Here we provide the first strategy to use a competitive Extendable Blocking Probe (ExBP) for allele-specific priming with superior selectivity at the stage of reverse transcription. In order to analyze highly similar RNA variants, a reverse-transcriptase primer whose sequence matches a specific variant selectively primes only that variant, whereas mismatch priming to the alternative variant is suppressed by virtue of hybridization and subsequent extension of the perfectly matched ExBP on that alternative variant template to form a cDNA–RNA hybrid. This hybrid will render the alternative RNA template unavailable for mismatch priming initiated by the specific primer in a hot-start protocol of reverse transcription when the temperature decreases to a level where such mismatch priming could occur. The ExBP-based reverse transcription assay detected BRAF and KRAS mutations in at least 1000-fold excess of wild-type RNA and detection was linear over a 4-log dynamic range. This novel strategy not only reveals the presence or absence of rare mutations with an exceptionally high selectivity, but also provides a convenient tool for accurate determination of RNA variants in different settings, such as quantification of allele-specific expression. Single nucleotide polymorphisms (SNPs) and point mutations are the most common types of genetic polymorphism , and theIn contrast to AS-PCR, allele-specific priming during reverse transcription would in principle allow for direct transformation of highly similar RNA variants into distinguishable allele-specific products in a single step, therefore, it has long been expected to be a promising alternative for analysis of RNA variants. However, pioneering investigators showed that reverse transcriptases could initiate primer extension from a mismatched primer with sufficiently high efficiency ,31, leadIn this report, we describe the first strategy employing an ‘extendable’ competitive blocking probe in reverse transcription (ExBP-RT) to achieve allele-specific priming with superior selectivity, which enables accurate detection and quantification of RNA variants. In ExBP-RT strategy, the mutated RNA template is selectively primed during reverse transcription by the mutation-specific primer, which is coupled to a unique signature at its 5′ end to support detection/discrimination of the allele-specific products in the following step. Most importantly, mismatch priming to the more abundant wild-type RNA template is substantially suppressed by the extendable wild-type-specific competitive blocking probe using a hot-start protocol in reverse transcription.ExBP-RT is a simple, universal strategy for ultrasensitive detection of mutations in RNA samples and moreover, it enables accurate determination of the RNA levels of expressed mutations, which might reflect the functional consequences brought upon the cells or tissues more faithfully than a DNA-based mutation detection assay . This stin vitro transcription using DNA templates with sequences corresponding to the wild-type and different mutated variants of the KRAS and BRAF genes. We prepared DNA templates for invitro transcription using PCR amplification of synthetic DNA oligonucleotides, with forward and reverse primers targeting ‘underlined’ sequences  according to manufacturer's instruction. The concentrations of resulting RNA samples were quantified using a NanoVue spectrophotometer , and the copy numbers of the different RNA variants were verified using quantitative RT-PCR . The primers for these RT-PCR assays were obtained from TAG Copenhagen A/S. The primer sequences are listed in Table The PCR products were used to synthesize RNAs by 2O, before the allele-specific reverse transcription reaction.Human RNA samples were extracted from formalin-fixed paraffin embedded (FFPE) samples of colorectal cancer tumor tissue using phenol-chloroform extraction . These sFor each analyzed mutation, a mutation-specific primer was designed to target the mutant RNA and a wild-type-specific blocking probe was designed to target the wild-type RNA Table . The mutIn the KRAS G12D mutation detection assay a non-extendable oligo that hybridizes to a region downstream of the priming site on the RNA template was used to prevent primer extension resulting from non-specific priming of allele-specific RT primers to a wrong locus downstream of the expected priming site. The sequence of this oligo was: 5′-GAATTAGCTGTATCGTCAAGGCACTAAAAAA-3′.2+ ion has been adjusted to 10 mM. In addtition, the unbound primers and nucleotides were degraded using 10 unit of Exonuclease I (Thermo Scientific) and 1 unit of Thermosensitive Alkaline Phosphatase (Thermo Scientific) before proceeding to the quantitative PCR step.Multiplex ExBP-RT assay contains, in the same reaction of reverse transcription, six different mutation-specific primers targeting all possible KRAS mutations at codon 12 and a common ExBP targeting the wild-type KRAS transcript . The PCR reactions were incubated at 95°C for 2 min, then for 42 cycles at 95°C for 5 s, 63°C for 20 s and 72°C for 10 s. In multiplex ExBP-RT, we amplified 1 μl of each cDNA synthesis product in the 10-μl qPCR reactions with QuantiTect SYBR PCR Kits (Qiagen) at 95°C for 15 min, then 45 cycles at 94°C for 15 s and 60°C for 45 s, in order to detect either mutant or total KRAS transcripts. The primer and probe sequences for each qPCR assay are listed in Table ® Universal Master Mix II, no UNG , 900-nM primers, 200-nM probe and 3600-nM blocker. Standard TaqMan thermocycling conditions were used: 95°C for 10 min, 40 cycles at 95°C for 20 s, at 60°C for 45 s. The oligonucleotides used for KRAS G12D mutation assays has been selected from the original report  according to the manufacturer's instructions in a 10-μl volume with 50 nM of each reverse primer. TaqMan PCR was performed with an RT volume of 1 μl in a 10-μl assay with 1× TaqManl report  as follo® 480 II system .Threshold cycle (Ct) values were calculated automatically using the default second derivative maximum method, which is built in the LightCycler7 copies) of matched templates (mutant RNA). The ratio of product formed in the first reaction normalized to product formed in the second reaction can be determined by quantitative PCR based on the difference in Ct values derived from two reactions (ΔCtwt-mt = Ctwild-type − Ctmutant). The selectivity of each ExBP-RT assay expressed as percentage was calculated as 2−ΔCt × 100%, which correspond to the lowest fraction of mutant transcripts to be detected as a distinct signal from the background signal derived from the wild-type template.The selectivity of each ExBP-RT or other assays for detecting mutant RNA transcripts among a surplus of wild-type transcripts is determined by comparing products formed in the first reaction containing mismatched template (wild-type RNA) with those formed in the second reaction containing the same copy number , so that the ratio of mutant versus wild-type KRAS RNA ranged from 10 down to 10−4 . The assays were performed using the ExBP-RT strategy followed by SYBR Green I-based quantitative PCR. Details on reaction conditions are described in the ‘Materials and Methods’ section. Mutant KRAS G12R RNA was detected as a signal distinct from the wild-type KRAS RNA at least in mixtures containing a proportion of 1:1000 or more of mutant KRAS G12R RNA . The superior selectivity of the assay has also been verified using various copies (108 to 103 copies) of wild-type KRAS RNA only or mutant KRAS G12R RNA only as template . The amplification products have been visualized on agarose gel 2% in order to confirm the expected size (59 bp) of amplified sequences . Omission of RNA template, mutation-specific primer or reverse transcriptase in negative control samples leads to complete lack of amplification.To demonstrate proof of principle, we prepared several RNA mixtures of two A Figure  and the The applicability and selectivity of the ExBP-RT strategy for analysis of RNA variants was assessed on a panel of different templates and mutation types to detect all six possible mutations at codon 12 of the KRAS gene and the BRAF V600E mutation. The primer sequences for each assay are listed in Table −ΔCt × 100%) was shown in Table The selectivity expressed as percentage of each ExBP-RT assay . When a non-extendable blocking probe is added to the reverse transcription reaction, the resulting ΔCtwt-mt increases modestly to 5.8 , which is in line with the original report, this translated into a relatively low selectivity due to the low PCR amplification efficiency of only 90% . The PCR primer with low Tm and the inhibiting effect of blocking probe probably compromise the PCR amplification efficiency in this ASB-PCR assay. When the blocking probe is excluded from the Mut2.1 assay, the selectivity of consequent AS-PCR assay is greatly attenuated to 20% (2−2.3 × 100%), which is also consistent with the original report. It is worthy noted that this Mut2.1 assay involve the primer:template mismatch (dA:dC), which is reasonably unstable. When the discriminating primer was designed to target the same mutation but on the other strand , the most stable primer:template mismatch (dT:dG) is involved and the selectivity of the assay is reported to be even worse  mutation has been selected as model, because ExBP-RT assay for detection of this RNA variant involve the most stable primer:template mismatch (dT:rG) . Differeen worse .7 copies) show early amplification (left red curve), whereas omission of RNA template or reverse transcriptase in negative controls leads to complete lack of amplification. All tested clinical samples were shown to contain comparable amounts  of total KRAS RNA , which are sufficient for the assay reproducibility , which accounts for ∼32.5% of all KRAS mutations , from FFcibility . Agarose2O or RNA extracted from KRAS-wild-type cell line COLO205, and omission of RNA template or reverse transcriptase also lead to complete lack of amplification. The mutation rate observed in archival FFPE samples from patients with colorectal cancer was slightly higher than what has been reported (27.7%) in a worldwide multicenter study using DNA-based mutation detection assays  extendable competitive blocking probes enable allele-specific priming during reverse transcription with superior selectivity, particularly when utilizing a hot start and subsequent slow cool down temperature protocol; (ii) extendable wild-type-specific blocking probes outperform non-extendable substitutes to suppress mismatch priming during reverse transcription and (iii) an engineered 5′-tail sequence in the mutation-specific RT primer allows for selective PCR amplification/enrichment of the rare variant, completely avoiding the amplification-dependent decay of selectivity which is a well known problem related to allele-specific PCR. This ultimately results in convenient assay for ultrasensitive detection of mutant RNA in the presence of a 1000–10 000-fold excess of the wild-type counterpart.Currently, various strategies have been established for SNP genotyping and mutation detection, usually containing the steps of target DNA amplification, allele discrimination reaction and detection/identification of allele-specific products . The tarIn the ExBP-RT strategy presented here, the allele discrimination reaction takes place during reverse transcription; accordingly the requirement of either performing a separate step for allele discrimination or handling of post-amplification products is avoided. Since the reverse transcription reaction is performed during a single cycle, the reaction time is significantly longer than the annealing and extension times typically used in PCR. This allows for optimizing the primers solely for allele discrimination, without any restrictions or compromises that arise from concurrent optimization to improve PCR performance. In particular, the length of the target-specific segment of the mutation-specific primers and blocking probe used in ExBP-RT is typically only about 10 nucleotides (Tm ≅ 37–50°C), which allows for optimal discrimination between mutant and wild-type variants in addition to assure high specificity of the priming during reverse transcription reaction. It is worthy noted that the Tm values of those primers and probes are sufficiently high for our ExBP-RT assay, where the lowest temperature of the RT protocol is 37°C. Most importantly, since the allele discrimination reaction takes place prior to selective amplification of the target cDNA products, the allele discriminating power achieved during reverse transcription is unaffected by the exponential PCR amplification as opposed to allele-specific PCR.Non-extendable wild-type-specific blocking probes have been widely used to reduce mispriming, and at the same time, to improve the selectivity of most previously described competitive allele-specific PCR assays ,24,49,50−3 – 10−4). Even the ExBP-RT assays for KRAS G12D (GGT>GAT) and KRAS G12S (GGT>AGT) mutations, which involve the most stable primer:template mismatch (dT:rG) .Unlike allele-specific PCR where stringent optimization of PCR reaction conditions is often required to achieve sufficient sensitivity ,21,51–53 (dT:rG) , exhibit alleles , as onlyThis technique is clearly in its infancy and our results must be interpreted in the context of a number of potential limitations. While there are several reports of modified nucleotides that significantly improve the discrimination between matched and mismatched primer:template duplexes ,52,55–58insitu platform. The demand for this type of analysis was highlighted in two recent papers describing methodology for allele-specific detection of individual mRNAs . This technique is valuable for mutation detection with ultra-high selectivity and for analysis of expressed mutations at the RNA level, which might, more faithfully reflect the functional consequences brought upon the cells or tissues. ExBP-RT is especially useful in situations where RNA is a mandatory starting material, such as in epigenetic studies to analyze allele-specific gene expression, miRNA variants, exosomal RNA variants or RNA editing and detection of mutations within the genome of RNA viruses. The analytical procedure of ExBP-RT is rapid and requires only moderate optimization. In combination with qPCR using intercalating dyes or probe-based detection, ExBP-RT is a sensitive strategy for mutation detection from RNA or for analysis of RNA variants. Although not examined in depth in this study, it is reasonable to assume that the ExBP-RT strategy might also support detection and discrimination of highly similar transcript variants in single cells in a solution-based or al mRNAs ,62.Supplementary Data are available at NAR Online.


