Giardia lamblia using a stem-loop RT-qPCR approach. Both small RNAs could be isolated from both total RNA and small RNA samples. Identification of the two small RNAs was carried out by sequencing the PCR-amplified small RNA products upon ligation into the pJET1.2/blunt vector. GlsR17 is constitutively expressed during the 72 h cultures of trophozoites, while the mature miR2 is present in 2-fold higher abundance during the first 48 h than at 72 h. Because it has been suggested that miRNAs in G. lamblia have an important role in the regulation of gene expression, the use of the stem-loop RT-qPCR method could be valuable for the study of miRNAs of G. lamblia. This methodology will be a powerful tool for studying gene regulation in G. lamblia, and will help to better understand the features and functions of these regulatory molecules and how they work within the RNA interference (RNAi) pathway in G. lamblia.Stem-loop quantitative reverse transcription PCR (RT-qPCR) is a molecular technique used for identification and quantification of individual small RNAs in cells. In this work, we used a Universal ProbeLibrary (UPL)-based design to detect—in a rapid, sensitive, specific, and reproducible way—the small nucleolar RNA (snoRNA) GlsR17 and its derived miRNA (miR2) of  Giardia lamblia is a flagellate protozoan that adapted over time to a parasitic lifestyle [G. lamblia is an early divergent microorganism, it has been taken as a good model to study gene regulation, because it shares mechanisms with both prokaryotic and eukaryotic organisms [ifestyle . This orifestyle . Since Grganisms .G. lamblia [Giardia [G. lamblia by small RNA isolation and ligation to RNA linkers [G. lamblia founded by in silico prediction, analysis of homology searching, or deep sequencing [It is known that small molecules of RNA regulate important cellular processes in different eukaryotic organisms, including  lamblia . Small n lamblia ,7,8,9,10[Giardia , althoug[Giardia . Some mi linkers , and als linkers ,14,15,16quencing ,18. Studquencing ,18.Giardia, suggesting that they might be involved in the regulation of this process [G. lamblia possesses expression regulatory mechanisms by PTGS or through the RNAi pathway involving small RNAs [Giardia, making conceivable its existence and usefulness to perform specific gene silencing. Analysis of the Giardia genome has revealed the presence of one copy each of the Dicer, Argonaute (Ago), and RNA-dependent RNA polymerase (RdRp) genes [Recently, it was reported that VSP genes are transcribed simultaneously in sense and antisense strands, which was proposed to result in the formation of double-stranded RNAs (dsRNAs) that are then degraded by the Dicer endonuclease complex . Long ds process . These sall RNAs ,21,22,23p) genes ,21,24. Ap) genes .G. lamblia, fluorescence in situ hybridization (FISH) was used to find the cellular location of the snoRNA GlsR17 and its product, miR2 [Because of the importance of small RNAs, different techniques have been used to detect miRNAs, including isolation of small RNA and ligation to RNA linkers  , Northerct, miR2 ; howeverct, miR2 . Stem-loct, miR2 ,32,33,34ct, miR2 ,36.G. lamblia. With this technique, we could isolate, identify, and quantify the expression of GlsR17 (ID: AY820298.1) and its derived mature miRNA, miR2. As far as we know, this is the first report that demonstrates the use of the stem-loop RT-qPCR method for the identification and validation of small RNAs in this parasite. This technique can thus be adopted for the quantification of small RNAs in G. lamblia, and used in analyses of genes that are regulated by small RNAs through the RNAi pathway.In this paper, we describe the use of the stem-loop RT-qPCR technique to detect different small RNAs in G. lamblia was obtained from the American Type Culture Collection (ATCC). Trophozoites were grown in tubes containing 7 mL of TYI-S-33 medium (pH 7.02) supplemented with 10% fetal bovine serum and antibiotics  and incubated at 37 °C. Upon reaching a confluent monolayer (after approximately 60 h) the cells were placed on ice for 20 min and then collected by centrifugation at 3400× g; the medium was discarded completely and the cells were washed twice with phosphate saline buffer before RNA extraction.The WB strain of ® Reagent  according to the manufacturer’s instructions. The concentration and the purity of the isolated RNA were quantified using a NanoDrop ND-1000 Micro-Volume , and its integrity was verified in a 0.8% (w/v) agarose gel under denaturing conditions.Total RNA was extracted using TRIzol® microRNA Isolation Kit , following the instructions of the manufacturer’s protocol. The small RNA obtained was electrophoresed in 3% (w/v) agarose gels and visualized with GelRed  on a MultiDoc-It .The extraction of small RNAs was performed with the mirPremierIn addition, RNAs with sizes ≈100 bp were copurified from total RNA and obtained by the aforementioned kit, following the protocol of Malone et al.  and NielGiardia genome database (http://giardiadb.org/giardiadb/) [The sequence for primer design of the GlsR17-Fw primer was obtained from GenBank, Accession ID: AY820298.1, and then compared to the reported sequence in the rdiadb/) . The priw/v) agarose gel. PCR products were also resolved by electrophoresis through 16% polyacrylamide gels to improve the resolution of the bands; these gels were performed according to the method reported by other authors [Primers were tested by endpoint PCR to analyze their specificity using cDNA as a template (see next section) and the enzyme Phusion High-Fidelity DNA polymerase , with the following amplification conditions: 30 s at 98 °C; 30 cycles of 10 s at 98 °C, 15 s at 60 °C, and 15 s at 72 °C; and, finally, 2 min at 72 °C. After amplification, the PCR products were separated by electrophoresis on a 3% , which were grown at 37 °C overnight on Luria-Bertani (LB) agar plates supplemented with 100 μg/mL ampicillin. The plasmidic DNA was extracted by using the GeneJET Plasmid Miniprep Kit (Thermo Scientific), as indicated by the manufacturer, and then the cloned fragments were sequenced.The PCR products were purified and ligated into the pJET1.2/blunt vector . Each construction was transformed into competent G. lamblia. This methodology consists of two steps: reverse transcription (RT) and real-time PCR. First, the stem-loop probe Stem-loop-GlsR17 was used to specifically capture the snoRNA GlsR17 and perform reverse transcription with the Revertaid reverse transcriptase (Thermo Scientific). Then, the RT product was quantified by RT-qPCR using SYBR Green (http://genomics.dote.hu:8080/mirnadesigntool) [We are proposing a stem-loop RT-qPCR approach for the identification and quantification of small RNAs (snoRNA/miRNA) in BR Green A. The Stigntool) . This soFor complementary DNA (cDNA) synthesis, 1 µg of total RNA was first treated with the enzyme DNase I (Thermo Scientific) to remove DNA contamination. Complementary DNA was synthesized from DNase I-treated total RNA or from small RNA, using the Stem-loop-GlsR17 primer in 20 µL reaction volume with dNTP mix (10 mM) and Revertaid reverse transcriptase (Thermo Scientific). The reaction was incubated for 30 min at 16 °C followed by 60 min at 42 °C, and then stopped by heating at 70 °C for 10 min. The cDNA was stored at −20 °C until use.TM Real-Time PCR System . The reactions were performed with the Fast SYBR® Green Master Mix kit (Applied Biosystems), using the following conditions: 95 °C for 30 s, followed by 40 cycles of 95 °C for 3 s and 60 °C for 30 s. Upon completion of the reaction cycles, melt curves were obtained by heating the reactions from 60 °C to 95 °C. The specificity of the primers was confirmed by the presence of a single peak in the melt curve generated for GlsR17 and miR2. Negative controls were a reaction lacking the reactive and a reaction without template (NTC control) to verify the absence of contaminating DNA. Calculation of the PCR amplification efficiency for each primer was performed