Monitoring the state of coral reefs is necessary to identify drivers of change and assess effectiveness of management actions. There are several widely-used survey methods, each of which is likely to exhibit different biases that should be quantified if the purpose is to combine datasets obtained via different survey methods. The latter is a particularly important consideration when switching methodologies in long-term monitoring programs and is highly relevant to the Caribbean today. This is because of the continuing need for regionally comparable coral reef monitoring datasets and the fact that the Global Coral Reef Monitoring Network (GCRMN)-Caribbean node is now recommending a photoquadrat (PQ) method over the chain intercept transect method widely adopted by the members of the first truly regional monitoring network, Caribbean Coastal Marine Productivity Program (CARICOMP), in the early-1990s. Barbados, a member of the CARICOMP network, has been using a variation of the chain intercept method in its long-term coral reef monitoring program for more than two decades. Now a member of GCRMN-Caribbean, Barbados is considering switching to the PQ method in conformity with other regional members. Since we expect differences between methods, this study seeks to quantify the nature of those differences to inform Barbados and others considering switching methods. In 2017, both methods were concurrently implemented at 21 permanent monitoring plots across three major reef types in Barbados. Differences in % cover estimates for the six major benthic components, that is, hard corals, sponges, gorgonians, macroalgae, turf algae and crustose coralline algae, were examined within and among reef types. Overall, we found a complex pattern of differences between methods that depended on the benthic component, its relative abundance, and the reef type. We conclude that most benthic components would require a different conversion procedure depending on the reef type, and we provide an example of these procedures for Barbados. The factors that likely contribute to the complex pattern of between-method differences are discussed. Overall, our findings highlight that switching methods will be complicated, but not impossible. Finally, our study fills an important gap by underscoring a promising analytical framework to guide the comparison of ecological survey methods on coral reefs. Monitoring is a fundamental part of resource management, and in the case of coral reefs is critically important for assessing their state and measuring the success of management actions , since cThe use of standardized monitoring approaches is important to minimize method biases and facilitate integration of data at broad spatial and temporal scales  . StandarWithin the Caribbean, there are several variant methodologies that have been used by regional long-term monitoring programs such as the Caribbean Coastal Marine Productivity Program  along the chain because preliminary surveys in Barbados have indicated that point-intercept sampling along the chain yielded similar results to continuous sampling, while being less time consuming . This chNow a member of GCRMN-Caribbean, Barbados is considering switching to the PQ method in conformity with other regional members. Since we expect differences between these two methods, this study seeks to evaluate the potential magnitude and nature of method biases between the CPI methodology used in Barbados and an adapted version of the PQ level-3 methodology recommended by the GCRMN-Caribbean, with a focus on different reef types. Our main focus here is to explicitly assess whether or not PQ data conversion procedures are likely to be needed so that future PQ datasets can be meaningfully and most accurately compared with the existing CPI historical baselines. We do so using the already established and on-going long-term monitoring program of Barbados; thus broader issues pertaining to the development of an adequate coral reef long-term monitoring program  are beyoBarbados is located in the southeastern Caribbean and has a narrow shelf with easily accessible coral reefs all along the sheltered west and semi-sheltered southwest coasts . These cThe linear CPI transect method used by the long-term Barbados Reef Monitoring Programme (BRMP) is reported in detail by In this study we worked alongside the BRMP survey team from 10 July–4 Sept 2017 to undertake a PQ survey at each of 21 reef sites using a slightly modified version of the Level-3 highly recommended PQ protocol of For the CPI method, data were transferred from underwater slates directly to an excel database and were manipulated using the pivot table tool to produce appropriate summary tables. For the PQ method, photographs were post-processed as recommended by the GCRMN protocol using the Coral Point Count with Excel extensions (CPCe) software  to overlA single benthic component % cover value was obtained from each permanent plot. This was achieved by simply dividing the total number of point records belonging to a given benthic component by the total number of valid point records for all components at the permanent plot.To assess differences between methods, we followed the approach outlined in In addition to plotting the differences between methods in % cover against the average % cover for both methods at each site, we also pooled these site estimates within each reef type to generate averages and 95% confidence intervals for each reef type. The 95% confidence intervals were generated via bootstrapping of site values using the “boot” package  in R R . Lack ofWe examined each benthic component separately with a twofold aim: (1) to assess whether, within a given reef type, differences in % cover scaled with the average % cover obtained from both methods, and (2) to identify potential systematic differences among reef types in % cover between methods. We used an analysis of covariance (ANCOVA) framework to conduct these analyses. This involved building a linear model with % cover between methods as a response variable and reef type  and the average % cover obtained from both methods  as predictors, along with their interaction.true abundance of a given benthic component into cover estimates using functional relationships that differ fundamentally among reef types. Under such scenario, accurately converting estimates between methods within and among reef types would require prior knowledge of each of the different linear functional relationships for each reef type.A statistically significant interaction between the categorical and numerical predictors would imply the existence of a scaling relationship between differences in % cover (between methods) and average % cover (of both methods) that differs in slope across reef types. This would mean that the two methods translate the In contrast, a lack of a significant interaction term but presence of a significant effect of average % cover would imply a scaling relationship between differences in % cover and average % cover that is similar among reef types. If there is also a significant effect of reef type, then the scaling would be similar among reef types but each type would have a different baseline (intercept) value. If there is not a significant reef type term, then all the reef types would share the same baseline value. In the latter case, a single linear functional relationship would be required for accurate conversions of method estimates within and among reef types.Finally, a lack of a significant effect of average % cover  would imply the absence of any scaling relationship between differences in % cover and average % cover. This would simplify conversions between methods within reef types as it would require simply adding (or subtracting) a constant value to each estimate. If there is also a significant effect of reef type, then such a constant would differ among reef types; if not, then the constant would be the same among reef types. The latter case would be the ideal scenario because it would imply the use of a single conversion constant for all estimates, irrespective of reef type.p > 0.05) model terms) to obtain the relevant intercept and slope estimates for each reef type. Thus, for each reef type, we obtained a simple linear model linking differences in % cover between methods to average % cover as given by Since our ultimate goal is to be able to meaningfully compare current and future PQ % cover estimates to historical CPI ones, we derived linear equations allowing the conversion of PQ estimates to CPI ones for our data. To streamline and simplify this process, we used the previous ANCOVA framework to derive the parameter estimates for the conversion equations. For each benthic component, we used the most parsimonious ANCOVA model  but not others  . MoreoveWe have demonstrated statistically significant differences in estimates of % cover between the PQ and CPI method at our reefs for the most commonly used benthic components in coral reef monitoring programs. Importantly, we have shown that the magnitude and nature of such differences depends variously on the benthic component of interest, the abundance (% cover) of that component, and the type of reef examined.Beyond showing that differences between methods are complex and statistically significant, we further argue that the magnitude of these method biases is important from a management perspective and should not be ignored. We illustrate this point by using additional CPI data from the BRMP to assess changes in hard coral % cover between 2012 and 2017 at the same 21 study sites. Comparing the 2012 estimates with those of 2017 obtained using the same CPI methodology reveals a statistically significant  overall increase in absolute % cover across all reef types . In contThus, our study shows that (1) % cover estimates obtained using the PQ method will need to be converted to allow for meaningful comparisons with historical data obtained using the CPI method in Barbados and (2) the nature of this conversion will differ depending on the benthic component of interest and the type of reef examined .What drives this complex pattern of differences between methods in cover estimates? Following The contour effect results from the fact that the PQ method samples the benthos through a 2D horizontal plane (bird’s-eye view) and as such it will systematically ignore information about the vertical contour (rugosity) of the benthos, whereas the CPI method purposely samples along that vertical contour . This im2 quadrats, representing a total sampled area of 35.6 m2 (17.8%) out of the 200 m2. In contrast, the CPI method involved sampling points distributed along ten chains averaging ~13 m in length (depending on the reef contour) and just 0.005 m wide, representing a total sampled area of little more than 0.65 m2 (0.33%). This is an intrinsic limitation of all line transect methods and the consequence is that, everything else being equal, they are more likely to underestimate the least abundant benthic components   . When suanalogs) . Data tranalogs)  is neithanalogs) –3F, yet Finally, to streamline and simplify the process of generating functions to convert PQ % cover estimates to CPI ones, we have here made use of the already existing ANCOVA statistical framework and outputs to (indirectly) derive the parameter estimates for the conversion functions . An alteIn conclusion, any attempt to transition between chain intercept transect methods and PQ methods will require describing the nature of the differences between methods, which is very likely to depend on both the benthic components of interest as well as the reef type. We suspect that this conclusion also applies to comparisons involving benthic methods other than the ones specifically examined in this study. It is recommended that the transition period involves surveying as many permanent sites  as possible using both methods so as to quantify as accurately as possible the varying nature of those relationships. Indeed, in this study we only had seven sites per reef type and it is possible that some of our analyses might have suffered from low power to detect more subtle differences. Importantly, future work should examine in more detail the practical, empirical and theoretical merits of different between-method conversion procedures, which was beyond the scope of our study. Finally, we believe that an analytical framework like the one presented in this paper can guide and help standardize the process of comparing reef survey methods, even beyond the context of benthic monitoring programs.10.7717/peerj.8167/supp-1Supplemental Information 1Benthic components shown are (A) hard corals, (B) sponges, (C) gorgonians, (D) macroalgae, (E) turf algae and (F) crustrose coralline algae. A solid line with an intercept equal to zero and a slope equal to one is shown in each panel for reference. Conversion formulae are given in Click here for additional data file.10.7717/peerj.8167/supp-2Supplemental Information 2n = 7). Conversion formulae are given in Benthic components shown are (A) hard corals, (B) sponges, (C) gorgonians, (D) macroalgae, (E) turf algae and (F) crustose coralline algae. Each panel shows site-specific values (left) and averages for each reef type (right) with corresponding 95% bootstrap confidence intervals . Original column shows the observed PQ values before conversion to chain point-intercept (CPI) values. The ANCOVA converted column shows the converted PQ values using the ANCOVA model outputs (see Percent cover are shown as means and standard deviations (Click here for additional data file.10.7717/peerj.8167/supp-6Supplemental Information 6Click here for additional data file.