This review focuses on three types of ribozymes that could have been involved in the synthesis of RNA, the core activity in the self-replication of RNA world organisms. These ribozyme classes catalyze nucleoside synthesis, triphosphorylation, and the polymerization of nucleoside triphosphates. The strengths and weaknesses regarding each ribozyme’s possible function in a self-replicating RNA network are described, together with the obstacles that need to be overcome before an RNA world organism can be generated in the laboratory.The RNA world hypothesis states that during an early stage of life, RNA molecules functioned as genome and as the only genome-encoded catalyst. This hypothesis is supported by several lines of evidence, one of which is the  Tetrahymena thermophila and RNase P) in 1982 and 1983 [The RNA World hypothesis ,2,3,4 waand 1983 ,6) place+, FAD, CoA, SAM and ThPP contain functional groups that are either attached to adenosine or strongly resemble the structure of nucleotides. Since there is no functional requirement for a cofactor to be a nucleotide derivative, they are thought to be remnants from an ancestral form of life in which RNA was the dominant macromolecule [Further support for the RNA World hypothesis comes from “molecular fossils” in today’s life forms: (i) Proteins are synthesized in every known organism by the ribosome, a large RNA/protein complex. It is the RNA portion that catalyzes peptide bond formation ,8, demonmolecule ; (iii) tmolecule : The 2'-molecule .in vitro selection [in vitro selections start from large, combinatorial libraries of RNA that are incubated with their substrate/ligand molecules . Such iolecules . For thetic RNAs , one of les, see ,17) or bles, see . With thylation  using PRPP as substrate [+, an essential redox cofactor. PRPP considerably simplifies nucleotide synthesis in modern metabolism by providing two of the three essential elements of a nucleotide in the form of activated R5P.In modern organisms, 5-phosphoribosyl 1-pyrophosphate (PRPP) is essential for all nucleotide synthesis. PRPP, which is obtained from ribose 5-phosphate (R5P) and ATP, brings together phosphate based energy metabolism with ribose carbohydrate chemistry. PRPP then reacts with nucleobases that are either scavenged or synthesized by nitrogen dependent metabolic pathways to yield a nucleotide product linking R5P and a nucleobase. Both the information containing and catalytic cofactor type nucleotides are synthesized by this strategy. Purine nucleobases such as adenine, guanine, xanthine, hypoxanthine, and 6-thioguanine can be reacted in a single step with PRPP to produce their corresponding nucleotide monophosphates (NMPs). Alternatively, the first step in ubstrate . PyrimidModern biology’s dependence on PRPP, and the advantages of modular RNA nucleotide synthesis with PRPP suggest that this molecule might have played an important role in a potential RNA World. However, promoting PRPP dependent nucleotide synthesis chemistry with RNA presents a potential problem: both PRPP and the nucleobases used to make nucleotides are small relative to the size of the catalytic RNA itself, making it unclear if RNA is up to the task of nucleotide synthesis. Specifically, it is a challenge for RNA to position its functional groups necessary for specific ligand binding and catalysis of a reaction into the tight space of a binding pocket for a small molecule. While riboswitches and RNA aptamers that specifically bind and recognize adenine, guanine, and derivatives are now well-understood ,50,51 fein vitro selections for pyrimidine and purine nucleotide synthesis have demonstrated the potential for RNA to promote nucleotide synthesis (15 distinct sequences) of random sequence RNA were ligated to PRPP via their 3'-termini. These pools were then incubated with either 4-thiouracil [N-acryloylaminophenylmercuric acetate [−1·min−1, while the two most abundant purine nucleotide synthase families named RA and MA had apparent efficiencies of 230, and 284 M−1·min−1 respectively. Only the pyrimidine family A and purine family RA had measurable Km values with the remaining families having reaction rates directly proportional to nucleobase concentration. This suggested that mechanistically, ribozymes isolated from purely random sequence can invest in either substrate binding or in chemical rate enhancement but have difficulty optimizing both binding and rate acceleration simultaneously. Consistent with this hypothesis reselection and truncation of the pyrimidine nucleotide synthase family A ribozyme improved chemical, apparent efficiency from 4.3 to 150 M−1·min−1 [Encouragingly ynthesis B. Selectiouracil ,53 or 6-iouracil . Those R acetate . Purine  acetate . Consist−1·min−1  and it iWhether or not a nucleotide synthase ribozyme had measurable nucleobase binding affinity, all families of nucleotide synthetase ribozymes were extremely sensitive to nucleobase modification and showed surprising parallels to the substrate preferences of highly evolved protein nucleotide synthase enzymes. For example, the family A pyrimidine nucleotide synthetase ribozyme was ~10,000 times slower with uracil than with 4-thiouracil and reactivity with 2-thiocytosine, 2-thiopyrimidine, 2-thiopyridine and 5-carboxy-2-thiouracil could not be detected . In contKm between pyrimidine and purine nucleotide synthase ribozymes  suggests that 6-thioguanine is considerably easier to bind (presumably via stacking interactions to the purine base) than 4-thiouracil. Consistent with these barriers to pyrimidine glycosidic bond formation, kinetic isotope measurements performed on the family A pyrimidine nucleotide synthase ribozyme point to an unusually dissociative reaction mechanism, where a positively charged oxocarbenium-ion is stabilized presumably by the negatively charged phosphodiester backbone of the ribozyme [The differences in apparent ribozyme efficiencies strongly suggest that pyrimidine nucleotide synthesis is the more challenging chemistry compared to purine nucleotide synthesis. This is consistent with the disfavored kinetics and thermodynamics of pyrimidine glycosidic bond formation relative to that of purine nucleotide synthesis . Additioribozyme .in vitro selected ribozymes are modular in nature, then it might be possible to convert a pyrimidine nucleotide synthetase into a purine nucleotide synthase by varying one subdomain, the substrate recognition domain, and conserving the other, catalytic domain. A high diversity set of RNAs whose sequences where derived from that of the family A pyrimidine nucleotide synthetase was constructed to test this hypothesis explicitly, but found no evidence for functional modularity [Given that ribozymes can easily be found that promote nucleotide synthesis chemistry, how might new small molecule chemistry have evolved in an RNA World? If dularity . Insteaddularity . Later idularity .Ribozyme substrate promiscuity may provide an additional mechanism to efficiently evolve new ribozyme functions rapidly. A ribozyme able to react with two alternative substrates can in principle be evolved into two distinct ribozymes, each optimal for its own substrate. Therefore, promiscuity could be exploited to rapidly populate an RNA world with activities that can be related to each other by promiscuity. Such an evolutionary mechanism is particularly interesting if ribozymes able to “metabolize” simpler RNA relevant substrates can, via promiscuity, naturally evolve to utilize substrates that carry a higher free energy potential and are more similar to today’s metabolites than the initial substrates. Experimental support for such a model was found unexpectedly by the selection of a ribozyme able to react tethered R5P to 6-thioguanine via an aldehyde dependent chemistry . Surpris3P [A values in the range of 12.3 while the 5'-hydroxyl groups has a pKA around 15 [Nucleotides require chemical activation to drive the entropically disfavorable RNA polymerization in aqueous medium. All known life forms use nucleoside 5'-triphosphates as energy currency, therefore the use of nucleoside 5'-triphosphates by RNA World organisms would fit well with their ancestry to today’s life forms. Assuming that nucleosides were synthesized on prebiotic Earth, how might they have been converted to 5'-triphosphates? Long, linear polyphosphates are ubiquitous in microbes and animals, serve multiple biological roles, and are a potential remnant of the RNA world . Polypho3P . Tmp rea3P . The pho3P  because round 15 ,71 but 2round 15 . An addiround 15 . The bigin vitro selection from a diverse library (~1014) of RNA sequences was performed [14 this suggests that about 1 in 1012 random sequences with a length of 150 nucleotides is able to catalyze the triphosphorylation of their 5'-hydroxyl groups. These results showed two important points regarding the RNA world: First, catalytic RNAs are able to use Tmp for the triphosphorylation of RNA 5'-hydroxyl groups, which demonstrated that RNA world organisms could have used Tmp as an energy source. Second, triphosphorylation ribozymes are relatively frequent (~1/1012 in our library), apparently about 20-fold more than ribozymes catalyzing RNA ligation [To obtain ribozymes that catalyze the triphosphorylation of RNA 5'-hydroxyl groups near neutral pH C, an in erformed . The RNAerformed . After ierformed . The lig−1 and 0.028 min−1, under selection conditions  [2, pH 8.1) the TPR1-catalyzed reaction rate was 0.16 min−1, about 107-fold faster than the uncatalyzed reaction. The Km for Tmp was 30 mM, leading to an apparent catalytic efficiency of 5.3 M−1·min−1. A modification at its 5'-terminus allowed the reaction to proceed in trans, allowing a 14-nucleotide long RNA oligonucleotide to be triphosphorylated at its 5'-terminus by the ribozyme. This allowed the confirmation of the triphosphorylated product by mass spectroscopy. The