using 10-fold dilution series of cDNA as a template and applying the formula E = 10(−1/k) [−ΔΔCt method was used for the quantification of the relative expression of the small RNAs of interest [Ald) housekeeping gene was employed for equal loading control in all experiments [Amplification was carried out in a StepOne10(−1/k) ,42,43, winterest . The experiments . Five reG. lamblia possesses snoRNAs, some of which have been proven to be precursors of mature miRNAs involved in the regulation of several genes [G. lamblia.The most important consideration for designing a strategy to specifically detect a specific small RNA is to know its precise sequence. al genes ,7. We chG. lamblia GlsR17, within the miR2 sequences, which identifies GlsR17 as a snoRNA of the C/D box class [The sequences corresponding to miR2 are located at the 3′-end of GlsR17 B and a Dox class . The relox class . The seqox class . The steG. lamblia. Because the resolutions of the agarose gels were not suitable, we decided to work with polyacrylamide gels for better definition of bands.The reported sizes for GlsR17 and miR2 are 144 and 25 nucleotides, respectively , so we uThen, the amplicons obtained for the GlsR17 by conventional PCR using a temperature gradient were resolved in these gels; no differences were found in products amplified between 60 and 75 °C from samples of total RNA or small RNAs C.Importantly, we demonstrated that from total RNA and small RNAs purified, both GlsR17 and miR2 were amplified. However, we needed to verify that the miRNA (miR2) obtained is not generated from the GlsR17 amplicon being used as template, and that it originated naturally by Dicer processing. For this reason, we decided to copurify small RNAs with sizes less than 100 bp A from RNG. lamblia.After this, the amplified fragments were ligated to the pJET2.1/blunt vector and sequenced. The resulting sequences showed the presence of a 144 bp fragment corresponding to GlsR17  and the m) for the amplified products, according to the melt curves, were 77.86 °C and 83.37 °C, respectively. This result confirms that the oligonucleotides used in the reaction are specific for each of the two small RNAs. The amplification efficiency was 98% for GlsR17 and 101% for miR2, which are adequate for relative quantification of expression by RT-qPCR using the 2−ΔΔCt method [To set the conditions and validate the primers GlsR17-Fw, miR2-Fw, and UniLoop for RT-qPCR, we performed a series of PCR reactions using different amounts of cDNA, previously obtained with the probe Stem-loop-GlsR17, as a template (from 0.02 to 200 ng). As can be observed in t method ,43,45,47Giardia duodenalis trophozoites in these conditions for 96 h , characterized by Ansell et al. [G. lamblia in the time studied and with the regulation of different genes. Also, changes in the expression of VSP genes in Giardia have been reported, and could be related to the levels of the regulatory molecule, miR2. As previously demonstrated, miR2 is involved in regulating the expression of VSP genes, proteins that exhibit increase during stationary and decay stages (60–96 h) of G. lamblia trophozoite [We performed an analysis of the abundance of GlsR17 and miR2 during the first 72 h of a culture of trophozoites in TYI-S-33 medium, with samples taken every 24 h . The anal et al. . Then, wphozoite .G. lamblia infection and the role that miR2 seems to have in this phenomenon, we decided to perform a sequence alignment with a larger number of sequences of genes encoding VSP proteins. As shown in The miRNA miR2 potentially participates in the regulation of at least 22 different genes encoding variant-specific surface proteins (VSPs), since putative miR2 binding sites are present at the 3′-untranslated regions (3′-UTR) of their mRNAs . These aThe study of small RNAs, including miRNAs, siRNAs, and PIWI-interacting RNA (piRNA), is of great importance due to their role in gene regulation in different organisms ,49. One Giardia: the RNA extraction method, the design of the stem-loop probe and PCR primers, and the conditions of RT-qPCR to quantify the expression of specific small RNAs, using the snoRNA GlsR17 and its derived miRNA product (miR2) as isolation and quantification tests.Therefore, it is of utmost interest to have techniques available that can reliably detect and quantify small RNAs. In this sense, the stem-loop RT-qPCR technique has proven to be highly specific to detect and suitable to quantify specific small RNAs ,36,53,57G. lamblia [G. lamblia were performed by small RNA isolation and ligation to RNA linkers [Giardia [G. lamblia will greatly contribute to the study of gene regulation and the role of miRNA in the possible antigenic variation in this parasite.snoRNAs are essential for the maturation of ribosomal RNA, and are localized to the nucleolus ,46. Some lamblia . Previou linkers , and bio linkers . The miRG. lamblia infections are associated with antigenic variation, which is generated by a continuous change of the VSPs expressed. From a repertory of around 190 VSP-encoding genes, Giardia can express only one VSP on the surface of each parasite at a particular time, and it spontaneously changes to a different VSP by unknown mechanisms [G. duodenalis showed transcriptional variation in axenic culture, during 96 hours, which includes the log, stationary, and declining stages of the in vitro culture [VSP-116 (GL50803_101765) is one of the genes expressed mostly after 60 h of culture, and according to the alignment performed for these genes and their miR2 binding sites, this gene or others could be regulated by this miRNA -mediated mechanism [The results reported by these authors confirmed that each of the miRNAs represses the translation of a reporter (luciferase gene) transcript tagged with their respective target sites, and this repression requires the presence of the Ago protein from echanism ,17,18.G. lamblia. Interestingly, we only used three primers to identify two small RNAs, one of them with a stem-loop to capture both small RNAs (GlsRNA17 and miR2), another that helped to obtain a specific small RNA by RT-PCR, and a third primer present in the internal sequence of the stem-loop (UniLoop-rev), which served to confirm by conventional PCR the capture of some small RNA. This will contribute to the study of gene regulation in G. lamblia, and in particular, to the role of miRNAs in antigenic variation through silencing of the expression of VSP proteins.In summary, our results demonstrate the feasibility of using the stem-loop RT-qPCR method for routinely and efficiently detecting and quantifying specific small RNAs (snoRNA/dsRNA/siRNA/miRNA) from total RNA in


Additionally, we demonstrated the utility of this method in detecting and characterising members of diverse RNA virus families within a human plasma background, some present at very low levels. By applying this method to a patient sample series, we have simultaneously determined the full genome of both a novel subtype of HCV genotype 6, and a co-infecting human pegivirus. This method builds upon earlier RNA metagenomic techniques and can play an important role in the surveillance and diagnostics of blood-borne viruses.RNA viruses cause significant human pathology and are responsible for the majority of emerging zoonoses. Mainstream diagnostic assays are challenged by their intrinsic diversity, leading to false negatives and incomplete characterisation. New sequencing techniques are expanding our ability to agnostically interrogate nucleic acids within diverse sample types, but in the clinical setting are limited by overwhelming host material and ultra-low target frequency. Through selective host RNA depletion and compensatory protocol adjustments for ultra-low RNA inputs, we are able to detect three major blood-borne RNA viruses – HIV, HCV and HEV. We recovered complete genomes and up to 43% of the genome from samples with viral loads of 10 As a group, they constitute the major source of emerging infections in humans such as