexes of all 10 segments. The RNA complexes of 10 segments are then packaged together with VP1, VP4. and VP6 into the assembling VP3 capsid layer 14. GenomiVP1 polymerase and capping enzyme VP4 are likely to be located beneath the VP3 layer at or near the 5-fold axis of icosahedral symmetry to facilitate the release of newly synthesized transcripts , 7. HoweThe smallest core-associated protein, VP6 (328 amino acids [aa]), has high binding affinity for both ssRNA and dsRNA species, suggesting that it is closely associated with the viral genome , 13. VP6In this study, we used RNA cross-linking and peptide fingerprinting (RCAP) to identify the RNA binding sites of VP6 using both a recombinant VP6 protein (reVP6) and VP6 in purified viral cores. The data demonstrate that multiple regions of reVP6 and core-associated VP6 interact with both ssRNA and dsRNA but that each source of VP6 had a largely unique RNA binding profile, with only one region in common. Mutagenesis of residues within the mapped RNA-binding regions followed by virus recovery using the RG system demonstrated that the VP6-RNA binding regions of the core-associated VP6 were essential for BTV replication, while those associated with reVP6 were dispensable. Within the essential binding sites, residues that recognize BTV RNA preferentially, which are possibly necessary for genome recruitment and packaging, were identified. This study highlights the essential role of the orbivirus protein VP6 in genome packaging and replication.During BTV replication, newly synthesized ssRNA segments are first packaged into the assembling viral cores, which, in turn, serve as templates for the synthesis of genomic dsRNA segments . VP6 hasin vitro cell-free assembly (CFA) assay  assay . In thisA) assay . Furtherin vitro  were selected for substitution mutagenesis. To perturb the potential RNA binding affinity, each residue was replaced with glutamic acid  either individually  or as a double substitution mutation . Each of these mutant segments, together with the other nine WT BTV RNA segments, was then transfected into BSR cells for virus recovery.VP6 has a high number of charged residues and readily binds nonspecific ssRNA and dsRNA in vitro , 18. We in vitro , indicatin vitro . Three rin vitro . To asse14-5EE) or Re2  did not affect virus recovery; recovered mutant viruses produced plaques similar in size to those of the parental virus (246-7EE and RK257-8EE) prevented virus recovery despite several independent attempts. To examine this further, two pairs of negatively charged residues from a conserved Glu-rich motif (EE-K-XX-EE) in the same Re3 region were also mutated to neutrally charged glutamine (EE225-6QQ and EE230-1QQ). Both mutant constructs were then tested for their impact on virus recovery by RG. In both cases, the virus was successfully recovered, suggesting that positively charged residues in region Re3, but not negatively charged residues, are important for viral infection. The positively charged residues located in RNA binding region Re3 are thus essential for virus replication.Mutations in Re1  in the Ca2–Re3 shared region (Ca2/Re3) were lethal, confirming these regions as critical for virus replication. Residues RK208-209 of VP6, which were previously proposed to contact BTV RNA by bioinformatics analysis, were not identified by RCAP . None of these mutants was recovered following RG transfection in the normal BSR cells (data not shown). However, when S9 RNA carrying critical Ca2/Re3 region mutations  was transfected into BSR cells, all the mutant VP6 proteins were expressed in the cells, and the localization was not different from that of WT VP6  . Three recombinant VP6 proteins were tested: a replication-competent mutant, RK208-9EE; a replication-incompetent mutant, RK257-8EE, which is located within the Ca2/Re3 region; and WT reVP6. In the EMSA, all three proteins exhibited strong band retardation, plausibly a measure of the nonspecific RNA binding function described above , or no VP6 (negative control), the level of incorporated genomic RNAs in the in vitro-assembled cores was measured by qRT-PCR. RNA packaging was significantly reduced from that with the WT when the RK257-8 mutant protein was present, almost