Mutation detection in clinical tumour samples is challenging when the proportion of tumour cells, and thus mutant alleles, is low. The limited sensitivity of conventional sequencing necessitates the adoption of more sensitive approaches. High resolution melting (HRM) is more sensitive than sequencing but identification of the mutation is desirable, particularly when it is important to discriminate false positives due to PCR errors or template degradation from true mutations.We thus developed limited copy number - high resolution melting (LCN-HRM) which applies limiting dilution to HRM. Multiple replicate reactions with a limited number of target sequences per reaction allow low level mutations to be detected. The dilutions used  are chosen such that mutations, if present, can be detected by the direct sequencing of amplicons with aberrant melting patterns.Using cell lines heterozygous for mutations, we found that the mutations were not readily detected when they comprised 10% of total alleles (20% tumour cells) by sequencing, whereas they were readily detectable at 5% total alleles by standard HRM. LCN-HRM allowed these mutations to be identified by direct sequencing of those positive reactions.KRAS exon 2 and EGFR exons 19 and 21. Both true mutations present at low levels and sequence changes due to artefacts were detected by LCN-HRM. The use of high fidelity polymerases showed that the majority of the artefacts were derived from the damaged template rather than replication errors during amplification.LCN-HRM was then used to review formalin-fixed paraffin-embedded (FFPE) clinical samples showing discordant findings between sequencing and HRM for LCN-HRM bridges the sensitivity gap between HRM and sequencing and is effective in distinguishing between artefacts and true mutations. The recent demonstrations of the clinical benefits of molecularly targeted therapies ,2 have gDideoxynucleotide sequencing is often considered the gold standard for detection of genetic changes as it allows these changes to be directly characterised. However, to be reliably detected, changes are required to be present at a proportion of at least 10-20% at the allelic level . Thus, lEGFR and KRAS mutations, although the principles can be extended to mutations in any gene. Reported techniques available for detection of mutations in these genes include; dideoxynucleotide sequencing, single strand conformation analysis [Various PCR-based techniques for detecting sequence variation have been reported, demonstrating both advantages and disadvantages in terms of sensitivity, simplicity, cost-efficiency and robustness. This article will focus on the detection of analysis , TaqMan analysis , amplifianalysis , denaturanalysis , pyroseqanalysis , massiveanalysis ,11, coldanalysis , mutant-analysis  and highanalysis ,15.KRAS mutations were able to be detected at levels as low as 5% by HRM [High resolution melting (HRM) is an in-tube scanning methodology that detects sequence variation by monitoring the melting behaviour of PCR amplicons using DNA intercalating fluorescent dyes. HRM has been used for a variety of genetic and epigenetic studies -18. It h% by HRM .Like other scanning methods, HRM results often need to be confirmed and characterised by a sequencing methodology. Dideoxynucleotide sequencing is the most commonly used methodology. Discordant results between sequencing and HRM may be anticipated if the mutant alleles are present at 5 to 20% due to the different sensitivity of the two methods.In this study, we report a new method, LCN-HRM, for detection and subsequent identification by sequencing of low levels of sequence variation, particularly those that are only detectable by HRM. The basic principle of this methodology is that low level mutant alleles which cannot be detected in the presence of large amounts of normal alleles are present at higher proportions when the sample is diluted at low copy numbers in multiple aliquots (limiting dilution) ,21. The KRAS exon 2 missense mutation whereas NCI-H1650 harbours a EGFR exon 19 deletion mutation. Peripheral blood from four normal individuals was used as a source of DNA for the quantitative estimation of target copy number and as normal DNA for the cell line dilution experiments. Genomic DNA was extracted from the cell lines and peripheral blood using the QIAamp DNA blood kit  according to the manufacturer's instructions. DNA was quantified with a NanoDrop ND-1000 Fluorospectrometer . Four formalin-fixed paraffin-embedded (FFPE) DNA samples from non-small cell lung cancer (NSCLC) patients were included to investigate the cause of previously reported discrepancies between HRM and sequencing results [This study was covered by an approval from the Peter MacCallum Cancer Centre Ethics Committee (project number 03/90). Two cancer cell lines, HCT116 and NCI-H1650, were used. HCT116 contains a  results .KRAS exon 2 [EGFR exon 19 [KRAS exon 2 were as follows. The reaction mixture  contained the template, 1× PCR buffer, 2.5 mM MgCl2, 200 nM each primer, 200 μM dNTPs, 5 μM SYTO 9  and 0.5 U HotStarTaq (Qiagen). The cycling and melting conditions were; one cycle of 95°C for 15 minutes; 55 cycles of 95°C for 10 seconds, 67.5°C for 5 seconds with an initial 10 cycles of touchdown from 67.5°C to 57.5°C (1°C/cycle), 72°C for 20 seconds; one cycle of 97°C for one minute and a melt from 70°C to 95°C rising 0.2°C per second. For LCN-HRM, the conditions were the same except that 60 cycles of amplification were used. The cycling conditions for the EGFR exon 19 assay were identical except that the initial annealing temperature was 65°C. The melting profiles of amplicons were analysed using the Rotor-Gene Software (v1.7).Real time PCR amplification and HRM were performed on the Rotor-Gene Q . The HRM primers for S exon 2  and EGFR exon 19  generateKRAS primers which generated a 189 bp product [EGFR primers which generated a 250 bp product [The amount of amplifiable template for each DNA sample is most accurately estimated by qPCR, particularly when an accurate dilution series is required. For high quality DNA, any amplicon should yield similar results. We used previously reported  product  and EGFR product . PCR conWhen dealing with FFPE specimens, the degree of fragmentation will affect the amount of template molecules that can be amplified. The effective copy number of amplifiable template for each DNA sample is again most accurately estimated by qPCR. In high quality DNA, there is an average of one copy of an autosomal gene per 3 pg of DNA. The effective copy number in the sample is obtained by comparing the Ct of the sample with the Ct value of a high quality reference. To correct for the variable amounts of DNA fragmentation, the amplicon used for the estimation needs to be in the same size range as the amplicons being screened for mutations. It is ideal to use the same amplicon that is being screened.Cts) was compared to the Ct value of reference DNA (Ctref) of a known concentration. The comparative quantitation analysis of the Rotor-Gene software was used to calculate the PCR efficiency (E) and the relative amounts of amplifiable template are related the formula ECtref - Cts) per reaction. To estimate the necessary dilution, the Ct value of the sample  were used to assess the relative sensitivity of DNA sequencing and HRM. The sensitivity testing was performed with primers and conditions for the 189 bp KRAS product as above. Sequencing reactions for each DNA dilution were performed using the Big Dye Terminator v3.1  and the results were analysed using Sequencher 4.6 .Dilutions of the KRAS and EGFR mutant cell lines, HCT116 and NCI-H1650, were used to show that LCN-HRM can detect low levels of different types of mutations (missense mutations and deletions respectively) and also to show that the mutations can be characterised by subsequent sequencing of individual LCN-HRM positive reactions.The Each cell line DNA was initially diluted at 5% mutant allele frequency by mixing with normal peripheral blood DNA based on qPCR data. The 5% cell line DNA mixtures were then further diluted to an estimate of average four copies in a one microlitre volume. Both cell line DNA dilutions were tested by LCN-HRM in 65 replicates with known positive and negative controls.The frequency of a mutant allele may be estimated by analysis of LCN-HRM reactions. The frequency of LCN-HRM positive reactions approximates the amount of mutant alleles present in the sample when the mutation frequency is low.For example, if 25 out of 72 LCN-HRM reactions (which were tested with an average of four copies per reaction) were scored as positive by melting curve analysis, the estimated frequency of the mutant allele would be 8.7% {25/(72 × 4)}. As the frequency of the mutant allele increases or the average copy number per reaction increases, this formula will become less accurate due to the possibility of two mutant sequences being found in one reaction.EGFR mutations by HRM but not sequencing and the last sample was positive for KRAS mutation by HRM but not sequencing. We tested those samples by LCN-HRM to review the discrepancies between HRM and the sequencing results. KRAS exon 2 LCN-HRM conditions were as above. TX13 was tested for mutations in EGFR exon 19 (250 bp product), and TX49 and TX86 were screened for mutations in EGFR exon 21 (212 bp product). EGFR LCN-HRM assays were carried out as previously described for HRM assays [DNA was previously extracted from four selected NSCLC samples  . The firM assays  except tPositive reactions showing aberrant melting profiles were selected and individually sequenced to verify the LCN-HRM results. The selected LCN-HRM products were directly column-purified using the PCR-M clean up kit  and were eluted in a final volume of 30 μl.EGFR exon 21 using the two kits. LCN-HRM was performed on the Rotor-Gene Q for both.Two different reagent kits with proofreading activity were assessed for their ability to accurately detect mutations: the FastStart High Fidelity PCR System (Roche) and HotStar HiFidelity polymerase (Qiagen). The fidelity was reported to be approximately four-fold (FastStart High Fidelity System) and ten-fold (HotStar HiFidelity) higher than HotStarTaq DNA polymerase (Qiagen). TX84 DNA was tested using LCN-HRM for 2, 200 nM each primer, 200 μM dNTPs, 5 μM SYTO 9, 1 U FastStart High Fidelity polymerase. The cycling conditions were; one cycle of 95°C for 2 minutes; 60 cycles of 95°C for 10 seconds, 65°C for 10 seconds with an initial 10 cycles of touchdown (1°C/cycle), 72°C for 30 seconds; one cycle of 97°C for one minute and a melt from 70°C to 95°C rising 0.2°C per second.For the FastStart High Fidelity PCR System (Roche), the reaction mixture in a final volume of 20 μl contained; 1× PCR buffer, 2.5 mM MgCl4, 200 nM each primer, 1.5 mM dNTPs, 5 μM SYTO 9, 0.5 U HotStar HiFidelity polymerase. The cycling conditions were; one cycle of 95°C for 5 minutes; 60 cycles of 95°C for 10 seconds, 67.5°C for 10 seconds with an initial 10 cycles of touchdown (1°C/cycle), 72°C for 60 seconds; one cycle of 97°C for one minute and a melt from 70°C to 95°C rising 0.2°C per second. All conditions were tested in 64 replicates.For HotStar HiFidelity enzyme (Qiagen), the reaction mixture in a final volume of 20 μl contained; 1× PCR buffer, 1.5 mM MgSOKRAS mutation) in normal DNA. To ensure the maximum accuracy in the sensitivity determination, qPCR of the KRAS amplicon was used to estimate the effective concentration of each DNA sample. The HCT116 cell line DNA was then serially diluted into normal DNA at ratios of 40%, 20%, 10% and 2% to give mutant allele frequencies of 20%, 10%, 5% and 1%.The relative sensitivity of mutation detection by dideoxynucleotide sequencing and HRM was compared using dilutions of HCT116 DNA . The same DNA mixtures were tested by LCN-HRM with an estimate of average of three copies of template per reaction. Melting curve analysis of LCN-HRM amplicons led to the identification of positive reactions which were expected to contain mutant alleles. 