SMN deficiency causes neurodegenerative disease spinal muscular atrophy (SMA). How the SMN complex assembles snRNP cores is largely unknown, especially how the SMN complex achieves high RNA assembly specificity and how it is released. Here we show, using crystallographic and biochemical approaches, that Gemin2 of the SMN complex enhances RNA specificity of SmD1/D2/F/E/G via a negative cooperativity between Gemin2 and RNA in binding SmD1/D2/F/E/G. Gemin2, independent of its N-tail, constrains the horseshoe-shaped SmD1/D2/F/E/G from outside in a physiologically relevant, narrow state, enabling high RNA specificity. Moreover, the assembly of RNAs inside widens SmD1/D2/F/E/G, causes the release of Gemin2/SMN allosterically and allows SmD3/B to join. The assembly of SmD3/B further facilitates the release of Gemin2/SMN. This is the first to show negative cooperativity in snRNP assembly, which provides insights into RNA selection and the SMN complex's release. These findings reveal a basic mechanism of snRNP core assembly and facilitate pathogenesis studies of SMA.The assembly of snRNP cores, in which seven Sm proteins, D1/D2/F/E/G/D3/B, form a ring around the nonameric Sm site of snRNAs, is the early step of spliceosome formation and essential to eukaryotes. It is mediated by the PMRT5 and SMN complexes sequentially  Small nuclear ribonucleoprotein particles (snRNPs) are major building blocks of the spliceosome, which carries out precursor mRNA splicing in eukaryotes. All snRNPs share a common feature: seven Sm  or Sm-like proteins (Lsm2-8) form a ring around a segment of the small nuclear RNA (snRNA) after which the snRNP is named. Correspondingly, the snRNPs can be divided into two classes: Sm-class snRNPs  and Sm-like-class snRNPs (U6 and U6atac snRNPs) , in U7 snRNA , Gemin2, binding outside 5Sm, constrains 5Sm in a narrow state, which enhances RNA specificity, selecting the cognate snRNAs, containing the snRNP code, to assemble into the Sm subcore. snRNAs’ assembly inside 5Sm widens 5Sm, unexpectedly causing Gemin2′s release. 5Sm's widening also allows SmD3/B to join to complete the Sm core, which further expedites Gemin2′s release. Although the concept of negative cooperativity is well known, it has never been described in snRNP assembly before. These results reveal negative cooperativity in snRNP core assembly for the first time, provide deep insights into the mechanism of Sm core assembly, mainly on RNA selection and the release of the SMN complex, and facilitate pathogenesis studies of SMA. In addition, the biogenesis of U7 snRNP, which is required for the 3′-end processing of histone mRNAs in metazoans, follows the same maturation pathway as the spliceosomal Sm-class snRNPs. The assembly of its core is also mediated by the SMN complex and requires a 3′-SL adjacent to the Sm site, although U7 snRNP core has Lsm10/11 heterodimer instead of SmD1/D2 and a slightly different Sm site, AAUUUGUU7 snRNA . We predGe2BD, containing SMN residues 26–62 (pET21-HMT-SMNGe2BD), was fused with an N-terminal His(6)-tag followed by maltose binding protein (MBP) tag and TEV cleavage site in pET21 vector (Novagen).All of the plasmids used in the studies contain human complementary DNAs (cDNAs). Full-length SmD1 and SmD2 (pCDFDuet-HT-D2-D1), full-length SmF and SmE (pCDFDuet-HT-F-E), full-length SmG (pET28-HT-G) and full-length Gemin2 (pCDF-HT-Gemin2) were constructed as described before . SmD1s  was purified by Ni-column first, followed by TEV protease cleavage, secondary pass of Ni-column, cation exchange, and gel filtration chromatography. SmF/E was purified by a similar procedure except that anion exchange was used instead. SmF/E and SmG were coexpressed and purified in the same way as SmF/E. Gemin2 and SMNGe2BD-5Sm complex, equal molar amount of the SmD1s/D2, SmF/E/G, and Gemin2(or Gemin2ΔN39)/SMNGe2BD complexes were mixed in gel filtration buffer  phosphine]) supplemented with 0.5 M NaCl, and subjected to superdex200 GFC . The fractions containing all seven components were checked by SDS-PAGE, pooled and concentrated to 7–12 mg/ml, and used for crystallization studies. To make the hexamer of the Gemin2ΔN39-SMNGe2BD-D1s/D2/F/E complex, equal molar amount of the SmD1s/D2, SmF/E and Gemin2ΔN39/SMNGe2BD complexes were mixed in the same gel filtration buffer as above, and subjected to superdex200 GFC. The fractions containing all six components were checked by SDS-PAGE, pooled and concentrated to 4–5 mg/ml, and used for crystallization studies.To make the heptamer of the Gemin2 (or Gemin2ΔN39)-SMNGe2BD-D1s/D2/F/E/G complex (Complex A) crystals were grown in 6% PEG8000, 100 mM Tris–HCl (pH 7.5–8.2), human Gemin2ΔN39-SMNGe2BD-D1s/D2/F/E complex (Complex B) crystals were grown in 4% PEG8000, 100 mM Tris–HCl (pH 7.5–8.2), and human Gemin2ΔN39-SMNGe2BD-D1s/D2/F/E/G complex (Complex C) crystals were grown in 1% PEG8000, 100 mM Tris–HCl (pH 7.5–8.2). They were all grown by hanging-drop vapor diffusion method at 20°C within a couple of days. They all form in space group P212121, but with various unit cell parameters  were incubated with 50 pM of U4 or U4ΔSm RNA at 37°C for 40 min. After that, 1/10 (v/v) glycerol was added to the reaction mixture and the RNPs were analyzed by 0.4% native agarose gel electrophoresis. RNA was visualized by SYBR green (Thermo Fisher Scientific).Binding of 7S or 7SΔN complex to U4 or U4ΔSm RNA was performed in total volume of 20 μl solution containing 20 mM Tris–HCl (pH 8.0), 250 mM NaCl, 2 mM MgCl2, 1 mM EDTA and 1 mM DTT, with their amounts described in detail in RNA-protein complex assembly assays were performed by incubating 5Sm or 7SΔN with various RNAs in final volume of 500μl in assembly buffer containing 20 mM Tris–HCl (pH 7.5), 250 mM NaCl, 2 mM MgClh is the OD value of the peak. For the traces of protein, RNA and RNA-protein complex, OD260nm values are about a half, 2 times and 1.9 times of OD280 nm values respectively. For the GFC traces, which contain two or more component peaks, make μ equal to the position of each component peak and adjust h and σ  to fit both the OD260 nm and OD280 nm traces to be similar to the experimental results by Microsoft Excel software. The separate component peaks are shown together in a plot and the combined trace in a separate plot  was truSince in the previous structure of the 7S complex the N-terminal tail  of Gemin2 is located inside the central RNA-binding pocket, it is possible that this N-tail induces the narrowness of the 5Sm. To test this possibility, we reconstituted Complex C, a derivative of Complex A with Gemin2ΔN39 replacing Gemin2, for crystallization. The crystal of Complex C had the same space group as Complexes A and B and similar unit cell parameters to them . HoweverIn addition, surprisingly, in one 7S complex crystal structure with the full-length Gemin2 (Complex A), we observed that there was no electron density inside the RNA-binding pocket of 5Sm Figure , in contGe2BD/Gemin2 (or SMNGe2BD/Gemin2ΔN39) and 5Sm at various ratios, and this way could not faithfully mimic the physiological state, in which 5Sm binds to Gemin2/SMN in an equal stoichiometry. In this study, we used preformed 7S and 7SΔN to examine snRNA binding with the representative U4 snRNA, which has features matching the snRNP code and had proved to assemble into the Sm core , AAUUUUUGA, could readily produce a stable Sm subcore (260nm to OD280nm (OD260/280), which can distinguish protein (OD260/280 is about 260/280 is about 2) and protein-RNA complex , and component analysis by SDS-PAGE followed by silver staining or Coomassie brilliant blue (CBB) staining. Whenever the GFC traces were complicated, simulations of the separate and the combined peaks were provided  (260/280 of 1.89)  from GFC separation  at the front, indicating no formation of Sm subcore on U4ΔSm snRNA , which has SLs flanking the Sm site  and had proved to assemble into the Sm core , and desn Figure . HoweverA Figure . These rA Figure . These oNext, we tested the 3′-side of U4 RNA on binding to 7SΔN. We changed the 3′-SL of U4 snRNA to a linear single strand (U4-3′ss). The GFC trace showed three peaks eluted at 13.11, 13.80 and 14.48 ml Figure , which w260/280 >1 and the presence of RNA in the peak by silver staining) eluted much earlier than the RNA peak (15.67 ml or 17.49 ml) , or deleted the 5′SL of U4 snRNA (U4-5′Δ), we observed an additional peak of RNA-containing complex  Figure  and F. T) Figure .260 and OD280 peak positions , and the other being a protein complex containing RNA  and its several derivatives  like U4, in which 2 SLs tightly flank the Sm site, (ii) like U4-5′ss or U4-5′Δ, containing the Sm site plus a 3′’SL but no 5′SL and (iii) like U4-5′Δ-3′ss, containing the Sm site plus a 3′ single strand but no 5′SL, were able to bind to 7SΔN, but they seemed to behave differently in terms of their expected Sm subcore sizes and protein components  and 7SΔN peak (13.75 ml) Figure . In contGe2BD. To test it, we made a derivative of flU4 snRNA, flU4-spacer (type 2 RNA), in which a room was created between the Sm site and its 5′ SL by disrupting the bottom 3 bp of 5′SL . The incubation of flU4-spacer with 7SΔN gave rise to a Sm subcore with a complete removal of Gemin2ΔN39  to 7SΔN, and observed an aberrant peak of RNA-protein complex. We suspected that the Sm subcore formation on this type of RNA causes a complete detachment of Gemin2ΔN39/SMNTo test the assembly of the type 3 RNA, we used a further derivative of flU4 snRNA, flU4-spacer-3′ss, which linearized the 3′ SL on the basis of flU4-spacer. The incubation of flU4-spacer-3′ss with 7SΔN generated a gel filtration profile similar to flU4, in which a small fraction of Sm subcore formed , which seems more efficient in forming the Sm subcore than flU4  with both 7SΔN and D3(1–75)/B(1–91) also produced the Sm core and caused Gemin2ΔN39 to dissociate, but the assembly did not proceed to a completion, as indicated by the presence of free RNA (peak at ∼12.7 ml), 7SΔN (lanes 13B–14B) and D3/B (lanes 16B–17A) Figure . This in260 appeared at 14.25 ml, close to the peak of the Sm subcore containing U4-5′Δ (14.29 ml), while the free RNA appeared at 16.88 ml, close to the peak of free U4-5′Δ-3′ss (16.62 ml) instead of the peak of free U4-5′Δ (17.48 ml), indicating that more U4-5′Δ was assembled into the Sm subcore.The Sm site plus either a 3′-SL or a single-stranded RNA can bind the 7S complex and assemble into the Sm core. But the above experiments suggested that they might have different efficiency. To directly compare assembly efficiency, we performed a competition study by incubating 7SΔN with equal molar amount of flU4-spacer and U4-5′Δ-3′ss. The large difference of their RNA sizes makes their subcore formation visible on SDS-PAGE. The major fractions of Sm subcore containing flU4-spacer appeared on lanes 11A–12B , whereas the major fractions of Sm subcore containing U4-5′Δ-3′ss on lanes 13B-15A  Figure . AlthougGe2BD alone /B1–91). The peak of the Sm core containing flU4-spacer-3′ss appeared at ∼12.2 ml, whereas the peak of the Sm core containing U4-5′Δ at about 14.5 ml Figure . Gemin2Δ1. The peThe assembly efficiencies of the two types (types 1 and 2) of RNAs containing the snRNP code, with or without the 5′ adjacent SL of the Sm site, into the Sm core have little difference, as demonstrated by the incubation of equal molar amount of flU4 (type 1) and U4-5′Δ (type 2) with 7SΔN and D3(1–75)/B(1–91) followed by GFC Figure . SimilarSuperposition of 7SΔN with U4 Sm core  Figure , B or U1In this study, we closely examined the assembly steps of the Sm core in the second phase, from the formation of SMN/Gemin2/5Sm, to the assembly of the Sm subcore, and finally to the completion of the Sm core by a combination of structural and biochemical approaches. We established that the narrow state of 5Sm bound by Gemin2/SMN is real and independent of Gemin2′s N-tail, and discovered its physiological role. We identified Gemin2′s second role in Sm core assembly in addition to being a holder of 5Sm—it serves