to the background level of incorporation observed in the absence of VP6 . As a control, BSR-VP6 cells, which are permissive for the growth of the mutant, were also infected with the same virus preparation, and RNA was extracted. All RNA samples were analyzed by qRT-PCR using primers specific for the detection of positive- or negative-sense RNA, as described above. In this analysis, quantification of the negative strand acts as a marker for dsRNA synthesis, as described previously  prevented virus recovery irrespective of the charge status of the mutated residues. These six sites are highly conserved among the VP6 proteins of different BTV serotypes and the related orbiviruses epizootic hemorrhagic disease virus (EHDV) and African horse sickness virus (AHSV). This suggests that the interaction between VP6 and RNA within the core is invariant, in agreement with a key functional role.Previous reports have implicated VP6, a protein with clusters of charged residues, in the packaging of the viral genomic RNA, but precise mapping of the binding sites and their contribution to virus replication was not reported , 14, 17.Recently, a specific site of VP6 (aa 276 to 287) was reported to interact with the inner layer capsid protein VP3, an interaction that was essential for virus assembly , 21, butin vitro RNA-binding regions of reVP6 were largely not specific, a conclusion supported by the EMSA data. The amino-terminal region (Re1) of reVP6 is also conserved among the orbiviruses, but changing the only positively charged residues in this region, KR14-5, did not influence virus replication, suggesting that this conservation of amino acid sequence is due to other functional reasons. The disorder prediction of VP6 structure showed that the N-terminal part of VP6 was more disordered than the C-terminal part, suggesting that the N terminus is highly mobile, with nonspecific binding, while the C terminus has a conserved function, which was consistent with our findings  that VP6 binds during packaging and the question of whether VP6 plays an active role in RNA complex formation remain to be investigated.One region revealed by the comparative RCAP analysis  was associated with RNA binding both 257-8 mutant virus, amplified in a helper cell line, although it was still able to synthesize positive-sense viral ssRNAs, only low levels of negative-sense RNAs were detected, insufficient to support viral rescue. These data may indicate marginal VP6 activity, below the threshold required for growth, or the residual activity of the VP6 incorporated from the BSR-VP6 cells used for mutant virus recovery. These data clearly indicate that VP6 is critical in an early function, such as selective binding to BTV RNA, and that the region encompassing aa 246 to 257 is a required motif.In an earlier report, a cell-free assembly assay was established whereby the sequential mixing of replicase proteins VP1, VP4, and VP6, together with BTV ssRNAs, followed by the sequential addition of the inner capsid proteins VP3 and VP7, resulted in the successful packaging of ssRNAs into a core structure . In the Cystoviridae family contain a hexameric ATPase, P4, that serves as an RNA-packaging motor . However, changing this site did not influence virus replication. E157, a site in the previously suggested helicase (DEAD box), also failed to show any influence on virus growth (unpublished observation). Both these sites are conserved within BTV but are not shared with EHDV or AHSV. Studies have shown that the ATP-driven duplex unwinding function is not necessarily the primary mechanism of helicase proteins , the VP6 of which is fully exchangeable with that of BTV-10, was used in RCAP for viral capsids. All mutations of VP6 were generated by site-directed mutagenesis, and sequences of these mutations and primers are available upon request. Transcripts for reverse genetic analyses were prepared using the mMACHINE T7 transcription kit (Thermo); RNA transcripts for gel shifting and competition assays were prepared using T7 polymerase (Thermo), following the manufacturers’ instructions.BTV-10 VP6 was used for mutational analysis and reverse genetics , 17. BTVE. coli strain BL21(DE3) pLysS. The His-tagged reVP6 proteins were