8/58 LCN-HRM reactions of the 5% HCT116 DNA mixture and 12/59 reactions of the 5% NCI-H1650 DNA mixture showed aberrant melting. Subsequent sequencing of those positive reactions clearly showed the presence of the c.38G>A KRAS mutation and delE746_A750 EGFR mutation respectively } and 6.7% with seven copies {30 LCN-HRM positive/(64 × 7)}. The same KRAS mutation, c.34G>T (p.G12C), was repeatedly detected when individual LCN-HRM positive reactions (9 from the reactions with four copies and 10 from the reactions with seven copies) were sequenced  has been frequently reported. This illustrates the potential dangers of working from just one sequence in a digital or low copy number situation.Non-identical EGFR exons 19 (TX13) and 21 . After sequencing the LCM-HRM positive products, multiple non-identical sequence variants at different positions were detected in all three samples. Those sequence variants are highly likely to be artefacts. A total of 5 different EGFR sequence variants, four exonic and one intronic, were found in TX13  and ten-fold  higher compared to the Taq polymerase.As the LCN-HRM assays were carried out with a Taq polymerase lacking proofreading activity (HotStar Taq) was used, nine out of 58 reactions (15.5%) were positive by LCN-HRM. A similar LCN-HRM positive rate was detected with the FastStart High Fidelity enzyme. Five out of 32 reactions (15.6%) were positive. Surprisingly, the highest LCN-HRM positive rate was found with the HotStar HiFidelity enzyme. Twenty-eight of 53 (52.8%) reactions were positive by LCN-HRM (Table One DNA sample (TX86) was tested with all three polymerases. When the Numerous non-identical sequence variants were detected in the sequencing of those 42 LCN-HRM positive reactions  in 19 multiple independent LCN-HRM replicates proves that the discordant results originated from the different sensitivity of the two methods.One sample, TX450, was selected for LCN-HRM analysis because although it was sequencing negative for a Another possible cause of discrepancy between HRM and sequencing is due to PCR artefacts as various non-identical sequence variations were identified in the other three FFPE samples tested. Artificial sequence changes are reportedly mediated by DNA polymerase error and/or damaged DNA templates ,23. A vaEGFR exon 21 assay using a FFPE sample, TX86, which had previously shown aberrant HRM melting profiles. The rate of PCR artefacts (which were confirmed by sequencing) was not reduced as the fidelity of DNA polymerase was increased .To understand whether the fidelity of DNA polymerase is associated with the generation of PCR artefacts, we used three DNA polymerase kits possessing different levels of proofreading activity. The frequency of LCN-HRM positive reactions was compared in the It is interesting that a higher LCN-HRM positive rate is seen in LCN-HRM performed with the DNA polymerase kit having the highest proofreading activity. This may be explained by considering that mutation-prone translesional extension at damaged DNA sites occurred more frequently, resulting in subsequent generation of more artefactual changes. The occurrence of translesional synthesis at abasic sites has been previously reported with a Taq polymerase with proofreading activity .KRAS mutation (c.34G>T) detected in multiple independent LCN-HRM products amplified from the TX450 can be considered as a true mutation. However, any variations that fail to be confirmed would be more appropriately interpreted as PCR artefacts as seen in TX13, TX49 and TX86  sites of mutation over those mutations that occur at non-canonical sites. Using these criteria, the identical ation c.3G>T detecFixation of tissue specimens in neutral buffered formalin (10%) is a widely used preservation method as it helps to maintain morphological features . The advAlthough the exact mechanism for the artefacts has not been elucidated, several explanations are possible. Firstly, adenosine residues tend to be incorporated complementary to damaged or cross-linked cytosine nucleotides, due to the so-called "A-rule", generating G to A (or C to T) mutations ,31. In tEGFR mutations in 177 NSCLC patients, comprising 13 deletions and 32 point mutations [As FFPE tissue is frequently used for genetic analysis, the results should thus always be cautiously interpreted. Tsao et al. reported an incidence of 45 utations . Howeverutations ,35, whicEGFR mutations were reported in both the stromal and epithelial tissue in breast cancer [TP53 mutations in both the stromal and epithelial tissue in breast cancer [TP53 mutations were detected in stroma of 17 breast cancer or breast cancer-associated fibroblast cultures [Recently, a large number of non-canonical t cancer . The samt cancer . Howevercultures . The vascultures ,40.In many cases, mutation analysis of FFPE samples in routine diagnostic situations involves low copy numbers being amplified due to the combination of limited amounts of template and degradation of DNA. Thus, a low copy number may arise inadvertently. Such cases are usually marked by late amplification and often by heterogeneity of melting patterns between samples. Interpretation is similar to that above. Sequencing is necessary to interpret the results and the presence of a mutational change must be confirmed using sequencing of independent reactions. In some cases, further dilution may be warranted to optimise the copy number being analysed.In conclusion, we have developed a new screening method, LCN-HRM, for detection of low levels of sequence variation. Analysis of multiple replicates of low copy numbers of template allows both the detection of templates with variant sequence (mutations) and enables sequencing to identify the precise changes involved.The previously reported discrepant results between HRM and sequencing are often due to low level mutant alleles but artefacts due to amplification of low copy numbers or to damaged DNA from FFPE tissues must also be considered. The interpretation of LCN-HRM results should thus be based on the reproducibility and position of detected sequence changes.The authors declare that they have no competing interests.HD participated in the study design, carried out the molecular genetic studies and co-wrote the manuscript. AD conceived the study, participated in the study design and co-wrote the manuscript. Both authors read and approved the final manuscript.


Transcriptional termination of mammalian RNA polymerase II (Pol II) is an essential but little-understood step in protein-coding gene expression. Mechanistically, termination by all DNA-dependent RNA polymerases can be reduced to two steps, namely release of the RNA transcript and release of the DNA template. Using a simple nuclear fractionation procedure, we have monitored transcript and template release in the context of both natural and artificial Pol II terminator sequences. We describe the timing and relationship between these events and in so doing establish the roles of the poly(A) signal, cotranscriptional RNA cleavage events, and 5′-3′ exonucleolytic RNA degradation in the mammalian Pol II termination process. Transcriptional termination (referred to hereafter as termination) is the ultimate step in the transcription cycle, which consists of three phases: transcriptional initiation, which involves the association of RNA polymerase with the DNA template; transcriptional elongation, in which the tight association of polymerase with the DNA template is maintained as the polymerase progresses through the body of the gene; and finally termination, when dissociation of the polymerase and DNA template takes place.E. coli RNA polymerase has resulted in a detailed description of the mechanism of prokaryotic termination  signal is required for Pol II termination, it has been known that major determinants of termination are the signals that organize processing of the pre-mRNA. This paradoxical situation, in which one process (pre-mRNA processing) appears to control another quite different process (transcription), is now explained by the understanding that transcription and processing of pre-mRNA are intimately linked processes occurring in a complex in which Pol II is just one component . It has Pol II termination involves several components: the poly(A) signal, pre-mRNA cleavage (at the poly[A] site or downstream sequences), pre-mRNA degradation, and specific terminator elements. However, a simple model for the mechanism of the termination process is that it involves two steps, namely transcript (RNA) release and template (DNA) release . Here weWe have examined the timing of events in pre-mRNA 3′ end processing and Pol II termination using the human β-globin gene as a model system. We employed a nascent pre-mRNA fractionation technique , subsequWe first examined the nuclear distribution of pre-mRNA derived from a construct that supports efficient Pol II termination. Nuclear run-on (NRO) analysis was employed to measure Pol II termination efficiency. HeLa cells were transiently transfected with βTERM, a construct that contains the full β-globin gene and terminator element (TERM), with transcription driven by the HIV-1 promoter activated by cotransfection of a Tat expression vector. NRO analysis of these transfected cells B shows sTo dissect the termination process at the β-globin terminator, we subjected HeLa cells transfected with βTERM to nuclear fractionation using the technique outlined above A. FollowTo further analyze the relation of transcript release to Pol II termination, we next carried out nuclear fractionation analysis of pre-mRNA from a construct, labeled βΔTERM, a derivative of βTERM from which the terminator element has been deleted  site in transcript release using a construct labeled βTERMΔpA, a derivative of βTERM containing a mutation that functionally inactivates the poly(A) site  downstream of the β-globin poly(A) site enhances termination, possibly through transcriptional pausing of Pol II . To confTo dissect the termination process on the βMAZ4 construct, we again conducted nuclear fractionation of transcripts from HeLa cells that had been transiently transfected with βMAZ4. Pre-mRNA from template and released fractions was subjected to RT-PCR analysis B as descWe next analyzed the nuclear distribution of βRZMAZ4 pre-mRNAs using RT-PCR analysis as above. The resulting PCR products are displayed in To examine whether the enhancement of transcript release by the introduction of the RZ was dependent on the presence of a functional poly(A) site, we next mutated the poly(A) signal in βRZMAZ4, forming βRZMAZ4ΔpA. NRO analysis of HeLa cells transiently transfected with βRZMAZ4ΔpA shows strong hybridization signals over the extragenic probes A and U3  site or RZ cleavage largely occurs when Pol II is associated with the DNA template. Degradation of the transcript then leads to template release. This explains how CoTC events in the β-globin terminator transcript lead to Pol II template release before cleavage at the β-globin poly(A) site has occurred.We next sought to determine when the released unprocessed pre-mRNAs, observed by nuclear fractionation analysis of βTERM C and βRZWe wished to provide more direct evidence that the pre-mRNA detected in the released fraction is still tethered to the released (terminated) Pol II complex. RNA immunoprecipitation (RIP) was employed to compare the abundance of unprocessed nascent transcripts associated with Pol II in cells transfected with constructs that did (βRZMAZ4) or did not (βMAZ4) promote transcript release. HeLa cells were transfected with βRZMAZ4 or βMAZ4 and subjected to formaldehyde crosslinking. After cell lysis and sonication of nucleic acids, a Pol II-specific antibody was used to immunoprecipitate Pol II-associated RNA. This RNA was then used as a template for RT-PCR analysis. cDNA synthesis was primed using primers 3′pA and F3′ to detect the 5′ and 3′ sections of the pre-mRNA from both samples. The resulting cDNAs were then real-time PCR amplified using the corresponding 5′pA/3′pA and F5′/F3′ primer pairs  site recognition in the Pol II termination process. To do this, we designed a new construct, labeled β5′RZ3′RZMAZ4, in which ribozymes were positioned both upstream and downstream of the poly(A) site  site  signal flanked by RZs, in β5′RZ3′RZMAZ4, was still able to function as a transcriptional termination signal using NRO analysis. Examination of the transcription profile of β5′RZ3′RZMAZ4 D shows strans-acting protein factors in this process  signal is required for Pol II termination , subsequ process . It has  process .For the human β-globin gene A, transcPol II termination on genes where there is no CoTC-termination element, and therefore no exonuclease entry site downstream of the poly(A) site, involves a different sequence of events B. Our reMost interestingly, our data show that Pol II termination on the human β-globin gene occurs prior to cleavage at the poly(A) site, for a significant fraction of the pre-mRNA. For these pre-mRNAs, poly(A) site cleavage could occur independently of the Pol II complex or, alternatively, together with the polymerase as part of a binary complex A. Our reWe have resolved a number of questions concerning Pol II termination. We have shown that poly(A) site recognition occurs rapidly and is essential to render Pol II termination competent. We also show, by RNA-mapping experiments, that 5′-3′ exonucleolytic degradation of cleaved pre-mRNA precedes Pol II template release. However, cleavage at the poly(A) site, which allows an entry point for 5′-3′ exonuclease, is only required in the absence of a downstream transcript cleavage event. We have demonstrated that Pol II termination occurs by a combination of the two original models for the poly(A) site dependence of Pol II termination, which were (1) that Pol II termination occurs in response to changes in the Pol II complex brought about by transcription of the poly(A) signal , and (2)A list of oligonucleotide sequences used as PCR primers is given in the 4 construct mut plasmids . βMAZ4 construct . VA and onstruct . βRZMAZ4Transient transfection of HeLa cells was performed as described previously .Nuclear RNA fractionation was performed as described .NRO analysis and single-stranded M13 probes used are as described previously . QuantitThe plasmid template and in vitro transcription conditions used for synthesizing the exon 3 selection probe and the protocol for magnetic selection of RNA hybrids have been described previously .cDNA was synthesized using SuperScript III (Invitrogen). DNA amplification was performed using Taq DNA polymerase or, when conducting real-time PCR, using a QIAGEN SYBR Green kit. All quantitations of real-time PCR products are based on the average of multiple experiments.In brief, the protocol of