Ebola, chikungunya, Zika, West Nile virus and Middle East respiratory syndrome-related coronavirus7. With new human RNA viruses being discovered each year8, the serological and nucleic acid amplification techniques that have dominated virus diagnostics for many years are becoming increasingly unable to respond to the ever-expanding range of pathogens.Single-stranded RNA viruses exhibit exceptional genetic diversity due to low fidelity replication mechanisms10. In developed countries, blood and transplant products are routinely screened for these and other viruses. However, even within these two relatively well-characterised virus species, new genotypic divisions and recombinant variants are being discovered13, and questions have been raised regarding the reliability of commercial assays in detecting new strains16.In parallel, there is a substantial global burden of long-established blood-borne RNA viruses of which the most prevalent are human immunodeficiency virus (HIV) and hepatitis C virus (HCV), infecting over 38 million and at least 100 million people worldwide, respectively18.Isolated from humans and several animal hosts, including pigs, Hepatitis E virus (HEV) has, over the course of the last decade, become the leading cause worldwide of acute viral hepatitis. With an estimated 56,600 deaths annually, it is a prime example of an emerging zoonosis with significant blood safety implications, for which conventional serological screening methods seem poorly developed19. A number of groups have attempted to detect and characterise RNA viruses of clinical relevance directly from sample material, but the low relative abundance of viral genomic material within clinical samples when compared to host-derived nucleic acid species limits their potential utility in diagnostic virology. In the absence of significant host depletion, genome coverage and depths are often low even at high viral copy numbers23.New avenues in diagnostic assay development have been opened up by the advent of Next Generation Sequencing (NGS) technologies. Metagenomics – the direct genetic analysis of genomes contained within a sample – represents one such possibility; instead of targeting specific genomic regions of predetermined targets, short DNA sequences (‘reads’) are generated that derive from the full range of genomic material present in the sample27.Several reports detail methods for partitioning viral and host material through physicochemical purification of virus particles using various combinations of filtration, differential centrifugation, precipitation and extra-virion nuclease digestion prior to extraction, but these also suffer from low virus read frequency and consequent low depth of coverage of partial genomes29. As with non-depleting methods, extensive further work is needed to fully characterise detected viruses, and when applied to diagnostic virology, the read depths and genome coverages remain low even at high viral loads33. Most groups selectively deplete rRNA by hybridising rRNA-specific DNA ‘scissor probes’ to the extracted nucleic acids, and digesting the rRNA/DNA duplexes with RNAse H35. This approach has been exploited to good effect with Lassa and Ebola viruses36.The most frequent alternative method is to selectively eliminate host nucleic acids, specifically ribosomal RNA species (rRNA), as they constitute approximately 80% of total cellular RNA. ‘VIDISCA’ is one such approach, where viral nucleic acids are preferentially amplified through the use of non-random hexamers that do not complement human rRNA sequences. In combination with NGS, partial genomes of novel viruses have been detected by this method37. A Φ29-based Multiple Displacement Amplification (MDA) system has been successful in generating whole genomes of HIV from low copy number samples. However, these were prepared by diluting high titre clinical HIV samples in PBS, such that the impact of high host background was mitigated38, and in general, MDA displays target amplification biases that limits its potential in metagenomics to detection and identification rather than whole genome reconstruction41.The extremely low amounts of RNA surviving host depletion (often in the picogram range) present a significant challenge to RNA library preparation methods, which typically require at least 100 ng of starting materialIn this study, we have established a sequence-independent RNA library preparation method suitable for the detection and characterization of blood-borne RNA viruses. The method is focused on increasing the relative abundance of viral RNA within the sample, during and after the RNA extraction process, with a specialised library preparation step able to process ultra-low RNA inputs. The RNA enrichment steps enable recovery of a higher proportion of reads of viral origin, constituting a major advance in making virus genome assembly less challenging, leading to notable improvements in sequencing coverages and depths.The protocol was tested in complex host-enriched samples containing HCV, HIV and HEV, and complete genomes were recovered from the equivalent of 2,000 IU/ml. A mixed virus panel comprising 18 different human RNA viruses, diverse in terms of genomic and structural characteristics, was analysed in order to evaluate the capability of the protocol to detect potential new or emerging viruses present in a plasma sample. By applying the method to a series of samples taken from an HCV-infected patient, we have demonstrated the utility of this technique in fully characterising the strain of HCV together with the complete genome of a previously undetected human pegivirus virus. Further investigation demonstrated that this patient’s HCV virus constituted a new subtype within genotype 6. A second manuscript detailing this clinical case is in preparation.All experiments were performed in accordance with the ‘Guidance on Conducting Research in Public Health England’ . This study only involved the use of archived, residual samples that were sent to the National Reference Laboratory for routine diagnosis and sequence characterization with consent for leftover sample to be used in other assays. The samples were anonymized by removal of any patient identifiable information and assignment of a non-specific project number prior to genetic characterization.g to remove cell debris. The final concentration of each virus in the primary panel sample was 106 IU/ml (copies/ml for HIV – implied by IU henceforth for convenience), and three serial tenfold dilutions in NHP were prepared from this stock.A complex host-enriched sample was prepared by diluting in negative human plasma  stored plasmas from four samples previously characterized by routine diagnostic testing to contain HCV (x2), HIV and HEV , together with a single 200 μl extraction of the original panel suspension.A reagent comprising a suspension in PBS of 18 RNA viruses with different genomic and structural characteristics was provided by the National Institute for Biological Standards and Controls . Each viral component and its approximate relative concentrations is given in Mee 43, and reported the presence of a virus belonging to genotype 6 but was unable to resolve the subtype with any further precision.Four plasma samples collected from a patient between 2014 and 2016 were submitted to Public Health England (PHE) for metagenomic analysis as previous genotyping results had been inconsistent. The most recent such test employed NS5b sequencingg to remove cell debris. Triplicate, duplicate and single extractions were performed on the diluted VMR Panel samples (referred to as ‘VMR Panel A/B/PBS’), the BBV Panel samples (‘106-3-A/B’), and the patient sample series, respectively. A negative control comprising 200 μl of the same plasma used to dilute the panels was also extracted.Before extraction, all samples were centrifuged for 10 min at 2,500 × The SPLIT RNA extraction kit (Lexogen) was used to extract 200 μl of each sample input, according to the manufacturer’s instructions. Acidic phenol was