purified using Ni-NTA affinity purification, eluting the purified protein with a buffer comprising 20 mM Tris-HCl, 200 mM NaCl (pH 7.4), and 250 mM imidazole. Imidazole was then removed by buffer exchange with Sephadex G-75 columns .The expression and purification of recombinant VP6 (reVP6) of BTV-10 by use of baculovirus in the Sf9 cell line have been described previously . Additiog. The peptide-RNA conjugates were reversed by a 1-h incubation at 70°C. Parallel control reactions to assess background signals were performed without the addition of formaldehyde or, in the case of the recombinant protein, without RNA. RCAP peptides were analyzed using an Orbitrap Elite hybrid ion trap mass spectrometer equipped with an electrospray ionization source (Thermo Fisher Scientific). The peptides were resolved using a Dionex UltiMate 3000 high-performance liquid chromatograph (HPLC) with a 1- by 150-mm Zorbax 300SB C18 column (Agilent) and were eluted using a linear gradient of 2% to 45% acetonitrile in water with 0.1% formic acid over 90 min with a flow rate of 50 μl/min. Tandem mass spectra were obtained using collision-induced dissociation in a data-dependent manner. Raw mass spectral data files were converted to Mascot generic format and were analyzed using SearchGUI , according to the manufacturer’s instructions. At 24 h posttransfection, cells were fixed with a 4% paraformaldehyde (Sigma) solution, permeabilized with 0.5% Triton X-100 (Sigma), blocked with 1% bovine serum albumin , and subsequently stained using homemade rabbit anti-NS2 and guinea pig anti-VP6 as primary antibodies and Alexa Fluor 546-conjugated anti-rabbit and Alexa Fluor 488-conjugated anti-guinea pig secondary antibodies (Thermo Fisher Scientific). Nuclei were stained using Hoechst 33342 (Thermo Fisher Scientific). Images were acquired using a 100× oil objective and a Zeiss Axiovert LSM510 confocal microscope supplied with LSM510 software.2HPO4, 100 mM NaCl [pH 7.4]) at 20°C. The far-UV CD spectral data were collected from 260 to 195 nm with a 0.5-mm rectangular cell path length at 20°C on the Applied Photophysics Chirascan and Chirascan Plus spectrometers  attached to a Peltier unit . The UV and CD spectra were smoothed  and analyzed using Origin, v6, and APL Pro-Data Viewer, v4.2.15. The percentage of secondary structural units (α-helix and beta strand) of protein from the experimental CD spectra was calculated using the K2D3 program as described previously (The circular dichroism (CD) spectra of reVP6 were recorded in CD buffer . Radiolabeled BTV S10 was heated to 65°C for 2 min, and the mixture of VP6 in binding buffer was added and incubated for 30 min at 4°C. Samples were then analyzed on 0.8% agarose gels in TBE . The gels were dried and analyzed by autoradiography or by use of an Amersham Biosciences PhosphorImager. For the competition assay, 18 nM radiolabeled S10 RNA was incubated with 4 μM reVP6 in the presence of 1, 3, or 6 μg  of nonspecific Xenopus elongation factor mRNA (Thermo Scientific). The mixture was analyzed as described above.RNA labeling and the electrophoretic mobility shift assay (EMSA) were performed as described previously . A typicMutations in the cDNA of S9 RNA that encodes VP6 were generated using site-directed mutagenesis (sequences available upon request), together with the other 9 BTV genome segments that were used to transfect BSR cells or a BSR cell line that stably expresses VP6 (BSR-VP6), as described by Boyce et al. . CytopatWT and mutant viruses were diluted, applied to BSR cell monolayers at a multiplicity of infection (MOI) of 0.01 to 0.1, and covered by an Avicel overlay as described by Matrosovich et al. . Cells wWT BTV, the virus with truncated VP6, and VP6 mutant viruses were used to infect BSR cells or BSR cells that stably express VP6 (BSR-VP6). The cells were harvested at 12 h postinfection (hpi), and viral particles were purified as described previously by Matsuo and Roy . The purin vitro cell-free assembly (CFA) assay has been described previously (The BTV eviously . BrieflyFive micrograms of purified WT or mutant His-tagged VP6 was bound with 30 μl of Ni-NTA agarose beads (Thermo) in a buffer of 150 mM NaCl and 40 mM Tris-HCl (pH 8.0). The protein-coated beads were then incubated with 0.3 μg (1.1 pmol) of BTV S10 RNA in the presence or absence of 30 μg (1 nmol) of yeast tRNA. After extensive washes, the bound RNA was eluted by heating and quantified by qRT-PCR.The extracted viral RNA from the single-cycle replication and CFA assays was subjected to RT using specific BTV S6 forward or reverse primers, followed by qPCR, using SYBR green master mix (LabTech) and S6 primers . RNA elu