Additional insights into patient preferences can be gained by supplementing discrete choice experiments with best-worst choice tasks. However, there are no empirical studies illustrating the relative advantages of the various methods of analysis within a random utility framework.Multinomial and weighted least squares regression models were estimated for a discrete choice experiment. The discrete choice experiment incorporated a best-worst study and was conducted in a UK NHS dermatology context. Waiting time, expertise of doctor, convenience of attending and perceived thoroughness of care were varied across 16 hypothetical appointments. Sample level preferences were estimated for all models and differences between patient subgroups were investigated using covariate-adjusted multinomial logistic regression.per se had the same impact upon choices as those with lower levels of attainment. The study also demonstrated the high levels of agreement between summary analyses using weighted least squares and estimates from multinomial models.A high level of agreement was observed between results from the paired model  and the marginal model (which is only an approximation to it). Adjusting for covariates showed that patients who felt particularly affected by their skin condition during the previous week displayed extreme preference for short/no waiting time and were less concerned about other aspects of the appointment. Higher levels of educational attainment were associated with larger differences in utility between the levels of all attributes, although the attributes per se. The good approximation of summary analyses to the multinomial model is a useful finding, because weighted least squares choice totals give better insights into the choice model and promote greater familiarity with the preference data.Robust policy-relevant information on preferences can be obtained from discrete choice experiments incorporating best-worst questions with relatively small sample sizes. The separation of the effects due to attribute impact from the position of levels on the latent utility scale is not possible using traditional discrete choice experiments. This separation is important because health policies to change the levels of attributes in health care may be very different from those aiming to change the attribute impact  Consequently, the utility estimates represent a set of deviations that cannot be used directly to make statements about the overall impact of attributes [Discrete choice experiments elicit people's preferences for goods or services based on intentions expressed in hypothetical situations . In tradtributes .Certain issues in Health Services Research require analysts to compare the overall impact of attributes. An example would be investigating the contention that "waiting time for an appointment is more important to patients than continuity of care" – a statement purely about attributes, with no reference to the associated levels. The issue of separating attribute impact weights and scales is essentially equivalent to estimating the utility associated with a particular attribute per se (its weight or impact in a utility function) separately from the additional utility gained/taken away by that attribute exhibiting an attractive/unattractive level . This issue has been explored and several methods now are available to help address it in the context of traditional choice experiments .Best-worst scaling , developVarious methods of analysis of best-worst choice data in a random utility framework have been described . BecauseThe additional information provided by best-worst scaling compared with a traditional choice model is useful to the researcher in three ways.1. Most importantly, asking about worst as well as best elicits more information about the respondent's utility function. This increases the researcher's ability to characterise heterogeneity in preferences and classify respondents into internally homogeneous groups. In certain circumstances best-worst methods can even be used to estimate individual-level utilities .2. For a given attribute, all of the level scale values are estimated  . This al3. When effects coding (rather than a dummy variable approach) is used to estimate the level scale values: the econometric model automatically estimates the statistical significance of both level scales and the overall attribute impact.A second issue worthy of exposition concerns the choice of regression model. Four models have been proposed for the analysis of best-worst scaling data in a random utility framework  – the reTherefore this paper has two aims:1. to illustrate, for the first time in a health or medical context, the ability of best-worst scaling to estimate sub-group preferences in terms of differences in both attribute impacts and level scale values,2. to offer recommendations on choice of analytic model and in particular to demonstrate the validity of least squares methods for aggregated analysesThe paper addresses these issues and demonstrates the flexibility of best-worst scaling methods in unbalanced designs (where the number of levels per attribute is not constant). Best-worst scaling methods, including a summary of the empirical case study, will be described first, followed by the results. The paper will conclude with the implications of this work.The empirical work was undertaken in the context of a project aimed at quantifying preferences for different aspects of access to dermatology secondary care services . The disConstruction of an appropriate design is described elsewhere,  and two Best-worst scaling data can be analysed in many ways . In the K attributes where nk represents the number of levels of attribute k, the total number of possible outcomes (pairs) in a main effects design is therefore 2 clogit command in Stata with cluster-adjusted (robust) standard errors [The paired method of analysis treats each unique best-worst pair as a unique choice outcome (where order matters). In a design with d errors . This red errors ,21. Effei  and the nine independent variables: three estimated impact and six estimated level scale parameters:The equation below sets out the relationship between the difference in utility between best and worst  model of choices. In particular, it assumes that for a given pair of attribute levels, the difference in utility simply changes sign when the best-worst choice is reversed. This can only be true if the distribution of the error term on the latent utility scale is symmetrical : the gumOne aim of the study was to estimate the effect of respondent characteristics  on utilities, which requires respondent-level choice data. Limited dependent variable models require differences in the probabilities of choice for the various outcomes in a choice set to be associated with differences in the explanatory variables. Respondent characteristics like age do not vary for potential best-worst pairs or attribute levels in a choice set; hence, they cannot affect choice probabilities and cannot be separated from the overall regression constant term. Thus, covariates are interacted with choice outcomes . These took the form of covariate-attribute impact interactions and covariate-level scale interactions. The former represented the additional impact a given attribute had upon the particular clinical-sociodemographic group whilst the latter represented the additional level scale utility derived by the particular patient group.Given that the marginal model is an approximation to the paired (maxdiff) choice model, inference about the effects of respondent-level covariates on preference is reported for the paired model. However, major differences that arose from using the marginal model also are reported. In terms of sample size, given that the original trial was not powered to detect differences between subgroups, it was decided to be conservative in all analyses and reporting. Therefore, respondents who did not provide complete choice and socioeconomic data were omitted. A series of regressions which partially adjusted for each of the socioeconomic/clinical factors listed below were conducted:• Age 60+• Left fulltime education at age 19+• In fulltime employment• Reporting severe problems on at least one item of the DLQI skin quality of life scale in the previous week• Being an 'acute' case • Being a 'chronic' case (having first seen their GP over a year previously)Influential covariates were then entered into a fully adjusted model. Given that best-worst scaling distinguishes between two types of preference – the attribute impact and the level scale values – statistically significant effects for either are reported.Discrete choice experiments in health economics usually have been analysed using limited dependent variable models like probit regression. Using weighted least squares regression on the (logged) choice frequencies would leave few, if any, degrees of freedom; for example, for the short questionnaire in this study mple size, which iOf the 119 individuals who received the 16-appointment questionnaire, 93 provided best-worst data that allowed estimation using any of the methods and 60 individuals provided complete best-worst choice data. Five of the latter individuals did not provide complete socioeconomic information; so, to be conservative, all analyses reported below pertain to the 55 who provided complete data. The minimum number of appointments answered was five whilst 85 individuals answered 14, 15 or 16 appointments. Stata chooses an attribute impact variable arbitrarily to drop in order to prevent the model being saturated. Therefore, once the least valued attribute was identified, all analyses were performed with this attribute impact omitted to ease interpretation.Table Waiting time was the attribute with least impact and its impact weight is therefore omitted – impact figures for the other three attributes therefore are relative to waiting time . Doctor expertise is clearly the most highly valued attribute, whilst convenience is valued slightly more than thoroughness of care. The result of separating overall attribute impact from level scale values is clear: whilst thoroughness of care is not the most important attribute per se, the two levels are very far apart on the utility scale. In contrast, for convenience of attending there is a difference of 2 × 2.53 = 5.06 units between the levels of thoroughness of care but only 2 × 1.02 = 2.04 units between the levels of convenience. This illustrates a key advantage of best-worst scaling over traditional discrete choice experiments: in the latter, only these differences between the