as a checkpoint of the assembly by a negative cooperativity mechanism. By binding the outside of the horseshoe-shaped 5Sm and constraining it in a narrow conformation, Gemin2 helps 5Sm select RNA substrates, allowing preferably the cognate snRNAs, containing the snRNP code, to assemble into the inside of 5Sm to form subcores; the assembly of cognate RNAs widens 5Sm, which in turn causes Gemin2′s release and allows SmD3/B to join to complete the assembly of Sm cores. Non-cognate RNAs might be able to temporarily enter the central RNA-binding site of 5Sm, but are unable to widen 5Sm; the assembly stalls in the 7S intermediate state, which cannot go on to recruit SmD3/B and cause Gemin2′s release until the non-cognate RNAs inside 5Sm are replaced by cognate ones. Our proposed mechanism is schematically drawn in Figure in vitro is a spontaneous process, why eukaryotes evolve so many assembly chaperones in this process is a central question. Early studies have proved that these chaperones, especially the SMN complex, help the assembly in an highly specific way  also assembled other types of RNAs  high abundance of snRNAs in cells compared with other non-cognate RNAs which containing just the Sm site  Geific way . In contific way ,59. Struific way . Second,e Figure . However Sm site ,61; (ii)The mechanism of the SMN complex's dissociation from the Sm core has long been elusive. Our findings provide the first model on it. Because Gemin2 is the major protein to bind Sm proteins  and therS. cerevisiae supports this idea . These strategies could be used to test if SMA is totally caused by deficiency of Sm core assembly and to develop possible therapeutics targeted on Sm core assembly.The major method used in this study to characterize protein-RNA interaction is GFC followed by SDS-PAGE, a two-dimensional separation approach. It is an approach commonly used in protein-protein interactions, yet much rarely used in protein–RNA interaction studies compared with EMSA. However, it is superior to one-dimensional EMSA when multiple-component systems are studied, as illustrated here by discovering the release of Gemin2 from Sm subcores, which escaped from many previous studies by EMSA ,12,15. SIn summary, we discovered a new mechanism in the assembly of snRNP core—the negative cooperativity between Gemin2 and RNA in binding to 5Sm, which simultaneously answers two basic questions in snRNP assembly: how does the SMN complex achieves high RNA assembly specificity and how it is released? This finding provides better understanding of the mode of action of the SMN complex and the snRNP assembly, including all spliceosomal snRNPs and likely U7 snRNP as well.Atomic coordinates and structural factors for the reported crystal structures of complexes A, B and C have been deposited with the Protein Data Bank under accession codes 5XJQ, 5XJS and 5XJR.gkz1135_Supplemental_FileClick here for additional data file.


RNA molecules play many crucial roles in living systems. The spatial complexity that exists in RNA structures determines their cellular functions. Therefore, understanding RNA folding conformations, in particular, RNA secondary structures, is critical for elucidating biological functions. Existing literature has focused on RNA design as either an RNA structure prediction problem or an RNA inverse folding problem where free energy has played a key role.In this research, we propose a Positive-Unlabeled data- driven framework termed ENTRNA. Other than free energy and commonly studied sequence and structural features, we propose a new feature, Sequence Segment Entropy (SSE), to measure the diversity of RNA sequences. ENTRNA is trained and cross-validated using 1024 pseudoknot-free RNAs and 1060 pseudoknotted RNAs from the RNASTRAND database respectively. To test the robustness of the ENTRNA, the models are further blind tested on 206 pseudoknot-free and 93 pseudoknotted RNAs from the PDB database. For pseudoknot-free RNAs, ENTRNA has 86.5% sensitivity on the training dataset and 80.6% sensitivity on the testing dataset. For pseudoknotted RNAs, ENTRNA shows 81.5% sensitivity on the training dataset and 71.0% on the testing dataset. To test the applicability of ENTRNA to long structural-complex RNA, we collect 5 laboratory synthetic RNAs ranging from 1618 to 1790 nucleotides. ENTRNA is able to predict the foldability of 4 RNAs.In this article, we reformulate the RNA design problem as a foldability prediction problem which is to predict the likelihood of the co-existence of a sequence-structure pair. This new construct has the potential for both RNA structure prediction and the inverse folding problem. In addition, this new construct enables us to explore data-driven approaches in RNA research. Ribonucleic acid (RNA), as an emerging nanoscale building block, is regarded as one of the most promising candidates to create nano-architectures and nano-devices for therapeutic and diagnostic purposes. Due to its unique biochemical properties and functionalities , such asIn general, RNA secondary structure research falls into two categories: The RNA structure prediction problem, which is to predict the folding result of base pairs given the RNA sequence; and the RNA inverse folding problem, which is to identify the appropriate assignment of nucleotides so that a targeted RNA secondary structure can be folded with certainty. For the RNA structure prediction problem, researchers have developed a variety of computational approaches to increase the prediction accuracy. One early effort is to use the comparative approach to infer a consensus secondary structure by aligning the given sequence with other existing RNA sequences. This requires large collections of RNA sequences for the analysis. A major challenge of this approach is the limited availability of RNA . An alteAs noted, previous research in both structure prediction and inverse folding has heavily relied on free energy as the metric to evaluate the stability of RNA structures –16. The δ difference from the MFE  Suppose we have two sequences of the same size with probability density set {p1, p2, p3…, pn + 1 − w} and {p1 + ϵ, p2 − ϵ, p3, …, pn + 1 − w} and p1 = p2 = … = pn + 1 − w = p > 0, ϵ > 0. The first SSE minus the second SSE equals − plog2p − plog2p + (p + ϵ) log2(p + ϵ) + (p − ϵ)log2(p − ϵ). The total number of distinct sequence segments with size w is 4w, since 4 different nucleotides could be assigned to each position arbitrarily. Therefore we have two cases depending on the cardinality of Segw.n + 1 − w ≤ 4w, the most uniform probability density set will occur when all elements of Segw are unique and then each element of SegUw would have probability In the cases where n + 1 − w > 4w there must exist elements Segw that are not unique. The most uniform probability density set will occur when Segw is partitioned into two groups of segments. The first group of segments will contain in  b = (n + 1 − w) mod 4w out of 4w and occur more frequently than the remaining group of 4w − b, which occur in equal amounts. For the group occurring in equal amounts, they must occur exactly b remaining elements must be In the cases where  Suppose we have two RNA sequences:seq1, take segment size 3 as an example:First, we calculate the scaled sequence segment entropy value of ent, 3 of seq2 is 0.947. The second sequence (seq2) may fold into more possible structures than the first one. This is reflected by scaled segment entropy value. The RVent, 3 of first sequence is 0.147, while the value of second sequence is 0.947. The higher scaled segment entropy value means the lower certainty of base pairings between RNA segments.Following the same steps above, we get RVAs the segment size increases, SSE converges to 1. To determine the appropriate segment size, we extract 342 RNA sequences from the PDB database and calculate their normalized SSE with different segment sizes starting with 3 and increment by 1. For each SSE calculated, we also calculate a condition index to check the linear dependency. Following Grewal , if the Vfe) of a given pair of sequence and structure and the minimum free energy value (Vmfe) that the sequence could achieved would be calculated. The program RNAeval [Vfe) of any pair of sequence and secondary structure. We use RNAfold [Free energy is used to measure stability of an RNA structure quantitatively. For pseudoknot-free RNAs, both the free energy value : The free energy value given to the sequence and base substructure. It is used to quantitatively measure stability of the base structure;Base substructure minimum free energy (Vbmfe): The minimum free energy value that the sequence could achieve without forming pseudoknots;Knotted substructure free energy (Vkfe): The free energy reduction brought on by the pseudoknots. In addition, we remove the energy increase caused by the “hairpin” since the hairpin is artificially created during the decomposition process.Since both the base substructure and knotted substructures are pseudoknot-free, free energy can be easily calculated. The following free energy based features are extracted for each pseudoknotted RNA by RNAeval  and RNAfs in equilibrium follows Boltzmann distribution:MFE-based prediction algorithms are generally far from perfect. In general, less than 40% of base pairs could be predicted correctly if a RNA is more than 500 nucleotides . Base paE(s) is the free energy of the structure, R is the gas constant and T the thermodynamic temperature of the system. After normalization, the probability of being in secondary structure s is:where where Z is partition function by summing over all the possible structure:pij is derived by summing up the secondary structure probability with i and j paired, qi is the probability of base i being unpaired. The following two metrics, calculated by using base pairing probability, have been widely used to evaluate the pseudoknot-free RNA secondary structure uncertainty, which can serve as features in ENTRNA for pseudoknot-free modeling:Ensemble Diversity (Ved): It measures the expected distance between the target secondary structure and all the other secondary structure. The lower ensemble diversity means the sequence has less ensemble diversity, which further implies the sequence would fold into the target secondary structure with high certainty.Expected Accuracy (Vea): It measures the expected number of bases that are in correct base pairing status. The higher expected accuracy means more bases are expected to appear in the target secondary structure, which further implies the sequence would fold into the target secondary structure with high certainty.Base pairing probability GC Content (PerGC): The percentage of guanine or cytosine nucleotides in the sequence. This is a sequence-based feature. GC content is believed to have an impact on RNA stability [tability ;Base pair percentage (Perbp): The percentage of base pairs for a given structure. This is a structure-based feature. Base pairs bring free energy reduction in most cases, which influences the structure stability.In addition to SSE, free energy and base pairing features, two more features are extracted from domain knowledge:In Tables Based on the training dataset generated, ENTRNA applies logistic regression as a classifier to predict the foldability using 11 features Tables  and 3 foTo evaluate the performance of ENTRNA, we measure the model accuracy as the mean of sensitivity and specificity:In order to identify the best feature combinations and parameter settings, we investigate ENTRNA performance exhaustively and record the best parameter settings and feature combinations in terms of Leave-One-Out cross validation accuracy. In addition, a blind test is conducted to evaluate the robustness and generalization of the proposed ENTRNA.Dataset I: 2084 (1024 pseudoknot-free + 1060 pseudoknotted) RNAs from the RNASTRAND database . The lenDataset II: 299 (206 pseudoknot-free + 93 pseudoknotted) RNAs extracted by CompaRNA  from theDataset III: 5 laboratory-tested pseudoknotted