dependence of the rate on the Mg2+ concentration suggested that each Tmp molecule coordinated one Mg2+ ion in a bidentate fashion and a second Mg2+ ion with the remaining negatively charged oxygen. The pH dependence of the reaction kinetics showed that a single deprotonation step was rate-limiting for the reaction, presumably the deprotonation of the 5'-hydroxyl group that made the nucleophilic attack on the trimetaphosphate. The secondary structure of the triphosphorylation ribozyme was analyzed using SHAPE analysis [Eight of the selected triphosphorylation ribozymes were analyzed for their reaction kinetics, and had rates between 0.013 min pH 8.3) . One of analysis  and base14C-labeled guanosine). However, the triphosphorylation of free nucleosides may not have been necessary for an RNA world organism: Only if RNA polymerization proceeds in 5'- to 3'-direction is it necessary to triphosphorylate free nucleosides  polymerase ribozyme, which facilitates the templated primer extension of 14 nucleotides, with an average fidelity of 97%. The R18 ribozyme has been the starting point for reselections which have generated the closely related R18 family: notable members include the B6.61 [The most successful polymerase ribozyme to date was developed in three stages: First, a ligase ribozyme was developed by osphates . Importaosphates , implyinosphates . Third, election . To do the B6.61   substrate, with an effective dissociation constant in the millimolar range . This caficiency . The temficiency . Only onficiency ) and 206ficiency ) when reficiency . More imficiency .in vitro selected in similar fashion as the R18 ribozyme [in vitro selection, but they have not yet been optimized like the R18 ribozyme. Therefore, while the R18 ribozyme family may have reached its fitness peak in the latest evolution experiments, some of the different accessory domains may give rise to polymerase ribozymes that are efficient enough for self-replication. It is also possible that a whole new approach may be needed to break free of the processivity barrier experienced thus far. A recent, elegant study demonstrates a solution to the problem of limited processivity: The cross-replication of two stereoisomeric ribozymes. Because the stereoisomers cannot form a stable Watson-Crick duplex with each other, these ribozymes are able to replicate their respective stereoisomer so that two of these ribozymes can potentially form a self-replicating system [Despite the increases in processivity described above it may be impossible to rid the relatives of the R18 ribozyme from its addiction to its favorite 10-nucleotide template sequence. A solution to this situation may be presented by polymerase ribozymes with different accessory domains, which were ribozyme . These ag system . The curin trans on substrate RNAs, and that ligase ribozymes are identified that condensate the RNA 5'-triphosphate with incoming nucleosides. The polymerase ribozyme faces a different problem related to substrate binding: Only one specific template sequence is bound so well that concatemers of this sequence facilitate the polymerization of 206 nucleotides [The ribozymes described in the three chapters above promote three types of reactions that might make it possible to generate an RNA World organism in the lab. What remains to be done to obtain such an organism? Three types of challenges remain: First, the three types of ribozymes are not yet efficient enough to sustain a self-replicating system of ribozymes, and second, their substrate specificities are not yet orchestrated to work with each other. For example, the ribozymes promoting nucleotide synthesis from PRPP and pyrimidine or purine nucleobases require tethering of the PRPP substrate to the ribozyme 3'-terminus ,39. To wleotides . Howeverleotides . It may leotides ,86,88,91leotides ,91, or tleotides .2+ that lead to the aggregation of lipid vesicles. Luckily, the coordination of Mg2+ with citrate was recently shown to protect lipid vesicles while allowing non-enzymatic RNA polymerization to occur [A third set of challenges to generating an RNA World organism in the lab stems from general chemical requirements for the components to work together . A potento occur . A similto occur . Anotherto occur , and theto occur . Perhapsto occur  no solutIf we are successful in generating an RNA world organism, what will we learn about the origin of life? How could we use such an “artificial” organism to find constraints on the origin of life? First, it would show us that, indeed, ribozymes are able to generate self-replicating and evolving systems, and thereby support the RNA World hypothesis. Second, RNA World organisms in the lab would make it possible to study them in ways that are currently impossible: The evolution of these simple organisms could be studied by sequencing their genome every few generations and following their mutations. Because these systems would probably consist of less than a dozen catalytic RNAs it would be possible to analyze and understand all mutual molecular interactions—and thereby understand, for the first time, a life-like system on the molecular level. These organisms would also evolve to become more efficient and would show us more efficient ways to construct RNA world organisms, and perhaps simpler and more likely ways how they could have originated.While the origin of life may have coincided with the origin of the RNA World it should not be forgotten that understanding the origin of life requires understanding the prebiotic chemistry that made the RNA World possible. For example, the prebiotic synthesis of ribose, nucleobases, and nucleotides is debated with very different models ,25 and i


Interpretable decision rules were derived from a quantitative structure–activity relationship (QSAR) model established using a set of substructure descriptors via decision tree analysis. Univariate analysis, feature importance analysis from decision tree modeling and molecular scaffold analysis were performed on both data sets for discriminating important structural features amongst active and inactive NAIs. Good predictive performance was achieved as deduced from accuracy and Matthews correlation coefficient values in excess of 81% and 0.58, respectively, for both influenza A and B NAIs. Furthermore, molecular docking was employed to investigate the binding modes and their moiety preferences of active NAIs against both influenza A and B neuraminidases. Moreover, novel NAIs with robust binding fitness towards influenza A and B neuraminidase were generated via combinatorial library enumeration and their binding fitness was on par or better than FDA-approved drugs. The results from this study are anticipated to be beneficial for guiding the rational drug design of novel NAIs for treating influenza infections.The fight against the emergence of mutant influenza strains has led to the screening of an increasing number of compounds for inhibitory activity against influenza neuraminidase. This study explores the chemical space of neuraminidase inhibitors (NAIs), which provides an opportunity to obtain further molecular insights regarding the underlying basis of their bioactivity. In particular, a large set of 347 and 175 NAIs against influenza A and B, respectively, was compiled from the literature. Molecular and quantum chemical descriptors were obtained from low-energy conformational structures geometrically optimized at the PM6 level. The bioactivities of NAIs were classified as active or inactive according to their half maximum inhibitory concentration (IC Influenza is a fatal disease of global public health concern. It is caused by influenza viruses which are envelope segmented-RNA viruses belonging to the Orthomyxoviridae family. The global estimate for seasonal influenza infection is as high as 1 billion cases per year in which approximately 3–5 million cases often develop progressive and severe illness leading to 250,000–500,000 fatalities per year worldwide . Among tα-ketosidic linkage between neuraminic acid  and carbohydrate residues , oseltamivir (Tamiflu) and peramivir (Rapivab). Zanamivir is the first approved nasally administered NAI and it exerts highly effective inhibitory activity against both types of influenza virus. This dihydropyran-based NAI was developed based on the structural modification of a sialic acid analogue called DANA . Due to Nevertheless, a number of drug candidates have failed in the late stages of the drug development process, primarily during clinical trials. These failures are a result of either insufficient therapeutic efficacy or adverse drug reactions at therapeutic doses. Balancing between favorable bioactivity and desirable adverse effects is essential for improving the therapeutic outcome after treatment . The bioTo reduce the failure rate in the late stages of drug design and development, it is necessary to understand both important molecular substructures and informative molecular features relevant to the activity of interest. Herein, we report the application of chemical space for exploring the important structure distributions related to neuraminidase inhibitor activities and the creation of a set of simple physicochemical properties that define the preferred physicochemical properties for neuraminidase inhibition. To achieve this objective, a large data set of neuraminidase inhibitors was collected from a publicly available database of protein-ligand interaction . This daA schematic workflow is presented in http://dx.doi.org/10.6084/m9.figshare.1612484.We first excluded the compounds with similar compound names, SMILES structures and protein targets to avoid bias in the prediction model. After the pre-preprocessing procedure, non-redundant data sets consisting of 347 and 175 NAIs for influenza A and B, respectively, were obtained. To categorize compounds as active or