levels are estimable.Table The only non-significant estimate in Table All covariates except age and employment status had at least one statistically significant effect upon preferences. The fully adjusted model therefore includes all interactions between attribute impact weights and level scale values for the remaining covariates. In the fully adjusted model being a 'chronic' case was associated with nonsignificant effects on all preferences, so all effects related to that covariate were omitted. Table Those who left higher education at age 19 or older exhibited 'widening' of the level scale values for all four attributes, although this did not reach significance at the 5% level for doctor expertise and convenience, but the attribute impacts were not significantly different on average. A possible explanation for this result concerns the association often observed between educational attainment and social class and/or income. Thus, it might be expected that greater access to alternative sources of health care  might mean that respondents with higher education experience greater differences in utility associated with levels of the attributes.Those with at least one of the ten factors severely disrupted by their skin condition or those with a total score of seven or more out of 30 on the DLQI   affected preferences in various ways. Like patients with a score of three on any DLQI item, this group had a strong preference for no waiting time (demonstrated by the lower utilities associated with the three lower levels). However, they also exhibited widening of the level scale values for the other three attributes, indicating that they are more willing to trade waiting time for changes in these than those who believe aspects of their daily lives are severely affected by their skin condition. These three attributes also have a higher impact on average.Figure 2 = 0.96. The high correlation also is apparent . This is encouraging, given that the marginal model weighted least squares regression has only 20 observations (a best and a worst frequency for each of the ten attribute levels).The two sets of parameter estimates are highly correlated, with RThis study is the first in health services research to separate the impact of attributes per se from their level scale values for various subgroups. It demonstrated that having self-reported severe skin problems narrows the range of scale values for non-waiting time attributes. There was a suggestion that certain socioeconomic factors, most notably leaving fulltime education at age 19+, caused the range of scale values to widen, leaving attribute impacts unchanged. Both sets of findings have intuitive explanations but given the relatively small sample they should be investigated further.The study also provides guidance about choice of analytic model. It demonstrated that although the marginal method of analysis makes potentially unwarranted assumptions about independence of best and worst choices and the nature of the error terms in the utility model, it provides a good approximation to the paired (maxdiff) model analysis, suggesting that the resulting estimates are consistent. Furthermore, the study demonstrates the flexibility and accuracy of aggregated analysis with as few as twenty observations when factors are manipulated according to a well-conditioned design matrix. In other words, multicollinearity problems and lack of variability in key factors that necessitate large datasets in many econometric and epidemiological studies do not apply. Agreement between weighted least squares and conditional logistic regression was high, and the benefits of effects coding in a best-worst context were illustrated.The sample size underlying the results was relatively small, which was due to a desire to be conservative in reporting results by excluding patients without full socio-demographic and choice data. However, similar findings were apparent  in analyses conducted among the 93 patients who provided at least some choice data.This study, like all discrete choice experiments, induced clustering in the data by obtaining multiple responses from individuals: two responses from the same individual tended to be more similar than two responses obtained from different individuals. Accounting for clustering via robust/sandwich/Huber-White procedures inflates the standard errors by the correlation in the error terms. Thus, it does not explicitly model heterogeneity in responses. However, the most popular approaches to modelling respondent-specific effects (random effects models) potentially are misleading. Not only do these models ignore other factors that might lead to variation in choice behaviour, virtually all published applications implicitly assumed constant error variances within and between individual responses. If the error variances do vary then the distribution of model estimates is confounded with the distribution of error variances, and the bias can be very large . So, a rMany discrete choice experiments in health services research suffer from designs more appropriate to traditional conjoint-analysis studies in which one tries to estimate individual-level  utilities rather than population parameters. In other words, using a common, small design for all respondents provides data for only a small part of the entire response surface, typically making it impossible to estimate interactions, which would provide more complete statistical information about the indirect utility function and protect the estimated parameters against unobserved effects . To an extent, this criticism can be levelled against the present study: splitting the sample into blocks and administering different versions of the questionnaire which together spanned the full factorial (32) appointments would have addressed this issue. However, practical constraints precluded such a design. In any case, future work will exploit advantages of the current design to investigate individual-level preferences.A final issue concerns anchoring of the utility estimates. The best-worst scaling choice data provide interval-scale estimates with unknown anchor; when total utilities for each appointment are constructed and ranked, analysts cannot know at which point utility becomes positive (indicating that the respondents will choose to attend the appointment rather than not attend). This may or may not be a limitation, depending upon how one wishes to use the estimates. Planning total service provision to match demand would require unconditional demand information, not the conditional demand information that these results provide. However, marginal changes in service provision can be addressed using these results by way of calculating marginal rates of substitution as in a traditional discrete choice experiment . Constructing an outcome or service index based on these results is also possible, but more generally it may be that the need for an anchor necessitates additional information from respondents.One of the aims of this study was to investigate differences in response rates and results between two versions of the questionnaire – one with 8 appointments and one with 16. Differences were found to be minimal , so futuIt should be standard practice to adjust for clustering in responses if using covariate-adjusted conditional logit models to analyse best-worst data. However, if modelling heterogeneity explicitly, it can be argued that it is more logical to exploit the power of best-worst methods to make individual-level inferences  than attempt to specify them as random effects. Indeed, best-worst scaling can model individual-level utility functions without statistically questionable distributional assumptions about preferences . SimilarThe usefulness of attribute impact as a concept is an empirical issue. Because it is simply the arithmetic mean of the levels of an attribute, the impact for an attribute like thoroughness which is defined by its two 'extreme' levels (yes/no) is arguably of little value. However, more generally, attribute impact undoubtedly would be useful to researchers; for example, a non-significant scale value coupled with a very small attribute impact (relative to other attributes) may indicate that an attribute is highly disliked per se and respondents do not perceive any difference between levels. Thus, unlike traditional discrete choice experiments, researchers would know that respondents particularly dislike this attribute per se and that policies that attempt to change patient perceptions of the good/service may be more fruitful.This study also asked respondents whether they would attend each appointment offered them. The results from the responses to this question provide an alternative set of utility estimates . Differences between the two methods will be investigated as will the extent to which the anchor provided by these data can be used to rescale the best-worst data. Future studies will consider utilising qualitative work and simulation studies to ascertain whether the cognitive processes undertaken by respondents provide support for such a data synthesis.This study shows that aggregated methods provide simple compact datasets yet give results that differ little from individual-level analyses. This is a potentially useful result, and one that some applied statisticians  may find surprising, given the multicollinearity problems common to many epidemiological and economic surveys. It also illustrates a key advantage of best-worst scaling over traditional discrete choice experiments – the ability to separate attribute impacts from level scale values. In so doing it provides additional insights over those from traditional discrete choice experiments that should prove attractive in health care research. In particular, this ability to ascertain whether patient subgroups exhibit differences in attribute impact and/or differences in level scale values may have implications for policy.The authors declare that they have no competing interests.TNF carried out all primary data analyses and drafted the paper. JJL designed the methodology, advised on study design and analysis and participated in redrafting of the paper. JC participated in the design and running of the study, and in redrafting of the paper. TJP performed statistical input to the study and participated in redrafting of the paper.The pre-publication history for this paper can be accessed here:


Tobacco Mosaic Virus (TMV-Cg) and Arabidopsis thaliana as a model system, we analyzed the viral small RNA profile in wild-type plants as well as rdr mutants by applying small RNA deep sequencing technology. Over 100,000 TMV-Cg-specific small RNA reads, mostly of 21- (78.4%) and 22-nucleotide (12.9%) in size and originating predominately (79.9%) from the genomic sense RNA strand, were captured at an early infection stage, yielding the first high-resolution small RNA map for a plant virus. The TMV-Cg genome harbored multiple, highly reproducible small RNA-generating hot spots that corresponded to regions with no apparent local hairpin-forming capacity. Significantly, both the rdr1 and rdr6 mutants exhibited globally reduced levels of viral small RNA production as well as reduced strand bias in viral small RNA population, revealing an important role for these host RDRs in viral siRNA biogenesis. In addition, an informatics analysis showed that a large set of host genes could be potentially targeted by TMV-Cg-derived siRNAs for posttranscriptional silencing. Two of such predicted host targets, which encode a cleavage and polyadenylation specificity factor (CPSF30) and an unknown protein similar to translocon-associated protein alpha (TRAP α), respectively, yielded a positive result in cleavage validation by 5′RACE assays. Our data raised the interesting possibility for viral siRNA-mediated virus-host interactions that may contribute to viral pathogenicity and host specificity.RNA silencing functions as an important antiviral defense mechanism in a broad range of eukaryotes. In plants, biogenesis of several classes of endogenous small interfering RNAs (siRNAs) requires RNA-dependent RNA Polymerase (RDR) activities. Members of the RDR family proteins, including RDR1and RDR6, have also been implicated in antiviral defense, although a direct role for RDRs in viral siRNA biogenesis has yet to be demonstrated. Using a crucifer-infecting strain of  Arabidopsis thaliana, a plant model whose genome encodes four DCLs, six RDRs and ten AGOs. At least four distinct small