The aim of the present study was to determine health-related risk and salutogenic factors and to use these to construct prediction models for future self-rated health (SRH), i.e. find possible characteristics predicting individuals improving or worsening in SRH over time (0–12 months).A prospective study was conducted with measurements  at 0, 6 and 12 months, involving 303 employees  from four information technology and two media companies.There were a multitude of statistically significant cross-sectional correlations (Spearman's Rho) between SRH and other self-ratings as well as physiological markers. Predictors of future SRH were baseline ratings of SRH, self-esteem and social support (logistic regression), and SRH, sleep quality and sense of coherence (linear regression).The results of the present study indicate that baseline SRH and other self-ratings are predictive of future SRH. It is cautiously implied that SRH, self-esteem, social support, sleep quality and sense of coherence might be predictors of future SRH and therefore possibly also of various future health outcomes. Self-rated health (SRH) is one of the most widely used single measures of perceived current health status -9. In spIt has been proposed that SRH represents an individual's general perception of health, including biological, psychological and social dimensions. Therefore SRH might be more sensitive in health monitoring than external measures of health . FurtherIn a previous article, we reported about some short-term (six months) beneficial effects of a web-based stress management and health promotion system on psychological and physiological indicators of health, stress and recovery . There iMost studies on SRH are of cross-sectional design. The findings of significant associations between different variables are more difficult to interpret compared to longitudinal studies with repeated measures. Consequently, it has been repeatedly shown that SRH correlates with a multitude of biological, psychological and social factors. Only few studies have examined predictors of future SRH longitudinally and combined the measure with other subjective and/or objective variables ,8-11,14.Therefore, the aim of the present study was to determine health-related risk and salutogenic factors and to use these to construct prediction models for future SRH, i.e. find possible characteristics predicting individuals improving or worsening in SRH over time.In collaboration with a White-Collar Union (Sif) and a Swedish Employers' Association (Almega), ten companies insured by the study's source of funding Alecta  were asked as to their interest in participating. These companies were selected and contacted by employees at Alecta, by mail and phone. The management departments of six out of the ten companies were interested. Informed of the basic inclusion criteria, i.e. minimum group of ten individuals and access to economic production data, 2–4 departments within each company were chosen and asked by the company management as to their interest in participating. The managers of the chosen departments in turn asked their employees whether they were interested in participating. No incentives were offered to the participants, with exception of the extensive blood sampling including feedback, which seemed to be a motivator for many participants.There is no information on the exact number of employees that were asked to participate in the study. An exception was one of the media companies where 95 out of 100 possible participants chose to participate. In general there was also a great interest from the other departments and similar participation rates is therefore estimated. Altogether, 317 participants from 22 departments/units in four information technology and two media companies enrolled in the study. The participating departments were, within each company, randomized by lottery to either the intervention or reference group. Fourteen participants were excluded because of communication-related problems (n = 7), change of mind in willingness to participate or leaving job before initiation of the study (n = 7). Thus, 303 persons finally participated in the study, out of which 26 participants (8.6%) dropped out. The reasons for dropping out were job termination (n = 7), change of workplace (n = 2), foreign service/moving abroad (n = 6) or other reasons (n = 11). There were no significant differences in dropout rates between the groups . There were no significant differences between the intervention and reference groups in socioeconomic background or psychophysiological measures at baseline. The participants had professions such as IT technicians, programmers, system developers as well as journalists/reporters, news presenters, sound technicians and photographers. The main type of work-site was open plan offices. Many participants from the IT-companies were partly located in the work sites of their customers for longer or shorter periods. For the media companies, some participants, such as photographers and reporters, were partially ambulatory and worked in different locations. The common feature for all participants was regular and daily computer usage at work.Out of the 303 participants, only the participants that had complete SRH scores from the baseline and 12-month follow-up (n = 230) measurement were selected for the final analyses. Consequently, participants with missing values in the first or last measurement were not included in the regression analyses and ANCOVA. More detailed information about the measurements is presented below.Table A questionnaire was compiled and included about 100 questions concerning socioeconomic status, consumption of caffeine drinks, expectations about the research project, self-rated health (SRH), stress and wellbeing at work as well as during leisure time, health economics and performance at work Table . Most ofThe complete list of biological markers analyzed in the current study is presented in Table Blood samples were collected from study participants between 7.00–11.30 am at each specific worksite (or nearby). Questionnaires were filled out during the same time period  in order for the outcome of the blood and questionnaire data to be as comparable as possible. The exact time for blood sampling were recorded for each participant at baseline and at the end of the study so that the blood could be collected at the same time (± 15 minutes). Participants were instructed not to eat or drink (except water), nor use nicotinic substances at least ten hours before blood sampling.For the present study the question: "How is your health at the moment?" was used and the VAS anchors were "very poor" on the left end and "very good" on the right end. It has been proposed that repeated measurements of variables, such as SRH, could benefit by being assessed using a VAS, since the VAS is probably more responsive, i.e. sensitive to detect clinically significant change , compared to a four or five point Likert scale. Furthermore, it has been suggested that VAS have several other advantages compared to the Likert scale, especially with regard to repeated measures -29. For 12 months ≥ SRHbaseline) or worsening (SRH12 months < SRHbaseline) in SRH over time. The parametric Unpaired samples t-test and the non-parametric Mann-Whitney U test were utilized for this purpose. SRH at the 12-month follow-up served as the dependent variable in the regression analyses. For the non-parametric logistic regression, the variable was divided by quartile split into high (top quartile) and low (remaining quartiles) categories.The program SPSS 13.0 for windows was used for statistical analyses. Initially, all variables were assessed for normality using Kolmogorov-Smirnov test. Thereafter, a new variable was created to assess possible differences in baseline means/ranks between participants maintaining/improving  with no statistically significant difference between the groups at the post-intervention follow-up, i.e. a six months from baseline . In thatCriterion validity refers to the degree to which a variable converges  or discriminates  between measures that should be related and non-related respectively. Spearman's rank correlations test was used for this purpose in a cross-sectional analysis of the baseline measurement. It was expected that the findings of the present study would be congruent with previous studies with cross-sectional design, where SRH has been related to socioeconomic factors as well as biological, environmental and psychosocial factors.Logistic and linear regression analyses were used to model the probability of maintenance/improvement and worsening in SRH over time. The regression models were estimated in four steps to address the questions if clinical/physiological measures/risk factors predict future SRH and if these variables retain their importance after adjustment for other self-reported measures. For the logistic regression, all variables were divided by quartile split into high and low categories to render comparable odds ratios. The top quartile was labelled "high" and the remaining quartiles "low". The independent variables, i.e. questionnaire items and physiological markers, were selected with the primary rationale to choose variables that previously have been associated with SRH. The secondary rationale was to choose isolated variables that were significantly associated with SRH in the cross-sectional analysis. In Table Factors such as socioeconomic status, marital status and gender are known to be associated with outcomes in health, and were therefore included as covariates in the first step of the regression analyses. Also group (intervention vs. reference) was included as a factor in the first step to adjust for possible study group effects. For the subsequent steps in the regression analyses, VAS-items from the questionnaire and physiological markers were used as independents. The rationale for the second step was to adjust for factors that might disturb the relationships, i.e. health-related behavioural factors. In the third step, factors important for mental and physical health and wellbeing were included. The fourth and final step included physiological variables.The funding source had no involvement in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. The ethics committees of Uppsala University (Dnr 01–188) and Karolinska Institute (Dnr 01355) approved the research project.Altogether, 230 participants were rendered for the final analyses as they had complete SRH scorings from the baseline and 12-month follow-up measurement. 