inactive, Qm), energy (E), dipole moment (μ), highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO) and energy gap of the HOMO and LUMO state (HOMO-LUMO). Furthermore, the second sets of molecular descriptors were calculated using DRAGON 5.5 Professional . The obtained descriptors include the molecular weight (MW), rotatable bond number (RBN), number of rings (nCIC), number of hydrogen bond donors (nHDon), number of hydrogen bond acceptors (nHAcc), Ghose-Crippen octanol-water partition coefficient (ALogP) and topological polar surface area (TPSA). In addition, sets of 307 substructure fingerprint counts (SubFPC) were generated to construct the predictive models of influenza A and B NAIs using PaDEL-Descriptor  and then subsequently converted to Gaussian input file format using Open Babel . Geometrscriptor .p value obtained from Student’s t-test , first quartile (Q1), median, mean, third quartile (Q3) and maximum (Max). In addition, statistical differences of descriptors among active and inactive NAIs were evaluated using the s t-test . Finally methods . The advThe aforementioned non-redundant data sets were divided into internal and external sets with the Kennard-Stone sampling algorithm  using raPrincipal component analysis (PCA) is a tool used for analyzing data sets that possess several inter-correlated quantitative dependent variables . To maniDecision tree (DT) is a simple, transparent and interpretable learning method that produces decision rules for the underlying data . PracticPerformance of the J48 algorithm was benchmarked against other commonly used classifiers such as the Naive Bayes (Bayes), support vector machine (SVM) and artificial neural network (ANN). The first classifier that was employed is SVM, which is a statistical learning method that had demonstrated wide utility in QSAR/QSPR modeling. A non-linear SVM was used herein by applying the radial basis function kernel to transform the original feature space to a higher dimensional space in which the SVM classifier linearly separate the inherent classes of the dependent variable via a maximum margin separating hyperplane. A grid search for the optimal parameters was performed according to a 10-fold cross-validation (10-fold CV) scheme using the R package e1071 . The secFour measurements were used to evaluate the prediction performance of the proposed model namely accuracy (Ac), sensitivity (Sn), specificity (Sp) and Matthews correlation coefficient (MCC), which are defined by the following equations: The chemical substructure analysis or molecular fragment analysis was performed to analyze the properties of the NAIs expressed by molecular descriptors using LibMCS software as implemented in ChemAxon’s JChem technology to identify and display the maximum common substructures of compounds in the data set . In brief, all chemical structures in SMILES format were initially converted to SDF format as an input file using MolConverter . LibMCS subsequently generated maximum common substructures present in the data set. The fragments were ranked according to structure-based hierarchical clustering algorithms, in which the bottoms of the hierarchy are the initial structure and then the next level contains the maximum common substructures of initial molecule clusters where all molecules that share the same common structure are placed in a cluster. Active and inactive fragments were distinguished according to To further understand the protein-ligand interaction site, a structure-based molecular docking approach was employed in this study. Sets of 148 and 45 active NAIs against influenza A and B, respectively, were subjected to docking with neuraminidase. In this study, crystal structures of 2009 pandemic H1N1 neuraminidase for influenza A (PDB accession code 3TI4) and B (PDB accession code 1A4G) were retrieved from the Protein Data Bank . The proNovel NAIs were generated via combinatorial library enumeration using AutoGrow 3.0  in whichhttp://dx.doi.org/10.6084/m9.figshare.1612484.Molecular structures of active compounds against both types of influenza neuraminidases were used as molecular founders in the enumeration of a new population of ligands. Grid box was defined to provide coverage of the active site of neuraminidase as well as loop positions 150 and 430  . The enup-value was used to compare the 13 descriptors in active and inactive groups of influenza A and B NAIs. The differences between active and inactive groups were considered statistically significant at p ≤ 0.05. Results from the t-test along with their p values are shown in A total number of 313 NAIs were collected from the BindingDB that consisted of 285 and 131 NAIs against influenza A and B, respectively, as shown in 50 value, which was 5.788 ± 2.023 (1.30 µM) and 5.107 ± 1.695  and inactive (357.692 ± 76.866) groups were significantly different with p < 0.05.MW refers to the molecular size of compounds and is an important parameter of Lipinski’s rule of five for drug-like molecules. Statistical analysis showed that the average molecular size of active compounds for influenza A NAIs (343.234 ± 56.916) was not significantly different from that of inactive compounds (328.415 ± 83.823) with RBN is the number of rotatable bonds in a molecule and provides a relative measure of molecular flexibility. RBN is defined as any single bond, not in a ring, that is bound to a non-terminal heavy atom. Amide C–N bonds are excluded from the count because of their high rotational energy barrier. As shown in p < 0.05.nCIC is calculated as the cardinality of the set of independent rings known as the smallest set of smallest rings. As shown in p < 0.05.nHDon refers to the number of hydrogen bond donors in a molecule. In brief, the active group was found to possess higher mean values of nHDon than the inactive group for influenza A NAIs, where as for influenza B NAIs, the active group was found to possess lower mean values of nHDon than the inactive group. As shown in p < 0.05) as also indicated by histogram plots in nHAcc describes the number of hydrogen bond acceptors in a molecule. ALogP is a computational method for estimating the 1-octanol/water partition coefficient (logP), which is a well-known measure of the molecular hydrophobicity also known as lipophilicity. As shown in p < 0.05 level while the active and inactive groups of influenza B NAIs were statistically significant. The corresponding TPSA values were 125.205 ± 24.370 (active) and 120.033 ± 37.060 (inactive) for influenza A NAIs, whereas the TPSA values of influenza B NAIs were 114/592 ± 27.661 (active) and 134.168 ± 25.007 (inactive).TPSA describes the contribution of polar atoms to the molecular charge based on an empirical measurement of the polar surface area of a molecule. Qm) describes the global measurement of the molecular charge. The histogram plot showed different distributions of Qm for influenza A and type B NAIs. Moreover, Qm exhibited a distinct Qm of 0.171 ± 0.042 and 0.165 ± 0.017 for influenza A and type B NAIs, respectively. This study suggested that the inactive group had higher Qm values when compared to the active group as shown in Qm values were statistically significant at p < 0.05 for the active and inactive influenza A NAIs were 0.163 ± 0.020 and 0.179 ± 0.055, respectively, while values of 0.158 ± 0.013 and 0.168 ± 0.018 were observed for the active and inactive groups of influenza B NAIs, respectively.Mean absolute charge (p = 0.823. It was found that the active group (−0.274 ± 0.083) had a slightly higher energy than the inactive group (−0.246 ± 0.119) for influenza A. However, the values of (−0.276 ± 0.099) and (−0.249 ± 0.089), which were observed in the active and inactive groups, respectively, of influenza B NAIs were not statistically significant at p < 0.05 (p = 0.129).Energy represents the summation of the atomic energy. Overall, no significant difference in energy were observed for NAIs of influenza A (−0.260 ± 0.103) and B (−0.258 ± 0.093) with p < 0.05 (p = 0.737). Further statistical analysis revealed that the dipole moment of actives versus inactives for both influenza A and B NAIs are also not significantly different, with p = 0.336 and p = 0.537, respectively.Dipole moment represents the asymmetric distribution of charge in a molecule. A high dipole moment value indicates a high charge distribution and vice versa. The dipole moment of NAIs for influenza A (4.210 ± 1.987) and B (4.181 ± 1.891) were not significantly different at p < 0.05. Moreover, in the case of influenza B NAIs, the HOMO value of the active group is not statistically significant (p = 0.573) at p < 0.05 as summarized in p < 0.05 as summarized in The highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) are the highest- and lowest-energy molecular orbitals that are occupied and unoccupied by electrons, respectively. HOMO is associated with ionization potential (ability to donate electrons), whereas LUMO is responsible for electron affinity (ability to accept electrons). It could be observed that the HOMO value of the active group is significantly different from that of the inactive group with p = 0.737 level. For analysis of influenza A and B NAIs, the HOMO-LUMO value of the active group is shown with the statistically significant results at the p < 0.05 level for both type A and B as summarized in HOMO-LUMO describes the kinetic stability and chemical reactivity of molecules. A small energy gap between these two states pertains to low kinetic stability and provides high chemical reactivity and vice versa . The hisp < 0.05) except for MW, TPSA and dipole moment. Similarly, several descriptors were also significant for differentiating the active and inactive class of influenza B NAIs with the exception of nHDon, ALogP, energy, dipole moment and HOMO descriptors. The active class of influenza A NAIs tended to have higher values of flexibility (RBN), hydrogen-bond