used to preferentially recover the large RNA fraction, which was eluted in 12 μl of nuclease-free water. RNA eluates were quantified using Qubit RNA HS Assay Kit (Thermo Fisher Scientific), which is accurate for concentrations between 250 pg/μl and 100 ng/μl.Ribosomal RNA depletion and DNA digestion was achieved using the RiboErase kit (KAPA Biosystems). As all sample extracts were below the detection limit of the Qubit quantification system, the total RNA input was less than the recommended 100 ng. The manufacturer’s specifications were followed with the exception of using the entire 10 μl of the extract, and after the DNA digestion reaction clean up, eluting the residual RNA was in 10 μl of nuclease-free water.In the case of the BBV Panel, two of the three extracts of each dilution were treated with the RiboErase kit before RNA library preparation. The third set of extracts remained untreated and was used to monitor the effect of the rRNA depletion and DNA digestion upon the subsequent library preparation and sequence analysis. In the case of the VMR Panel (the two duplicates) and the negative control, rRNA and DNA depletion was performed on all extracts. In the case of the uncharacterized HCV strain, extracts from all four samples were treated with RiboErase. An additional, untreated, extract of sample 4 was included, again to monitor the process.Libraries were constructed from 10 μl of extracted RNA or 10 μl of rRNA-depleted DNAse-digested RNA, using the NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs). As the protocol is designed to use a minimum RNA input of 10 ng, several modifications were made to adapt it to an ultralow RNA input. These are listed in Table To determine the relative abundances of viral inserts, libraries constructed from the BBV Panel were analysed by qPCRs with primers and probes targeting each of the three viral components Refs . ReactioLibraries labelled with different indexes were diluted to 2 nM and pooled. Sequencing was performed on an Illumina MiSeq instrument using the MiSeq Reagent Kit V2 (300 cycles) (Illumina) according to the manufacturer’s guidelines, with the following minor modifications. The library pools were denatured with 0.2 N sodium hydroxide for 2 minutes rather than 5, diluted in kit reagent HT1 to produce a 20 pM solution and then these were further diluted to 11 pM. Of this library pool dilution, 600 μl were loaded onto the MiSeq cartridge.All paired end FASTQ files were processed with Trimmomatic v0.30, removing the Illumina adaptor sequences, then trimming leading and trailing bases with phred scores below 20. Reads were discarded where the length of either trimmed end was below 50 bases.47 and submitted to the SPAdes de novo assembler48 without error-correction, applying the default kmer sizes of 21, 33, and 55. Output contigs that matched each virus were identified with the nhmmer function of the HMMER v3.1b2 package49 using hidden Markov models (HMMs) built from alignments of each virus . Base frequencies at each nucleotide position within each component virus sequence were obtained from BAM files using QuasiBAM v2.2, an in-house C++ program that tabulates base frequencies at each nucleotide position within a reference and generates consensus sequences based upon user-defined depth and variant percentages52.For the determination of genome sequences of blood-borne viruses, trimmed FASTQ sets were normalised using the normalise-by-median.py script in the Khmer package et al.38). The second file was used solely to derive counts for reads mapping rRNA which would otherwise be subsumed into the human genome mapping results. From the filtered SAM files, the numbers of reads mapping to each reference sequence were counted. Counts for each of the constituent sequences of the human genome and rRNA were pooled into a “human” count and an “rRNA” count. QuasiBAM was used to derive nucleotide frequencies from which depth and coverage data were calculated. A minimum depth of 10 was required for inclusion in a derived consensus sequence for the BBV Panel (1 for the VMR Panel).Mapping of trimmed paired-end FASTQ to one or more virus reference genomes was also performed using BWA MEM 0.7.5a. In each case, two independent mappings were performed, using as a reference the viral sequences, supplemented firstly by the March 2009 ‘GRCh37’ release of the human genome, and secondly by a set of human rRNA sequences  present in the plasma diluent was discovered in the SPAdes contigs file. A HMM profile was constructed from an alignment of GenBank sequences  were used as the reference sequence when mapping that sample’s corresponding trimmed paired-end FASTQs, as well where only incomplete HCV genomes were obtained.To obtain full-length HCV genomes, each FASTQ set was submitted to the SPAdes-HMMER-mapping process. Where a complete genome was not obtained, HCV-matching contigs were aligned to the full-length genomes using MEGA56 IU/ml. Three tenfold serial dilutions in plasma were made from this original Panel. Ribosomal RNA depletion was performed on two of each set of triplicate extractions prior to all three being subjected to the modified library preparation protocol.A Blood-Borne Virus (BBV) Panel was prepared, comprising two strains of HCV (genotypes 1a and 1b), and one each of HIV and HEV diluted in NHP to 103-B data and included in the mapping references.Data from the most concentrated rRNA-depleted samples were used to generate individual virus genome sequences for use in reference mapping. During this data analysis, an unexpected human pegivirus (HPgV) was found and traced to the NHP diluent. The full genome sequence of this HPgV was determined from the 106-3-untreated/A/B). Each test sample yielded over 800,000 reads with the exception of 103-A, which gave just over 140,000 reads. With the exception of the two 106 samples, in which only a very small volume of NHP was added to the clinical samples, the percentage of reads mapping to the HPgV remained relatively constant at 29–39%. The exception is 105-B, in which the overall viral read percentage was lower than expected, with a corresponding elevation in reads mapping to the human genome suggesting possible incomplete DNAse digestion during the rRNA depletion step  with 105-B, reflecting the reduced overall viral reads in this dataset, but at a minimum depth of 1, 99.6% coverage was achieved with this sample, with only a 32-base sequence in Pol having no coverage. At 104 IU/ml, HCV 1a and HEV continued to give 98.1–99.7% coverage with median depths over 120. HCV 1b and HIV gave 91.2–93.5% coverage (82–95 median depth) and 55.0–90.2% coverage (12–83 median depth) respectively, and in 103-B, despite only 0.23% of all reads mapping to the four viruses collectively, genome coverages of 18.1–72.5% were achieved, with median depths up to 29.With increasing dilution, the total viral read percentages (excluding HPgV) decline from over 60% to 0.23%. Complete and near-complete genome coverages with depths greater than 10 were achieved at 104 IU/ml, three of the four viruses achieve combined coverages of >99.4% each, and 93.5% in HIV. At 103 IU/ml, the combined coverages for the four viruses are effectively what would be expected were the individual coverages independent, i.e. covAUB ≈ 1 − [(1 − covA)(1 − covB)].Figure 5-A to 2.9-fold for HIV at the lowest dilution. Concomitantly, the ratio for HPgV rose markedly, from 4.8-fold in 106-A to 175 in 103-B, reflecting an effectively constant viral load against decreasing quantities of Panel viruses .The percentage of reads mapping to RNA virus genomes in the rRNA-depleted BBV Panel samples was between 40 and 150-fold higher than in corresponding untreated controls. Individual target virus ratios decreased as they became more dilute, from over 100-fold for HCV in 1042, the Threshold Cycle (Ct) of the coronavirus was >36 and the other three were not detected, hence these four targets were excluded from further analysis. Notwithstanding influenza virus A H3N2 and