73 participants had missing values in one or both measurement occasions, and were thus precluded from further analyses. The means in SRH for the total sample at baseline was 66.5 , after six months 68.5  and after twelve months 68.6 . Paired samples t-tests between the baseline and 12-month follow-up measurement revealed that these differences were not statistically significant. Table The parametric Unpaired samples t-test and the non-parametric Mann-Whitney U test revealed that there was a statistically significant difference in baseline ratings of SRH between the participants maintaining/improving and those worsening in SRH. Participants worsening in SRH had a higher (better) baseline mean or rank compared to those maintaining/improving .Figure Criterion validity was assessed using Spearman's Rank correlation test. Baseline SRH significantly correlated with numerous variables that are known to be related, indicating good overall criterion validity Table .Table In addition to lower baseline ratings of SRH, the linear regression identified higher baseline ratings of sleep quality and sense of coherence as significant predictors of higher SRH at the 12-month follow-up. Altogether, this model accounted for 27.4% of the explained variance. Socioeconomic variables were not significant predictors in any of the regression models.The aim of the present study was to determine predictors of future SRH. The study period was one year and conducted on a working population from IT and media companies. The logistic regression identified baseline scorings of SRH, self-esteem and social support to be significant predictors of future SRH. The linear regression also revealed baseline ratings of SRH, sleep quality and sense of coherence as significant predictors of future SRH.The cross-sectional correlation analysis revealed that SRH significantly correlated with other self-rated and objective measures. Most of these associations have been confirmed in previous studies ,5,10,14.An interesting finding was that there were some moderate to strong correlations between baseline SRH and other baseline measures, such as leisure time, social support, stress management, mental energy and self esteem (positive) and between SRH and frequency of stress, pain, BMI and fears/melancholy (negative). These findings have all been confirmed in the different studies cited in the above paragraph. It was also interesting to note that there were negative correlations between SRH and biological markers such as CRP and fibrinogen. This finding confirms what we have found in clinical practice, where increased levels of CRP and fibrinogen are common in patients with stress-related syndromes.One might expect that some of the socioeconomic variables would have predicted future SRH. In this sample, however, the contrasts between the participants are undoubtedly smaller than in the normal population, rendering a lesser variance. This might explain why the socioeconomic variables were not significant predictors of future SRH in this study. However, annual income was a marginally significant predictor in the final logistic regression model. Furthermore, one year is a rather short time to expect significant predictive effects from these otherwise predictive variables.With exception for SRH, the logistic and linear regression analyses yielded different predictors. One possible partial explanation might be that the dichotomization of variables needed for logistic regression decreases the variance and statistical power compared to the linear regression that retains more of the variance. Moreover, the chosen cutoff is not necessarily the biologically correct one. Another explanation is that SRH accounts for a major part of the variance. In fact, when the baseline SRH variable was removed as a predictor, the regression analyses showed more similar results. Significant predictors in the logistic regression were then physical activity, sense of coherence and social support, and in the linear regression, sleep quality, sense of coherence and social support.Self-esteem and social support as well as sleep quality and sense of coherence has previously been identified both as predictors and/or mechanisms of maintaining and improving health and general wellbeing -39. ThesThe strongest predictor of future SRH was baseline SRH. Findings from previous prospective studies confirm the result of this study, which implies that the results of this study may be valid ,10. For Finally, it is particularly important to address one of the findings of the present study. SRH improved in both study groups  at the 6 and 12 months post-intervention follow-ups respectively. However, as shown in the regression analyses in the present study, "study group" was not a significant predictor in any of the regression models. This implies that the web-based intervention neither had short-term nor long-term effects on SRH. Thus, the result may indicate that primarily SRH, but also sleep quality and sense of coherence are more profound indicators of health status, and that SRH is not easily affected by temporary circumstances. Rather, it might be affected on a longer-term basis by general health status, total load of life, life-events or other burdens that have not been captured by the regression analyses or measures assessed in the present study. For example, one partial explanation might be that the active intervention period, i.e. 0–6 months, was conducted during a turbulent time. This general turbulence was soothed during the 12-month follow-up, which partly and generally could explain an improvement in SRH. Furthermore, sleep quality was one of the factors that improved in the intervention group compared to the reference group at the 6-month follow-up. Perhaps participants that for different reasons were able to sustain a good sleep benefited more with regard to SRH. However, as for now, it is not possible to draw other reliable conclusions than that the intervention had no long-term effect on SRH.There are some methodological considerations that have to be addressed. With regard to generalizability of the results it is important to note that the study group consisted of a healthy, working sample from IT- and media companies. Therefore the results of this study may not be generalizable to for example a sample of individuals suffering from different long-term disorders and diseases or an elderly, retired sample.A multitude of possible predictors of SRH have been found in previous studies. This study confirms some of the previous findings. Future research should preferably focus on finding explanations and consistent patterns of predictors of future SRH. An interesting aspect that could render valuable information is to assess predictors of individuals that fluctuate in SRH over time. It would be interesting to know if fluctuation per se in SRH is a salutogenic or pathogenic pattern on a long-term basis. There is also a need to develop and assess psychophysiologically based explanatory models about the predictive ability of SRH on future health outcomes.The results of the present study and others indicate that SRH and other self-ratings are predictive of future subjective and objective health outcomes. However, different settings, types of population and methodology and statistical analyses strategies of various studies examining SRH makes it difficult to compare results and therefore to draw reliable conclusions. This study cautiously implies that SRH, self-esteem, social support, sleep quality and sense of coherence might be predictors of future SRH and therefore possibly also of various future health outcomes.Following the termination of this study, BA and DH have commercialized the web-based health promotion and stress management tool. The titles referring to any of the persons/authors involved in this article are made without any considerations to ownership to possible intellectual property rights.BA was the principal project designer as well as the project leader and DH accomplished the practical study logistics. DH conducted the statistical analyses and drafted the manuscript, with substantial and essential input from TT, UMA and BA. All the authors have read and approved the final version of the manuscript.


Examination of host cell-based inhibitors of HIV-1 transcription may be important for attenuating viral replication. We describe properties of a cellular double-stranded RNA binding protein with intrinsic affinity for HIV-1 TAR RNA that interferes with Tat/TAR interaction and inhibits viral gene expression.in vitro. Analysis of the effect of NF90ctv-TAR RNA interaction in vivo showed significant inhibition of Tat-transactivation of HIV-1 LTR in cells expressing NF90ctv, as well as changes in histone H3 lysine-4 and lysine-9 methylation of HIV chromatin that are consistent with the epigenetic changes in transcriptionally repressed gene.Utilizing TAR affinity fractionation, North-Western blotting, and mobility-shift assays, we show that the C-terminal variant of nuclear factor 90 (NF90ctv) with strong affinity for the TAR RNA, competes with Tat/TAR interaction Structural integrity of the TAR element is crucial in HIV-1 gene expression. Our results show that perturbation Tat/TAR RNA interaction by the dsRNA binding protein is sufficient to inhibit transcriptional activation of HIV-1. Highly Active Antiretroviral Therapy (HAART) administration utilizes a combination of inhibitors of viral protease and reverse transcriptase to markedly reduce circulating viral levels ,2. Howevin vivo. Given the functional importance of Tat-TAR interaction in viral life cycle; Tat protein and the TAR element both present attractive targets for therapeutic drug design.The nascent transcripts from HIV-1 Long Terminal Repeat (LTR) contain a unique structured RNA domain within the 5'-nontranslated region known as the transactivation response (TAR) element which is critical for efficient transcription of viral promoter in response to Tat ,4. The TAgents affecting the Tat/TAR interaction could prevent transcriptional activation of HIV-1 genome either by steric hindrance, a shear displacement mechanism, or by deprivation of Tat-cofactor molecules  ,14. The NF90ctv is a C-terminal variant  of the NWe studied the unique C-terminal variant of NF90 (NF90ctv), where the C-terminal 70 amino acids of arginine/glycine rich domain is substituted largely by acidic residues due to a CT insertion in exon 15 that alters the translational reading frame. Cells expressing NF90ctv stimulate a transcriptional program of IFN response genes which is responsible in part for their ability to inhibit HIV-1 replication . NF90ctv2-Tat72, (SV40 promoter driven vector encoding the 72 amino acid first exon of Tat), pCMV-NF90ctv  [Recombinant plasmids for expression in mammalian cells were constructed as follows: pJK2 , pSVsity CA) . pOZ (bi6 cells) in 0.5 ml culture medium supplemented with 20 μg/ml polybrene. An aliquot of the culture supernatant was collected and stored at -80°C. Production of p24 antigen was analyzed by enzyme-linked immunosorbent assay (ELISA) according to the manufacturer's instructions .GHOST(3)CXCR4 cells were obtained from the NIH AIDS Research and Reference Program. The cell line is derived from human osteosarcoma (HOS) cells by stable transduction with HIV-2 long terminal repeat (LTR)-driven green fluorescent protein (GFP) reporter, human CD4 receptor, and human CXCR4 chemokine receptor genes. To generate cell lines stably expressing NF90ctv, GHOST(3)CXCR4 cells were transduced with pOZNF90ctv or the plasmid with 'empty vector', using transduction and selection protocols described elsewhere . For HIVThe purification