RNAs with synthetic sequences. All 5 RNA strands were obtained through in vitro transcription and further purified by gel electrophoresis. The RNA strands folded themselves in a buffer solution with a slow cooling process. Among the 5 sequences, 4 of them were not able to produce the designed well-formed rectangle nanostructures. The length of RNA sequences ranges from 1618 to 1790 nucleotides. This is used to test ENTRNA on long structural-complex pseudoknotted RNAsIn this research, we prepare 3 separate datasets to train, cross-validate and blind test ENTRNA. The details are as follows:P. To create the unlabeled dataset U, we generate 100 sequences for each secondary structure by using existing computational algorithms. Specifically, we use secondary structures in the positive dataset as seed structures, generate the sequence solutions by three different RNA inverse folding algorithms. The reent, 3)Normalized SSE with segment size 3 (RVgc)GC percentage (Pered)Ensemble Diversity (Vea)Expected Accuracy (Vfe)Pseudoknot-free RNA normalized free energy . By directly applying the trained model on the 206 RNAs (blind testing), 165 RNAs are correctly predicted. We conclude ENTRNA model is robust in predicting the foldability of pseudoknot-free RNAs.ent, 3)Normalized SSE with segment size 3 Normalized SSE with segment size 8 (RVRVkfe)Pseudoknotted RNA base substructure normalized free energy  RNA examples will certainly help improve the robustness of the model.Introducing thermodynamics (free energy) into RNA folding has been a revolutionary milestone since more than three decades ago. It provides the foundation to computational algorithms for RNA design based on three assumptions: (1) One RNA sequence has a single unique target conformation. (2) The thermodynamic parameters are accurate to derive the free energy characterizing a specific structure. (3) An RNA structure at minimum free energy (MFE) is the most stable structure. The “stable” here refers to the thermodynamic stability calculated in silico. However, recent research has proven that the same RNA sequence may fold into several structures, known as multi-conformation. The thermodynamic parameters used in calculating free energy are only estimates using nearest neighborhood methods. And, many natural RNAs discovered in cells are in an alternative structure with higher-than-the-minimum free energy.The issues with the three assumptions motivate us to reformulate the RNA structure prediction problem to an RNA foldability prediction problem. As a result, one sequence with its respected multiple potential structures, and one structure with its respected multiple sequences can all be assessed with a unified foldability prediction model. We propose ENTRNA as a data-driven framework for the RNA foldability prediction. In addition, we propose a new metric sequence segment entropy (SSE) as an additional feature for ENTRNA in conjunction with free energy and other RNA domain commonly used features . Since the unique challenge in designing data-driven approaches for RNA designs is the lack of failure examples, we propose the application of PU (Positive-Unlabeled) learning to make up the failed RNA sequence-structure pairs for the training dataset.The performance of ENTRNA is validated using both pseudoknot-free and pseudoknotted datasets. In addition, 5 laboratory tested long structural-complex pseudoknotted RNAs with synthetic sequences are used to blindly test the model performance. The superior experiment results show that our method is able to learn from existing RNAs and apply its learning in predicting foldability of unknown RNAs. Unlike previous computational based methods, our method stands at the machine learning perspective to understand and exploit reported RNAs.


Here, we used optical tweezers to study the unfolding/refolding of rpoS inhibitory stem in the absence and presence of Mg2+. We found adding Mg2+ decreased the free energy of the RNA junction without re-arranging its secondary structure, through confirming that this RNA formed a canonical RNA three-way junction. We suspected increased free energy might change the relative orientation of different stems of rpoS and confirmed this by small angle X-ray scattering. Such changed conformation may improve Hfq-bridged annealing between sRNA and rpoS RNA inhibitory stem. We established a convenient route to analyze the changes of RNA conformation and folding dynamics by combining optical tweezers with X-ray scattering methods. This route can be easily applied in the studies of other RNA structure and ligand-RNA.3′ downstream inhibitory stem plays a crucial role in locking  For E. directly –4. RpoS tory stem. Therefotory stem, 6. Bactn needed . The inhn needed . Thus, irpoS RNA with optical tweezers, and dissected the RNA structure from the single molecule level. We analyzed the structure and folding/unfolding kinetics of rpoS mRNA inhibitory stem, by combination of optical tweezers results with overall RNA topology obtained by SARX. Through this work, we showed that the combination of optical tweezers and SAXS is a useful strategy to explore the structure-and-dynamics of RNA molecules, especially when their high-resolution three-dimensional structure are not available.RNA structure and kinetics draw constant interest in gene regulation and protein translation processes . HoweverrpoS 5′-UTR was obtained by PCR amplification from Ec strain BL21 (DE3). The gene was subsequently inserted into pET-22b (+) vector (Novagen) and verified by DNA sequencing. The rpoS 5’-UTR with and without mutation were transcribed from DNA template as described in section 1 of rpoS 5’-UTR nucleotide 466–552 which represents the core portion of rpoS 5′-UTR inhibitory stem, and two DNA/RNA hybrids with biotin and digoxigenin labels at the 5’ and 3’ ends, respectively.The cDNA of the 2 may be presented if otherwise noted. Optical tweezers experiment was accomplished in our “instrument for single molecule force spectrum” . Optional 10 mM MgClrpoS 5’-UTR nucleotide 466–552 which represents the core portion of rpoS 5′-UTR inhibitory stem in the middle, and two DNA/RNA hybrids with biotin and digoxigenin labels at the 5’ and 3’ ends, respectively  at SSRF. The wavelength (λ) of X-ray radiation was set as 1.033 Å. Scattered X-ray intensities were collected using a Pilatus 1 M detector (DECTRIS Ltd). The sample-to-detector distance was set such that the detecting range of momentum transfer  of SAXS experiments was 0.01–0.45 Å−1. SAXS data were collected as 20 × 1 s exposures and scattering profiles for 20 passes were compared at 20°C using 60 μl sample in 50 mM Tris-HCl, pH 7.0, 150 mM NaCl. Measurements were carried out at two different concentrations of 2 and 4 mg/ml. The data were analyzed in the ATSAS package  following DAMMIN  with 20 rpoS 5′-UTR nucleotide 466–552 capped with two 5′-guanine and two 3′-cytosine was prepared by PCR amplification from the target plasmid using a forward (GAAATTAATACGACTCACTATAGGATCCGTAAACCCGCTGCGTTATTTCG) and a reverse (GGACCCGTGATCCCTTGACGGAACATTCAAGCAAA) primers. The in-vitro transcription mixture contained DNA template, 40 mM Tris, 10 mM DTT, 5 mM NTPs, 40 mM MgCl2, 1 mM spermidine, 0.01% (v/v) Triton X-100, 1 mg T7 RNA polymerase. The reaction was incubated in a water bath at 37°C for 4 hours. The transcription product was precipitated with ethanol at -20°C overnight, then dissolved in DEPC-treated water. The 91-nt RNA sample was separated by electrophoresis on urea-containing polyacrylamide denaturing gels and purified by Elutrap Electroelution System . Final RNA product was dialyzed into an SAXS buffer  and quantified by absorbance at 260 nm.RNA sample for SAXS was prepared by in-vitro transcription. The DNA template for transcription of rpoS mRNA inhibitory stem was previously reported as a three way junction [http://unafold.rna.albany.edu/?q=mfold) also gave a same structure . Expected RNA extensions were calculated with worm-like-chain model according to changes in number of nucleotides and helix ends in In order to validate our interpretation, we stretched RNA molecules without D2 region. Rip lengths measured from some FECs indicated D1, RNA junction, D3-a and D3-b were opened in an order which is consistent with the secondary structure predicted by Mfold. Sometimes D1 and RNA junction were opened simultaneously. Such simultaneous opening also occurred on D3-a and D3-b occasionally .2+ binding on the conformation of rpoS inhibitory stem, the RNA was again stretched in the presence of excess Mg2+ to investigate solution structure of inhibitory stem. In fact, rip lengths in the presence of Mg2+ is highly consistent with the length of the secondary structure model predicted under no Mg2+ condition. For most of FECs that contain three rips, favored unfolding pathways were divided into three groups: a→c→f→h, a→c→e→h and a→c→d→h (vs. 7.30 nm). The third rip has a rip length of 8.12 nm; which is close to the opening length of D3-a, while the fourth rip length is 11.07 nm long which matches the simultaneous opening of D2 and D3-b (11.93 nm according to the RNA secondary structure). In general, the RNA extension is fitted nicely with the secondary structure prediction.Magnesium ions are often found to play a crucial role in stabilizing RNA tertiary folding. To learn the impacts of MgrpoS inhibitory stem maintains same secondary structure arrangement in the absence and presence of Mg2+. We further suspected whether Mg2+ binding may affect the free energy stored inside the inhibitory stem. A theory developed by Gavin Crooks [2+, and listed in 2+ were also calculated with Mfold software . From FECs with and without magnesium ion both agreed with the intermediate states of predicted RNA secondary structure, which suggests n Crooks  illustra2, the free energy of RNA junction increased from 18.9 to 34.9 kJ/mole. The significantly increased free energy of all RNA subunits due to the presence of Mg2+ suggested that magnesium ions dramatically enhanced the internal interaction of rpoS inhibitory stem. Noticing that the stem orientation was mostly determined by RNA junction [2+ might compressed RNA junction with reduced free energy. Compressed RNA junction rearrange the relative orientation of different stems of inhibitory three-way junction.With the addition of 10 mM of MgCljunction , we hyporpoS inhibitory stem of the RNA sample by visualizing the overall topology of RNA inhibitory stem  plots of inhibitory stem with and without Mg2+ both contain two peaks 4 motif located upstream of the three-way junction studied here and a “U5” loop motif capping D2. Hfq binding with “U5” loop motif partially open the inhibitory stem to facilitate the sRNA annealing and ribosome binding [2+ reoriented RNA stem by reforming RNA junction through optical tweezer experiments and SAXS topology study later. The SD sequence of rpoS 5’-UTR is immediately adjacent to the D1. Mg2+-binding reduced the distance between D2 U5 site and SD sequence. The shorter distance may improve Hfq-bridged annealing between sRNA and rpoS. Idealy, our strategy of combining optical tweezers and SAXS can be further expanded to the investigation of Hfq-rpoS RNA interaction and may pave a way towards better understanding of how RNA stability was affected by different ligands.Peng et al. previously indicated that Hfq folds the  binding . In thisRNA structure determination is highly challenging given the facts that RNA molecules are usually difficult for crystallization and molecular weight limitation of solution nuclear magnetic resonance (NMR) for RNA samples. SAXS has been widely used to investigate the overall conformation of biological macromolecules in the recent decade. It is particular useful in defining the topology structure of folded RNA molecule due to strong electron density along phosphate-sugar backbones . OpticalS1 FileDescription of sample preparation, optical tweezers setup, methods used in data analyzing and table of rip lengths.(DOCX)Click here for additional data file.