donors (nHDon) and acceptors (nHAcc) as well as chemical reactivity/stability (HOMO-LUMO) while possessing low values for lipophilicity (ALogP), ring moiety (nCIC), molecular energy and charge (Qm). On the other hand, the active class of influenza B NAIs had the tendency of being smaller in size (MW), less molecular flexibility (RBN), ring moiety (nCIC), hydrogen-bond acceptors (nHAcc), charge (Qm) but higher chemical reactivity/stability of molecules (HOMO-LUMO). Nevertheless, in practice, compounds used for treating influenza B are the same compounds used to develop treatments for influenza A. As the univariate analysis can only provide an overview of the general features of NAIs therefore multivariate analysis was performed to construct predictive models using substructure descriptors for classifying the bioactivity of NAIs as well as discerning key features for differentiating active NAIs from their inactive counterparts.In summary, these results indicated that several descriptors were significant for differentiating the active and inactive class of influenza A NAIs  were found to characterize the features of active compounds owing to its distribution in the spatial location of the active compounds when the scores and loadings plots are superimposed. It can thus be seen that active compounds were accounted by hydrogen bond propensities, molecular orbital energies as well as the rotatable bond count and polar surface area. Likewise, the other cluster of descriptors consisting of ALogP, HOMO, nCIC and molecular energy were found to define the inactive set of compounds as indicated by the red cluster, which corresponded to lipophilicity, electron donating propensity and number of rings.Furthermore, PCA was applied to explore the chemical space of NAIs for influenza A  shows thQm dominating the negative end. Moreover, dipole moment and molecular energy were found as terminal descriptors at the positive end of PC3 with RBN and MW on the negative end. Putting these findings into perspective, it can be seen that the first PC was accounted by molecular orbital energies and hydrogen bond donating and accepting propensities, the second PC was characterized by structural features comprising of the molecular weight, number of rings, lipophilicity and rotatable bond count while similarly the third PC was rationalized by the rotatable bond count and molecular weight. The loadings plot  with their site-moiety preferences as illustrated in The analysis of the binding anchor of 45 active NAIs targeting influenza B revealed four different anchor sites of the binding pocket: Elec1, Hbond1, vdW1 and vdW2 as shown in Linking the results from molecular docking and decision tree revealed pertinent knowledge for targeting key residues of neuraminidases from influenza A and B. As mentioned above, the top three informative descriptors of influenza A NAIs were LUMO, nHDon and nHAcc while nHAcc, energy and HOMO-LUMO were informative descriptors for influenza B NAIs. Analysis of the catalytic pocket of neuraminidase from influenza A and B revealed the presence of the following key residues: arginines, aspartic acid, glutamic acids and tyrosine. The neuraminidase from influenza A had five arginines , one aspartic acid , two glutamic acids  and one tyrosine  while five arginines , one aspartic acid , two glutamic acids  and one tyrosine . Arginines can act as both electron acceptor and hydrogen bond donor and this is well supported by the decision tree model in which LUMO and nHDon were the highest and second highest feature usage for influenza A NAIs. Aspartic and glutamic acids can act as hydrogen bond acceptor, which is supported by the decision tree model where nHAcc were the third highest feature usage for influenza A NAIs and the highest feature usage for influenza B NAIs. Tyrosine can act as both hydrogen bond donor and acceptor, which is in line with nHDon and nHAcc descriptors of influenza A NAIs where it afforded the second and third highest feature usage while the nHAcc descriptor had the highest feature usage for influenza B NAIs.Enumerating compound library with robust bioavailability is a challenging task in the drug discovery process of NAIs. To address this challenge, the Ghose’s criteria was applied for filtering enumerated ligands in which the lipophilicity was set to be in the range of −0.4–5.6 and molecular weight was set to be in the range of 160–480 Da. Ligand enumeration for both types of influenza neuraminidase was subsequently performed via the automatic evolutionary algorithm of AutoGrow 3.0. The enumerated ligands were subjected to post-filter removal via the decision tree model described above. This resulted in total sets of 17 and 19 drug candidates for targeting the active site of neuraminidase from influenza A and B, respectively. These candidates were also subjected to comparison with FDA-approved drugs  and the long-acting laninamivir . Pariticularly, the binding energy and molecular properties of enumerated ligands and reference drugs are compared as shown in According to Observation of the molecular structures of the top ten enumerated ligands against influenza A suggested that the dihydropyran scaffold was mainly selected to support the chair conformation of ligands. There are 4 substitution sites surrounding this privileged structure as shown in A1 and B1 that afforded the lowest binding energy against neuraminidase of influenza A and B, respectively, was selected as a representative structure and shown in Analysis of the top ten enumerated ligands against influenza B revealed three scaffold types  that support the chair conformation of the ligand inside the catalytic pocket of neuraminidase. Although most of the enumerated ligands possessed distinct scaffold  but substitution sites around the privileged structure were found to be the same. The R1 substitution site of the cyclohexene scaffold  is mainly occupied by either the aromatic ring that is attached to amino and hydroxyl groups or the heteropentacyclic ring that is surrounded by both polar and non-polar moiety as shown in de novo designed NAIs proposed herein, which may possibly increase the percentage of bioavailability when administrated orally. Notably, the algorithm enumerated ligands targeting the 150- and 430-cavity found at the periphery of the catalytic pocket of neuraminidase. It should be noted that ligands capable of interacting with either the 150- or 430-cavity of influenza neuraminidase had the tendency of exhibiting lower binding energy. The enumerated NAIs discussed herein have been demonstrated to be promising candidates for development as drugs against influenza.It has been shown that the evolutionary algorithm in combination with bioisosteric replacement of polar moiety as performed in AutoGrow could improve the lipophilicity of The emergence of novel influenza strains that possess resistance mutations emphasize the importance of finding novel therapeutic agents for treatment and prophylaxis. The increase in the emergence of influenza viruses, particularly mutant variants, calls for the development of novel promising NAIs, in addition to the three currently approved NAIs, for preparedness against influenza. Nevertheless, there are several compounds that were tested to evaluate their inhibitory activity against influenza neuraminidase. Expanding the chemical space available in public databases of NAIs provides an opportunity to investigate the molecular factors relevant to the bioactivity of NAIs. In addition, a combination of various computational approaches revealed the structure–activity relationships of NAIs, which are essential for rational drug design to develop new promising therapeutic agents against influenza neuraminidase. Therefore, this work reports a large-scale study of the chemical space of NAIs against influenza type A and B and performs statistical and QSAR investigations of both molecular and quantum chemical properties that contribute inhibitory activity against influenza neuraminidase. Moreover, maximum common molecular substructures and their functional groups were analyzed from a ligand-based perspective. In addition, the binding modes of active NAIs were investigated to observe important amino acid residues and their site-moiety preferences that facilitate protein-ligand interaction. Moreover, informative descriptors leading to good performance of the QSAR model were achieved in combination with a statistical analysis that revealed the molecular properties that distinguish between active and inactive classes of NAIs. The molecular properties of the active group include a higher number of rotatable bonds, number of hydrogen-bond donors and acceptor atoms, total energy of molecules and kinetic stability. In addition, the active group also appeared to possess fewer cyclic rings and lower lipophilicity and charge suggested by the univariate analysis. The maximum common substructures observed in NAIs are primarily cyclohexene-based, dihydropyran-based and cyclopentane-based scaffolds in the molecular framework. These fragments were suggested to be privileged structures contributing to neuraminidase inhibition. Functional group analysis revealed important functional groups and the characteristic patterns amongst active and inactive compounds. Results from the decision tree models suggested that the bioactivity of NAIs can be classified according to their functional groups. Furthermore, results from binding mode analysis revealed key interactions that facilitated protein-ligand binding along with their moiety preferences. Combinatorial library enumeration in the context of fragment-based molecular docking produced novel NAIs with higher binding fitness and robust bioavailability when compared to FDA-approved and existing lead compounds.10.7717/peerj.1958/supp-1Supplemental Information 1Click here for additional data file.