and characterization of NF90ctv binding to TAR RNA was examined by stepwise fractionation of HeLa nuclear extract. The SP Sepharose chromatography fractions eluted at 0.25 M and 0.5 M NaCl were applied to a TAR affinity column. Briefly, 200–250 μg of biotinylated TAR RNA was bound to NutrAvidin Plus beads . Binding of RNA to affinity beads packed in a 0.8 × 7.0 cm column occurred for 30 minutes at 4°C with rocking. The SP Sepharose pool was applied to the column, recycled four times and the TAR RNA bound fractions were recovered with a 2.0 M KCl step elution. Proteins contained in the partially purified TAR fraction were analyzed by SDS-PAGE and North-Western blots .Electrophoretic mobility shift assays (EMSA) with labeled TAR RNA revealed that the SP Sepharose and the TAR RNA bound fractions were able to retard TAR RNA mobility in non-denaturing acrylamide gels.500 ng of protein from the TAR RNA purification step was incubated with 0.2 pmoles of radiolabeled TAR RNA. Competition for radiolabeled TAR RNA binding was done with increasing amounts of unlabeled wild-type TAR RNA and mutant TAR RNA transcripts TM12, TM18 and TM27.2, 0.01% NP40 containing 5% milk). Following a 10 minute wash, the bound protein fraction was probed with 32P-labeled TAR RNA  in the NorthWestern buffer containing 0.2% milk and 50 U/mL RNasin for 2 hours. The blots were washed, air dried and exposed for autoradiography overnight at -70°C. Control RNA probe included human globin RNA. TAR RNA bound protein fractions (25 μg) were also monitored by Western blot analysis and probed with anti-NF90 polyclonal antibody.Equal amounts of protein (25 μg) from the TAR RNA bound fraction was transferred to immobilon-P and blocked for 2 hours in NorthWestern buffer  amount of pHIV-LRT-β gal reporter (LacZ gene under the control of the HIV-1 LTR) was cotransfected with increasing amounts of pCMV-NF90ctv , or together with 5 μg of pSV2-Tat72 encoding the 72 amino acid first exon of Tat. To control for transfection efficiency, 0.2 μg of pCMV-CAT plasmid DNA was cotransfected. The final total amount of DNA in each reaction was adjusted with salmon sperm DNA. After 48 hours, cell extracts were prepared and standardized for total protein using a modified Bradford assay (Bio-Rad). Colorimetric β-galactosidase and CAT assays were performed as described [The effect of NF90ctv on Tat-mediated transactivation of HIV-1 LTR was assessed in both HeLa and Jurkat cells using CaClescribed . In each6 of non-infected or HIV-1pNL4-3 or pseudotyped VSVG-HIV-1 infected GHOST-CXCR4/pOZ-NF90 or GHOST-CXCR4/pOZ empty-vector transduced cells were washed twice with PBS and lysed in culture flask by addition of 5 ml of RNAZOL. Following extraction with 0.5 ml chloroform, the RNA was precipitated with isopropanol and washed with 75% Ethanol. 15 μg of total RNA were loaded into each lane of 1% Formaldehyde-agarose gel and electrophoresed under standard conditions. The RNA was transferred to Nitrocellulose membrane  by capillary action using 10 × SSC and cross-linked using ultraviolet light. Membranes were prehydrated in 6 × SSC, 1% SDS solution containing 150 μg of salmon sperm DNA for 2 hours at 65°C. The pre-incubated blots were hybridized at 65°C in shaking water bath for approximately 20 hours with 32P-random prime labeled DNA fragment of whole HIV genome . Membranes were washed twice (5 minutes each in 1 × SSC 1% SDS at room temperature), at 15 minutes each in 1 × SSC, 10% SDS at 37°C and finally for 1 hour at 0.1 × SSC 1% SDS at 65°C. The blots were wrapped in Saran wrap and the radioactive bands were detected . To control for RNA loading, levels of 18S and 28S or β-actin RNA were used as reference.Total RNA was isolated from cells using RNAZOL . Briefly, 20 × 102) were added to the reaction for a final volume of 200 μl. The TAR/Tat complex was incubated with beads for an additional 1 hr on ice. Next, various concentrations of purified NF90ctv protein  were added to the mixture. All samples were further incubated on ice for an additional hour. Finally, samples were centrifuged at 4°c for 5 minutes, and washed (3X) with TNE300 + 0.1% NP-40 . A final wash with TNE50 + 0.1% NP-40 was performed. Bound complexes were separated on a 4–20% SDS/PAGE and Western blotted either with anti-Tat mAb or anti-NF90c antibodies. The same Blot was cut in half for either Tat or NF90c Western blot.One microgram of purified biotin-labeled TAR RNA was mixed with one microgram (1 μg) of purified Tat protein for 10 minutes on ice. Next, 100 μl of 30% strepavidin-sepharose beads in binding buffer  for 2 hrs and cross-linked , and samples were sonicated to reduce DNA fragments to ~200 to 800 bp for ChIP assays essentially as described earlier [OM10.1 cells, a promyelocytic line containing transcriptionally latent, single copy of wild-type HIV-1 integrated proviral DNA  , were in earlier . DNA bouTo detect proteins that interact with the TAR region of HIV-1 LTR, a three-step purification process was devised to fractionate nuclear proteins from HeLa cells, including a Sulpho-phosphate Sepharose (SP Sepharose) chromatography step followed by TAR RNA affinity chromatography. The final fraction, a 2.0 M KCl eluate (TAR affinity fraction) contained proteins p160, p110, p90, and p62. To determine which proteins from the TAR affinity fraction directly interacted with TAR RNA, North-Western analysis was performed using radio-labeled TAR RNA, with beta-globin RNA as a control. The identity of the 90 kDa band was confirmed by Western blotting using anti-NF90 polyclonal antibody and further established through N- terminal sequence analysis. As described Figure , non- spFigure As the interaction of proteins with the TAR RNA is likely to be dependent on the RNA structure, in addition to the recognition of the linear sequence motifs, we investigated the possible binding site of NF90ctv to TAR RNA using structural mutants of TAR RNA, and competition with unlabeled RNAs. The secondary structures and free energies of the mutant TAR RNA were predicted with an RNA-folding program . The TARThe TAR RNA mutant, TM18, represents an "antisense" TAR with major alterations in the primary sequence of stem I, II, III, and IV, while retaining the secondary structure of wild type TAR RNA Figure . When TMTo determine whether full length TAR RNA was required for NF90ctv binding or segments of the TAR RNA structure are sufficient, we utilized deletion mutants of HIV-1 LTR. The TAR mutant TM12 contained the lower TAR stem regions I and II and the loop sequence from the wild type TAR Figure . Results6 cells using CaCl2/Hepes precipitation method  HIV-1 transcription in HeLa cells by transfecting (2.5 μg) of pHIV-LTR/β-galactosidase reporter plasmid, and increasing amounts  of pCMV-NF90ctv per 5 × 10in vivo, we analyzed RNA isolated from HIV-1 infected cells that were stably transduced with NF90ctv expressing vector as compared with control cells transduced with the empty vector [To assess whether NF90ctv affects HIV-1 transcripts y vector . Northery vector  was usedWe next asked whether NF90ctv could effectively compete with Tat for TAR RNA binding. To do this, we designed a competition experiment where biotinylated wild type TAR RNA was mixed with Tat protein for 10 minutes and then increasing concentration of purified NF90ctv protein was added to the mixture. The resulting complex was then washed and bound proteins were resolved by 4–20% SDS/PAGE, and Western blotted with either anti-Tat or anti-NF90ctv antibody. Results of such an experiment is shown in Figure We previously reported that transcriptional activation of latent proviral DNA by TNF-α induction of OM10.1 cells, a promyelocytic cell line that contains single copy integrated proviral DNA, is mediated by Tat . It was Among the epigenetic marks of transcriptionally silenced chromatin, histone H3K9 methylation, and in particular different degrees of H3K9 methylation suggest regulated suppression of transcriptionally active chromatin . HistoneEukaryotic cells depend on recognizable RNA secondary structures for a variety of normal cellular pathways. Cellular RNA-binding proteins appear to function as information sensors, extracting the information content from specific RNA structural domains to initiate downstream signaling that translate analog to digital information . SignifiIn the present study we utilized a C-terminal variant of the cellular RNA-binding protein (NF90ctv) that was initially isolated by HIV-1 TAR RNA affinity fractionation. We focused on the C-terminal variant of NF90 to further explore its mechanism of action as a potential antiviral target protein. In an earlier report , we descThe idea that TAR may be a novel target for drug intervention is supported by the fact that any natural or induced mutation that destabilizes the TAR structure disrupts base pairing in the TAR stem region . Also loNF90 and NF45 are subunits of a heterodimeric protein originally isolated as a putative transcription factor thought to bind to the antigen receptor response elements (ARRE) of the IL-2 gene promoter . InteresNF90 protein has two dsRNA binding domains as well as a putative nuclear localization signal (NLS), a leucine-rich nuclear export signal (NES) and a C-terminal domain that is arginine, glycine (RG) rich . In quieReichman and Mathews  analyzedin vitro transcription, transient expression analysis and nuclear run-on experiments [Transcription activation by Tat occurs through TAR and requires proper folding of the TAR RNA hairpin structure . The roleriments -53. Binderiments . These sin vivo as well as by examining the epigenetic modifications of HIV-1 genome to assess the consequence of competing Tat/TAR RNA interaction in the presence of NF90ctv. We utilized pHIV-1 LTR-β gal and pSV-tat constructs to transfect HeLa cells in the presence and absence of NF90ctv. The basal level of transcription of HIV-1 LTR as judged by β-galactosidase reporter gene expression was stimulated by Tat. However, addition of NF90ctv significantly inhibited Tat-mediated transactivation. These results suggest that NF90ctv may effectively sequester TAR RNA and block Tat-TAR interaction thereby limiting Tat-mediated transactivation of HIV-1 transcription. Importantly, the competition of Tat-TAR RNA interaction mediated by NF90ctv leads to epigenetic marks of transcriptionally silenced HIV-1 chromatin.We approached the issue by biochemical binding/competition assays, transcription Inhibition of the Tat-TAR interaction is considered as a realistic approach to develop new anti-HIV compounds. Here we present a novel HIV-1 Tat/TAR antagonist, NF90ctv which inhibits Tat transactivation and attenuates viral production. Examining host cell response as a result of constitutive expression of NF90ctv, Krasnoselskaya-Riz et al,  reportedIn summary, we have identified a novel cellular protein that is able to bind to the TAR element and suppress Tat-mediated transcriptional trans-activation of HIV-1 LTR. NF90ctv recognition of TAR enables it to inhibit specific steps in the viral life cycle, in parallel with the activation of innate antiviral defenses of the host.