RNA-generating pathways have been identified in Arabidopsis; each associated with a subset of the core silencing factors cis-antisense transcript-associated siRNA (nat-siRNA) and trans-acting siRNA (ta-siRNA) pathways, respectively Most eukaryotes possess a remarkably conserved RNA silencing system in which double-stranded RNA (dsRNA) precursors are processed into 21- ∼24-nucleotide (nt) small RNAs that regulate the activity of genes, genetic elements, and invading viruses in a sequence-specific manner The role of RNA silencing as an ancient antiviral defense mechanism has been firmly established in plants and some animals Turnip Crinkle Virus (TCV). Accumulation of virus-derived small RNAs from TCV, but not those from Cucumber Mosaic Virus (CMV) or Turnip Mosaic Virus (TuMV), was impaired in the Arabidopsis dcl2 mutant concomitant with its hyper-susceptibility to TCV, suggesting a role of DCL2 in viral small RNA biogenesis dcl double and triple mutants uncovered important and partially redundant roles for both DCL4 and DCL2 in viral siRNA biogenesis ta-siRNAs dcl4 mutant or when DCL4 activity is blocked by a silencing suppressor such as the TCV capsid protein (p38), the role of DCL2 in antiviral defense was unmasked with the accumulation of DCL2-dependent 22-nt small RNAs as the major viral siRNA species Recent studies have also shed light on the host RNA silencing machinery in plants that functions in antiviral defense. Among the four DCLs in Arabidopsis, DCL2 was the first family member shown to play a role in antiviral defense against Δ2b) strain, but not the wild type strain of CMV, suggesting that RDR1 activity could be masked by the 2b protein, a CMV-encoded silencing suppressor Despite significant advances in understanding virus-induced RNA silencing, several key aspects concerning the biogenesis and function of virus-derived small RNAs in plants remain obscure. For example, the nature of viral RNA molecules that trigger the host RNA silencing pathway remains unclear. Because dsRNA molecules are known to form as the replicating intermediate of an RNA virus, the dsRNA form of a replicating RNA virus was initially assumed to be the silencing trigger in early models, predicting production of equal amounts of sense and antisense viral siRNAs in infected host cells. However, limited molecular cloning of small RNAs derived from several positive-strand plant RNA viruses has revealed a strong strand bias towards the genomic sense strand, which could argue against the idea of genome-length viral dsRNA as being the sole precursor Tobacco Mosaic Virus (TMV-Cg) and Arabidopsis thaliana as a model virus-host system, virus-derived small RNAs were captured from systemically infected tissues of wild type Arabidopsis (Col-0) as well as rdr1 and rdr6 mutant plants at 3 days post-infection (dpi). Here we report the first high-resolution small RNA map for a plant virus, revealing features of TMV-Cg-derived siRNA populations indicative of the mechanism of their biogenesis. Both RDR1 and RDR6 were found to play important roles in biogenesis of TMV-Cg siRNAs, supporting a model for viral siRNA biogenesis in plants that involves multiple DCL and RDR factors. In addition, a large set of host genes was predicted as potential targets for posttranscriptional silencing by TMV-Cg-derived siRNAs, revealing a layer of virus-host interactions that may contribute to viral pathogenicity and host specificity.To address these questions, we took a small RNA deep sequencing approach to capture and analyze the viral small RNA profile from host plant cells at an early infection stage. Using a crucifer-infecting strain of rdr mutant plants. TMV-Cg infects Arabidopsis systemically and causes mild disease symptoms RDR1 in Arabidopsis rdr1 and rdr6 mutants, respectively  platform (rdr6 infected with TMV-Cg) to 28.8% (Col-0 mock infected) of the total reads, indicating that an indexed sequencing strategy did not create significant bias among the source libraries  was less than 2.8%, allowing reliable across-library comparisons to be made for a specific small RNA component. Small RNAs <18-nt or >25-nt in length  were discarded from further analysis  as well as the platform . Removalplatform . It is wibraries . Remarkaanalysis . A compuanalysis  in suffirdr1 and rdr6 libraries To examine the genomic distribution of the viral small RNAs, small RNAs were mapped to the TMV-Cg genome containing four open reading frames encoding the ∼120 kDa and ∼180 kDa replicase proteins, the ∼30 kDa movement protein (MP), and the ∼17.5 kDa CP, respectively . A genomrdr1 and rdr6 mutant libraries, respectively. In contrast to the abundant viral small RNA reads in the infected wild type library, the rdr1 library  contained substantially less TMV-Cg-derived small RNA reads , although both libraries contained a similar number of small RNA reads of host origin  also contained decreased TMV-Cg-derived small RNA reads  compared to those in the infected wild type library, although to a much lesser extent compared to the rdr1 library  and 22-nt species (12.9%), with the 21-nt species being, by far, the most abundant , indicatpathways . When thpathways . The str species . The ratrdr1 and rdr6 mutant libraries, with a much more profound reduction found for the most part in the rdr1 library  Given the potential sequence complexity of viral siRNAs, it is possible that some of them may target the transcripts of host genes for posttranscriptional regulation. To explore this possibility, an informatics analysis to systemically identify the potential host targets was performed for each of the 21-nt computationally generated TMV-Cg siRNAs. A target prediction algorithm with a scoring stringency similar to those previously used for miRNA target prediction was applied in this procedure  in vitroNicotiana tobaccum orthologs of RDR1 are inducible upon TMV infection or salicylic acid (SA) application and play a role in antiviral defense Nicotiana benthamiana ortholog of RDR1 is an inactive natural variant, which has been postulated to be responsible for N. benthamiana's hyper-susceptibility to many viral pathogens RDR1 was recently shown to be required for production of viral siRNAs derived from a silencing suppressor-deficient CMV mutant (CMV-Δ2b), suggesting that the role of RDR1 could be masked in plants infected with wild type CMV Using a small RNA deep sequencing approach, we demonstrated an important role for Arabidopsis RDR1 and RDR6 in the biogenesis of TMV-Cg-derived siRNAs. The RDR6, on the other hand, was among the first RNA silencing genes recovered in genetic screens for mutants defective in sense transgene-induced posttranscriptional gene silencing (PTGS) N. benthamiana demonstrated a role for RDR6 in limiting the virus from entering shoot apical meristems, likely through promoting virus-specific secondary siRNA production in systemic tissues ta-siRNA pathway in Arabidopsis suggests that RDR6 functions to convert a cleaved transcript into dsRNA, likely in a primer-independent manner in vitrordr6 mutant, an alternative RDR may redundantly function in this postulated pathway, as suggested by the moderate decrease in phased viral siRNA production in the rdr6 mutant.rdr mutants is rather puzzling, since the assumed function of a host RDR protein is to synthesize dsRNA from ssRNA templates. Subsequent processing of dsRNA by DCLs would yield an equal amount of sense and antisense siRNAs, whose half life in the host cell will largely depend on their selective incorporation into an AGO complex. Perhaps the nascent viral RNA strand resulting from a host RDR activity undergoes certain types of chemical modification such as methylation. While such a modification may not affect processing of the resulting dsRNA by a DCL, it may prevent the modified siRNA strand from being efficiently recruited into an AGO complex. For TMV, the positive strand RNA synthesized during an infection could be a hundred-fold more abundant that the negative strand Loss-of-function mutations in either RDR1 or RDR6 led to reduced strand bias, as well as reduced overall abundance of the TMV-Cg-derived small RNA population, suggesting that both of these host RDRs play distinct roles in promoting silencing of the TMV-Cg RNAs. An alteration in strand bias of viral small RNAs in Virus infection can cause a wide range of disease symptoms in a plant host, which is often associated with perturbation of host gene expression in vivo. While mainly evolved as a viral counter defense strategy, various virus-encoded silencing suppressors could also suppress the activity of viral siRNAs on potential host targets. The replicase subunit of TMV  is a potent RNA silencing suppressor in vivoin vitroCPSF30 and TRAPL, respectively, harbored a 5′-terminal A or C, we infer that the nucleolytic activities detected by 5′ RACE were likely from AGO2 and/or AGO5. Finally, the extent to which viral siRNAs could modulate host gene expression will also depend on the abundance of functional viral siRNAs. Since the source materials used for viral small RNA analysis in this study were sampled at an early infection stage, a more profound perturbation of host gene expression may be detected at a later stage when viral siRNAs accumulate to a much higher level. It is currently unclear why certain TMV-Cg-derived siRNAs with better-scored predicted host targets were found at low abundance  and rdr6-15 (SAIL_617H07) mutant alleles have been described previously th true leaves) per plant were manually inoculated with purified TMV-Cg . A parallel set of control plants were mock-inoculated with the buffer following the same procedure. Systemic tissues consisting of leaves and young inflorescences were collected at 3 dpi for RNA extraction. The local inoculated leaves were also collected in parallel for infection analysis. Each sample consists of pooled tissues from a group of 6 plants .The 32P-labeled 491 bp CP-gene fragment . The blot was stripped and re-probed with a 32P-labeled 765 bp cDNA fragment  for Actin.Total RNA extraction, purification, and Northern blots were done essentially as described AC-3′5′- GUUCAGAGUUCUACAGUCCGACGAUC; (2) 5′-CA adapter: CA-3′5′-GUUCAGAGUUCUACAGUCCGACGAUC; (3) 5′-GU adapter: GU-3′5′-GUUCAGAGUUCUACAGUCCGACGAUC; and (4) 5′-UG adapter: UG-3′5′-GUUCAGAGUUCUACAGUCCGACGAUC. The sequence of the 3′ RNA adapter which is 5′-monophosphorylated and 3′-idT blocked is: 5′-P-UCGUAUGCCGUCUUCUGCUUGUidT-3′. The final ligation products were PAGE-purified and reverse transcribed (RT) using SuperScript III reverse transcriptase , with the DNA oligonucleotides 5′-CAAGCAGAAGACGGCATACGA-3′ as the RT primer. The first-strand cDNA was then PCR amplified for 15 cycles using the Phusion high fidelity DNA polymerase , with the primers 5′-CAAGCAGAAGACGGCATACGA-3′ and 5′-AATGATACGGCGACCACCGACAGGTTCAGAGTTCTACAGTCCGA-3′. The amplified cDNA was PAGE-purified, pooled and submitted to Illumina for sequencing.Small RNA isolation and library construction were done essentially as described The small RNA sequences were computationally extracted from the raw sequence tags generated by Illumina and parsed into the four source libraries using Python scripts, based on the 5′-adapter index and the partial 3′-adapter sequence see . For eac5′-TCTGGCTGACCTGGTGTTGTGATT-3′ and CPSF30-576R 5′-TGGCTGGCCTTGCATTGGAACTT-3′. The gene-specific primers used in 5′RACE for TRAP α-like were TRAPL-780R: 5′-GCCCCCTAACAAAGCGTGTGAGAT-3′ and TRAPL-711R: 5′-ACCCTCAAGCCATTCATCATGCGAA-3′. Primers for SCL6-III were described A set of 12,566 TMV-Cg-derived 21-nt siRNAs were computationally generated see . PutativSupplementary Materials and Methods S1(0.33 MB PDF)Click here for additional data file.Table S1Arabidopsis genes predicted as TMV-Cg-siRNA targets.(4.98 MB XLS)Click here for additional data file.Figure S1Detection of TMV-Cg-siRNAs by Northern blot assays. (A) Northern blot assays with probes specific to TMV-Cg-siR696 (+) (upper panel) and TMV-Cg-siR696 (−) (lower panel). DNA oligonucleotides with sequence corresponding to TMV-Cg-siR696 (+) and TMV-Cg-siR696 (−) were load as positive controls in lanes 1 and 2, respectively. (B) Northern blot assays with probes specific to TMV-Cg-siR5293(+).(0.12 MB TIF)Click here for additional data file.Figure S2Additional predicted TMV-Cg-siRNA targets that were selected for validation by RLM-5′RACE. Sequence alignments between the TMV-Cg siRNAs and the respective predicted targets are shown.(0.09 MB TIF)Click here for additional data file.