Oligonucleotide microarrays are widely used in various biological studies. In this review, application of oligonucleotide microarrays for identifying binding sites and probing structure of RNAs is described. Deep sequencing allows fast determination of DNA and RNA sequence. High-throughput methods for determination of secondary structures of RNAs have also been developed. Those methods, however, do not reveal binding sites for oligonucleotides. In contrast, microarrays directly determine binding sites while also providing structural insights. Microarray mapping can be used over a wide range of experimental conditions, including temperature, pH, various cations at different concentrations and the presence of other molecules. Moreover, it is possible to make universal microarrays suitable for investigations of many different RNAs, and readout of results is rapid. Thus, microarrays are used to provide insight into oligonucleotide sequences potentially able to interfere with biological function. Better understanding of structure–function relationships of RNA can be facilitated by using microarrays to find RNA regions capable to bind oligonucleotides. That information is extremely important to design optimal sequences for antisense oligonucleotides and siRNA because both bind to single-stranded regions of target RNAs. Microarrays contain a library of oligonucleotides or polynucleotides with each spotted in a defined location. It is difficult to say unambiguously when microarrays appeared on the scene –5. ArrayThis review describes investigations in which DNA or RNA microarrays were used for identifying oligonucleotide binding sites and probing structure. Deep sequencing allows fast determination of DNA and RNA sequence. High-throughput methods for the determination of secondary structures of RNAs have been developed –17. ThesStudies of RNA structure with oligonucleotide microarrays were started by E. Southern ,18–26. TPhe (Phe was performed in the presence of 3.5 M tetramethylammonium chloride (TMACl) which reduces the sequence dependence of association constants relative to 1 M NaCl and 10 mM MgCl2. The results provided the following conclusions: (i) only a few of 65 dodecamer probes bind to tRNAPhe, (ii) the hybridization results depend on salt (3.5 M TMACl versus 1 M NaCl/10 mM MgCl2), (iii) only four regions of tRNAPhe  strongly bind to the microarray probes, (iv) strength of hybridization covers two to three orders of magnitude, (v) hybridization strongly depends on RNA binding region, sometimes shifting binding region by one position results in changing hybridization yield up to 15-fold, (vi) hybridization yield is not always proportional to length of DNA probes, (vii) hybridization is the same for probes attached at the 5′ or 3′ end to the glass support. The authors observed hybridization of probes to single-stranded loops and often to adjacent helical regions. They postulated that even a short single-stranded region is sufficient for duplex nucleation and subsequent invasion of an adjacent stem, especially when the single-stranded region has A-form character and stacks on the stem. The authors concluded that ‘major determinants of hybridization lie in the structure of RNA’  between complementary and mismatched probes is larger than for long probes.Escherichia coli was selected as target because computer programs such as Mfold  and at 4°C, where probe binding was significantly enhanced relative to 0.15 M NaCl, 4 mM MgCl2 and 0.04 M NaCl, 10 mM MgCl2. Strong hybridization was reported to loops B and C but not loop E, which is known to be unusually stabilized by Mg+2  heptanucleotide probes . Ribosomas Mfold  and RNAsas Mfold  predict  by Mg+2 . Thus, m+2, E. coli 5S rRNA forms a different secondary structure , however, improves discrimination between A-U and G-U because A-s2U is more stable than A-U, whereas G-s2U is less stable than G-U (o37) of 5′(AmUm)3/3′(UA)3 and 5′(GmCm)3/3′(CG)3 duplexes are −2.8 and −12.2 kcal/mol, respectively, whereas melting temperatures (in 1 M NaCl) are 11 and 71°C, respectively ). This disadvantage can be eliminated, however, by using modified probes as described below.The results with 5S rRNA revealed advantages and disadvantages of the microarray approach. Advantages of short probes include limited interference with target RNA secondary structure and ability to have probes representing all possible sequences. Another advantage is that probe binding often does not completely overlap with chemical modification, so that complementary information is generated. A disadvantage is that a short probe may have more than one binding site. This is particularly problematic because A-U and G-U pairs have similar stability –48. Replthan G-U ,49,50. Abased on , (http:/o37) of LNA-2′OMeRNA/RNA duplexes by ca. 1.5 ± 0.5 kcal/mol per single LNA nucleotide, which increases binding constant by roughly 10-fold at 37°C. Little or no additional substitution is achieved if an adjacent LNA is added. This phenomenon may be caused by C3′-endo conformation of LNA nucleotides forcing 3′-adjacent nucleotide also to adopt C3′-endo conformation and thus facilitate formation of A-form helix  residues –53. Therrm helix . At termA second approach to improve thermodynamic stabilities is to replace A with 2,6-diaminopurine riboside as either a 2′-O-methyl or LNA nucleotide . The 2,6o37) has to be more favorable than −6 kcal/mol to observe clearly detectable hybridization signals. For hybridization to target sequences with high A/U content it is often difficult to get ΔGo37 more favorable than −6 kcal/mol. For this reason, a third approach for designing isoenergetic probes is to add LNA-G to the 3′-end. Model studies showed that 3′-terminal mismatches GL-A, GL-U and GL-G stabilize 2′OMeRNA/RNA duplexes by 1.6, 1.5 and 1.4 kcal/mol, respectively, at 37°C , Samia cynthia (R2Sc), Coscinocera hercules (R2Ch), Callosamia promethean (R2Cpr) and Saturnia pyri (R2Spy)  of binding of the modified probe library to complementary sites of the R2Bm 5′ RNA if the sites were single stranded was −9.8 ± 1.2 kcal/mol.The first structural studies using isoenergetic microarrays were performed on the roughly 330-nt 5′-regions of R2 retrotransposon RNA from ) Figure ,36. InitN-methylisatoic anhydride (NMIA). The same RNA secondary structure was predicted by RNAstructure from thermodynamics with microarray constraints alone as with constraints from both microarray and chemical mapping data  by 0.1–0.4 kcal/mol at 37°C, whereas a 3′-unpaired UUC stabilized by 1.0–1.9 kcal/mol  bulges, internal loops and dangling ends bind strongly to microarray probes; (ii) a terminal stem can also bind strongly, presumably due to invasion of stem by the modified oligonucleotide; (iii) internal stems do not typically bind strongly. Along with further results described below, the data demonstrate that the location of the structural motif in the context of the whole target structure and both secondary and tertiary interactions influence the accessibilities of RNA to probe binding ,33,62,63Bacillus subtilis (RNRspBs) that was used to solve the crystal structure  and helMany approaches are being developed to target RNA with oligonucleotide mimics as therapeutics. It would be advantageous to develop approaches that use short oligonucleotides. The results for RNRspBs show that even a crystal structure does not allow obvious design of suitable oligonucleotides. Microarray experiments, however, rapidly reveal binding sites in target RNAs. The results suggest also that short oligonucleotides may induce refolding of RNA into an alternative conformation that could abrogate function.+2, the 3′-splice site of influenza A segment 7 mRNA is in equilibrium between a hairpin and a pseudoknot conformation. In the two conformations, the splice site and other functional elements exist in different structural environments, suggesting that splicing can be controlled by a conformational switch that exposes or hides the splice site similarly as postulated for HIV-1 RNA (+2 and only the pseudoknot is present when Mg+2 is replaced with Co(NH3)6+3. Microarray probing of the two conformations revealed different patterns of binding, suggesting that splicing could be regulated by oligonucleotides. Because both proteins encoded in segment 7 are essential, the splice site is a potential therapeutic target.Isoenergetic microarrays are being used to probe sequences in influenza A that are predicted to fold into stable, conserved structures –69. In tIV-1 RNA ,70. OnlyThe functions of two other structures predicted by bioinformatics  are unknMicroarray mapping of tRNAs revealed the ability of microarrays to detect positions of modifications that affect base pairing and also subtle differences in local structure.iMet can denote the first amino acid in polypeptide synthesis and only the elongator tRNAmMet allows extension of polypeptide. Studies on initiator tRNAiMet and elongator tRNAmMet from Lupinus luteus showed that differences in structure of those tRNAs produce different patterns of probe binding  and 3 mM MgCl2 in hybridization buffer is required for binding at sites 52 and 56 of the tRNAiMet TΨC loop. The tRNAmMet TΨC loop is more accessible for probes.A second difference concerns binding to the anticodon loop. The binding sites of tRNASaccharomyces cerevisiae tRNAPhe and its unmodified RNA transcript provide another demonstration of microarrays revealing positions of modifications , N2-methylguanosine (m2G) and N2,N2-dimethylguanosine (m22G) in internal positions influenced thermodynamic stabilities of hybridization duplexes . Di. DiSacchduplexes ,73. Not clusions –76.Microarray mapping can also be used to study RNA in complex with protein and/or other RNAs . The firFormation and stabilities of complexes were first analyzed by gel electrophoresis. Then hybridizations were performed with DsrA alone and with Hfq. The microarray mapping of isolated DsrA confirmed its published secondary structure ,79. As srpoS mRNA. It was postulated that the regulation is achieved by interactions of DsrA RNA and the 5′UTR of rpoS mRNA  require conditions that could influence the structure of RNA. For example, some reagents used for chemical mapping require presence in reaction mixture of ethanol  or dimethylsulfoxide (for NMIA).Moreover, microarray mapping is simple and fast. The 850 penta/hexanucleotide probes that form hybridization duplexes thermodynamically stable enough for mapping can be multiply printed on a large number of single microscope slides that can then be used to map any RNA.Of course, isoenergetic microarrays have limitations. Pentanucleotide probes can have multiple complementary binding sites, particularly in large RNAs. Moreover, U binds to A and G with roughly equal stability . Additioin vitro transcribed RNA and RNA isolated from natural sources could be used to search for natural modified nucleotides within single-stranded regions of RNA. It should be particularly easy to detect modifications of functional groups involved in base pairing . Comparisons between microarray binding and secondary structures predicted by thermodynamics guided by chemical mapping can reveal unusual folding. For various reasons, an RNA may fold into multiple structures or its folding may be determined by kinetics rather than thermodynamics. In such cases, comparison of chemical mapping and microarray binding could discriminate between very different potential structures. For example, it has been proposed that encapsidated Satellite Tobacco Mosaic Virus (STMV) has a single structure  use of methods not requiring radioactivity to detect hybridization of target RNA to microarrays. These include fluorescence quenching  application of oligonucleotide probes containing 2-thiouridine residues to improve selectivity of base pairing with A in comparison to G ,49,50, , (iii) duenching , other luenching  or mass uenching .Applications of microarrays could be expanded to include probing more complex folding. For example: (i) tertiary interactions within RNA could be probed with spacer-linked oligonucleotides simultaneously complementary to different fragments of target RNA, and (ii) sequences allowing formation of bimolecular triplexes, quadruplexes and parallel duplexes could be identified.