Mononegavirales are highly diversified eukaryotic viruses including significant human pathogens, such as rabies, measles, Nipah, and Ebola. Elucidation of their unique strategies to replicate in eukaryotic cells is crucial to aid in developing anti-NNS RNA viral agents. Over the past 40 years, vesicular stomatitis virus (VSV), closely related to rabies virus, has served as a paradigm to study the fundamental molecular mechanisms of transcription and replication of NNS RNA viruses. These studies provided insights into how NNS RNA viruses synthesize 5′-capped mRNAs using their RNA-dependent RNA polymerase L proteins equipped with an unconventional mRNA capping enzyme, namely GDP polyribonucleotidyltransferase (PRNTase), domain. PRNTase or PRNTase-like domains are evolutionally conserved among L proteins of all known NNS RNA viruses and their related viruses belonging to Jingchuvirales, a newly established order, in the class Monjiviricetes, suggesting that they may have evolved from a common ancestor that acquired the unique capping system to replicate in a primitive eukaryotic host. This article reviews what has been learned from biochemical and structural studies on the VSV RNA biosynthesis machinery, and then focuses on recent advances in our understanding of regulatory and catalytic roles of the PRNTase domain in RNA synthesis and capping.Non-segmented negative strand (NNS) RNA viruses belonging to the order  Mononegavirales comprises highly diversified eukaryotic viruses with a monopartite negative strand RNA genome (rarely bipartite genomes), which includes important human pathogens  , and Filoviridae , Bornaviridae, Nyamiviridae, Mymonaviridae, Sunviridae, Artoviridae, Lispiviridae, and Xinmoviridae (The order  (EBOV)] . Since goviridae . Over thoviridae .Vesiculovirus genus in the Rhabdoviridae family. VSV has served as a prototype to elucidate the fundamental molecular mechanisms of transcription and replication of NNS RNA viruses, since its virion-associated RNA-dependent RNA polymerase (RdRp) activity was discovered ] is an arthropod-borne animal virus belonging to the scovered . A bullescovered . An RdRpscovered , and is scovered . In the scovered , which iscovered .N, P, M, G, and L, which are arranged in tandem from the 3′- to 5′-end , Paramyxoviridae , Pneumoviridae , Filoviridae , Bornaviridae , Nyamiviridae , and other families share the same gene organization with VSV, but have diversified their structural genes and often acquired additional structural and/or non-structural genes during evolution , Newcastle disease virus (Paramyxoviridae), MeV, HRSV], VSV has proven to be a remarkable model to elucidate the mechanisms of RNA biogenesis by NNS RNA viruses. Early studies using in vitro transcription systems with detergent disrupted VSV particles and purified RNPs revealed that VSV packages all enzymes required for primary transcription into virions, including RdRp  proteins are catalytic and regulatory subunits, respectively, of the RdRp complex  and 5′-trailer (Tr) sequences, respectively, and contains the five internal genes that are tandemly connected via intergenic regions  of ∼47 nt ppp(5′)Am-: N7-methylguanosine(5′)triphospho(5′)2′-O-methyladenosine]  and P proteins  accumulated in infected cells play a key role in co-replicational encapsidation of the antigenome or genome  is a capsid protomer for the intact nucleocapsid, the assembled N/RNA polymer . StudiesMedium resolution reconstructions from electron microscopy studies of the VSV  and RABVThe VSV and RABV N protein structures also revealed detail on how RNA is stored by the capsid as well as the unique structure adopted by the RNA upon encapsidation. When the N protein subunits assemble to form the nucleocapsid, they generate a continuous tunnel that sequesters the RNA upon encapsidation and protecting the RNA against degradation by nuclease and base-catalyzed hydrolysis . The N- 0–P complex, the N-terminal helical region of P (residues 17–31) interacts with the central hinge region of N  (The VSV P protein (265 amino acids) is a dimeric, non-globular molecule containing structured domains and disordered regions . During  complex . The N-tes 6–35)  and the es 6–35) , while ies 6–35) . The dimes 6–35) .0   of recombinant VSV L protein was reported to initiate transcription from a naked RNA template with a 19-nt VSV Le promoter sequence (0.2 μM) in the absence of the P protein   resides ongation . In addiongation  is requinthesis) . Althougnthesis) . Thus, tnthesis)  appears  protein , althoug protein .Non-segmented negative strand RNA viral L proteins share six conserved regions  , in whicThe first electron microscopic (EM) analysis of the VSV L protein  revealed that it consists of an N-terminal ring-like structure and a flexible C-terminal appendage containing three globular domains, which were predicted to be responsible for RNA synthesis and cap formation, respectively . The P pC)   of the VSV L protein at 1.8 Å resolution showed that residues 43–371 constitute a flat domain  composed of two subdomains (I and II) . The NTDC) , the PACV RdRp L , and theV RdRp L , suggestV RdRp L . Some coV RdRp L . In our a-5k432) , D290 ani). Although there is a possibility that amino acid residues in the RdRp domain serve as a general base  and a general acid  to mediate deprotonation of the 3′-OH group and protonation of leaving PPi, respectively, as proposed for other polymerases -dependent MTase core fold with a glycine-rich SAM binding motif G[-]GxG  and a 2′-O-MTase motif, namely K–D–K–E catalytic tetrad  (N7 and nucleoside1 (N1)-2′-O positions (1-2′-O-MTase (VP39), the second lysine residue in the K–D–K–E tetrad may play a critical role in cap-specific N1-2′-O-methylation by steering the 2′-OH oxygen orbital toward the methyl group of SAM  . Similar5–E1833) , the sinositions . As suggp of SAM  rather tp of SAM .N7-methylguanosine (m7G) linked to the first nucleoside (N1) of mRNA through an inverted 5′-5′ triphosphate bridge (ppp). Lower eukaryotic mRNAs have an m7GpppN1- cap structure , whereas the cap structure of higher eukaryotic mRNAs is further methylated at 2′-O positions to various degrees into m7GpppN1m- (cap 1) and m7GpppN1mpN2m- (cap 2)  is sequentially formed on pre-mRNA by mRNA capping enzyme with the RNA 5′-triphosphatase (RTPase) and mRNA guanylyltransferase (GTase) activities followed by a cap-specific MTase(s) (reviewed in i). (2) GTase transfers a GMP moiety of GTP (GMP donor) to ppRNA (GMP acceptor) via a covalent enzyme-(lysyl-Nζ)–GMP intermediate to form GpppN1-RNA with concomitant release of PPi. (3) mRNA (guanine-N7-)-methyltransferase (G-N7-MTase) transfers a methyl group from SAM to GpppN1-RNA to generate m7GpppN1-RNA (cap 0-RNA) and a byproduct, S-adenosyl-L-homocysteine (SAH). (4) In higher eukaryotic cells, mRNA (nucleoside1-2′-O-)-methyltransferase (N1-2′-O-MTase) methylates cap 0-RNA to yield m7GpppN1m-RNA (cap 1-RNA) (2-2′-O-)-methyltransferase (N2-2′-O-MTase) methylates cap 1-RNA to produce m7GpppN1mpN2m-RNA (cap 2-RNA) -methyltransferase (Am1-N6-MTase) often methylates the cap 1 structure to generate m7Gpppm6Am-RNA   . (5) Furp 2-RNA) . (6) If enosine) . m6A metof mRNAs , althougof mRNAs .N7-MTase methylates GTP to produce m7GTP. (3) mRNA N7-methylguanylyltransferase (m7GTase) transfers m7GMP from m7GTP to ppRNA via a covalent enzyme–m7GMP intermediate to generate m7GpppN1-RNA (cap 0-RNA). Interestingly, although alphaviruses do not have N1-2′-O-MTase, a structural element within the 5′-untranslated region of their cap 0-RNA genome confers resistance to the IFIT1-mediated restriction (Saccharomyces cerevisiae viruses L-A and L-BC) have a new class of mRNA m7GTases. Totiviral m7GTase transfers an m7GMP moiety of host m7GpppRNA to viral ppRNA through a covalent enzyme-(histidyl-N)-m7GMP intermediate to generate viral m7GpppN1-RNA, thereby causing decapping of host mRNAs  of mRNAs (1 (A1)-2′-O position followed by the G-N7 position to sequentially generate GpppAm and m7GpppAm (cap 1)  . Therefo7GMP) transfer mechanisms employed by eukaryotes and other viruses (Vesiculovirus) (Lyssavirus) (Nε2)–pRNA (L–pRNA) intermediate to yield GpppA-RNA in an mRNA-start sequence dependent manner (Km for GDP (0.03 μM)  , and RABsavirus) , use a psavirus) . In the savirus) , 2008. Gt manner . PRNTaset manner . Howevert manner  that are0.03 μM) . In addie pppRNA , althoug1R2C3) and the fifth residue (G5) are essential and important, respectively, for the pRNA donor substrate activity  and higher (10 μM) Km values for SAM, respectively, co-transcriptionally methylate the cap structure on mRNAs, producing GpppAm in the presence of limited concentrations (< 0.1 μM) of SAM and m7GpppAm  in the presence of higher concentrations (> 5 μM) of SAM  and minor (GpppA- → m7GpppA- → m7GpppAm-) pathways  under the reported conditions, although it was fully capable to generate m7GpppAm on mRNAs co-transcriptionally when using our reconstituted transcription system (Using the VSV ) of SAM . In addim7GpppAm . It is ipathways . Since tpathways . Rahmeh n system . The reain vitro transcription reactions is known to induce production of mRNAs with an extremely long poly(A) tail  tail . Similar(A) tail  as well (A) tail  of the V(A) tail . These oParamyxoviridae) L protein is enough to specifically methylate a capped 5-nt RNA with the SeV mRNA-start sequence (GpppAGGGU) at the G-N7 position, but not at the A1-2′-O position, to produce ∼10 fmol of m7GpppA within 2 h -2′-O-methylation similar to eukaryotic cap methylation. In contrast, recombinant C-terminal fragments of the L proteins of human metapneumovirus (HMPV) (Filoviridae)  of a recombinant form of the SeV  , closelyviridae)  were repin vitro , althoug7Gppp(m6)A1mp(m6)A2(m)-, where A1 is predominantly m6Am and A2 is A, Am, or m6Am  are present in the VSV PRNTase domain Wx(3–8)ΦxGxζx(P/A) , (Y/W)ΦGSxT (motif B), W (motif C), HR (motif D), and ζxxΦx(F/Y)QxxΦ (motif E) . These mfamilies . Motifs families , forminge domain , but aree domain . The dome domain , which ie domain .Nε2 position of H1227 in the VSV PRNTase domain via a phosphoamide bond  of the VSV L protein were originally identified as essential for the formation of a product sensitive to tobacco acid pyrophosphatase, most probably 5′-terminal GpppA cap, on RNA by alanine scanning mutagenesis , althougide bond . H1227 iide bond . A propoide bond  requiresOur extensive mutagenesis analysis further identified G1100 in motif A, T1157 in motif B, W1188 in motif C, and F1269 and Q1270 in motif E as essential or important for the PRNTase activity in the step of the intermediate formation . These kOγ1 atom of T1157, while phosphate three is positioned to interact with the side chain of Q1270. The adenine base punches into a second cavity on the opposite side of the cleft from the guanine. F1269 sits