In plants, RNA silencing regulates key biological processes such as development, response to stress, genome integrity, and antiviral resistance. RNA silencing functions through diverse classes of small RNAs (sRNAs) that associate with ARGONAUTE (AGO) proteins to repress highly sequence-complementary target transcripts , most of which are also phased  are a class of sRNAs arising from double-stranded RNA (dsRNA) precursors. Secondary siRNAs are those siRNAs whose dsRNA precursor synthesis is triggered by an upstream sRNA-guided transcript cleavage event followed by RNA-dependent RNA polymerase (RDR) activity  approaches such as virus induced gene silencing (VIGS) or hairpin-based silencing after the initial targeting of transgene-derived (primary) siRNAs , modified TAS transcripts are cleaved by a specific microRNA (miRNA)/AGO complex , and one of the cleavage products is converted by RDR6 to dsRNA, which is processed by DCL4 into phased tasiRNA duplexes in 21-nt register with the miRNA cleavage site. atasiRNA/syn-tasiRNA guide strands, typically designed to contain an AGO1-preferred 5' U, are incorporated into AGO1 to direct silencing of one or multiple transcripts at one or multiple sites (http://p-sams.carringtonlab.org/) , but not as atasiRNAs or syn-tasiRNAs as reported  as individual 21-nt guide sequences that may have been designed computationally to be highly specific in silencing the corresponding target transcript(s), to be preferentially and selectively loaded by AGO1 or to avoid transitivity effects.After having reviewed the literature, it seems necessary to make some brief remarks to improve the proper and consistent use of the terminology related to these secondary siRNA-based tools. For example, the production of tasiRNAs from a transgene including a gene fragment fused downstream to a miRNA trigger target site should always be referred to as MIGS, and not to as atasiRNA/syn-tasiRNA as observed in several works  highly specific silencing , (ii) the study of genes whose complete knock-out induces lethality, (iii) multitargeting, as well as the targeting of duplicated genes, antisense transcripts and individual isoforms, and (iv) the spatio-temporal control of silencing when transgene expression is regulated with tissue specific or inducible promoters. Moreover, as gene knock-down tools, it might be possible to develop secondary siRNA-based strategies for the fine-tuning regulation of secondary siRNA activity to induce the desired degree of target gene silencing.The atasiRNA/syn-tasiRNA approach seems especially attractive due to its multiplexing capability and high specificity, as well as for the availability of high-throughput cloning strategies and automated design tools for the simple generation of atasiRNA/syn-tasiRNA constructs (Carbonell et al., The author confirms being the sole contributor of this work and has approved it for publication.The 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.


Pyrenophora tritici-repentis is the causal agent of tan spot, a major disease of wheat (Triticum aestivum). Here, we used RNA sequencing to generate transcriptional datasets for both the host and pathogen during infection and during in vitro pathogen growth stages.The fungus P. tritici-repentis isolate M4, RNA datasets were generated for wheat inoculated with P. tritici-repentis (infection) and a mock (control) at 3 and 4 days post-infection, when scorable leaf disease symptoms manifest. The P. tritici-repentis isolate M4 was also RNA sequenced to capture gene expression in vitro at two different growth stages: 7-day old vegetative mycelia and 9-day old sporulating mycelia, to coincide with a latent growth stage and early sporulation respectively. In total, 6 RNA datasets are available to aid in the validation of predicted genes