The External RNA Control Consortium (ERCC) is an ad-hoc group with approximately 70 members from private, public, and academic organizations. The group is developing a set of external RNA control transcripts that can be used to assess technical performance in gene expression assays. The ERCC is now initiating the Testing Phase of the project, during which candidate external RNA controls will be evaluated in both microarray and QRT-PCR gene expression platforms. This document describes the proposed experiments and informatics process that will be followed to test and qualify individual controls. The ERCC is distributing this description of the proposed testing process in an effort to gain consensus and to encourage feedback from the scientific community. On October 4–5, 2005, the ERCC met to further review the document, clarify ambiguities, and plan next steps. A summary of this meeting and changes to the test plan are provided as an appendix to this manuscript. The External RNA Control Consortium (ERCC) is an ad-hoc group with approximately 70 members from private, public, and academic organizations. The group was initiated in 2003 to develop a set of external RNA control transcripts that can be used to assess technical performance in gene expression assays. The external RNA controls will be added after RNA isolation, but prior to cDNA synthesis. They are being designed to evaluate whether the results for a given experiment are consistent with defined performance criteria. All ERCC work is intended to apply to quantitative, real-time reverse transcriptase polymerase chain reaction (QRT-PCR) assays as well as one-color and two-color microarray experiments.The ERCC has worked together to define the desired properties of the transcripts, general protocols for their application, and an analysis scheme for performance assessment. In December 2003, the group developed a specification document that was discussed and refined in a public workshop at the National Institute of Standards and Technology (NIST) . ProtocoIn the past year, the ERCC has refined specifications, generated and collected control sequences, evaluated optimal polyadenylated (polyA) tail length and identified a path forward for access and distribution of the controls. We are now initiating the Testing Phase of the project as described in this document.validation: "Confirmation, through the provision of objective evidence, that requirements for a specific intended use or application have been fulfilled." Based on the results of the test and qualification experiments, the ERCC will select a set of external RNA controls that perform consistently across technologies and platforms. DNA clones of the controls, basic informatics tools and appropriate documentation will be available to the public. Commercial products (e.g. primer sets and pools of transcripts) may also be developed and made available as Certified Reference Materials.During ERCC Testing, candidate external RNA controls will be evaluated in both microarray and QRT-PCR gene expression platforms. This document describes the proposed experiments and informatics process that will be followed to authoritatively test and qualify individual controls. Qualification of a control sequence is consistent with the ISO 9000 definition of The ERCC is committed to open access and inclusive practices. We are distributing this description of the proposed testing process in an effort to gain consensus from the scientific community and to confirm the value of the final products. We hope it will be carefully reviewed by clinical and research laboratory scientists. On October 4–5, 2005, NIST hosted an ERCC Testing Workshop as an open forum to encourage feedback from the community and to invite volunteers to participate in the testing phase tasks. Comments from the meeting are posted on the NIST site  for furtThe five specific aims of the testing project will result in production of a well-characterized, tested set of controls with demonstrated acceptable performance on major microarray platforms and commonly used QRT-PCR methods. The specific aims are as follows.1. Design and produce the reagents necessary for the testing plan, including candidate external RNA controls, prototype arrays, primer sets for QRT-PCR and informatics tools for managing and annotating the testing results.2. Qualify the reagents. Identify and minimize cross reactivity and potential interactions between the external controls, the probes used for their detection and background RNA molecules.3. Qualify the assay by collecting performance data in multiple gene expression assays. Identify the linear range, sensitivity and reproducibility of individual candidate controls. Define performance criteria and select a candidate reference set of external RNA controls for future testing.4. Qualify the product by using the candidate reference set of external RNA controls in typical microarray and QRT-PCR assays. Extend analyses to multiple RNA backgrounds and testing sites. Confirm the performance quality of the set of transcripts and the informatics tools used for their analysis. Finalize the reference set and ERCC products.5. Distribute DNA clones of the external RNA controls and informatics tools to general scientific community. Publish report on ERCC materials, testing data and analysis methods. Write application use and general protocols.In this document, the term "external RNA controls" refers to unlabeled, polyadenylated sense transcripts that are added to an RNA sample prior to processing and used to measure technical performance of the assay system. Although labeled transcripts will be generated during the testing effort to characterize the hybridization dynamics of each control, the final ERCC product is not intended to be used as a "hybridization control" in microarray experiments.The external RNA controls (sometimes referred to as "spikes") are intended to be added to total RNA samples before initiating the gene expression experiment. For microarray assays, a pool of multiple external RNA controls can be added to a single sample, then labeled and hybridized in parallel with the target. If each of the added spikes is introduced at a different concentration, a calibration curve can be constructed to indicate the linear range of the hybridization. Different pools of external RNA controls can be used in separate hybridizations (one-color system) or in different channels of the same hybridization (two-color system). For QRT-PCR assays, a single external RNA control can be added to the RNA sample and amplified simultaneously with the target sequence (two-color system) or independently in a replicate well (one-color system).Several sets of external RNA controls are currently available for microarray research -9, but fThere are two RNA transcript quantification methods for QRT-PCR assays, absolute and relative quantification. Absolute quantification is very useful and accurate when QRT-PCR is used for measuring one or a few targets, but it often requires generation of template standards for each target and it may become cumbersome especially when many targets are analyzed ,11.When QRT-PCR is used for gene expression profiling, or measuring dozens of transcripts simultaneously, relative quantification is often used. In this case, users rely on internal genes for normalization, usually a "housekeeping" gene or other transcript whose expression level is thought to be invariant. This approach has its own limitations. For example, an accurate relative comparison of gene expression requires similar primer affinities for both the target and the internal control, which are often difficult to achieve. Also, recent reports -17 have External RNA controls would provide an alternative method for normalization in relative quantification assays. The combination of external and internal or invariant controls is recommended as the most robust approach to optimal experimental control. Dose dependence, tissue specificity and degradation issues impact consistency of information and can be controlled for using a combination of controls. In addition, internal controls are more appropriately custom designed for analyte control in assays with a clearly defined intended use and therefore are by definition assay-dependent. The external RNA controls will provide a complementary resource to internal and assay-specific custom controls.The ERCC product will be a set of clones that have been well characterized for performance on multiple microarray and QRT-PCR platforms. Candidate clones are submitted to the ERCC and evaluated as described in this document. Based on the testing results, the ERCC will select clones that perform acceptably on all participating platforms to be used as the reference set.i.e., artificial) or are derived from genes in several non-mammalian species. Inserts are 500 – 2000 bp with a 20–30 bp polyadenylated tail. These clones are given freely without intellectual property rights. The ERCC welcomes additional submissions. Interested parties should contact Dr. Janet Warrington for further information [At this time, a number of organizations have submitted 140 candidate transcripts to be tested. As shown in Table This work culminates in the selection and distribution of materials that support the use of external RNA controls in expression assays. At the completion of the testing phase, the ERCC will release three products for use by the scientific community:• DNA clones and sequences of the reference set of external RNA controls• Basic informatics tools• Publication of data, test results, protocolsSeveral additional reagents and documents will be developed during the testing phase. Many of the documents will be issued electronically to the general scientific community via NIST  as supplThe testing work is divided into five sequential phases to coincide with the specific aims listed above. Milestones will be used to indicate the completion of each phase Table .The proposed methods and specific tasks associated with each phase of testing are described in the following sections. The testing will be performed in parallel by three working groups: microarray group, QRT-PCR group and informatics group. A fourth group responsible for RNA production will be contracted by NIST during phase 1. All of the ERCC members will participate in the documentation and publication tasks.This section