parainfluenza virus type 3 also not being detected by the qPCR, we recovered reads from both, with genome coverages ranging from 2.7% to 21.6%. Almost no reads belonging to the panel’s DNA viruses were found.The ability of our method to recover genome sequences from a range of RNA viruses in the context of human plasma was evaluated using a Virus Multiplex Reference (VMR) Panel, putatively containing 25 genomically and physicochemically diverse viruses. Two plasma-diluted panels and one PBS-diluted panel were tested Table . No readq values . The HPgV clustered with genotype 1 strains, and is distinct from the NHP strain.Libraries from the BBV Panel extractions including the NHP negative control were subjected to virus-specific qPCR for the detection and quantification of HCV, HIV and HEV. All were detectable in the sample libraries, but were undetectable in the RiboErase-treated negative control library  and substantial fractions of complete genomes at 103 IU/ml. When applied to a series of clinical samples, we could elucidate simultaneously the full genome sequences of both a novel subtype belonging to HCV genotype 6 and a hitherto-undetected human pegivirus. Additionally, our system was able to recover viral sequences from a panel of diverse RNA viruses diluted in human plasma, with a broad correlation between the genomic coverage and depth metrics and approximate concentration. Although full genomes were not assembled in many cases, the independence of read distribution gave sufficient genome coverage for identification.This study has addressed these limitations by establishing a novel methodology suitable for the agnostic detection and characterization of blood-borne RNA viruses in plasma samples. By depleting host-derived nucleic acids and making modifications to an existing library preparation protocol to account for ultra-low RNA input quantities, we have been able to reconstruct effectively full-length genomes of HCV, HEV and HIV from plasma samples with viral loads of 10The vast majority of RNA molecules in a human plasma sample are host-derived, of which up to 80% comprises the six species of human rRNA. Their presence in our libraries was minimised by two key protocol steps in our modified protocol. Firstly, we selected an extraction method that combined a phenol/chloroform step with a column format (Lexogen SPLIT RNA) which increased the amount of extracted viral RNA by up to one log when compared to other extraction methods (data not shown). Perhaps more importantly, by controlling the final precipitation step, small RNA molecules below 150 nt such as 5 S rRNA and tRNA are excluded from the eluates, as are the majority of molecules of human genomic DNA.36. Methods that do not deplete rRNA generally give poor recovery of viral reads, yielding viral genome fragments that necessitate further work56, low read numbers even at viral loads over 104 IU/ml33, or at best, requiring dilution of both host and virus in PBS in order to recover full HIV genomes at low copy numbers38.Secondly, we employed DNA probes complementary to human rRNA such that hybridisation and subsequent digestion by RNAse H dramatically reduced their frequency in the finished libraries. Whilst this methodology has been successfully used in the detection and characterisation of two haemorrhagic fever viruses, the frequency of viral reads was often below 1% and an additional hybrid-capture step was employed to elevate read numbers57, but in several studies (and in the authors’ laboratory), significant amplification biases have been observed, leading to gaps in target genome coverage60. Consequently, we adopted an approach using a standard RNA library preparation kit, but with substantial modification to compensate for their minimum RNA input requirements of at least 10 ng and optimally 100 ng-1 µg.The resultant rRNA-depleted sample extracts typically contain quantities of nucleic acid in the low picogram range. Library preparation through hexamer-mediated reverse transcription followed by Multiple Displacement Amplification constitutes an easy and effective means of amplifying very low amounts of DNA37. Lower amounts of RNA thus require shorter optimum fragmentation times and we found that 1 minute at 94 °C was optimal in terms of breadth of genome coverage.We made key changes to the RNA fragmentation and adaptor-ligation steps of the NEBNext Ultra Directional RNA Library Prep Kit protocol. While prior RNA fragmentation with heat and divalent cations improves sequence coverage, over-fragmentation of target genomes leads to the loss of material during the library preparation processUnder standard kit conditions, our ultra-low RNA inputs dramatically skewed the ratio of cDNA to adaptor. The resulting adaptor excess led to the preferential amplification of adaptor dimers during the PCR step, and despite increasing cycle number to amplify low RNA inputs, we were generally unable to generate sufficient quantities of target-specific material. Accurate quantification and consequent equimolar pooling of libraries was compromised, as was the MiSeq clustering efficiency. We found that a reduced final adaptor concentration of 1.4 nM was crucial in reducing the amount of adaptor dimers in libraries from rRNA-depleted samples whilst simultaneously extending the PCR cycle number.61, so whilst we speculate that the depths and coverages of target viruses would be greater yet in these samples had it not been for the confounding effect of the unexpected human pegiviruses in both the plasma diluent and the patient sample series, it was reassuring to see the method performed well under such conditions.In the present study, serial dilutions of the Blood Borne Virus Panel were prepared in negative human plasma, reducing both the absolute quantity and relative frequency of the viral RNA targets while maintaining the complexity of the sample in terms of host nucleic acid, thus mimicking that of a clinical sample. With rRNA depletion, the number and diversity of viral reads was consistently high, with over 35% of all reads mapping to constituent virus genomes. Throughout the three sample series, we obtained relatively high genome coverages of low-frequency viral targets. Co-infections with multiple blood-borne viruses are common38 and for the VMR Panel41, and we were able to recover from a patient sample a large percentage of the genome of a previously uncharacterised subtype of HCV genotype 6 when present at 2 × 103 IU/ml, a diagnosis not possible using existing genotyping assays. The presence of an undiagnosed pegivirus in this sample further demonstrated the utility of the method in metagenomic analysis of blood-borne virus co-infections where the relative abundances of each virus can be highly variable22. Furthermore, in three of the four samples, depths greater than 1,000 were routinely obtained, which are likely to be sufficient to call minority variants for clinical resistance62. A full description of the patient series and the new HCV strain are provided in a separate manuscript (in preparation).In our experiments using negative human plasma as sample diluent, we were able to recover levels of viral genomes comparable to previous work using PBS, both for BBV Panel viruses64 and other random amplification-NGS techniques31 have detected novel viruses in diverse clinical samples, but all have required further techniques to achieve full genome sequences.Our approach can therefore not only accurately characterise rare or novel variants of existing viruses, but also generates the same level of information regarding unexpected viruses present in the sample. By comparison, VIDISCATogether with the VMR Panel results, we were able to recover identifying sequence from both enveloped viruses , and non-enveloped viruses . For the majority of viruses in the VMR Panel, whilst dilution in plasma reduced the total percentage of reads recovered when compared to the panel diluted in PBS, a greater breadth of genome coverage was achieved. In the absence