of P. tritici-repentis and wheat. The datasets generated offer an insight into the transcriptomic profile of the host–pathogen interaction and can be used to investigate the expression of a subset of transcripts or targeted genes prior to designing cost-intensive RNA sequencing experiments, that would be best further explored with replication and a time series analysis.To capture gene expression during wheat infection with the  Pyrenophora tritici-repentis causes tan spot disease of wheat (Triticum aestivum). Tan spot is an economically significant leaf disease, which has a major impact on the wheat industry worldwide. Here, we present exploratory RNA sequence data sets with the following aims: (1) to investigate in planta gene expression of both the host and pathogen during wheat tan spot infection by P. tritici-repentis, (2) to investigate in vitro P. tritici-repentis gene expression during vegetative and sporulating growth stages, and (3) to provide RNA sequencing for bioinformatics support of gene predictions in P. tritici-repentis [The necrotrophic fungal pathogen ng aims:  to invesP. tritici-repentis, 28 and 23 million read pairs respectively for 3 and 4 days post-inoculation of control wheat, and 23 and 26 million read pairs for 7-day old vegetative fungal mycelia and 9-day old sporulating mycelia respectively (Data file 1)  [To determine host gene expression during GS V1.0) . Over haP. tritici-repentis expression during host infection, datasets from 3 and 4 days post-infection were also individually aligned to the P. tritici-repentis genome of isolate M4 [For olate M4 . Only 0.P. tritici-repentis genes expressed at different mycelia growth stages, the in vitro vegetative and sporulating datasets were individually aligned to the M4 genome [A total of 10,933 M4 transcripts were expressed in vitro and of these 8548 transcripts were found expressed in both vegetative and sporulating mycelia (Data file 4).To profile 4 genome  with appTriticum aestivum) variety Machete were inoculated with the P. tritici-repentis race 1 M4 isolate or a mock control solution [The fully extended leaves of the 2-week-old susceptible wheat , further purified using Zymo-Spin columns  as per the manufacturer’s guidelines prior to LiCl precipitation. RNA samples were pooled from 3 biological replicates. Isolated RNA was ribo-depleted and sequenced as un-stranded, 100 bp pair-end (PE) reads on an Illumina HiSeq2000 machine. A total of 30.6 Gb of raw sequence of 6 libraries was obtained. Further method details can be found in Supplementary file 1.P. tritici-repentis M4 reference genome (NCBI GenBank accession NQIK00000000.1) [Reads were quality checked with FASTQC  and trim00000.1)  using Bo00000.1) , 7. Expr00000.1) .The data sets generated were pooled from three biological RNA samples and therefore have no replicates for differential expression studies. The downloadable sequence data is stored raw and requires quality filtering before use.


PUF60. Finally, we propose that differential distribution of RNA processing steps detected in cells lacking PUF60 and the PUF60-paralog RBM39 is due to the RBM39 RS domain interactions. Together, these results provide new insights into regulation of exon usage by the 3′ss organization and reveal that germline mutation heterogeneity in RRMs can enhance phenotypic variability at the level of splice-site and branch-site selection.PUF60 is a splicing factor that binds uridine (U)-rich tracts and facilitates association of the U2 small nuclear ribonucleoprotein with primary transcripts. PUF60 deficiency (PD) causes a developmental delay coupled with intellectual disability and spinal, cardiac, ocular and renal defects, but PD pathogenesis is not understood. Using RNA-Seq, we identify human PUF60-regulated exons and show that PUF60 preferentially acts as their activator. PUF60-activated internal exons are enriched for Us upstream of their 3′ splice sites (3′ss), are preceded by longer AG dinucleotide exclusion zones and more distant branch sites, with a higher probability of unpaired interactions across a typical branch site location as compared to control exons. In contrast, PUF60-repressed exons show U-depletion with lower estimates of RNA single-strandedness. We