describes the production and quality control processes for the candidate external RNA clones used in testing. NIST will be soliciting these manufacturing tasks through standard governmental procurement process.E. coli clones (strains carrying plasmids) will be compiled. This file will also contain the potential plasmids, which will be used for the production of the external RNA controls. A portion of the DNA plasmid or E. coli stock will be sent to the selected manufacturer(s) for the production of the ERCC reagents to be used in the testing project.DNA clones for candidate external RNA controls will be collected and stored in a NIST laboratory. Preliminary sequence information will also be collected from each clone contributor. Each clone will be assigned a unique identification number that coincides with all bioinformatic nomenclature specification requirements. A list of all candidate external RNA controls with vector, insert characteristics for the DNA plasmids and in vitro transcription (IVT) template preparation. Ambiguities will be noted and will be further investigated by re-sequencing and database comparisons. The ERCC Informatics subgroup will determine the "correct" sequences to be used for microarray probe and QRT-PCR primer design. Once all of the sequences have been collated and verified, these plasmids will be used for the next phase of production.Each plasmid will be grown in a small scale (~10 ml culture), purified and used for DNA sequence verification. Primer extension reactions will be designed to obtain full-length insert sequences. Both strands will be sequenced. These sequence files will be compared to the sequence submitted by the clone contributor. It will be important to verify both the presence of a polyA tail and the 3' restriction site to be used for linearization during e.g., T7, T3).All of the clones will be grown in 1 liter cultures to generate 1–2 mg of plasmid DNA. Samples of the bacterial cultures will be saved to create two sets of triplicate glycerol stocks properly labeled and stored at -80°C. One set will be sent to NIST and one set will remain at the manufacturer's site until the completion of the project, at which time the second set will be also be returned to NIST. Each purified plasmid will undergo a set of quality control tests to measure DNA concentration, confirm purity and verify the ability to be linearized at a restriction site located 3' of the polyA tail region. This last confirmation ensures the usability of the clones in the IVT reactions. The sequence will be re-verified using a single pass primer extension from the RNA polymerase promoter sequence  and the stability of the transcript . The quality of the stock transcripts will also be confirmed by measuring the length of the RNA to determine if it matches the expected size. The Agilent 2100 Bioanalyzer will be used for analysis of integrity, stability and nucleotide length.The quality of the Production RNA Transcript Stocks will be assessed for several characteristics, including concentration, purity, integrity, stability and size. Concentration will be determined using rigorously developed standard operating procedures for UV absorbance. Purity has two aspects: the integrity of the transcript  and normalized to 100 ng/ul at 1000 nt in length. For example, RNA transcripts that are 750, 1200, and 2000 nt in length will be diluted to 75, 120 and 200 ng/ul respectively.To determine the molar concentration of 1000 nt transcript, a formula or software script will be used to calculate exact molecular weight (MW) given RNA sequence. The RNA (single-stranded) molecular weight will be calculated for the phosphorylated, protonated form of the molecule using the following formula:MW = (#A × 329.21) + (#C × 305.18) + (#G × 345.21) + (#U × 306.17) + 18.02Stocks of individual RNA transcripts will be available in two forms: 96- well plates or screw-top tubes. Each RNA will be diluted and 50 ul aliquots of each normalized concentration will be transferred to a pre-specified well of a 96-well plate. Wells will be spot-checked for volume. Plates will be sealed with tape. Barcode tracking will be utilized to identify lots and all other tracked information. Plates will be labeled, dated and stored at -80°C until final packaging and shipping. The RNA transcripts will also be distributed in individual tubes at an equal molar concentration (to be determined).A series of RNA mixtures will be made according to the experimental plans. A description of all the pools required for microarray testing is presented in Table The RNA transcripts will be reverse transcribed with an oligo(dT)-T7 promoter primer and second strand synthesis will be performed to create cDNA templates for the synthesis of pre-labeled cRNA for each external RNA control. To allow testing in multiple microarray platforms, three types of cRNA labels will be used: biotin, DIG and amino-allyl. This labeled cRNA will be purified and quantified as above, normalized to equal molar concentrations, and pooled as shown in Table This section describes the testing methods necessary to develop a set of external RNA controls that can be used to assess the technical performance of microarray experiments. It is anticipated that many of the microarray vendors will participate in the ERCC testing, including Applied Biosystems, Affymetrix, Agilent, GE Healthcare and Illumina. Spotted, non-commercial microarrays will also be contributed by the USDA and NCI. This collection of microarray products include both one-color platforms, which hybridize one labeled target to a single microarray, and two-color platforms, which hybridize two targets with different labels to a single microarray.The microarray testing phases are designed to evaluate the candidate external RNA controls on both one-color and two-color platforms using the same pools of transcripts. Many of the experiments are designed to initially generate sufficient, quality data using relatively few microarrays and pools of transcripts. They may be expanded to a larger range of transcript concentrations and/or a greater number of replicate samples, as desired. A description of all required external RNA control pools is presented in Table After sequence verification, each array manufacturer will design probes targeting all of the candidate external RNA controls and generate microarrays to be used during testing.in silico validation. The oligonucleotides will be synthesized with 5' amine modifications through a custom synthesis and spotted on glass slides.Long DNA oligonucleotide (70-mer) probes will be designed by a joint effort of USDA and TIGR upon completion of sequence collection and The goals of the Prototype Testing phase, addressed in two experiments, are to ensure that the RNA transcript stocks and the probes to detect each of the external RNA controls exhibit a basic level of functionality.e.g., controls 1–48 in pool 1, controls 49–96 in pool 2 and controls 97–144 in pool 3) and a fourth pool of all pre-labeled transcripts will be generated. For one-color platforms, each pool of targets will be hybridized separately in triplicate against the test arrays. For two-color platforms, the pool 1–3 transcripts will be coupled to Cy3, while the pool 4 transcripts will be coupled to Cy5. Each test pool of Cy3-labeled transcripts will be hybridized in triplicate against reference pool 4 of Cy5-labeled transcripts.The first experiment is designed to check for unacceptable levels of cross-hybridization between the full set of candidate probes. To observe hybridization characteristics apart from labeling efficiencies, cRNA targets for each external RNA control will be pre-labeled with biotin, DIG or amino allyl molecules and pooled before hybridization. Assuming 144 candidate external RNA controls, the pre-labeled targets will be split into three pools . Examination of the relative signals for the probes whose targets were hybridized to the arrays should allow identification of probes that show potential cross-reactivity to another sequence included in the same pool. As a negative control, three arrays will be hybridized to cRNA targets generated from at least one representative background human sample in the absence of any external RNA controls. This representative background RNA sample will be from a human tissue (or set of tissues) chosen from the Microarray Quality Control Project [Each pool will initially be tested in the absence of labeled background cRNA. The expected result is that probes will only show a significant signal when the target they were designed against is in the pool hybridized to the array  in the representative human background total RNA. A second pool will be created in which the concentrations are reversed. Both pools will go through three independent target preparation reactions and hybridizations. For one-color platforms, each labeled pool of transcripts will be hybridized to a separate microarray. For two-color platforms, targets from both pools can be labeled with different Cy dyes and hybridized to the same microarray. The observed ratios across the two pools will be compared to the expected 4-fold change. External RNA controls that do not label or give the expected response (something reasonably close to a 4:1 intensity ratio) will be removed from the pool of candidate external RNA controls.The second experiment in the Prototype Testing phase will test whether the external RNA controls can be labeled in the presence of a complex background of total RNA. It will also demonstrate their ability to detect known differences in transcript abundance between two pools. One pool will contain external RNA controls in one of two concentrations  Require a minimal number of arrays and pools; 2) Introduce transcripts as series of pools with balanced cRNA load that are made at a central site, rather than in individual testing labs; and 3) Use the same pools on both one-color and two-color platforms.To best achieve these objectives, this phase of array testing is based on modified versions of a Latin Squares design for one-color platforms and a Graeco-Latin Square design for two-color platforms . Illustri.e., a different relative mass). For simplicity, multiple transcripts are present at the same concentration in this modified design, rather than each transcript at a different concentration. This design can be referred to as a modified (or