Here, we describe the functions of some cncRNAs identified from bacteria to humans. Because the functions of many RNAs across genomes remains unclear, we propose that RNAs be classified as coding, non-coding or both only after careful analysis of their functions.For many decades, the major function of mRNA was thought to be to provide protein-coding information embedded in the genome. The advent of high-throughput sequencing has led to the discovery of pervasive transcription of eukaryotic genomes and opened the world of RNA-mediated gene regulation. Many regulatory RNAs have been found to be incapable of protein coding and are hence termed as non-coding RNAs (ncRNAs). However, studies in recent years have shown that several previously annotated non-coding RNAs have the potential to encode proteins, and conversely, some coding RNAs have regulatory functions independent of the protein they encode. Such bi-functional RNAs, with both protein  Although initially lncRNAs were thought to function strictly as RNAs and not code for proteins, recent studies have showed that many previously annotated non-coding RNAs can recruit ribosomes and encode short peptides coding and non-coding roles (cncRNAs). cncRNAs, carrying both protein coding and RNA-intrinsic functions, call for reviewing the concept where mRNAs were considered a passive step in the transition of genetic information from DNA to protein. These dual function RNAs also present a potential evolutionary link between mRNAs and ncRNAs , which were previously thought to be inherently different  and gene silencing by RNA interference (RNAi) ifferent B. Here, 2Small non-coding RNAs have been shown to regulate post-transcriptional gene expression in all kingdoms of life, including bacteria. Bacterial genomes encode a large number of small transcripts (sRNAs) in the range of 50–350 nucleotides. Bacterial sRNAs can be grouped in two classes: (1) antisense RNAs that function via base-pairing with their targets, and (2) protein-binding sRNAs 2.1Staphylococcus aureus RNAIII was the first bacterial sRNA reported to have dual functions. S. aureus is a potent pathogen and its virulence is attributed to both cell surface-associated proteins and secreted toxins. The 5′ region of RNAIII encodes a secreted 26 aa peptide, δ-hemolysin (hld), which targets host cell membranes, causing lysis agr locus. RNAIII sRNA is the major effector of the agr response coagulase (an enzyme), staphylococcal protein a (a cell surface-associated factor), and rot (a transcription factor). Consistently, this region of the RNA is more conserved among different isolates of S. aureusα-hemolysin (hla), a secreted factor by preventing the formation of a translational inhibitory complex. This region overlaps with the coding sequence of hld, hence the base pairing activity of RNAIII with mRNAs may prevent translation of hldhld is regulated at several levels and there is a possible interplay between production of δ-hemolysin and the antisense functions of RNAIII.2.2Sugar transport related), a 227-nucleotide sRNA, is induced during glucose-phosphate stress conditions resulting from disruption of glycolytic flux and accumulation of glucose-6-phosphate. SgrS actively alleviates stress by negatively regulating the stability and translation of the major glucose transporters, ptsG and manXYZ, via base pairing ptsG mRNA, and hence base pairing leads to translation repression and mRNA degradation  that stabilizes gapA operon RNA. SR1P was reported to directly bind to GapA protein, but the mechanisms underlying this mode of regulation are not fully understood SR1 is a dual function RNA identified in the gram-positive bacterium, 3Plants exhibit a remarkable developmental plasticity and extensively regulate their gene expression profiles in response to environmental cues and stress. RNA-mediated regulation appears to play a significant role in adaptation to varying environmental conditions 3.1Early nodulin 40 (ENOD40) is the best-studied example of a cncRNA in plants. It was first identified as a gene expressed during early stages of root nodule formation, resulting from the symbiotic association of leguminous plants with rhizobial bacteria ENOD40 positively correlate with the rate of nodulation in transgenic plants ENOD40 was proposed to be a non-coding RNA. However, the molecular mechanisms underlying its activity remained unclear for many years Medicago truncatula (a model legume plant) showed that there are two conserved short ORFs in the ENOD40 transcript and that the 5′ORF is highly conserved ENOD40 in roots resulted in cortical cell divisions at high frequency. By targeting wild type and truncated/mutated ENOD40 to the cortical cells in roots, Crespi and colleagues showed that translation of both short ORFs is required for the activity of ENOD40. Interestingly, deletion of an inter-ORF region of the RNA with a predicted secondary structure also affected the activity of ENOD40, without altering translation of the ORFs. These results emphasized the importance of both the RNA structure and short ORFs, and imply a dual role for ENOD40 RNA in plant roots.ENOD40 RNA. MtRBP1 was found to be cytoplasmic in nodule primordia cells expressing high levels of ENOD40, whereas MtRBP1 localized to nuclear speckles in other root cells. Consistent with this, upon expression of ENOD40 in heterologous cells, MtRBP1 relocated from the nucleus to the cytoplasm. While the short ORFs encoded by ENOD40 did not play a role in localization of MtRBP1, the RNA was found to be directly required for cytoplasmic localization of MtRBP1. The function of this RNP (ribo-nucleo protein) is still unknown, although it has been proposed to function as a translational regulator in the cytoplasm ENOD40 bind to sucrose synthase (SUC1) and inhibit phosphorylation. Phosphorylated SUC1 undergoes proteasomal degradation. Thus, ENOD40 peptides regulate the turnover of SUC1. These diverse functions substantiate the bi-functional nature of ENOD40. Recent studies in Arabidopsis and rice have identified a number of RNAs similar to ENOD40 that can code for short ORFs Yeast-three-hybrid studies showed that a novel protein, MtRBP1, interacts with 3.2M. truncatula, MtHAP2-1, is regulated by a peptide, uORF1p, which is encoded by its uORF. MtHAP2-1 is a key regulator in the nodule meristem and functions in nodule development. Alternative splicing of the first intron in the 5′UTR of MtHAP2 is predominant during nodulation, and results in production of uORF1p. Unlike other uORFs that regulate translation by ribosomal stalling, uORF1p represses translation by binding to the 5′UTR of MtHAP2-1 It has been observed that short ORFs in the 5′UTR  of an RNA can contribute to gene regulation 3.3M. truncatula miR171b with only 0.85% SNPs, suggested the possibility of ORFs in the sequence. Indeed, two ORFs were found in the 5′ region of pre-miRNA 171b, encoding short peptides of 5 and 20 amino acid residues, respectively. Further analysis with a β-glucuronidase (GUS) reporter showed that only the ORF encoding 20-amino acid peptide named as miPEP171b is expressed and translated at the lateral root initiation site. Interestingly, miPEP171b specifically enhances the expression of miR171b, and not other miRNAs when overexpressed as pre-miRNA in M. truncatula roots and in tobacco leaves. Addition of synthetic miPEP171b to the seedlings of M. truncatula increased the levels of miR171b and affected lateral root development. Analysis of 50 pre-miRNA sequences from Arabidopsis thaliana showed presence of at least one ORF in each sequence M. truncatula and A. thaliana, positively correlated with accumulation of corresponding miRNAs. Inhibition of RNA synthesis during overexpression of miPEPs and analysis in RNA polymerase subunit mutants suggest that miPEPs function as transcriptional regulators of the corresponding miRNAs A recent report from Combier and colleagues shows that some pre-miRNA transcripts in plants have functional ORFs 4Xenopus, Drosophila and more recently in zebrafish suggest that besides coding for proteins, localized RNAs can have additional non-coding functions.Early embryogenesis of many animals relies on a large number of transcripts maternally deposited in the oocytes and mediating first steps of development prior to commencement of the zygotic gene expression program. Some of these maternal RNAs are required for oocyte maturation while others are stored in the form of mRNPs and are translated and/or degraded in an orchestrated manner during early phases of embryonic development. Hence, maternally deposited RNAs are under tight post-transcriptional regulation that includes regulated processing, localization and translation 4.1VegT was identified as a maternal RNA localized to the vegetal cortex Xenopus laevis oocytes. VegT codes for a T-box transcription factor that patterns the mesendoderm along the dorso-ventral axis Xenopus oocytes, and that the vegetal cytoskeleton is important for anchorage of germ-line specific RNAs and formation of the germinal granules VegT has an mRNA-intrinsic function. VegT mRNA molecules are integrated into the multilayered cytoskeleton which collapses and disintegrates in the absence of RNA. The integrity of the cytoskeleton is important for correct distribution of the germ plasm and germinal granules at the vegetal cortex  was identified as a maternal-effect gene required for antero–posterior patterning during Drosophila embryogenesis osk mutants identified in the maternal effect screen that produced embryos lacking abdomen and germ cells lacked functional Osk protein but still expressed mRNA osk alleles with reduced or no osk mRNA showed more severe and earlier defects during oogenesis compared to osk alleles that express mRNA. Females harboring RNA null mutations failed to lay eggs and were sterile as a result of an early arrest during oogenesis osk is mediated by osk RNA and not Osk protein. To confirm this possibility, in a series of elegant experiments, Ephrussi and colleagues showed that overexpression of merely the osk 3′UTR was sufficient to rescue the eggless phenotype of osk RNA-null mutants. Therefore, they suggested that the osk 3′UTR might function as a scaffold to assemble RNP complexes that are required for oocyte development 4.3sqt exhibit mild dorsal defects, raising questions regarding the contribution of maternal sqt in dorsal specification sqt do not make functional protein, mutant sqt RNA is expressed and localized in homozygous sqt insertion mutant embryos. Furthermore, mutant sqt transcripts expand dorsal progenitors in early zebrafish embryos. Using a variety of mutations that disrupt Sqt protein, we showed that sqt RNA functions in the initiation of embryonic dorsal, independent of Sqt protein. Over-expression of the sqt 3′UTR sequences rescues the dorsal defects resulting from depletion of maternal sqt. Subsequent analysis of sqt RNA function in maternal mutants affecting Wnt and Nodal signaling showed that the dorsalizing function of the sqt 3′UTR requires Wnt/β catenin signaling Squint (Sqt) is a Nodal-related signaling molecule belonging to the transforming growth factor beta (TGFβ) superfamily. Nodal signaling plays important roles during embryonic development with essential functions in germ layer patterning ybx1 females as early as the one-cell stage, indicating premature processing of the mRNA in mutant embryos. Consistent with this observation, Sqt protein is precociously translated in maternal ybx1 mutants compared to wild-type embryos. This leads to premature and deregulated Squint/Nodal signaling, which is catastrophic for embryonic development and maternal ybx1 mutants typically do not survive beyond early gastrula stages We also uncovered another level of regulation that likely controls the coding and non-coding functions of sqt in a spatial and temporal manner. Consistent with the non-coding function of sqt RNA in early embryos, maternal sqt RNA is