also describe PUF60-regulated, alternatively spliced isoforms encoding other U-bound splicing factors, including PUF60 partners, suggesting that they are co-regulated in the cell, and identify PUF60-regulated exons derived from transposed elements. PD-associated amino-acid substitutions, even within a single RNA recognition motif (RRM), altered selection of competing 3′ss and branch points of a PUF60-dependent exon and the 3′ss choice was also influenced by alternative splicing of  Spliceoproteins . U2AF isproteins , SRSF3 ad hoc onproteins , often ipoly-U-binding factor 60 kDa, also known as FIR, Hfp or Ro-bp1) is a splicing factor homologous to U2AF65 (UHM ligand motif (ULM) domains present in U2AF65 (in vitro and a frequent overexpression in (pre-)malignant tissues  was found to bridge U1 and U2 snRNP contacts by binding the U1 snRNP core protein U1A and Prp5 ATPase, which interacted with the SF3B1 homolog  is an RNA processing factor and a hormone-dependent transcriptional co-activator with a domain structure similar to U2AF65 and PUF60 ,21. RBM3 homolog . RBM39 a homolog . The U2A homolog , yet as  homolog . Down-re homolog , but RBMPUF60 mutations in patients with a variable developmental delay, intellectual disability, spinal segmentation defects, and cardiac, ocular and renal abnormalities, first described for 8q24.3 microdeletions by Dauber et al.  293 cells were grown under standard conditions in DMEM supplemented with 10% (v/v) bovine calf serum (Life Technologies). The cells were treated with small interfering RNAs (siRNAs) targeting PUF60 or RBM39. The siRNA sequences were GCAGAUGAACUCGGUGAUGdTdT (PUF60) and GGAUCUACUGUCAUUUGUAdTdT (RBM39), as reported previously ,37. Tran® Ultra DNA Library Prep Kit for Illumina® (E7370L), size-selected and multiplexed before paired-end sequencing on the HiSeq 2500 Ultra-High-Throughput Sequencing System (Illumina) in the Wellcome Trust Centre for Human Genetics.For library preparations, total RNA was used to isolate intact poly(A)+ RNA with the NEBNext poly(A) mRNA magnetic isolation module (E7490L), employing the Human/mouse/rat Ribo-Zero™ rRNA Removal Kit (Cambio/Epicentre) according to manufacturers’ recommendations. The libraries were prepared using the NEBNextFor transcription inhibition, HeLa cells were treated with 50 μM 5,6-dichlorobenzimidazole riboside  for 5 h, as described . For co-P values  <0.05 were selected for visual verification in the Integrative Genomics Viewer (IGV) (http://www.broadinstitute.org/software/igv) to exclude false positive hits. Visualization of full transcripts was necessary to exclude errors introduced by adjacent or overlapping transcripts, misannotation of RefSeq mRNAs and low-abundance transcripts. The visual verification of DEXSeq-detected changes included inspection of alternative polyadenylation sites annotated in the APA atlas   and BowtPA atlas  in each PA atlas ,45.Total RNA from independent depletion experiments was extracted using TRI reagent, treated with DNase I (Promega) and reverse-transcribed with the Moloney murine leukemia virus reverse transcriptase  and oligo(dT) primers according to the manufacturer's recommendations. PCR primers were designed to amplify two or more isoforms with different sizes  16). Ex. Ex16). de novo motif discovery and motif enrichment analyses (http://regulatorygenomics.upf.edu/Software/SVM_BP/ (http://www.lecb.ncifcrf.gov/∼toms/sequencelogo.html) with equiprobable background composition.Browser-validated sequences were examined using the MEME suite, including analyses . Both unanalyses  employedanalyses  that are/SVM_BP/ . Intrins/SVM_BP/ ,51. AligProbability that an n-mer is Unpaired) as a measure of RNA single-strandedness for splicing regulatory sequences, employing the equilibrium partition function of RNAfold and energy minimization (n = 123) and control exons (n = 97 344). Controls were obtained from the ensGene table of the human hg38 genome assembly of the UCSC genome browser (n = 96 590) or AG..GC (n = 754) dinucleotides were considered. To obtain additional controls that have the same nucleotide distribution, we used shuffle from the squid package (available at http://eddylab.org/software.html) to shuffle sequences