semi-) latin square experiment.Phase 3 will characterize a putative set of clones that are selected based on their performance in phase 2. In this discussion, we will assume the set includes 96 clones. These external RNA controls will be split into four groups of 24 controls each , allowing for wider participation during this phase of testing, instead of limiting participation to those facilities that are able to run the potentially hundreds of arrays required for complete Latin Square or Graeco-Latin Square experiments. The potential drawback to this design is that it allows for measurement of only a limited number of target concentrations. For those interested in measuring the external RNA control performance across a wider range of target concentrations, the experiment can be expanded without the requirement of additional pools. This expansion can be accomplished by diluting each of the pools further to establish other concentration ranges, prior to introducing them into the background human total RNA.Examples of three such dilution ranges are provided in Table i.e., the original stock plus Dilutions 2–4) would consume 48 arrays (plus the three negative control arrays) and would measure each of the 96 potential external RNA controls at 16 concentrations ranging from an estimated mass ratio of 1:1,000 down to 1:5,000,000.Participants can choose to test a few or many different ranges. Testing all four ranges  experiment consists of testing each external RNA control at multiple concentrations, one per array, requiring several arrays. In contrast, a single array DRC experiment consists of multiple concentrations and multiple external RNA controls per concentration, all tested on a single array. Because the entire experiment is contained within a single array, each external RNA control is measured only at a single concentration. Therefore, the intensities from all of the probes are used together to construct the DRC across the entire concentration range. During the Functional Testing phase, the target metrics determined during the Proof of Concept phase will be used to create a single-array DRC external RNA control pool. An example single array DRC pool is shown in Table e.g., 1:1,000) are under-represented compared with the lower concentrations . Additionally, external RNA controls originating from the same species will be evenly distributed across the concentration range to minimize the effects of removing them from experiments performed with background RNA from the same species.To keep the ratio of external RNA controls to background RNA as low as possible, the higher concentrations of external RNA controls .Up to three pooling schemes will be tested, each with triplicate hybridizations. For one-color platforms, each labeled DRC pool of transcripts will be hybridized to a separate microarray. For two-color platforms, targets from different DRC pools can be labeled with different Cy dyes and hybridized to the same microarray .Once the final single array DRC pool has been chosen, a small series of forced failure experiments will be carried out to mimic how the system will respond to common failure modes  and target-specific probes with fluorescent 5' exonuclease activity . The testing plan will generate data on both platforms, using the same primer sets. The DNA-binding detection assays will use a single tube, one enzyme (rTth) and SYBR Green I based protocols. The target-specific detection assays will use a two-step protocol developed for the TaqMan® system.The QRT-PCR testing phases are designed to use the same pools of transcripts developed for microarray testing and to evaluate the candidate external RNA controls on multiple QRT-PCR platforms. There are two commonly used methods of detecting the QRT-PCR amplicons: DNA-binding dyes  will be finalized and used to determine the entirety and specificity of RNA transcripts. For target-specific detection assays, a fluorescent 5' exonuclease detection probe will also be designed. The sequences of all QRT-PCR reagents and their locations on the RNA transcripts as well as the sizes of amplicons and their predicted Tm will be provided to the community. All primers and detection probes will be blasted against Genbank for potential cross-reactivity.With the DNA-binding detection assays, the concentration and ratio of primers must be optimized to prevent fluorescent signal from "primer dimers" or nonspecific amplicons. Experiments will be performed to develop amplification parameters for ABI 7900HT and Stratagene MX3000 using a single tube, one enzyme (rTth) and SYBR Green I based QRT-PCR protocol. With the target-specific detection assays, the primer and detection probe concentrations and thermal cycling conditions will be as suggested by the manufacturer. cDNA will be generated using standard kits and random primers prior to amplification.QRT-PCR will be used to assess the quality of the RNA transcripts produced for each of the candidate external RNA controls. Individual transcripts will be evaluated for entirety, stability, and DNA contamination. The specificity of each primer set and detection probe will be determined by amplifying individual transcripts in equal molar pools of the candidate controls. QRT-PCR can also be used to verify transcript ratios in pools with variable concentrations of the candidate controls.Each set of QRT-PCR primers as well as any detection probes will be tested for cross-reactivity with other external RNA transcripts by amplifying its perspective RNA transcript from three different RNA sources. First, individual transcripts will be amplified from a pool containing multiple RNA transcripts at equal molar concentration  data will be stored in FASTA format; 2) where appropriate, annotation will include unambiguous cross-references to gene identifiers in public databases; and 3) maintainability and version control.e.g., data normalization); 3) develop prototype tools that can be used for the exploration of the analysis approaches; and 4) test prototype tools using existing or synthetic data.The Analytical Informatics work in this phase is exploratory and will establish prototype tools for the potential analysis approaches. The major tasks for the analytical informatics work at this phase are: 1) identify appropriate QRT-PCR analysis approaches; 2) investigate various analysis approaches for microarray technical performance, including evaluation of preprocessing strategies  be a function describing relationship between expected signal and spike concentration. Also, let εS(c) be a function describing relationship between standard deviation of signal and spike concentration.2. Let 3 Define signals S and S* (S < S*) as reliably resolved if and  ( <) as reliably resolved if expected signals produced by these concentrations are reliably resolved.Define concentration levels  as reliably resolved if concentration levels  and  are reliably resolved.Define concentration fold change –  where  and  are the ends of the longest interval of target concentrations such that f (ct) ≤ 2 ∀ ct ∈ .Define linear range as Thus, the linear range is the largest continuous interval of target concentrations such that a two fold increase of concentration anywhere within this interval gives rise to reliably resolved expected signal levels.4. Using these assumptions we will explore several models to determine linear range and minimal reliable resolved concentration fold change.Approach 4 – fitting the spike-in probe behavior on an individual array to a reference model of known, acceptable performance . The slope measures ratio flattening . The model clearly differentiates between failures to observe expected ratios that are due to normalization and effects that are due to ratio flattening. This is important, because the two effects are often confused and misdiagnosed.This model has the nice feature of physically reasonable and appealing interpretations of the slope and intercept. The intercept is the log of the bulk normalization constant for the external RNA control .Implementations for the analytical approaches will be developed in the prototyping phase. These implementations will be tested against modeled/simulated data, as well as against existing data, where possible. As data become available from the QRT-PCR and microarray testing activities, those data will be used to evaluate the prototype analytical implementations. The analyses may be implemented with a variety of numeric and graphical tools . The QRT-PCR analysis approach may be developed as a separate bioconductor package, with the emphasis likely to be on a graphical display of performance measures as a time series.Development of web-based implementations of the analysis implementations will be investigated, and common data formats for input and output will be specified and implemented.The bioconductor package will be published and released to the community. A manuscript will accompany publication of the package, describing the analytical approaches embodied in the package, and demonstrating performance with the validation data. All relevant performance data from the testing and development of the ERCC analytical informatics will be collated and published at this time.The reference sequence database will be published and made available on the web in both flat-file formats and a common sequence database format (FASTA).Performance data from the testing will be published. Collate performance data (from Test Reports), including probe performance data, in backgrounds.Identify least burdensome path for collection and distribution of data• Organize analysis jamboree• Plan publication of results and timing for publication(s)• Organize controls symposium• The tasks described in this document have been designed and reviewed by many ERCC members. They represent our best consensus at this time, but may not be the final format of testing. A summary of the issues discussed at the ERCC Testing Workshop on October 4–5, 2005 is provided in Appendix 2 and copies of the presentations are posted on the NIST website .ERCC, External RNA Control ConsortiumQRT-PCR, quantitative, real-time reverse transcriptase polymerase chain reactionNIST, National Institute of Standards and TechnologypolyA, polyadenylatedin vitro transcriptionIVT, MW, molecular weightDRC, dose response curveCy, Cyanine DyeCt, Cycle ThresholdThe ERCC reviewed feedback on the Proposed