translationally repressed during early cleavage stages 5HOTTIP, Mistral, etc.) and repressors   was the first mammalian RNA to be discovered with dual roles, protein coding and non-coding, in myogenic differentiation SRA functions as a coding or a non-coding RNA  expressed in tissues affected by myotonic dystrophy DMPK mRNA with expanded CUG repeats (CUGexp-RNAs) is transcribed but the transcripts are sequestered as discrete foci in nuclei leading to cytoplasmic depletion of DMPK mRNA Myotonic dystrophy (DM) is an autosomal dominant inherited disease characterized by slow progressing multi-systemic symptoms like muscle wasting, myotonia, cardiac defects and reduced cognitive ability. By positional cloning, the DM1 mutation associated with type 1 myotonic dystrophy was identified as a variable length polymorphism which resulted from increased number of trinucleotide CUG repeats in the 3′UTR of DM protein kinase  were found to share miRNA response elements (MREs) with PTEN. Their RNAs were shown to relieve miRNA-mediated repression of PTEN. Consistently, Pandolfi and colleagues showed that copy number loss of these ceRNAs during cancer promotes tumorigenesis by repressing PTEN. These interactions were shown to be reciprocal as PTEN mRNA can also regulate the expression of VAPA protein Coding and non-coding transcripts can function as a sponge to bind miRNAs and alleviate the repressive activity of miRNAs on the target mRNAs. Such RNAs that regulate the activity of other RNAs by directly competing for miRNA binding are named as competing endogenous RNAs (ceRNAs) and any perturbation in their levels can lead to disease states 7Drosophila osk and zebrafish sqt) or alternatively, do they utilize the primary sequence for encoding proteins while reserving the secondary or tertiary structure of the same region for non-coding roles? Determining cncRNA conformation using emerging experimental approaches Here, we reviewed the emerging class of bi-functional RNAs that combine protein-coding and noncoding functions in a single RNA molecule. The current list of these molecules might be limited, but phylogenetic analysis and RNA structure predictions suggest that this list is likely to expand in the future


Chimeric RNAs originating from two or more different genes are known to exist not only in cancer, but also in normal tissues, where they can play a role in human evolution. However, the exact mechanism of their formation is unknown. Here, we use RNA sequencing data from 462 healthy individuals representing 5 human populations to systematically identify and in depth characterize 81 RNA tandem chimeric transcripts, 13 of which are novel. We observe that 6 out of these 81 chimeras have been regarded as cancer-specific. Moreover, we show that a prevalence of long introns at the fusion breakpoint is associated with the chimeric transcripts formation. We also find that tandem RNA chimeras have lower abundances as compared to their partner genes. Finally, by combining our results with genomic data from the same individuals we uncover intronic genetic variants associated with the chimeric RNA formation. Taken together our findings provide an important insight into the chimeric transcripts formation and open new avenues of research into the role of intronic genetic variants in post-transcriptional processing events. Transcripts formed from exons of two or more different genes are known to play a major role in cancer development The most prevalent type of chimeric transcripts found in the human genome are tandem RNA chimeras originating from genes residing on the same strand and chromosome Here, for a first time we identified and characterized chimeric transcripts found in a large cohort of population sample of individuals lacking severe phenotypes by using RNA sequencing data isolated from lymphoblastoid cell lines of 462 individuals representing 5 populations from the 1000 Genomes project. By taking advantage of the genomic data available from the 1000 Genomes project, we could link for a first time the mechanism of tandem RNA chimera formation to specific genetic variants.http://www.repeatmasker.org) to filter out breakpoints overlapping with repetitive elements.In this study we used RNA sequencing data from lymphoblastoid cell lines of 462 individuals from five populations 91 CEPH , 95 Finns , 94 British , 93 Toscani  and 89 Yoruba , who participated in the 1000 Genomes project  were estimated with Flux Capacitor v 1.2.3 The calculation of the open reading frame of the fusions was based on the CDS information in the gene model, provided by the reference GTF file and it is implemented in the FusionMap software.Finally, the novelty of the fusions was assessed via queries against known annotation databases for read-through events: ConjoinG The distances between the fusion breakpoints was estimated as |bp2 – bp1|, where bp1 is the breakpoint of upstream parent gene and bp2 is the breakpoint of the downstream parent gene involved in the RNA chimera. The frequency counts for each chimeric transcript were estimated as the number of individuals from each population harboring the chimeric transcript.The sizes of the exons and introns residing at the fusion breakpoint were estimated by taking into account all possible transcript combinations between the chimeric genes.Distances, frequency plots and intron lengths distribution plot were generated with ggplot2 package within R environment The exon exclusion pattern was assessed by estimating the frequencies of the excluded exons from the two parent genes during the tandem RNA chimera formation. We took into account all possible transcript combinations.As a reference annotation for all analyses above we used Gencode v12.We created custom modified Gencode v12 reference gtf file to accommodate all possible transcript isoforms of tandem RNA chimeras by combining exons of the upstream partner gene up to the fusion breakpoint with exons of the downstream partner gene after the fusion breakpoint and assigning a new transcript ID. Then, for each fusion we assigned a new gene ID. In four cases the breakpoint was predicted to be away from the exon-intron boundaries and therefore, we modified the exon boundary to match the predicted breakpoint. Subsequently, all bam files mapped with GEM All custom scripts and the modified gtf file are available on request.The association between tandem RNA chimera formation and genetic variants has been performed on custom annotated 1000 Genomes Phase I, release v3 vcf files, based on Gencode v12 Further, the identified variants were functionally annotated by utilizing data available from Ensembl regulatory build. Subsequently, the associated with RNA chimeras variants were overlapping with genomic locations for transcripts associated with RNA binding proteins by using data in bed format produced by RIP-chip GeneST, Ribonomic profiling on Affymetrix GeneChip® Human Gene 1.0 ST Arrays To explore variants in poly(A) sites and signals, we used annotated by Havana, Poly(A) sites and signals Gencode v12 We used a pipeline based on FusionMap software tool We observed 89 intrachromosomal genes residing on the same strand, 8 of which implied inversion since the direction of the fusion transcript was inverted relative to the annotation  was known ACTB->POTEM, ACTB->POTEE and SP100->HMGB1) have been found in normal population C2orf27A->NBEA, HILPDA->EFCAB3, FARSB->TRIM61) were previously identified only in cancer samples In addition to the tandem RNA chimeras we report 6 intrachromosomal fusions located on different strands, only one of which  as shown in the venn diagrams .We further focused to study in more detail the tandem RNA chimeras as the most prevalent type amongst the identified RNA chimeras. In addition, the majority of the tandem RNA chimeras have been already confirmed in the literature. Moreover, tandem RNA chimeras are most likely to represent genuine read-through or intergenic splicing events rather than being a result from genomic structural variations. Furthermore, the data on structural variations available from the 1000 genome project We further sought to study the exon exclusion pattern in the tandem RNA chimera formation. We took into account all possible fusion transcripts , we found that the chimeric genes tend to have larger introns at the fusion breakpoint as compared to the rest of the introns comprising the partner genes, with estimated Kolmogorov-Smirnov tests, D = 0.278, p-value<2.2e-16 and D = 0.389, p-value<2.2e-16 for the 5′ intron and 3′ intron respectively . We obseTo explore further the mechanism of tandem RNA chimera formation, we took advantage of the available genomic data from the same individuals provided by the 1000 genome project, with functional re-annotation with Gencode v12 as described in To check the hypothesis that deletions or mutation in the poly(A) signal of the 5′ partner gene drive the tandem RNA chimera formation, we inspected the poly(A) signals and sites as described in Methods. We did not observed in any 5′ partner genes deletions in the poly(A) signals. Two genes (LRRC33 and SDHD) out of 81 5′ partner genes were detected to have single nucleotide polymorphisms (A->G) in their poly(A) signal . Similarly, we could not identify any genes bearing deletions in their poly(A) sites. Only seven genes were identified to have single nucleotide polymorphisms in these sites  and SNPs with MAF >5%.By using this approach we identified 54 variants associated with the formation of 3 chimeras  tail and is involved in NMD pathway NRXN1->EIF2AK2, PRIM1->NACAPRKAA1->TTC33, CTBS->GNG5SLC35A3->HIAT1UBE2J2->FAM132APPIP5K1->CATSPER2 and YARS2->NAP1L1TRIP12->SLC16A14 and TFG->GPR128 have been found in cancer patients with clear cell renal carcinoma TFG->GPR128 in healthy individuals MAPKAPK5->ACAD10 and POLR1A->REEP1 have been detected in autistic individuals Our observations also demonstrate that many chimeras naturally occurring in normal populations have been mistaken for cancer-specific. For example File S1File includes Figures S1–S3 and Tables S1–S8. Figure S1: Regional association gene plots for CTBS->GNG5 chimera. Results are shown in the region flanking 100 kb both sides of the index SNPs. The marker SNPs are shown in purple and the color of the dots represent the degree of linkage disequilibrium (based on r2) in relation to the index SNP based on the March 2012 release of the 1000 Genomes data in European population. Figure S2: Regional association gene plots for HMSD->SERPINB8 chimera. Results are shown in the region flanking 100 kb both sides of the index SNPs. The marker SNPs are shown in purple and the color of the dots represent the degree of linkage disequilibrium (based on r2) in relation to the index SNP based on the March 2012 release of the 1000 Genomes data in European population. Figure S3: Regional association gene plots for TAP2->HLA-DOB chimera. Results are shown in the region flanking 100 kb both sides of the index SNPs. The marker SNPs are shown in purple and the color of the dots represent the degree of linkage disequilibrium (based on r2) in relation to the index SNP based on the March 2012 release of the 1000 Genomes data in European population. Table S1: Intrachromosomal RNA chimeras residing on the same strand, which orientation implies inversion. Table S2: Identified tandem RNA chimeras located on the same strand. Table S3: Identified intrachromosomal RNA chimeras located on different strands. Table S4: Identified interchromosomal RNA chimeras. Table S5: Gene expression values estimated for tandem RNA chimeras partner genes in each human population. Table S6: All annotated transcripts and exons residing at the fusion junction for the identified tandem RNA chimeras. Table S7: Genetic variants found in poly(A) sites of tandem RNA chimeras upstream genes. Table S8: All identified genetic variants associated with tandem RNA chimera formation.(PDF)Click here for additional data file.