upstream/downstream of PUF60-regulated exons, excluding the splice sites and the last/first 10 nt of the intron. Shuffle was run with parameters -d -w and 100 to preserve both mono- and di-nucleotide distribution. Using the latest version of RNAfold (v. 2.4.3), we computed pentamer PU values as described , employing clone pET28a-PUF60-His described previously  using BamHI/EcoRI and human U1-70K EST  as a temmyc  were purchased.Western blot analyses were carried out as described . Antibod2+ and washing with water, cells were embedded in glycerol containing DABCO (Sigma). FRET efficiency was measured by the acceptor photobleaching method as described (after – CFP before) × 100/CFP after.HeLa cells were transfected with fluorescent proteins-tagged constructs using Lipofectamin LTX (Invitrogen) according to the manufacturer's protocol, grown for 24–26 h and fixed in 4% paraformaldehyde/PIPES (Sigma) for 10 min at room temperature. After rinsing with PBS supplemented with Mgescribed  using thHeLa cells were grown on 15 cm Petri dishes to ∼60% confluence and then transfected with 1 μg of plasmid DNA per 1 ml of DMEM using Lipofectamine LTX (Invitrogen) according to manufacturer's instructions. Cells were harvested at >90% confluency into buffer NET2  supplemented with a complete mix of protease inhibitors  and pulse-sonicated on ice for 90 s. Cell extracts were incubated (2 h) with Protein-G agarose beads  covered with goat polyclonal antibodies against GFP . Co-immunoprecipitated proteins were eluted into the protein sample buffer  and incubated at 95°C for 10 min. Proteins were resolved on SDS-PAGE, transferred onto membranes and probed with anti-GFP , anti-RBM39 , anti-U2AF35 , anti-U1-70K , anti-U1C  and anti-SF3B4  antibodies.2fold values >0.3 (1.23×) and >0.1 (1.07×) in the context of full transcripts in IGV confirmed 258 events in PUF60- cells and 198 events in RBM39- cells, respectively  whereas RBM39 was slightly upregulated , despite the more efficient PUF60 depletion . Motif enrichment analysis against the compendium of known RBPs , which contribute to accurate selection of 3′ss . We founinset). The PU values averaged for positions –18 to –40 nt upstream of PUF60-activated 3′ss, a typical location of human BPs, were significantly higher than for control exons . We also detected an increase in PU values 6–8 nt upstream of their 5′ss. The PU values computed for 100-nt flanking intronic segments upstream but not downstream of PUF60-activated exons correlated with changes in exon inclusion levels in PUF60- cells  of PUF60-activated exons.The U-rich regions of PUF60-activated 3′ss were mirrored by an increased RNA single-strandedness, with the peak of PU values shifted further upstream of 3′ss as compared to human control exons, having either GT or GC 5′ss Figure . GC 5′sss Figure  and G. Fs Figure  but not de novo motif identified in their high-guanine background is shown in Figure Because the number of internal exons upregulated in PUF60- cells and not associated with altered APA sites (termed PUF60-repressed exons) was low for a comparable analyses Figure , we exteDLGAP5 and PIGP, The number of IGV-validated RBM39-dependent and APA-unrelated internal exons was much lower than for PUF60, precluding similar analyses. However, exons downregulated in RBM39- cells also displayed U-rich regions upstream of 3′ss , with twTaken together, global sequence characteristics of PUF60-activated exons are consistent with a requirement for functionally significant PUF60 binding to more accessible pre-mRNA segments upstream of a large subset of 3′ss to promote their use.OGDH exon 4a, which is preceded by a weak PPT and intron-distal BPs, was repressed by PUF60 and activated by U2AF subunits; by contrast, OGDH exon 4b was activated by PUF60 and repressed by U2AF. Exon 4b is preceded by a long U-rich PPT and a high-score distant BP(s) near the 5′ss of intron 4a. The predicted BP(s) are close to or below a minimum distance threshold (∼50 nt) for the productive U1-U2 assembly  expression in the brain (Comparison of U2AF(35)-dependent  and PUF6assembly , most lihe brain .TIAR (TIAL1) exon 3 and the inclusion of its 51-nt portion into the mRNA. This segment encodes an extra 17 residues within the