Different high-throughput sequencing techniques have different reproducible sequence bias and generate different profiles of short RNAs. The Terminator exonuclease does not process double stranded RNA, and because short RNAs can quickly re-anneal at high concentration, this assay can be misleading if the substrate is not denatured and not analysed in a dilution series. The sequence profiles and Terminator digests suggest that CymRSV siRNAs are produced from the structured positive strand rather than from perfect double stranded RNA or by RNA dependent RNA polymerase.A large amount of short interfering RNA (vsiRNA) is generated from plant viruses during infection, but the function, structure and biogenesis of these is not understood. We profiled vsiRNAs using two different high-throughput sequencing platforms and also developed a hybridisation based array approach. The profiles obtained through the Solexa platform and by hybridisation were very similar to each other but different from the 454 profile. Both deep sequencing techniques revealed a strong bias in vsiRNAs for the positive strand of the virus and identified regions on the viral genome that produced vsiRNA in much higher abundance than other regions. The hybridisation approach also showed that the position of highly abundant vsiRNAs was the same in different plant species and in the absence of RDR6. We used the Terminator 5′-Phosphate-Dependent Exonuclease to study the 5′ end of vsiRNAs and showed that a perfect control duplex was not digested by the enzyme without denaturation and that the efficiency of the Terminator was strongly affected by the concentration of the substrate. We found that most vsiRNAs have 5′ monophosphates, which was also confirmed by profiling short RNA libraries following either direct ligation of adapters to the 5′ end of short RNAs or after replacing any potential 5′ ends with monophosphates. The Terminator experiments also showed that vsiRNAs were not perfect duplexes. Using a sensor construct we also found that regions from the viral genome that were complementary to non-abundant vsiRNAs were targeted  Cymbidium ringspot virus (CymRSV) derived short RNAs using three different methods. Profiling of viral short interfering RNAs revealed a different sequence bias for the 454 and Solexa high-throughput sequencing platforms. We also found that viral short RNAs are primarily produced from the positive strand of the virus and produced with very different frequency along the viral genome. The hybridisation approach showed that the profile of viral short RNAs is determined by the virus itself because the profiles were the same in different species and it also showed that the process was RDR6 independent. We used the Terminator exonuclease to study the 5′ end of viral short RNAs and discovered that this enzyme cannot digest double stranded RNA. A control perfect duplex was only partially processed even after denaturation. Since double stranded short RNAs can quickly re-anneal, this assay must be carried out using different concentrations of the substrate. We found that most of the CymRSV short RNAs had 5′ monophosphate and were not perfect duplexes. Taken together, these results suggest that CymRSV short RNAs are produced from the structured positive strand rather than from perfect double stranded RNA or by RNA dependent RNA polymerase. We also found that regions from the viral genome that are not complementary to highly abundant viral short RNAs were targeted in the plant just as efficiently as regions recognised by abundant short RNAs.Viral RNA is processed into short RNAs in plants, which guide a complex to the viral RNA and cause cleavage of the viral RNA. We profiled  The RNA silencing based antiviral plant response is one of the best studied antiviral strategies in plants. The key element of RNA silencing based antiviral strategies is the virus derived small interfering RNA (vsiRNA), which guides the RNA induced silencing complex (RISC) to target viral genomes in plants and invertebrates Plant RNA viruses are strong inducers as well as targets of RNA silencing and high levels of vsiRNAs accumulate during the viral infection. However, despite of the extensive studies of siRNA biogenesis the origin of plant viral siRNA is still not understood. vsiRNAs are thought to be processed from ds viral RNA replication intermediates, local self-complementary ds regions of the viral genome or through the action of RNA-dependent RNA polymerases (RDRs) on viral RNA templates DCL4 and DCL2 are the most important plant DICERs involved in virus induced RNA silencing and they can process ds or hairpin viral RNAs into vsiRNAs of 21 and 22 nt, respectively. Although DCL4 is the major player in vsiRNA production, in the absence of DCL4, DCL2 is also sufficient to produce 22 nt vsiRNA, which are biologically active in antiviral silencing response The accumulation of vsiRNAs may also depend on the presence of virus expressed silencing suppressor proteins. Several silencing suppressor proteins sequester the primary vsiRNAs thus inhibiting the accumulation of secondary vsiRNAs and the antiviral response Arabidopsis, RDR6 and RDR2 are required for virus  or sense transgene triggered RNA silencing, the spread of long-range cell-to-cell silencing, and the reception of the long-distance RNA silencing signal Tobacco rattle virus (TRV) derived vsiRNAs and antiviral silencing are strongly dependent on the combined activity of the host-encoded RNA-dependent RNA polymerases such as RDR1, RDR2, and RDR6 suggesting that viral single-stranded RNAs, might be converted by RDR enzymes to dsRNAs, which could serve as a substrate for vsiRNA production In Cymbidium ringspot virus (CymRSV) is a member of the Tombusvirus genus containing a positive single-stranded RNA genome with five open reading frames (ORFs) In this work we analysed the composition and the molecular nature of vsiRNAs in virus infected plants in order to gain a better insight into the biogenesis of vsiRNAs using the high throughput 454 and Solexa sequencing strategies.Nicotiana benthamiana infected with in vitro transcripts of either wild type CymRSV or with a mutant form of the virus that did not express the p19 silencing suppressor protein (Cym19stop). The cDNA libraries were sequenced on the 454 platform yielding around 100 000 sequences for each library  containing one highly abundant and a few less abundant hot spots on the positive strand was selected for validation. Five hundred 21mer oligonucleotides (complementary to the plus strand of CymRSV) in a one nucleotide sliding window were designed to cover the entire selected region and spotted on a membrane. The short RNA fractions (19–24 nt) were isolated from first systemic leaves of plants infected with patterns  providinin vitro synthesised and phosphorylated RNA oligonucleotides in decreasing concentration without or after denaturation and compared these with undigested samples  from the 5′ end or without modifying the 5′ end. When short RNAs are dephosphorylated the 5′ monophosphate, diphosphate or triphosphate is removed and then the short RNAs are re-phosphorylated ensuring that all short RNAs have a 5′ monophosphate.We also studied the 5′ end of vsiRNAs by ligating another adapter molecule (different from the 454 5′ adapter) to the 5′ end of vsiRNAs. cDNA libraries of short RNAs were generated using total RNA extracted from early systemic leaves of Solexa sequencing of the four libraries resulted in over one and a half million reads for each library . The ratAlthough most redundant vsiRNAs matched perfectly the viral genome, we observed a higher ratio of not perfectly matching non-redundant reads/perfectly matching non-redundant reads for the positive strand vsiRNAs compared with the negative strand vsiRNAs (p<0.05). One possible explanation for this is the fact that a lot more sequences are derived from the positive strand therefore there is a higher probability to observe sequencing errors in positive strand vsiRNAs. In fact the difference is more pronounced for the wild type virus compared to the mutant virus most likely because the positive/negative strand vsiRNA ratio is higher for the wild type (15×) than for the mutant (2.7×) sample. We also simulated the effect of sequencing errors on positive and negative strand vsiRNAs. The perfectly matching positive and negative strand vsiRNAs were separated from the wild type data set and different rates of sequencing errors  were simulated. The ratio of perfectly matching sequences to those matching with 0 or 1 mismatch was calculated. We found a similar effect on the positive and negative strand vsiRNAs when redundant reads were used but a much more pronounced effect on the positive strand vsiRNAs when the simulation was applied to non-redundant reads . This reThe abundances of reads in all four libraries were plotted on the viral genome  and hot Size distribution and 5′ nucleotide bias was compared between the four libraries and specifically between vsiRNAs derived from hot spots . A slighAll of our results  suggest that vsiRNAs are produced from structured + or − strands, rather than from the double-stranded replicative form or from host RDR generated double-stranded RNA. To explore this further one could predict the secondary structure of the viral genomic RNA or the hot spot regions. However, prediction of RNA secondary structure of long molecules is not reliable. It is also very likely that long RNA molecules have several possible conformations, which is difficult to model by using computational methods. Prediction of shorter regions is more reliable but this approach completely ignores that sequences far away from each other can pair with each other. Therefore secondary structures of hot spot regions are not informative either. We took a different approach and investigated whether the sequence reads derived from the + strand can potentially form duplexes with each other allowing up to four mismatches. We found a large number (8492) of such potential duplexes  suggestiN. benthamiana plants inoculated with in vitro transcript of Cym19stop virus. In the absence of the silencing suppressor protein the viral siRNAs are incorporated into RISC and target the GFP mRNA if they are complementary to the viral fragment in the sensor construct In order to understand the biological role of hot spots, we carried out a functional analysis of viral siRNAs. Different regions (200 nt length) of the viral genome in both plus and minus orientation were selected from hot spots and from non hotspots regions . These wWe used three approaches to profile vsiRNAs: 454 and Solexa high-throughput sequencing and hybridisation of 5′ labelled vsiRNAs to two arrays of DNA oligonucleotides covering a 520 and a 206 nt region of the viral genome. All three approaches gave reproducible results because total RNA extracted from wild type or suppressor deficient CymRSV infected plants gave very similar results for each technique. The hybridisation and Solexa sequencing showed good correlation with each other whereas the profile obtained using 454 sequencing was not in agreement. This suggests that ligation of the 454 adaptors have