of any host nucleic acid background, it is possible that the PBS extracts had such ultra-low quantities of RNA that despite the adjustments made to the library preparation protocol, the RNA was over-fragmented, leading to a smaller number of genome fragments that were individually amplified to a greater extent than the larger array of fragments surviving the plasma extraction.et al. were only able to recover a percentage of reads exceeding 6% at a viral load over 107 copies/ml. At an influenza A virus concentration of over 105 copies/ml, this dropped to just 0.5%, and at a reovirus concentration of 103–104 copies/ml, no viral reads were detected24. With our method, whole genomes were obtained for those with the highest viral loads, and for minority viral targets, there was a correlation between ostensible quantity and coverage, including for two viruses undetectable by the panel distributor42, a result superior to that recently obtained from influenza in clinical respiratory samples65. Again, the presence of high quantities of one or more target is likely to have inhibited the representation of the minority species such that if tested individually, superior depths and coverages would seem likely. With further reduction to the fragmentation time, or even its abolition, it may be possible to use this method to reconstruct genomes from old, partially degraded samples such as those recently used to re-evaluate the early HIV epidemic in the Americas66.In developing a similar approach, Kohl et al.67 identified a second source of contamination consisting of incorrect reads from other libraries that were sequenced during the same sequencing run due to TruSeq index misassignment . Although cross-contamination between samples during the library preparation can be another source of contamination, the qPCR results suggest no BBV Panel genomes were present after library preparation in the negative control sample.Our negative control data suggest that the level of contamination is low, with most viral reads therein belonging to the most abundant VMR Panel member. Nelson 65, but here, only simple bioinformatic processing is needed for detection and identification of known viruses, and by applying only moderately more advanced tools, an agnostic approach to virus detection can be taken, together with characterisation of the full genome even at low viral loads.To conclude, by applying the three adaptations of selective large RNA extraction, rRNA depletion-DNAse treatment, and the extensively modified library preparation in combination, NGS data sets can be produced from plasma samples that are rich in RNA virus sequence data. Complex bioinformatic processing has been employed to identify viruses within a metagenomic datasetSupplementary Information


Metastasis is a major cause of mortality in cancer. Identifying prognostic factors that distinguish patients who will experience metastasis in the short-term and those that will be free of metastasis in the long-term is of particular interest in current medical research. The objective of this study was to examine if select genetic polymorphisms can differentiate colorectal cancer patients based on timing and long-term risk of metastasis.The patient cohort consisted of 402 stage I-III colorectal cancer patients with microsatellite instability (MSI)-low (MSI-L) or microsatellite stable (MSS) tumors. We applied multivariable mixture cure model, which is the proper model when there is a substantial group of patients who remain free of metastasis in the long-term, to 26 polymorphisms. Time-dependent receiver operator characteristic (ROC) curve analysis was performed to determine the change in discriminatory accuracy of the models when the significant SNPs were included.XRCC3 Thr241Met (p = 0.042) and the 3R/3R genotype of TYMS 5’-UTR variable number tandem repeat (VNTR) (p = 0.009) were associated with decreased time-to-metastasis. ROC curves showed that the discriminatory accuracy of the model is increased slightly when these polymorphisms were added to the significant baseline characteristics.After adjusting for significant baseline characteristics, two polymorphisms were significantly associated with time-to-metastasis: TT and TC genotypes of the XRCC3 Thr241Met and TYMS 5’-UTR VNTR polymorphisms are associated with time-to-metastasis, and may have potential biological roles in expediting the metastatic process. Once replicated, these associations could contribute to the development of precision medicine for colorectal cancer patients.Our results indicate  Colorectal cancer is a worldwide health concern, especially in developed regions . It is eWhen considering metastasis as the disease outcome, it is possible that a proportion of the cohort does not experience the outcome during a long follow up period. Thus, such cohorts consist of patients who experience metastasis (i.e. patients who are “susceptible” to metastasis) as well as those that remain free of metastasis in the long term  –7. When Patient consent was obtained by Newfoundland Colorectal Cancer Registry (NFCCR) –14 at thTYMS rs34743033 in our study cohort; this allele was treated like 3R allele during the analysis.We examined the 26 polymorphisms listed in The survival outcome of interest was time-to-metastasis. Patients who did not experience metastasis by the end of the follow-up time were censored at the time of the last follow-up.We modeled time-to-metastasis by using the logistic Weibull cure model, a parametric proportional hazard mixture cure model ,19, whicPrior to analysis, Kaplan-Meier survival curves were obtained for the baseline characteristics  and polyBRAF V600E mutation status (present versus absent), adjuvant 5-fluorouracil (5-FU) chemotherapy treatment status (yes versus no), and stage (II versus I and III versus I)  . Then, eA p-value less than 0.05 was considered significant unless otherwise was stated.To determine if the polymorphisms can more accurately discriminate between patients in terms of their risk of metastasis at different time points, we performed time-dependent receiving operator characteristic (ROC) analysis . The areAll statistical analyses were performed using R v. 3.0.1.The baseline characteristics for this cohort can be found in XRCC3 rs861539  and genotypes homozygous for 3 repeats (3R/3R) in TYMS rs34743033  were significantly associated with a shorter time-to-metastasis in patients who were susceptible to metastasis after diagnosis  and the second with time-to-metastasis (in patients who are susceptible to metastasis). In our study, after adjusting for significant baseline characteristics, two out of 26 polymorphisms showed significant associations with time-to-metastasis in patients who are susceptible to metastasis. The genotypes containing the minor allele (TT + TC) of s Tables .XRCC3-rs861539 + significant baseline characteristics, Model 3) TYMS-rs34743033 + significant baseline characteristics, and Model 4) XRCC3-rs861539 + TYMS-rs34743033 + significant baseline characteristics. We also considered four different endpoints: specifically 3-, 5-, 7-, and 9-years follow-up time. As shown in We then proceeded with time-dependent ROC analysis, performed under four multivariable models: Model 1) significant baseline characteristics only, Model 2) XRCC3-Thr241Met and TYMS-5’ UTR VNTR, were significantly associated with early metastasis in colorectal cancer. Patients with these genotypes were more likely to experience metastasis in a short time, but the long-term risk of metastasis was not significantly different in the patient subgroups. Additionally, time-dependent ROC curve analysis indicated these polymorphisms slightly increased the discriminatory accuracy of the model at different time points considered . Previously, the variant protein has been shown to be associated with DNA adduct levels and increased risk of tetraploidy, linking this polymorphism to cancer [XRCC3 Thr241Met polymorphism deserves further functional characterization, particularly to examine