RRM1 domain  transcripts. Overall, these results reveal a PUF60-dependent regulation of U-binding proteins that interact with each other.Apart from altering 3′ss selection of a nscripts , PUF60- 6 Figure  and H, rPUF60 or RBM39 depletion also influenced alternative splicing of other hnRNPs that bind U-rich motifs Figure –F. Both HNRNPD exon 7.hnRNP D AUF1) isoforms are produced by alternative splicing of exons 2 and 7 . Exon 7 1 isoformFinally, the gene encoding hnRNP M, which interacts with PUF60, generates at least two protein isoforms, with isoform M1 lacking a 39-aa peptide encoded by the retained intron 6 . RetentiTaken together, these results uncover co-regulation of U-bound hnRNPs by PUF60 and/or RBM39 and identify alternative RNA processing events that reveal their coordinated expression, linking the two UHM-containing proteins to mainstream splicing regulators.Alus  tails of ancient free left Alu monomers (FLAMs) (Alus and are similar to rodent B1 elements (Alus with [(T)nG]n repeats in their PPTs identified 40 candidate exons  are the most abundant transposed elements in the human genome, with >1.5 million copies of mammalian-wide interspersed repeats (MIRs) and younger, primate-specific Alus . InclusiAlus , and TIAAlus . To testAlus . In PUF6 (FLAMs) . FLAMs pelements . Both maelements . A searcelements  for exonte exons , which hectively . Browserectively , but mosce sites . Taken tFunctional annotation clustering of genes with PUF60-dependent exons using DAVID  showed aUnlike U2AF65, RBM39-RNA interactions were observed close to transcription start/termination sites in 5′ and 3′ untranslated regions . To explPVR), namely, reduce PVRα isoforms by repressing a proximal splice site .,90.UBE2Fs Figure , was spls Figure –H, had ns Figure , and, uns Figure  for D159s Figure , suggestg Figure .U2AF1 exon Ab  of competing 3′ss in the m Figure  and D. Tm BP-76; . In contIn the human PUF60 RRM1/RRM2 crystal structure model , E181 c–I could UBE2F exon 5 in cells overexpressing the Δ2Δ5 isoform compared to the WT, despite similar expression levels in transfected cultures .Finally, we examined function of alternatively spliced PUF60 variants that lack exon 2- and/or exon 5-encoded peptides . The extended U-rich segments whose shuffled versions partly but not fully recapitulated the increase in PU values . The obalues n repeats present downstream of 5′ss, spatially approximating splice sites and obviating the need for U2AF for U2AF . It may for U2AF , can suptop) have been thought to reflect U2AF65 binding, which was detected at almost 90% of annotated 3′ss . This 3′ss organization may provide more space for non-competitive or non-cooperative RNA binding by U2AF65/PUF60 and other stimulatory or inhibitory proteins such as PTB than shorter PPTs, potentially explaining the opposite splicing outcomes. GANAB exon 6 probably serves as the most illustrative example -binding factors in the absence of U2AF65 in some but not all RNAs and U2AF was not strictly required for splicing  present ,15. Subs present ,16   , which i073DSH/) ,15,21. S073DSH/)  and, unl073DSH/) . G-tripl073DSH/) ,99 that 073DSH/) . Future Overall, human PUF60 may have evolved to promote splicing of introns that acquired longer U-rich tracts that displace BPs to a suboptimal location further upstream Figure . Togethen motifs that bind PUF60 were found also in PPTs of PUF60-regulated SINE exons NE exons . Unlike lu exons , but it eir 3′ss , the U-eeir 3′ss , the PUFeir 3′ss ,88 .First, we have shown that distinct disease-causing amino-acid substitutions in the same RRM dramatically influence the choice of competing 3′ss of PUF60-dependent exons Figure . This obn)Gn] elements upstream of cryptic 3′ss, including SINE-derived 3′ss, would be prime candidates. They could also modulate repression of Alu elements by hnRNP C. Although most disease-causing T>G substitutions upstream of canonical exons produce de novo 3′ss by creating AG dinucleotides (in vitro has been shown for short synthetic RNAs representing a common T>A polymorphism (rs689) in the PPT of INS intron 1 . The mRNA isoforms with and without exon 6 are about equally represented in liver and kidney .Supplementary DataClick here for additional data file.