to one side of the entrance to this cavity and is in position where by rotation of the side chain could π-stack with the adenine. The adenine base is also positioned ∼3 angstroms from the side chains of N1264 and S1224, which could interact with atoms N6 and N7, respectively. The active site histidine, H1227, sits between phosphate two and three of the cap analog.To speculate functions of the VSV PRNTase domain in the cap formation, we performed a docking study with a GpppA cap analog corresponding to a 5′-terminal part of a capped RNA product (GpppAACAG-) and found that it fits in a crevice adjacent to motifs B–E . The guain vitro RNA capping as well as replication of recombinant VSV in host cells  in the intermediate formation step, and can be replaced with histidine yielding partial activity, but not with lysine, in the pRNA transfer reaction , D (H1227 and R1228), and E  . The arost cells . Howeverormation   extended from the PRNTase domain into the RNA exit cavity of the RdRp domain . The pri capping . In conte domain .De novo initiating RdRps of other unrelated viruses  often have a “priming loop,” which facilitates primer-independent transcription initiation with initiator and incoming nucleotides by stabilizing their initiation complex formed at the 3′-terminal of their genomic RNAs  at the 3′-terminal UG sequence of the e genome . Based oe genome  and the e genome , the VSVe genome . In thisage RdRp , the tryde novo initiation  of the tryptophan residue (W1167) on the VSV priming-capping loop is not required for internal initiation  position, releasing a 5′-triphosphorylated abortive N mRNA fragment   in the gene-start sequence, but prematurely terminates transcription, resulting in production of uncapped transcripts of 40–200 nt . Since 5d N1–40) . TherefoN gene, producing unusual N mRNA fragments initiated with GTP , such as an internal fragment with residues 41–68 (N41–68) and 3′-polyadenylated fragment with residues 157–1326 (N157–1326)  transcripts of heterogeneous lengths (100 to 500 nt). Furthermore, these mutations were reported to repress 3′-polyadenylation of transcripts when using their reconstituted transcription system in the presence of rabbit reticulocyte lysates , putative PRNTase inhibitors as well as mutations in a putative PRNTase domain of the L protein also cause premature termination of mRNA synthesis, resulting in production of 5′-uncapped abortive transcripts (< 50 nt)  . It shoutive VSV  had alream mRNAs . In contam mRNAs , 2009 sh lysates , 2009. H lysates , the cap< 50 nt) . Thus, iRhabdoviridae, Paramyxoviridae, Pneumoviridae , Filoviridae, Bornaviridae, and Nyamiviridae families possess a PRNTase or PRNTase-like domain with the conserved motifs A–E  belonging to the Chuviridae family in the order Jingchuvirales  (see Mymonaviridae), and 6 miviruses , while motif E is absent in those of all known miviruses. Interestingly, L proteins of 4 novirahbdoviruses  see . As in town) see , motif Coviruses  and 22 moviruses , therebyNucleorhabdovirus genus of Rhabdoviridae, Bornaviridae, and Nyamiviridae have a PRNTase-like domain, but lack an MTase domain  in PRNTase and PRNTase-like domains of selected viruses . The phye domain , we suggAs described in this review article, the numerous biochemical and structural studies on the VSV RNA biosynthesis machinery have led to the remarkable discoveries, provoking paradigm shifts in understanding unique roles of NNS RNA viral proteins in transcription and replication. Those include the finding that the rhabdoviral L proteins catalyze the unique mRNA capping reaction by the unconventional mechanism involving their GTPase and PRNTase activities. The striking differences between host and viral mRNA capping systems emphasize the potential of NNS RNA viral PRNTase domains as attractive targets for developing anti-viral agents.in vitro transcription or capping systems for other NNS RNA viruses has hampered the progress in our understanding of their precise mechanisms of mRNA capping. Our hypothesis is challenged by studies on some paramyxoviral L proteins that suggest that their C-terminal portions may carry out conventional mRNA capping with their RTPase and GTase activities . These studies would provide definitive evidence to distinguish between unconventional and conventional capping mechanisms. Unfortunately, this approach cannot be applied to 5′-G-started mRNAs of NNS RNA viruses, such as HRSV  enzymes  and/or other impurities that affect the reactions, and their enzymatic products are unambiguously identified using appropriate methods. It is also very important to demonstrate that these recombinant proteins exhibit enzymatic activities and substrate specificities that are the same as or similar to those of their native forms, if available. The classical approach to perform e of VSV , it woul as HRSV . NeedlesIt is now apparent that rhabdoviral PRNTase domains perform covalent catalysis in the pRNA transfer reaction to GDP to produce the cap structure . Howeverde novo initiation by L proteins of other NNS RNA viruses and identify their priming elements, if any. Detailed investigation along these lines would certainly advance our understanding on how mononegaviral RNA biosynthesis machineries play common and virus-specific roles in transcription and replication at the molecular level, and eventually reveal an Achilles’ heel for a target in developing anti-viral agents.Non-segmented negative strand viral L proteins may have retained evolutionary conserved elements critical for common functions, but diversified some other regions for virus-specific functions. Thus, the important studies would be to explore virus-specific functions of respective NNS RNA viral L proteins. Since mRNAs of NNS RNA viruses belonging to different families are unique due to virus-specific mRNA-start sequences that are distinct from those of rhabdoviruses , it woulTO conceived and wrote the manuscript, and prepared the figures. TG wrote the part of the manuscript, performed the docking study, and prepared the structural images.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.


Every transcription cycle ends in termination when RNA polymerase dissociates from the DNA. Although conceptually simple, the mechanism has proven somewhat elusive in eukaryotic systems. Gene-editing and high resolution polymerase mapping now offer clarification of important steps preceding transcriptional termination by RNA polymerase II in human cells. The most important sequence element for transcriptional termination on protein-coding genes is the polyadenylation signal (PAS), which consists of an AAUAAA hexamer (or a variant thereof) followed by a U or GU rich element ,2. The fThe role of a molecular torpedo in the termination process has been controversial. RNA interference (RNAi) of the human 5ʹ-3ʹ exonuclease, Xrn2, or mutation of its budding yeast equivalent, Rat1, was originally shown to disrupt termination on transfected plasmids and endogenous genes respectively ,7. AlthoE.coli DHFR degron allowing its depletion over the course of several hours. In both cases, this is much faster than the proteins can be depleted by RNAi and it revealed an unambiguous and general termination defect upon Xrn2 elimination. Loss of CPSF73 caused a strong inhibition of PAS cleavage and very extensive read-through transcription. This could not be restored by expressing its inactive derivative confirming its identity as the PAS nuclease and the importance of RNA cleavage to termination. The difference between our results and those obtained using RNAi likely reflect the speed and magnitude of depletion possible with inducible degrons. Our findings support a principal mode of termination in which PAS cleavage precedes degradation by Xrn2 and is summarised in We recently addressed the role of RNA cleavage and degradation in termination by employing gene editing to bring Xrn2 or CPSF73 under inducible control . Xrn2 waMammalian native elongating transcript sequencing (mNET-seq) was used to establish the effects of Xrn2 loss on transcription ,14. Thisin vitro [In some cases, Xrn2 elimination caused enhanced signal over regions where there was already evidence of accumulated Pol II in normal cells. This may be due to Xrn2 terminating polymerases that are paused or arrested and is consistent with features that enhance Xrn2-dependent termination in vitro . Moreovein vitro . Xrn2 loWhile the majority of protein-coding genes show read-through upon Xrn2 loss there are cases where this is much more extensive – extending tens of kilobases further than normal. Perhaps these are examples of where Pol II does not pause and responds more acutely to Xrn2 loss or these genes may not employ alternative termination mechanisms that could act in the absence of Xrn2 (see below). Other possibilities would include slower 3ʹ end processing that would delay the production of an Xrn2 entry site or rapid Pol II elongation rates previously shown to extend transcription . A more It is important to note that, on most genes, mNET-seq and RNA-seq signals eventually drop to near-background levels even when Xrn2 is absent . AnalysiAnother interpretation of these data is that there is Xrn2-independent termination that still requires CPSF73, which may play a more underpinning role in the process through alternative mechanisms. Interestingly, exosome depletion stabilises some read-through RNA in the absence of Xrn2, which may derive from such processes . The exiin vitro systems have been used to show that PAS-dependent termination can occur without RNA cleavage [More generally, does the function of CPSF73 in termination depend on its cleavage activity? Experiments using cleavage , but it cleavage . Alternacleavage ,19. TherPol II transcribes many different classes of genes, some of which use endonuclease cleavage for 3ʹ end formation. One example are so-called lnc-pri-miRNA genes that utilise microprocessor cleavage at their 3ʹ end . ImportaOther transcript classes that undergo 3ʹ end cleavage include those coding for snRNAs and replication-dependent histones (RDH). RDH genes employ a complex similar to that used for other protein-coding genes with CPSF73 as the endonuclease . The 3ʹ These unaffected transcript classes generally derive from shorter genes which may preclude the recruitment of important protein co-factors or dictate a Pol II C-terminal domain (CTD) modification status that promotes termination differently. For example, the choice of termination pathway in budding yeast is influenced at least in part by the relative densities of Serine 5 and 2 phosphorylation (Ser5p and Ser2p) on the CTD . Ser5p iC.Elegans protein-coding genes to Xrn2-dependent termination is determined by promoter identity [The short nature of RDH and snRNA genes also makes them susceptible to termination via an Ars2-dependent 3ʹ end processing pathway that is not active on longer genes (showing some similarity to Nrd1 termination in budding yeast) . Althougidentity . Intriguidentity ,27.The torpedo model envisages that Xrn2 chases Pol II and then signals termination by a process that is still not understood . We havein vitro and Sen1 is an RNA:DNA helicase that can also terminate polymerase in purified systems [E.coli polymerase whereas Rat and Xrn2 promote Pol II termination in the same highly purified system [RNA degradation may be required to deliver other important termination factors to the polymerase. A relatively small number of proteins are directly capable of inducing Pol II termination and include Xrn2, Pcf11, Sen1 (SETX in humans) and TTF2. Pcf11 causes dissolution of stalled elongation complexes  systems ,29. Both systems ,30. TTF2 systems . RNA degd system .in vitro [In argument of an indirect role for exonucleases in cells, work performed in budding yeast showed that Pol II-associated products of PAS cleavage continued to be degraded in the presence of mutated Rat1, yet the termination defect remained . In thisin vitro , its inain vitro .In human cells, Xrn2 loss had no obvious impact on Pcf11 recruitment to genes or on PAS cleavage in general . Xrn2 el