some sequence preference and not necessarily the most abundant molecules are present at high frequency in the cDNA library. This was also reflected by a bias to sequence reads starting with C nucleotide in the 454 library (data not shown) compared with a bias for U and A in the Solexa library . This hoBoth sequencing approaches identified more negative strand vsiRNAs in the p19 mutant virus infected plants, which mainly mapped to the last 1700 nt of the viral genome (downstream of nucleotide 3000). This shows a good correlation with the strongly increased level of subgenomic RNA 2 negative strand in the mutant virus infected plants compared with wild type virus infected plants, suggesting that the subgenomic RNAs also contribute to the vsiRNA pool.C. elegans where an RDR directly produces siRNAs without Dicer activity The Solexa and array approaches both identified regions from which vsiRNAs were generated at a higher than average frequency. Although this was reported previously based on small scale sequencing of vsiRNAs it could not be ruled out that those observations were influenced by the small data size. This comprehensive study confirmed that there are hot spots on the viral genome that produce specific vsiRNAs at a very high abundance. We also showed that the positions of these hot spots are the same in at least two different hosts indicating that it is determined by the virus itself. The profile of vsiRNAs was also identical in wild type plants and in plants where RDR6 accumulation was suppressed. The symptoms of these two plants following CymRSV infection were also very similar (data not shown) demonstrating that RDR6 is not required for vsiRNA production from the CymRSV genome. Some viruses, such as cucumber mosaic virus The CymRSV encoded silencing suppressor (p19) was shown to bind primary siRNAs and suppress the accumulation of DCL-D secondary siRNAs by blocking the activity of the primary siRNAs Although DCL-I secondary siRNAs have not been described in plants, plant virus derived siRNAs are good candidates for being direct products of an RDR. Most plant viruses are RNA viruses therefore vsiRNAs could be produced by the viral RDR or alternatively by one of the host RDRs. In addition, vsiRNAs were shown to be generated from hot spots on the viral genome that could be preferred sites of unprimed RNA synthesis. We took two different experimental approaches to analyse the 5′ structure of vsiRNAs at a genomic scale because DCL-I secondary siRNAs possess 5′ triphosphates (since the 5′ ends are not generated by Dicer cleavage but by RNA synthesis) and primary siRNAs have 5′ monophosphate. First we digested RNA extracted from virus infected plants with the terminator exonuclease and compared the level of vsiRNAs in treated and untreated samples by Northern blot. A similar level of vsiRNA in treated and untreated samples would suggest that most vsiRNAs carry 5′ triphosphates since the enzyme can only process molecules with 5′ monophosphate but not molecules with 5′ triphosphates. Our experiments revealed that most of the CymRSV vsiRNAs were processed by the enzyme when the samples were diluted thus we concluded that most vsiRNAs carry a 5′ monophosphate, although it cannot be ruled out that there is a small amount of vsiRNA with 5′ triphosphates.We also used another approach to study the 5′ structure of vsiRNAs where we profiled the short RNAs after ligating an adaptor to the 5′ end either directly or after de- and re-phosphorylation. The direct ligation only reveals vsiRNAs with 5′ monophosphate while the other approach also identifies vsiRNAs with 5′ triphosphate. If the profiles are different that suggests that there are vsiRNAs with 5′ triphosphate or diphosphate ends because they would be included in the dephosphorylated library but not in the directly ligated library. However, if the sequence profiles of the two libraries are the same that would indicate that there are not vsiRNAs with 5′ triphosphate or diphosphate because removing the 5′ phosphates does not have any effect. The patterns of vsiRNA hot spots in plants infected with the wild type virus were identical when the short RNAs were ligated to the 5′ adapter directly or after de- and re-phosphorylation. This argues against the idea that vsiRNAs in hot spots are mainly siRNAs with triphosphate 5′ end because in that case we should have seen a shift between the patterns obtained in the two experiments. The mutant virus also generated a similar vsiRNA profile regardless of the ligation method.in vitro synthesised and phosphorylated RNA oligonucleotides. We found that the enzyme did not digest the non-denatured duplex at all. The duplex was partially digested following denaturation but only at lower concentration. The fact that the duplex was not digested at all at high concentration suggests that short RNAs can re-anneal very quickly but renaturation happens less frequently at lower concentrations therefore the enzyme activity increased dramatically. These results demonstrate that any RNA sample analysed by the terminator exonuclease has to be denatured and digested at different concentrations. This conclusion has an important implication beyond the plant virology field since the terminator exonuclease can be used to study the 5′ structure of RNA molecules in diverse systems, including endogenous siRNA biogenesis in animals.To investigate the 5′ end of vsiRNAs we also used another approach that is based on the ability of the Terminator™ 5′-Phosphate-Dependent Exonuclease to distinguish between 5′ monophosphate and 5′ triphosphate (i.e. only digests RNA with 5′ monophosphate). Since a negative result was possible in the terminator exonuclease experiments (i.e.: no digestion of vsiRNAs), it was important to monitor the enzyme activity. A possible internal control is to monitor the level of miRNAs before and after exonuclease treatment since this class of short RNAs has 5′ monophosphate and present in the RNA extracted from virus infected plants. However, we observed during our preliminary experiments that different samples showed different ratios of digested vsiRNAs while the miRNA was always completely digested (data not shown). We hypothesised that a big difference between vsiRNAs and miRNAs is their accumulation level. Small scale short RNA cloning and sequencing experiments found that the majority of the short RNA population in virus infected plants is virus derived Interestingly, vsiRNAs were digested with a similar efficiency without or after denaturation, which is different from the efficiency of the digestion of a perfect duplex and very similar to the digestion pattern of imperfect duplexes. This suggests that vsiRNAs are not perfect duplexes but there are mismatches between the two strands. The most likely explanation is that most vsiRNAs are not generated from long perfectly matched double stranded RNAs but from precursor-miRNA like imperfect intramolecular structures. This is also supported by previous observation Identifying the precursor-miRNA like structures is not easy on long RNA molecules. Qi et al (2009) searched for stem-loop structures around hot spots of vsiRNAs on the TMV-Cg genome but did not find these structures N. benthamiana at least in the case of processing CymRSV RNA. However, this hypothesis has to be tested using different dcl mutants but these do not exist in N. benthamiana at the moment.It was shown in TCV (turnip crinkle virus) and TRV infected Arabidopsis plants that DCL4 is the primary nuclease to produce vsiRNAs but if DCL4 is absent or suppressed DCL2 can also produce vsiRNAs It was shown before that vsiRNAs do mediate cleavage of viral RNAs Adaptors were removed from both 454 and Solexa samples by searching for the last eight bases of the 5′ adaptor (in the case of 454 samples) and the first eight bases of the 3′ adaptor (for both 454 and Solexa samples) using the UEA sRNA tools adaptor removal application vsiRNA sequences were mapped to the CymRSV genome using PatMaN Boundaries of hot spot regions were initially determined using a simple algorithm designed to detect peaks in the profile then checked manually on the graphical plots. Sequence logos  were draA Perl script was written to identify vsiRNAs that could potentially base-pair with each other. Firstly sRNA sequences from the CymRSV PHOS Solexa sample were mapped to the plus strand of the CymRSV genome using PatMaN, allowing for one mismatch to the reference genome. All sequences matching to the plus strand of the CymRSV genome were then given as input to the script which used FASTA3 A. tumefaciens infiltration was carried out according to Silhavy et al. (2002). For coinfiltration of N. benthamiana leaves, mixtures of strains carrying sensor constructs (OD600 = 0.15) and strains carrying suppressor constructs (OD600 = 0.3) were used. Total RNA from Agrobacterium-infiltrated N. benthamiana and virus infected plant leaves was isolated using Trizol reagent All sensor constructs were prepared from the previously reported 35S-green fluorescent protein (GFP) binary plasmid In vitro transcription of CymRSV and Cym19stop RNAs from linearized template plasmids and inoculation of RNA transcripts onto Nicotiana benthamiana, N. benthamiana GFP16c/RDR6i line N. clevelandii plants were performed as described previously Total RNA was extracted from 100 mg of systemicly infected leaf tissue N. benthamiana as described by Moxon et al. Small RNA between 19–24nt were cloned from systemic leaves of N. benthamiana was isolated from 15% denaturing polyacrylamide gel. The eluted sRNA fraction was divided into two and one half was not treated  while the other half was de-phosphorylated with Shrimp Alkaline Phosphatase and re- phosphorylated with T4 Polynucleotide Kinase . The resulting sRNAs were ligated to adaptors in the following reaction. The purified, adaptor ligated short RNAs were converted to DNA by RT-PCR and the DNA was sequenced on a Solexa platform (Illumina). The small RNA libraries are submitted to GEO and can be accessed through a super series number: GSE17278.Small RNA fraction (19–24 nt) of total RNA extracted from systemic leaves of in vitro transcribed virus infected plants was subjected to electrophoresis through an 8% denaturing polyacrylamide gel followed by staining in 1× Tris-borate-EDTA and 0.5 µg/mL ethidium bromide solutions for 5 min. The 19–24 nt fraction was visualized by UV light and excised from the gel. The gel slice was crushed, covered with 2 volumes of elution buffer  and incubated overnight. The gel residues were pelleted by centrifugation and the supernatant was precipitated with ethanol. The RNA (∼100 ng) was dephosphorylated and then labeled in a 10-µl reaction in the presence of γ-32P-ATP and RNasin with 8 units of T4 polynucleotide kinase. The labeled 19–24 nt RNAs were used for hybridization either to membranes  containing five hundred 21mer DNA oligonucleotides in a one nucleotide sliding window covering a 520 nt region  complementary to the 19mer sense RNA or to the sense RNE of siRNA171a or to the sense RNA of siRNA171b respectively. Hybridization was performed in Ambion ULTRAhyb-Oligo Buffer at 37°C following the manifacturer′s