Testing Plan at a NIST-hosted workshop on October 4–5, 2005. The meetings were attended by more than 50 participants, including ERCC members from Europe  and the US. During the first day of the meeting, summaries of the test plan were presented by representatives from each of the four subgroups. Suggested improvements and possible testing issues were discussed as listed below:Perhaps the ERCC set should include different types of controls (less than 100 bp or no polyA tail) that would support new labeling technologies or gene expression applications. Many members liked this possibility, and although it is outside the scope of the current ERCC initiative, it may develop into future ERCC activities. A request was made for early release of the submitted but not confirmed sequence of the external RNA controls. Another ERCC deliverable describing how to validate the quality of the external RNA controls was suggested.The external RNA control concentrations used during phase 2 cross hybridization experiments as well as the exact definition of cross-reactivity were discussed. It was noted that identifying the specific transcript responsible for cross hybridization observed in a pool of 24 candidates may require many subsequent hybridizations with individual controls. Early definitions of the concentrations in the Latin square and dose response curve experiments are needed, with an emphasis on accommodating the ranges of both channels in two-color arrays. After a thorough discussion, it was decided to include pre-labeled external RNA controls in phase 2 of testing. Many of the microarray technology developers indicated that the test arrays might include multiple probes or probe sets in order to identify the best performing sequences. This format was acceptable, as long as participants agreed not to change probe sequence between phases.The proposed test plan uses dilutions of equimolar pools of 96–140 the candidate RNA controls in the QRT-PCR assays. At the meeting, it was decided that plates of individual RNA transcripts would be more useful during the initial testing in phases 1–4. It was recognized that only 1–3 external RNA controls at a time would be used in QRT-PCR assays due to limitations in the number of fluorophors that can be detected. There was also some discussion that QRT-PCR assay optimization may require more than 2 primer sets described in the proposed test plan. A new application for the controls in the validation of thermal cyclers and other QRT-PCR instruments was discussed.The ERCC will need a plan for data storage and distribution. NCI, NCBI, and FDA representatives volunteered to provide a data repository for Test Plan data. A working group will be formed to identify needs of the ERCC and identify which of these data repositories would be a good fit. Participants were directed to the CLSI MM16-P document for a list of possible performance metrics. Preliminary review of these metrics could be initiated now using already available gene expression data on many of the candidate external RNA controls. There was some discussion on whether the external RNA controls should be optimized and selected to have the best possible results  or left imperfect to better reflect typical probes or probe sets on the microarrays.After nine hours of review and discussion, consensus was achieved on the ERCC Test Plan by a show of hands with no major outstanding issues. On the second day of the meeting, preliminary resource requirements were identified and the scope of testing (sample number etc.) was better defined. Key features of this discussion are summarized below:1. In an effort to efficiently utilize the RNA reagents, early stages of testing (Phases 1–4) will be performed only at developer sites and limited to one site per platform. We estimate that up to 10 microarray and 4 QRT-PCR commercial developers will participate. If resources permit, 3 or 4 noncommercial development sites (e.g. NCI or USDA) will be included to represent home-made, spotted microarrays.2. Phase 5 will be divided into two parts with separate goals. In Phase 5A, the last experiment of Phase 4 will be repeated at user sites to confirm that results can be reproduced using the same materials and protocols as at the developer sites. In Phase 5B, a set of the best performing external RNA controls will be distributed to user sites and incorporated into typical experiments with their materials and protocols. The intent is to establish performance of the external RNA controls in a broad variety of routine applications and protocols. One possible Phase 5B experiment would be to repeat a previous gene expression experiment to validate that similar differential expression results are observed with and without the inclusion of external RNA controls.3. A tentative list of criteria for technology developers and user test sites was developed. It was decided that all sites should have the following attributes: 1) Demonstrated experience in gene expression platform; 2) Ability to contribute materials and labor; 3) Commitment to deposit all testing data in publicly available database; and 4) Agreement to meet ERCC timeline. In addition, developer sites should have demonstrated capacity to design and create the necessary reagents as well as a commitment to follow the test plan and collect data on all candidate clones. User test sites may be asked to contribute a novel application to the ERCC goals and to provide sample material for the complex RNA background. It is not necessary to have contributed sequences to be considered as a test site.4. While the external RNA controls are likely to be useful in RNA samples from a variety of species, testing will emphasize human, mouse and rat RNA. A Stratagene representative offered to provide universal reference RNA samples from these three species to be used as the complex RNA background in Phases 1–4. Test microarrays will include probes or probe sets for both the candidate external RNA controls as well as genes included on their typical human, mouse and rat arrays (as determined by each developer). This design will enable global normalization methods and aid in cross hybridization experiments. The developers may elect to pre-screen their test arrays using RNA from a variety of species.Action items and next steps will be further discussed in the monthly ERCC conference calls.3Certain commercial equipment, instruments, or materials are identified in this document. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the products identified are necessarily the best available for the purpose.


Within eukaryotes there is a complex cascade of RNA-based macromolecules that process other RNA molecules, especially mRNA, tRNA and rRNA. An example is RNase MRP processing ribosomal RNA (rRNA) in ribosome biogenesis. One hypothesis is that this complexity was present early in eukaryotic evolution; an alternative is that an initial simpler network later gained complexity by gene duplication in lineages that led to animals, fungi and plants. Recently there has been a rapid increase in support for the complexity-early theory because the vast majority of these RNA-processing reactions are found throughout eukaryotes, and thus were likely to be present in the last common ancestor of living eukaryotes, herein called the Eukaryotic Ancestor.We present an overview of the RNA processing cascade in the Eukaryotic Ancestor and investigate in particular, RNase MRP which was previously thought to have evolved later in eukaryotes due to its apparent limited distribution in fungi and animals and plants. Recent publications, as well as our own genomic searches, find previously unknown RNase MRP RNAs, indicating that RNase MRP has a wide distribution in eukaryotes. Combining secondary structure and promoter region analysis of RNAs for RNase MRP, along with analysis of the target substrate (rRNA), allows us to discuss this distribution in the light of eukaryotic evolution.We conclude that RNase MRP can now be placed in the RNA-processing cascade of the Eukaryotic Ancestor, highlighting the complexity of RNA-processing in early eukaryotes. Promoter analyses of MRP-RNA suggest that regulation of the critical processes of rRNA cleavage can vary, showing that even these key cellular processes (for which we expect high conservation) show some species-specific variability. We present our consensus MRP-RNA secondary structure as a useful model for further searches. There is high interest in discovering new roles of RNA in modern eukaryotes -4. The nMRP) generating the mature 5.8S rRNA  and Plasmodium yoelii [GenBank: BM161600 and GenBank: BM160961]. Validation of the MRP-RNA candidate from Cryptosporidium parvum with RT-PCR shows that this sequence is expressed in trophozoites . These Plasmodium and C. parvum results are particularly important because they show expression outside the animal, fungi and plant groups. In addition, five of our MRP-RNA sequences occur in Genbank records : G. gallus [GenBank: AADN01006913], T. nigroviridis [GenBank: CAAE01012081], P. falciparum [GenBank: NC_004325] and P. yoelii [GenBank: AABL01002665]. That these do not overlap coding sequences is additional support for our computational approach. Interestingly, the candidate for the D. melanogaster MRP-RNA is on the negative strand of an intron in the Dmel_CG10365 gene [GenBank: AE014297], although the function of this gene is still unknown.Our MRP-RNA candidates were checked against existing gene records and EST databases to support our bioinformatic approach. Of our new MRP-RNA candidates, two are found in EST databases: Strongylocentrotus purpuratus, appears to have five closely related sequences, although some could turn out to be artefacts of the current assembly. Multiple MRP-RNA genes have been observed in plants [Takifugu rubripes [A single copy of the MRP-RNA gene was found in most species. However, the sea-urchin, n plants . Humans n plants  typicallrubripes  indicateGiardia lamblia. We examined the rRNA organisation in G. lamblia to determine if an A3 site, normally cleaved by MRP, was present. The order of rRNA subunits are in general similar throughout eukaryotes [E. cuniculi and Nosema apis) contain no ITS2 region and have no cleavage between the 5.8S and the 28S rRNA subunits. Another group of microsporidia, including Nosema bombycis and N. spodopterae, are exceptions to the standard