RNA silencing (VSRSs) are a diverse group of viral proteins that have evolved to disrupt eukaryotic RNA silencing pathways, thereby contributing to viral pathogenicity. The p19 protein is a VSRS that selectively binds to short interfering RNAs (siRNAs) over microRNAs (miRNAs). Mutational analysis has identified single amino acid substitutions that reverse this selectivity through new high‐affinity interactions with human miR‐122. Herein, we report crystal structures of complexed p19‐T111S (2.6 Å), p19‐T111H (2.3 Å) and wild‐type p19 protein (2.2 Å) from the Carnation Italian ringspot virus with small interfering RNA (siRNA) ligands. Structural comparisons reveal that these mutations do not lead to major changes in p19 architecture, but instead promote subtle rearrangement of residues and solvent molecules along the p19 midline. These observations suggest p19 uses many small interactions to distinguish siRNAs from miRNAs and perturbing these interactions can create p19 variants with novel RNA‐recognition properties.Viral suppressors of 6BJG, 6BJH and 6BJV.Model data are deposited in the PDB database under the accession numbers  AGOArgonauteCIRVCarnation Italian ringspot virusdsRNAdouble‐stranded RNAHis8‐tagocta‐histidine tagmiRNAmicroRNAntnucleotideRISCRNA‐induced silencing complexRNAiRNA interferencesiRNAshort interfering RNAssRNAsingle‐stranded RNATBSVtomato bushy stunt virusVSRSviral suppressor of RNA silencingin vitro and living systems; their specialized binding properties and amenability to engineering and multiplexing have made them powerful tools for probing RNA biology . VSRSs are a diverse group of viral proteins that have evolved to disrupt eukaryotic RNA silencing pathways, thereby contributing to viral pathogenicity The p19 protein is the VSRS expressed by tombusviruses, is the most widely studied of the VSRSs. The unique features of the p19 protein are evident from structural and biochemical studies that demonstrate p19's ability to bind to small dsRNAs with size specificity and independently of the nucleotide sequence of the RNA miRNAs are endogenous small RNAs that are potent regulators of gene expression, are critical in host–pathogen interactions and can serve as biomarkers of disease in vitro and in vivoMismatches and bulges in dsRNA structure are important determinants of intermolecular recognition, as they can cause distortions in the helical backbone which can be specifically recognized by RNA binding proteins in vivo, engineering the p19 binding site to allow enhanced affinity for specific patterns in miRNA secondary structure would broaden p19's applicability for miRNA detection and sequestration.Base pair mismatches in miRNAs alter p19's ability to bind these RNAs with high affinity  We have previously observed that a single point mutation to p19's binding site at the threonine 111 position to either a histidine (p19‐T111H) or a serine (p19‐T111S) leads to a ~50‐fold increase in the binding affinity of p19 for miR‐122  at 25 °C for 4 h. Cells were harvested by centrifugation, resuspended in lysis buffer  and lysed by a single pass through a M‐110P homogenizer .Plasmids were transformed into BL21 DE3 cells, and cultures were grown from single colonies in 150 mL LB+ 100 mm Tris pH 8.0, 0.3 m NaCl and 0.5 mm TCEP) over Nickel resin . The resin was washed with wash buffer . The his‐tagged p19 was eluted with 50mm Tris pH 8.0, 0.3 m NaCl, 0.3 m imidazole and 0.5mm TCEP and was dialysed in buffer (50 mm Tris (pH 8), 300 mm NaCl and 1 mm TCEP) with 2 mg of tobacco etch virus (TEV) protease at 4 °C overnight to remove the N‐terminal 6‐histidine tag. Gravity filtration over Nickel resin  allowed capture of the portion of the his‐tagged p19 molecules which remained uncleaved, as well as the TEV protease (containing a 6‐histidine tag). The tag‐free p19 protein was then concentrated using Amicon Ultra‐5 Centrifugal Filter tubes  to 0.5 mL and purified by size‐exclusion chromatography on a Superdex 200 10/30  in FPLC buffer .Protein purification was performed by gravity filtration of the bacterial lysate suspended in lysis buffer  2000 spectrophotometer, with the calculated extinction coefficient of 34 950 GL2 siRNA is 21 nucleotides long with two nucleotide overhangs, in which we used modified deoxythymidine nucleotides for the overhangs. The RNA was custom‐ordered from Thermo Scientific and was prepared as follows by the manufacturer: the individual strands were 5′ phosphorylated, converted to the 2′ hydroxyl, annealed and desalted, and purified by polyacrylamide gel electrophoresis. The sense strand (CGUACGCGGAAUACUUCGAUU) and antisense strand (UCGAAGUAUUCCGCGUACGUU) were annealed to allow siRNA duplex formation. We resuspended the purchased annealed siRNA duplex in DEPC‐treated water.−1) for 1 h at 4 °C. Crystals of p19–RNA complexes were grown using hanging drop vapour diffusion at 4 °C. Drops contained a 1 : 1 ratio of protein–RNA complex (0.8 μL of 2mg·mL−1) to 0.8 μL reservoir solution containing 3–12% PEG 1500, 100 mm sodium acetate pH 4.6 and 10–40 mm MgCl2. The best crystals were grown from drops that were seeded with smaller crystals, which had been crushed via vortexing with seed beads , and streaked through the drops using one of Cupcake the cat's whiskers. The crystals developed a hexagonal morphology over the course of 1–2 weeks at 4 °C. The crystals were harvested with nylon loops, cryo‐protected in the reservoir solution supplemented with 30% ethylene glycol , and flash‐frozen in liquid N2. Data were collected under cryogenic conditions at beamlines 12‐2 at Stanford Synchrotron Radiation Lightsource (SSRL) Protein–RNA complexes were formed by mixing 1.2 molar equivalents of RNA with 1 molar equivalent of protein (2 mg·mL1RPU) The p19–siRNA crystals diffracted X‐rays to a maximum resolution of 2.3–1.8 angstroms. The data collected from the p19–siRNA complexes  were indexed and scaled using XDS In pursuing structural basis for the high affinity of the p19‐T111X mutants towards the mammalian miR‐122, we first sought to understand the impact of the mutations on the overall architecture of the p19 protein. Crystals of wild‐type CIRV p19 (p19‐WT) and the p19 mutants p19‐T111H and p19‐T111S in complex with a perfectly duplexed siRNA were grown and were found to diffract to 2.2 to 2.6 Å  Next, we examined the structures of the p19‐T111X mutants to assess the impacts of the amino acid substitution on the overall topography of the p19 dimer. As displayed in Fig.−1. This change in the free energy upon binding could be due to the T111H or T111S mutation providing a favourable change in enthalpy (ΔH), through generating increased contacts between the binding site and the miRNA (e.g. ~2 hydrogen bonds). These could be direct interactions with the secondary structure of the miRNA or could be an increase in the number of water‐mediated hydrogen bonds that are prevalent in the p19–RNA binding site. Therefore, the orientation and organization of hydrogen bonds associated with the mutated residues are expected to play a key role in providing the free energy difference associated with binding.In pursuing structural determination of the p19 mutants, we sought to examine specific interactions between the protein and the miRNA which could explain the observed 50‐fold enhancement from WT on miR‐122 binding affinity, without altering the protein's affinity for siRNA ligands The p19 mutants p19‐T111S and p19‐T111H contain two chemically distinct mutations that give rise to nearly identical changes in the RNA binding properties of p19  4JK0), where a glutamine mutation has been introduced at the same 111 site in the p19 protein from the tobacco bushy stunt virus (TBSV). p19 is highly conserved among tombusviruses, and the TBSV p19 and the CIRV p19 share 86% amino acid identity and the same protein architecture The p19‐T111 site of each p19 monomer is positioned on the second beta‐strand (counting the beta‐strands from N‐C termini) and the two T111 sites in the dimer insert into the minor groove of the central region of the bound RNA, in proximity to the RNA backbone Fig.  . Figure Water molecules in protein–RNA binding sites contribute to binding affinity, providing hydrogen bond opportunities between the protein binding site and RNA, as well as shielding of unfavourable charge interactions between the two molecules In comparing the water molecules in the binding site between the p19‐WT and the p19‐T111H mutant, we observe that most of the water molecules shift positions in the binding site. In examining the hydration near the 111 site, we observe that an ordered water molecule engaged by the WT threonine is displaced by the histidine in the p19‐T111H structure Fig. . This ob4KTG, 4J5V, 4KNQ, 4JNX, 4JGN, 4KQO and 4J39) The structures determined here highlight T111 as uniquely positioned for access to the nucleotide bases along the central base pair of the bound RNA duplex, which is the position of the central mismatch of miR‐122. In support of this argument, others have observed in structures of p19 in complex with CNG repeat RNAs containing G:U and U:U mismatches, another form of noncanonical RNA duplex, that p19 is able to influence the geometry of the RNA helix, stabilizing irregular dsRNA geometries into more regular Watson–Crick formations  for influencing miR‐21 activity The authors declare no conflict of interest.DF, IM and JP designed and conceived of the project. DF and NS collected the data. DF, JP and IM interpreted the results. DF wrote the manuscript with conceptual and editing help from JP and IM.