instruction.19mer and 21 mer synthetic RNA molecules were phosphorylated and 30 µl of sense RNA (10 µM) and 30 µl of antisense RNA (10 µM) were incubated in 90 µl annealing buffer  to form siRNA duplex . We also prepared mismatch containing siRNA duplexes on the same way by incubating sense RNA with different mismatch containing antisense RNA . We digested the resulting siRNA duplexes for one hour at 30°C in decreasing concentration  in a 10 µl reaction in the presence of 0.25 U Terminator™ 5′-Phosphate-Dependent Exonuclease (Epicentre Biotechnologies) without or after 1 minute 90°C denaturation. Terminator treated and non-treated samples were loaded onto 0.5× TBE 15% UREA-Polyacrylamide gel. After electrophoresis the samples were transferred to Zeta-probe GT BioRad membranes by Semi-dry blotting. The membranes were hybridized with γ-32P-ATP labelled DNA oligonucleotides. Cym mix probe was a pool of five oligonucleotides  and complenetary to the negative strand of the virus genome. Cym3025 was also complementary to the negative strand of the virus genome. Cym minus probe was a pool of two oligonucleotides (cym1021 minus and cym3710 minus) and complementary to the positive strand of the virus genome. Cym 4632 LNA was also complementary to the positive strand of the virus genome. U6 detects the U6 snRNA while miR159 LNA detects the mature strand of miR159 and contains locked nucleic acid (LNA) nucleotides. The oligonucleotide sequences used for hybridisation are available in RNA extracted from CymRSV infected plants was mixed with 19mer siRNA duplex and was diluted containing decreasing concentration of total RNA and siRNA duplex . We digested the resulting RNA and siRNA duplex mixture in a 10 µl reaction in the presence of 0.25 U Terminator™ 5′-Phosphate-Dependent Exonuclease without or after 1 minute 90°C denaturation for one hour at 30°C. Terminator treated and non-treated samples were loaded onto 0.5× TBE 15% UREA-Polyacrylamide gel. After electrophoresis the samples were transferred to Zeta-probe GT BioRad membranes by Semi-dry blotting. The membranes were hybridized with γ-Figure S1454 profile of CymRSV and Cym19stop vsiRNAs. The normalised number of vsiRNAs in the two 454 datasets  containing each nucleotide in the virus genome was plotted against the positions of nucleotides in the viral genome.(10.19 MB TIF)Click here for additional data file.Figure S2Terminator digest of + strand vsiRNAs. The membranes shown on (0.31 MB JPG)Click here for additional data file.Figure S3in vitro synthesised and phosphorylated siRNAs were annealed to each other to generate either perfect duplexes or imperfect duplexes (A). Please note that the imperfect duplexes contain mismatches and additional U∶G pairs. The perfect duplexes were digested with Terminator™ 5′-Phosphate-Dependent Exonuclease in decreasing concentration without (left panel) or after denaturation (right panel) (B). The two imperfect duplexes were also digested with Terminator™ 5′-Phosphate-Dependent Exonuclease in decreasing concentration without denaturation (C). The efficiency of the digestion was monitored by northern blot assay using a probe complementary to one of the strands of the synthetic siRNAs.Terminator digest of perfect and imperfect duplex synthetic siRNAs. The terminator assay was carried out as described for (0.21 MB JPG)Click here for additional data file.Figure S4Accumulation of genomic viral RNA in wild type and p19 mutant virus infected plants. Total RNA was extracted from wild type and p19 mutant virus infected plants. The RNA was separated on 1.2% denaturing formaldehyde agarose gels and blotted to membranes. The membranes were hybridised with + strand, − strand or actin specific probes. All four samples contained less + strand RNA and more − strand  in the mutant virus infected plants. G: genomic viral RNA; sg1: subgenomic RNA 1; sg2: subgenomic RNA 2.(0.07 MB JPG)Click here for additional data file.Figure S5Simulation of the effect of sequencing errors on positive and negative strand vsiRNAs. The effect of sequencing errors on positive and negative strand vsiRNAs was simulated by applying sequencing errors at different rates  on perfectly matching positive and negative strand vsiRNAs (either redundant or non-redundant sequences). The ratio of perfectly matching sequences to those matching with 0 or 1 mismatch was calculated. We found a similar effect on the positive and negative strand vsiRNAs when redundant reads were used but a much more pronounced effect on the positive strand vsiRNAs when the simulation was applied to non-redundant reads.(0.03 MB XLS)Click here for additional data file.Figure S6Comparison of 454 and Solexa profiles of vsiRNAs. Profiles of vsiRNA obtained by the 454 and Solexa platforms are shown on the top of each other. Red and blue lines represent 454 and Solexa profiles, respectively.(0.12 MB JPG)Click here for additional data file.Figure S7Nucleotide distributions in vsiRNAs 5′ end. First nucleotides of vsiRNAs obtained through Solexa sequencing of the four small RNA libraries were analysed for each size category (18–24 nucleotides). The top four and bottom panels show the result for all reads and hot spots, respectively.(0.32 MB JPG)Click here for additional data file.Figure S8N. benthamiana following two different protocols. The 5′ adapter was either directly ligated to the short RNAs (PHOS) or first depohosphorylated and then re-phosphorylated before adapter ligation (CIP).Separate Solexa profiles of 21 and 22 nt vsiRNAs. The 21 and 22 nt vsiRNAs were separated from the Solexa datasets (wild type and mutant virus), and their normalised number was plotted against the positions of nucleotides in the viral genome. Short RNAs were sequenced from wild type (G11) or silencing protein disabled (19) virus infected (0.16 MB JPG)Click here for additional data file.Table S1Potential vsiRNA duplexes derived from the + strand. All sequences matching to the plus strand of the CymRSV genome were searched against the reverse complement of all plus strand genome matching sequences. Potential duplexes with four or fewer mismatches and a maximum of one bulge are listed. The number of reads is shown in brackets after each sequence.(1.29 MB TXT)Click here for additional data file.Table S2Potential vsiRNA duplexes derived from the − strand. All sequences matching to the minus strand of the CymRSV genome were searched against the reverse complement of all minus strand genome matching sequences. Potential duplexes with four or fewer mismatches and a maximum of one bulge are listed. The number of reads is shown in brackets after each sequence.(0.56 MB TXT)Click here for additional data file.Table S3Sequences of oligonucleotides. Sequences of oligonucleotides used for the dot blot and northern blots are listed.(0.09 MB XLS)Click here for additional data file.


Carollia perspicillata, and in an obligate fruit-eating bat, Artibeus obscurus, captured at mineral licks and at control sites in the rainforest. Carollia perspicillata with a plant-dominated diet were more often captured at mineral licks than individuals with an insect-dominated diet, although insects were more mineral depleted than fruits. In contrast, nitrogen isotope ratios of A. obscurus did not differ between individuals captured at mineral lick versus control sites. We conclude that pregnant and lactating fruit-eating bats do not visit mineral licks principally for minerals, but instead to buffer the effects of secondary plant compounds that they ingest in large quantities during periods of high energy demand. These findings have potential implications for the role of mineral licks for mammals in general, including humans.Many animals in the tropics of Africa, Asia and South America regularly visit so-called salt or mineral licks to consume clay or drink clay-saturated water. Whether this behavior is used to supplement diets with locally limited nutrients or to buffer the effects of toxic secondary plant compounds remains unclear. In the Amazonian rainforest, pregnant and lactating bats are frequently observed and captured at mineral licks. We measured the nitrogen isotope ratio in wing tissue of omnivorous short-tailed fruit bats,  Geophagy or the consumption of soil and clay by animals is geographically widespread and known from a variety of vertebrate and invertebrate taxa including humans  sites. If bats visit mineral licks primarily to consume valuable nutrients, we expected to find the opposite pattern in C. perspicillata. We also predicted that the obligate fruit-eating Artibeus obscurus15N at both mineral licks and control sites. In addition, we expected to find high levels of minerals in mineral lick soils. To test this hypothesis, we compared the mineral content of clay that we collected from mineral licks with data from fruits and insects from the literature.Omnivorous phyllostomid bats, such as its e.g., each ofits e.g.. Carolliet al.et al.et al.et al.15N) were reported in the same publication. Here we only report data for comparisons among individuals of the omnivorous Carollia perspicillata and the obligate fruit-eating Artibeus obscurus.We studied bats at the Tiputini Biodiversity Station in Ecuador  between 14 March and 13 April 2007. Habitat and climate are described in Voigt 15N of C. perspicillata and A. obscurus captured at both types of sites with a two-tailed Mann-Whitney U-test. All work was conducted with the approval of Boston University's Animal Care and Use Committee.We collected clay and water from the same six mineral licks where bats were captured, following Carollia perspicillata  and 13 Artibeus obscurus . Numbers of females and males did not differ significantly between mineral licks or control sites . The δ15N in wing tissue from C. perspicillata captured at mineral licks was significantly lower than in wing tissue of conspecifics captured at control sites .We captured 15 7, calcium and magnesium by a factor of 106, and sodium and potassium by a factor of 105.Clay at Tiputini mineral licks was enriched in five minerals  relative to fruits and insects . These mThe reasons why mammals visit mineral licks remains controversial, and could potentially vary geographically, depending on the properties of clay, as well as on the overall diet of animals. Ungulates from temperate regions, for example, show sex-specific seasonal variation in visits to licks, which appear to be associated with meeting sodium requirements during female reproduction and antler development in males C. perspicillata captured at control sites had higher δ15N than at mineral licks. Differences in 15N enrichment was approximately equal to one trophic level C. perspicillata encountered at mineral licks consumed mainly fruits, whereas those at control sites relied more on insects. Generally, most bats captured at mineral licks in the Amazonian lowlands are frugivorous Two recent studies indicated that pregnant and lactating females of frugivorous bat species are frequently captured at mineral licks in the Amazonian rainforest During reproduction, female bats not only must supply their offspring with calcium and other nutrients, but they also must meet higher energy requirements