eukaryote ordering, having the fused 5.8S/28S subunit before the 18S rRNA subunit [G. lamblia rRNA has the standard ordering of eukaryotic rRNA, and its ITS1 region can be folded into a secondary structure with a short six nucleotide single stranded region between the two helices, a possible A3 cleavage site  folds into a helix followed by an AC rich single-stranded region which could be the cleavage site for MRP. Future experimental analysis will determine the exact cleavage sites in these ITS regions.As before ,31 we dikaryotes   ,39,40. RDrosophila, specificity is determined by the presence of the TATA box and the sequence of the PSE element [S. cerevisiae uses a different RNA polymerase III promoter structure [We find that MRP-RNA is probably transcribed by RNA polymerase III throughout eukaryotes but the set of RNA Polymerase III promoter elements may vary . Comparisons of six species of Drosophila  show a conserved PSE element (consensus sequence gcTTAtaATTCCCAAct) 23 nucleotides upstream of a TATA box (consensus sequence taaAta) which is about 16 nucleotides upstream of the transcription start site. The range of RNA polymerase III promoter structures and the lack of information about these promoter elements from protists make it difficult to identify promoter elements from protist MRP-RNA genes. Preliminary analyses of promoter regions from apicomplexa (Plasmodium and Cryptosporidium) indicate likely TATA boxes, but at this stage we cannot predict the presence of PSE or DSE elements. The AT richness of this region makes promoter prediction difficult until such time as we have more experimental information about promoters in apicomplexa. A table of promoter elements is available from the corresponding author upon request.Promoter comparisons show there can be differences in MRP-RNA promoter elements between some closely related species. For example in fish, the MRP-RNA promoter region for ribed in  characteAnalysis of the secondary structure of MRP-RNA Fig. . Our namDictyostelium discoideum, Anopheles and the nematode Brugia malayi. The P10 helix is often long, typically 20–40 nucleotides, but in extreme cases (Pezizomycotina and Cryptosporidia) over 200 nucleotides. P15/ymP7 is present in Saccharomycetes yeasts and some apicomplexa. ymP8 is present in S. pombe, all Saccharomycetes with known MRP-RNAs, and some Pezizomycotina yeasts. The distinction between ymP7 and ymP8 is not always clear (e.g. Coccidioides immitis). There are some species-specific divergences from our secondary structure model. P19 is absent from Ciona intestinalis and P6 is absent from microsporidia and D. discoideum. P6 is absent from Cryptosporidia in previously published secondary structures [Details of the consensus MRP-RNA secondary structure are as follows. P3 nearly universally has two helices  separated by an internal loop; except for the absence of P3b in microsporidia and an additional P3c helix in Cryptosporidia, ructures , but theGARA) [GARAR and GARA but others are possible including the fish Tetraodon nigroviridis (CAAAG), cabbage Brassica oleracea (GAGG), Babesia bovis (TAAAG) and Eimeria tenella (GCGAG). Cryptosporidia, Plasmodia, T. vaginalis and some ascomycete fungi do not appear to have the GARAR motif. The three basidiomycete fungi also have varied GARAR motifs; two species (Coprinus cinereus and Laccaria bicolor) have GAAAG as part of a bulge on P8. This region is suggested by [AnAGUnA, the 'U' and the first 'A' sometimes being substituted. This motif is not recognisable in T. vaginalis and some Alveolata. In S. purpuratus (sea-urchin) the motif is in a non-standard position, overlapping and extending beyond P2.The GARAR motif (R = A or G), recently noted by  and discGARA) . The majested by  to be anS. cerevisiae). As well as nuclear rRNA and mitochondrial primer cleavage functions, in S. cerevisiae at least, it has an additional function of promoting cell cycle progressing by cleaving CLB2 mRNA in its 5' UTR region at the end of mitosis [The RNA cascade connects a number of RNA-based complexes where RNA is processing other RNA molecules. Figure  mitosis ,53. It iS. pombe [One main conclusion from this study is that, with the placement of MRP in the RNA-processing cascade of the Eukaryotic Ancestor, we see little change in basic RNA-processing throughout eukaryotes. Eukaryotes and prokaryotes have basic differences in their processing of their rRNA transcripts ; the maiS. pombe . It is lE. coli P-RNA [The cleavage of site A3 in the ITS1 region by MRP is similar to the cleavage of the tRNA in the bacterial system by P. However, we do not know whether the eukaryotic-type of RNA-processing cascade has evolved from the bacterial RNA-processing system. Bacteria, archaea and eukaryotes have probably changed their original RNA-processing cascade, each in their own evolutionary trajectory . Nor do li P-RNA . We can The high similarity of secondary structure between MRP and P  is indicS. cerevisiae [The GARAG motif is an interesting addition to the MRP-RNA secondary structure. This pentaloop  is potentially a protein or RNA binding site, which would explain its conserved nature. GNRA tetraloop motifs are also found in bacterial P (Type B but not Type B), archaeal P (both Type A and Type M) and also possibly in the ep9 helix of P from the yeast revisiae . They arrevisiae . The newrevisiae . This moThe promoter region analysis indicates that RNA polymerase III is used throughout eukaryotes to transcribe MRP-RNA. It is interesting that there is such a range of promoter elements for MRP-RNA transcription and that the spacing between different elements appears critical in some species and not others. This may indicate that the regulation of MRP differs between groups of eukaryotes even for such an essential function as rRNA cleavage. There is little information about RNA polymerase III transcription in protists and the possible promoter regions are seldom reported when new ncRNAs are characterised.C. elegans and C. briggsae, although complete genomes have been available for these species for several years. Similar exceptions are the protists Giardia lamblia and Entamoeba histolytica. However, MRP-RNA [Brugia malayi [C. elegans [G. lamblia [C. elegans and C. briggsae again did not result in a plausible MRP-RNA candidate. We have also not yet recovered any MRP-RNA from a G. lamblia RNA library  . Nevertheless, in C. elegans, G. lamblia and E. histolytica the rRNA gene arrangement is generally the same as in other eukaryotes [G. lamblia and E. histolytica [Trichomonas vaginalis and the microsporidian E. cuniculi both of which have had MRP-rRNAs [G. lamblia does not contain a nucleolus, but it is expected to contain a eukaryotic-like rRNA processing system due to the presence of many pre-rRNA processing proteins [G. lamblia [Trichomonas vaginalis [G. lamblia and even other excavates such as the Eugelenozoa (e.g. Trypanosoma brucei), using present techniques in computational analysis which rely heavily on sequence homology in the P4 region.Although MRP has been characterised in many eukaryotes, it has yet to be found in the nematodes  MRP-RNA , was foua malayi . P-RNA h elegans  and G. l lamblia ,61 but e lamblia  based onkaryotes , althougtolytica . Short IRP-rRNAs . G. lambproteins . Some pr lamblia . Two MRP lamblia  have beeaginalis ) means tIt is likely that the major protein and RNA components of the RNA processing cascade evolved before the Eukaryotic Ancestor  It is iThe RNA-processing cascade is now seen as a complex feature of the ancestral eukaryotic cell. Only when we understand which eukaryotic processes were in the Eukaryotic Ancestor we can then consider how they evolved.We present the organisation of RNA-processing in eukaryotes as a cascade of RNA-based processing reactions cleaving or modifying other RNA molecules. The main components of this cascade are conserved throughout eukaryotes and are likely to have been present in the Eukaryotic ancestor. We can now place MRP in this cascade and thus basic RNA-processing has been preserved in eukaryotes. Analysis of MRP-RNA promoter regions suggest, however, that regulation of these critical processes differs between species showing that even these key cellular processes are showing some species-specific variability. Computational searches for ncRNAs are difficult due to the necessary incorporation of secondary structure as well as sequence information. Our consensus secondary structure for MRP-RNA provides a useful model for further search strategies.The conserved regions around the P4 pseudoknot are important for finding potential candidate MRP-RNAs. A genome is scanned for regions similar to the conserved sequences from known MRP-RNAs then candidates are evaluated for stereotypical secondary structure. Candidates with suitable secondary structure are evaluated for upstream promoter regions expected for a gene transcribed by RNA polymerase III, then blasted against EST databases  for any gaaAGuCCCC and acnnnanGGGGCUnannnu respectively, paired bases in uppercase). We have three levels of search criteria. Using the tightest criteria, 5'P4 and 3'P4 can be separated by 120 to 280 bases and we allow just one deviation from the consensus . The second, slightly looser, search criteria allows 100 to 360 bases between 5'P4 and 3'P4, and two deviations from the consensus. The loosest criteria allows a 80 to 500 base separation of P4, and two deviations from the consensus or a single violation of the expected Watson-Crick pairings. Genomes are scanned with the tightest criteria first, then with subsequent relaxed criteria if the first scan fails to identify an MRP candidate with suitable secondary structure. The Perl programs used are available upon request.In more detail, the algorithm allows the search of genome sequences for closely located sequences which match or nearly match the consensus 5'P4 and 3'P4 regions (taken to be Vertebrate  and yeasMW carried out the search and secondary structure analysis and drafted the original manuscript. PFS contributed to the search of new and not easily available genomes. DP participated in the design of the study and contributed to the evolutionary discussions. LC carried out the promoter analysis and drafted the final manuscript. All authors read and approved the final manuscript.MRP-RNA sequences from a wide distribution of eukaryotes.Click here for file