Telomerases are ribonucleoprotein (RNP) reverse transcriptases. While telomerases maintain genome stability, their composition varies significantly between species. Yeast telomerase RNPs contain an RNA that is comparatively large, and its overall folding shows long helical segments with distal functional parts. Here we investigated the essential stem IVc module of the budding yeast telomerase RNA, called Tlc1. The distal part of stem IVc includes a conserved sequence element CS2a and structurally conserved features for binding Pop1/Pop6/Pop7 proteins, which together function analogously to the P3 domains of the RNase P/MRP RNPs. A more proximal bulged stem with the CS2 element is thought to associate with Est1, a telomerase protein required for telomerase recruitment to telomeres. Previous work found that changes in CS2a cause a loss of all stem IVc proteins, not just the Pop proteins. Here we show that the association of Est1 with stem IVc indeed requires both the proximal bulged stem and the P3 domain with the associated Pop proteins. Separating the P3 domain from the Est1 binding site by inserting only 2 base pairs into the helical stem between the two sites causes a complete loss of Est1 from the RNP and hence a telomerase-negative phenotype in vivo. Still, the distal P3 domain with the associated Pop proteins remains intact. Moreover, the P3 domain ensures Est2 stability on the RNP independently of Est1 association. Therefore, the Tlc1 stem IVc recruitment module of the RNA requires a very tight architectural organization for telomerase function in vivo. Inside cells, ends of linear DNA molecules incur losses during each round of DNA duplication. This occurs because of the so-called “end-replication problem” which is caused by the inability of the canonical semiconservative replication machinery to completely copy both strands of DNA . Given tT. thermophila, which contains a very short telomerase RNA, no general overview structures of telomerase RNPs have been determined , is a prime example, being 1157 nt long  and vertebrates (310 to 560 nt) . The TR  nt long . The Tlc nt long . The pre nt long . At the  nt long A. The se nt long . The dis nt long . In addi nt long . These l nt long . Further nt long . Previou nt long . Given t nt long . However nt long . Therefo nt long .Given this proposed flexibility, here we investigated whether the Est1-binding element on Tlc1 . The respective RNAs also contained 10 MS2 core protein (MS2CP) binding stem–loops near the 3′-end of the RNA which, in conjunction with the expressed MS2Cp-ProA fusion protein, can be used to immunopurify the RNP . However, insertion of 2 bp or more completely abolished in vivo telomerase activity . Furthermore, inserting more bps into the same place in the WT Tlc1 never allowed a recovery of in vivo functionality, even if in theory with 12 bp a full helix turn and perhaps more was achieved . Inserting 3 bp proximal of the bulged stem CS2 site, in effect lengthening the stem IVc overall at its base, had no discernible effect on telomere length maintenance in vivo . Taken together, these results suggest that stem IVc with the P3-like domain and the Est1 binding site is a tightly organized module in the yeast telomerase RNP. While the stem can be lengthened at its base without any measurable effect on telomerase function, it is very sensitive to perturbations within.Previous results showed that the distal bulged stem–loop, including the CS2a element, of stem IVc of the Tlc1 RNA is functionally interchangeable with the P3 domain of the Rpr1 and Nme1 RNAs . Coimmun the RNP . The pre the RNP B as well the RNP C. When s the RNP B, lane 6 the RNP B, lane 7 the RNP C, lane 5 the RNP , but the the RNP B, lane 8 the RNP B, lane 9 the RNP . As showachieved . These rWe considered the possibility that inserting 3 bp in a sensitive area of the RNA could alter the overall local RNA organization and hence cause the loss of Est1 independently of the distal P3-like domain. While mFold predicted 2D structures that were consistent with an intact bulged stem CS2 area and a native P3-like domain folding, we probed the structures adopted by the various variants of the stem IVc RNAs by SHAPE in vitro. As shown previously, such SHAPE analyses on the WT stem IVc RNA yield nucleotide reaction patterns that are in complete agreement with the predicted structures . FurtherPrevious results showed that a tagged Pop1 protein can be used to immunoprecipitate active telomerase and that recombinant Pop1 stimulated telomerase activity in vitro . Howeverest1Δ-cells) that express that Cdc13–Est2 fusion protein, the Tlc1 RNAs with the CS2Δ or the WT + 3 mutations allowed telomere maintenance in a fashion that is very similar to the wt Tlc1 RNA . Upon long-term culturing of these cells, telomeres gradually lengthen beyond the wt length, an effect that was not previously observed (tlc1Δ-cells), the ΔP3 Tlc1 RNA could not support telomere maintenance: The mechanism switched to a recombination-based elongation and the terminal restriction fragment patterns changed to one typically seen in such survivor cells . In contrast, cells that contained the WT + 3 RNA or the CS2Δ RNA eventually maintained telomeres at ∼400–500 bp , similar to what is seen in the cells without Est1 . These sizes are very comparable to what is observed in est1Δ-cells that express a wt Tlc1 RNA , again essentially a telomerase RNP without Est1. These results therefore show that Est1 association with the telomerase RNP influences elongation characteristics of the enzyme in a way that is independent from its function in telomerase recruitment.Finally, these results also show that Est1 plays a direct role in telomere elongation dynamics. For example, in the presence of a wt Tlc1 RNA and the Est1 protein, telomeres are over-elongated to reach equilibrium lengths of over 2 kb, as previously described  can be changed without loss of function. For example, it differs on the RNA of very closely related Saccharomyces species or introduction of the P3-elements of the Nme1 or Rpr1 RNAs also cause that sequence to change, yet telomerase in all these cases remains fully functional in vivo  does not alter the structure of the RNA in this area, as assessed by SHAPE  as compared to when it is not associated with telomerase . Note that in all these experiments, a wtEst1 protein is expressed and present in the cells and the results therefore cannot be ascribed to a lack of the Est1 protein in general with pleiotropic effects or an inability to interact with Cdc13. In addition, the terminal telomere length phenotype in these cells with the Tlc1-CS2Δ or Tlc1-WT + 3 RNAs is also different from the one observed in cells lacking the Tlc1 RNA altogether . In the latter, no telomerase is present and telomere maintenance eventually switches to a recombination-based mechanism. Taken together, telomere elongation in the cells expressing the Cdc13–Est2 fusion protein is telomerase dependent but Tlc1 RNA mutants, which are unable to associate with Est1, mediate a much reduced elongation as compared to wt Tlc1 RNA. Therefore, these results directly show that, at least in the Cdc13–Est2 fusion situation, Est1 also contributes to telomere elongation during the reaction cycle and not only via its interaction with Cdc13.In addition, the results presented here include in vivo evidence that the Est1 protein makes a contribution to catalytic telomerase activity that is independent from its recruitment function. Previous genetic and biochemical experiments already suggested that Est1 contributes to telomere maintenance in ways that are independent from its interactions with Cdc13, and hence recruitment . Our datFinally, the results obtained with the WT + 3 construct demonstrate that a functional P3 domain with the associated Pop-proteins does stabilize the Est2 protein on the RNP. In contrast to the Est1 interaction, this stabilization is not affected by RNA sequence modifications on stem IVc as long as they leave the P3-like domain intact . TherefoIn summary, the results presented here demonstrate that the stem IVc domain of the budding yeast telomerase RNA Tlc1 is a very tightly organized module that minimally comprises the proper RNA structure, the Est1, and the Pop1/Pop6/Pop7 proteins. Furthermore, in order for a functional telomerase RNP to assemble, Est1 most likely directly interacts with the Pop-proteins. Next, while previously this domain was thought to be required exclusively for telomerase recruitment to telomeres, the combined evidence . For western and northern blots, as well as telomerase activity assays, the strain YVL3493 was used as a base to create NLYH125, NLYH128, and NLYH494. HA3-POP1 was integrated by linearizing pNL09 with SpeI, grown on Sc-URA, and then on 5-FoA to select for clones that have lost the plasmid backbone. Clones were screened for HA3-Pop1 expression by western blot. Tagging of POP6 with the HA3 epitope in NLYH125 was achieved by PCR-based gene targeting using the pFA6a-3HA-KMX plasmid and this generated strain NLYH128 . The beads were washed and resuspended as described.Total protein extracts were prepared as described in 3 binding analyses, the samples were run on 15% SDS-PAGE gels. For HA3-Pop1, Est1-Myc12, and FLAG3-Myc12-Est2 visualization, inputs and IP samples were mixed with 2× Laemmli loading buffer, heated and separated on 8% SDS-PAGE gels. After transfer onto Hybond-ECL nitrocellulose membranes , membranes were blocked in 5% milk/PBS-Tween and incubated with a 1:10,000 dilution of mouse monoclonal anti-ProA (Sigma), or with a 1:5000 rabbit polyclonal anti-ProA (Sigma), or a 1:1000 dilution of mouse anti-HA (Roche) antibodies. Secondary antibodies were HRP-conjugated sheep anti-mouse IgG and donkey anti-rabbit IgG , diluted 1:5000 in 1% milk/PBS- T. Blots were visualized with a LAS-4000 .After the removal of TMG3 from IP beads, input and IP samples were mixed with 2× Laemmli loading buffer. The proteins were then denatured for 5 min at 98°C, separated on either 8% or 15% SDS-PAGE gels. For Pop6-HARNA-IP and northern blot analyses were performed as described in CEN4 genomic locus (primers: 5′-ATGCTGTCTCACCATAGAGAAT-3′ and 5′-CGCTCCTAGGTAGTGCTTT-3′). Probes for hybridization were obtained by random priming labeling procedure (After selection for cells that had lost pAZ1(TLC1 WT) on 5-FOA plates and consecutive streaking on selective media up to the desired generations, cells from indicated passages were grown in liquid media. Genomic DNA was extracted, digested with XhoI, subjected to agarose gel electrophoresis (0.75% agarose), transferred to a nylon membrane, and hybridized to a 300 bp fragment containing 280 bp of telomeric repeats derived from pYLPV (pCT300)  and a 44rocedure . Data we2). Then, the samples were reacted with either 10 mM N-methylisatoic anhydride (NMIA) or DMSO for 30 min at 37°C. Reverse transcription reactions were performed with InVitrogen SuperScript-III RT according to the supplier's protocol. Gels were exposed on GE phosphorScreen and scanned. Nucleotide reactivity was analyzed by QuantityOne. After background adjustment, the reactivity ratio between treated (10 mM NMIA) and untreated (DMSO) molecules was calculated for each position. To normalize the reactivity pattern, each nucleotide was compared to the highest reactivity value (A21-WT), thus giving a ratio from 0 to 1, where a value between 0.2 and 0.4 was considered significantly reactive and values above 0.4 were considered highly reactive.Wild-type and mutant  RNAs were T7-transcribed from a DNA template with a RT primer binding site at the 3′ end (CGCGGAGCTAAAGAGAAGCGGAAG), essentially as described before . For the32P] dGTP was monitored to determine telomerase activity. Extension products were separated on 18% polyacrylamide/8 M urea electrophoresis gels and visualized using a Typhoon FLA9000 apparatus . As internal controls, 12-nt (5′-TTAGGGTTAGGG-3′) and 16-nt (5′-TAGGGTAGTAGTAGGG-3′) primers were 5′-end labeled and added to the samples before ethanol precipitation at 2000 cpm/µL. Quantification was performed using the Quantity One program (Bio-Rad) by adding telomerase extension products signals and dividing them by the loading control signals to give relative telomerase activity (RTA) ratios with respect to wild-type conditions.Yeast telomerase activity assays were carried out as previously described  with 10%Supplemental material is available for this article.