whether it is biologically linked to metastasis.XRCC3 is a DNA repair protein and key component of homologous recombination . The XRCo cancer . A numbeo cancer ,26–30. Ao cancer  associatTYMS polymorphisms are among the most studied variants in colorectal cancer due to the function of the encoded protein. TYMS codes for thymidylate synthase (TYMS), an enzyme that is involved in nucleotide synthesis. This enzyme can be inhibited by 5-FU, a chemotherapeutic agent commonly used in treatment of colorectal cancer [TYMS polymorphisms; the 28 bp variable number of tandem repeat at the 5’ UTR and a 6 bp indel at the 3’ UTR. Our analysis identified that one of these variants was associated with outcome in colorectal cancer; specifically the homozygosity for the 3R allele of the 5’ UTR VNTR predicted early time-to-metastasis compared to 2R/3R and 2R/2R genotypes . Strengths include examining a well described patient cohort with long follow-up times, having a specifically defined end point , focusing on a homogenous patient cohort by considering the MSI-L/MSS subtype of colorectal cancer, and application of the mixture cure modeling to adequately address our research questions.XRCC3-Thr241Met and TYMS 5’ UTR VNTR, whose specific genotypes are significantly associated with early metastasis in colorectal cancer. These results, once replicated in other patient cohorts, could provide further insight into the variability of colorectal patient prognosis and provide potential biomarkers for early metastasis. Identifying such biomarkers that have time-varying effect on the risk of experiencing metastasis could be used in clinical management of patients by giving more appropriate treatment and surveillance decisions for different time periods.In conclusion, we have identified two polymorphisms, S1 FigMSI: microsatellite instability; MSI-H: MSI-high; MSI-L: MSI-low; MSS: microsatellite stable.(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 FigXRCC3 Thr241Met polymorphism or TYMS 5’-UTR VNTR polymorphism and (B) their corresponding conditional survival function estimates for the patients susceptible to metastasis.(A) Kaplan-Meier survival functions stratified according to the  Under the assumptions of the mixture cure model, the population is viewed as a mixture of susceptible and non-susceptible individuals to metastasis, where susceptible refers to patients who will experience metastasis and non-susceptible individuals are long-term metastasis-free survivors who are viewed as  cured. The upper plots in (A) show the Kaplan-Meier estimates of the survival curves of time-to-metastasis (T) for each genotype category considered  = Pr(T > t|x) where x denotes the covariate (genotype category of the corresponding polymorphism)). On the other hand, the lower plots in (B) show the estimated conditional survival curves for the susceptible group under each x level  = Pr which is the probability that the susceptible person will survive beyond a specified time t without metastasis). Hence, in the upper plots the probability of survival is for the population under consideration including both susceptible and non-susceptible individuals, but the lower plots are for the survival function of time-to-metastasis in the group of susceptible individuals. The conditional survival curves for the susceptible group in the lower plots are obtained from the mixture cure model S(t|x) = Pr(T > t|x) = p(x) + (1 − p(x))S0(t/x) where p(x) denotes the probability of being long-term metastasis-free survivor and thus 1 − p(x) is the probability of being susceptible to metastasis. Hence, the curves in the lower plots were obtained by plugging the Kaplan-Meier estimates of S(t|x) and p(x) in S0(t|x) = (S(t|x) − p(x))/(1 − p(x)).(TIF)Click here for additional data file.S1 Tablea with that in subgroup b among those who are susceptible to metastasis. OR: odds ratio for metastasis . OR compares metastasis proportion in subgroup a with that in subgroup b. CI: confidence interval; diff.: differentiated; 5-FU: 5- fluorouracil.HR: hazard ratio for time to metastasis among susceptible group. HR compares metastasis rate in subgroup (DOCX)Click here for additional data file.S2 TableBRAF mutation status, 5-FU treatment status, and disease stage. HR: hazard ratio for time to metastasis among susceptible group. HR compares metastasis rate in subgroup a with that in subgroup b among those who are susceptible to metastasis. OR: odds ratio for metastasis . OR compares metastasis proportion in subgroup a with that in subgroup b. CI: confidence interval. *There were 3 patients with a 4R allele in TYMS rs34743033; this allele was treated like 3R during the analyses.Each row represents a separate fit and is adjusted for location, grade, (DOCX)Click here for additional data file.


Short Tandem Repeats (STRs) are frequent entities in many transcripts, however, in some cases, pathological events occur when a critical repeat length is reached. This phenomenon is observed in various neurological disorders, such as myotonic dystrophy type 1 (DM1), fragile X-associated tremor/ataxia syndrome, C9orf72-related amyotrophic lateral sclerosis and frontotemporal dementia (C9ALS/FTD), and polyglutamine diseases, such as Huntington’s disease (HD) and spinocerebellar ataxias (SCA). The pathological effects of these repeats are triggered by mutant RNA transcripts and/or encoded mutant proteins, which depend on the localization of the expanded repeats in non-coding or coding regions. A growing body of recent evidence revealed that the RNA structures formed by these mutant RNA repeat tracts exhibit toxic effects on cells. Therefore, in this review article, we present existing knowledge on the structural aspects of different RNA repeat tracts as revealed mainly using well-established biochemical and biophysical methods. Furthermore, in several cases, it was shown that these expanded RNA structures are potent traps for a variety of RNA-binding proteins and that the sequestration of these proteins from their normal intracellular environment causes alternative splicing aberration, inhibition of nuclear transport and export, or alteration of a microRNA biogenesis pathway. Therefore, in this review article, we also present the most studied examples of abnormal interactions that occur between mutant RNAs and their associated proteins. C9orf72 amyotrophic lateral sclerosis and frontotemporal dementia (C9ALS/FTD), Friedreich’s ataxia (FRDA) and nine polyglutamine diseases, such as Huntington’s disease (HD) and a number of spinocerebellar ataxias (SCA). DM1 and DM2 are caused by a CTG expansion (50 to >3500) in the 3′UTR of the dystrophia myotonica protein kinase (DMPK) gene and by a CCTG expansion (75 to approximately 11000) in the first intron of the zinc finger protein 9 (ZNF9) gene, respectively  gene  gene represent the most common genetic abnormality in C9ALS/FTD  gene is the causative agent of FRDA  gene and of at least 60 CAG repeats in the 10th exon of the ataxin 3 (ATXN3) gene, respectively, is sufficient to cause pathogenic effects  are common in intergenic regions and in untranslated and translated regions of protein-coding genes. Such repeats are characterized by genetic instability as well as by an ability to expand  a toxic RNA gain-of-function mechanism in which expanded toxic RNA species tend to form intracellular RNA foci that sequester important proteins from their normal cellular functions; (2) a toxic protein gain-of-function mechanism in which the presence of polyQ stretches encoded by elongated CAG repeats results in protein conformational changes, altered protein-protein interactions and aggregate formation; and (3) aberrant loss-of-transcript and loss-of-protein functions in which transcript or protein expression is inhibited by the expanded repeats. However, taking into account the occurrence of bidirectional transcription across the expanded repeats  and enzymatic  cleavages, the structures of CCUG, AAG and all CNG repeat motifs  in solution were analyzed  adopt higher-order RNA structures, two comparative studies were performed  and enzymatic  structure probing and biophysical methods  spectra and gel mobility analysis). As a result, TNRs have been grouped into four different structural classes: (1) unstructured RNAs; (2) semistable hairpins; (3) fairly stable hairpins; and (4) very stable G-quadruplexes. In agreement with previously described studies, CUG repeat motifs  form fairly stable hairpins  or CAG, CGG, CUG and CCG  has been visualized using electron microscopy  and enzymatic (S1 and T1 nucleases) structure probing of in vitro-transcribed RNAs containing increasing lengths of CUG repeats  together with flanking sequences . The analysis demonstrated that five repeats, which is the most common, non-pathogenic number of repeats in the population, do not form any secondary structures. Upon increasing the length of the CUG repeats, the stability of the formed structures increased: 11 repeats formed unstable hairpins, 21 repeats formed semi-stable hairpins, and the expanded 49 CUG repeats formed fairly stable hairpins. Moreover, as the sequences flanking the repeats did not “freeze” the repeat alignment, thus resulting in alternative structures, the CUG repeat hairpins are referred to as “slippery” , similar to the previously described CUG repeats, form hairpin structures in solution, with a stem composed of periodically occurring standard C-G and G-C base pairs that are divided by a single, periodic non-canonical A-A pair  forms a 4-nt apical loop. However, when an odd-numbered hairpin was studied (CAG17), a larger 7-nt loop appeared  form fairly stable hairpins   and N1 atom of the A(anti) (N6H⋅⋅⋅N1 hydrogen bond). Moreover, the second closing A-A base pair, as well as, the A-A base pair located in the center of the duplex all had anti-anti conformations with no hydrogen bonds  Figure . This ty) Figure . In the 2+) and enzymatic RNA structure probing experiments with the use of a battery of probing reagents, e.g., S1, Mung Bean nuclease and RNases T1, T2, V1 and H.Until now, the structures formed by CAG repeats in their native, transcript context are the most extensively studied TNRs. These studies focused on assessing whether specific sequences flanking the CAG repeats contribute to the overall characteristics of the CAG hairpin structures, i.e., the formation of the multiple alignment hairpins (“slipped” hairpin) or a single alignment hairpin  transcripts, which are affected by both the specific flanking sequences and another type of neighboring, triplet repeats, have been established n] have polymorphic CCG repeat tract [(CCG)7 or 10 nt] at their 3′ side that is separated by a 12-nucleotide specific sequence. This specific neighborhood causes the HTT CAG repeat variants to have a tripartite modular structure composed of the base, which is the most stable part of the stem and where the 5′ part of the CAG repeats are engaged in base pairing with CCGs; the central module, which is formed by the partially base pairing CAG repeats with 12-nucleotide specific sequence; and the terminal section, which is part of the hairpin structure and which is composed exclusively of CAG repeats. The difference between normal and mutant HTT transcripts is only restricted to the terminal section, which in the mutant transcript gets elongated, while the other structural modules remain the same. As the stability of the base module consisting of base-paired CAG and CCG repeats is much higher than other hairpin modules, the latter may form alternative structural variants resulting from the slippage effect of the CAG repeats , in the context of the entire first exon (harboring the repeats) and the neighboring 5′UTR sequence, have been investigated by in vitro selective 2′-hydroxyl acetylation analyzed by primer extension (SHAPE) analysis  or short , not one but two different types of neighboring, triplet repeats, together with specific flanking sequences, contribute to the formation of a composite CAG repeat hairpin structure 3] directly upstream of a polymorphic, expansion-prone CAG repeat tract [(CAG)n]. Moreover, six monomorphic CAG repeats [(CAG)6] are located downstream of the CAG repeat tract and are separated by an 18-nucleotide specific sequence. As presented in Figure 3 repeats fully base pair with the last three CAG repeats of the (CAG)n tract to form a strong 12-bp stabilizing clamp, which is responsible for the presence of both normal and mutant AR transcripts in only the “frozen” type of hairpin form with a single RNA alignment. In addition, further stabilization of the repeat hairpin is conferred by the base-pairing system of the nearest specific CAG flanking sequences. Moreover, the monomorphic (CAG)6 repeat tract, which is located 18 nt downstream from the polymorphic, expansion-prone CAG repeat tract [(CAG)n], is not involved in the formation of the long repeat hairpin structure, but rather, forms an autonomous short hairpin. The only difference between the normal and mutant AR transcript is the length of the CAG repeat hairpin, which is formed solely by polymorphic expansion-prone CAG repeats and which contains either a 4- or 7-nt terminal loop, depending on the CAG repeat number according to the rule observed for isolated, clamped, CAG repeat structures  transcripts . The stem structure and loop size follow the pattern observed for model of isolated CAG repeats containing a GC clamp   and two CAA triplets (78%–95% in populations), respectively, were shown to destabilize the stem of the single, long CAG repeat hairpin. If two interruptions break the regularity of the CAG repeat tracts, they are always separated by one CAG repeat in the ATXN1 transcripts and by four CAG repeats in the ATXN2 transcripts. Depending on how the CAU and CAA interruptions are organized in transcripts, they can widen the existing terminal loop, nucleate out additional loops, split the sequence into two separate hairpins (mainly in ATXN1 transcripts), or form specific branched structures with the interruptions localized in terminal loop/s  were found to form hairpins with the stem composed of periodically occurring C-G and G-C base pairs that are separated by a single non-canonical G-G pair , a 4-nt apical loop was formed. In the case of odd-numbered CGG repeat hairpin (CGG17) a tighter 3-nt terminal loop was observed , together with other three CNG, CAA and CGU motifs, form fairly stable hairpins  and N7, N2H atoms from the G(anti), respectively (O6⋅⋅⋅N1H and N7⋅⋅⋅N2H) 4C oligomers in solution are highly polymorphic, and other type of structures can be adopted depending on the presence of different cations , the length of the repeats and the concentration of RNA used. For example, when the G(CGG)2C oligomer is studied in Na+ solutions, it maintains a balance between G-quadruplex/duplex structures, but when it is studied in HeLa cellular extracts where K+ ions are prevalent, the G(CGG)2C oligomer almost exclusively forms duplexes. Recently, a novel quadruplex architecture formed by the 8-bromoguanosine-modified molecule GCBrGGCGGC was characterized -G(anti) conformations, thus increasing the thermodynamic stability and the homogeneity of the RNA structures that formed. As the folding rules of both the quadruplexes formed by CGG repeats are yet unclear and may depend on other factors, it is of great interest to study these structures further.The exact structural properties of transcripts containing CGG repeats have been a matter of debate. While strong biophysical and biochemical evidence for CGG duplex and hairpin structures has been presented ) of increased severity depending on the extent of CGG tract expansion  in the CGG repeat tract. These AGG triplets were shown to destabilize the single long CGG hairpin structure in different ways   ; and (2) a stable zero hydrogen bond conformation, which is stabilized by a specific hydration pattern, as suggested by in silico computational analysis. Moreover, it is hypothesized that these extremely weak and dynamic C-C non-canonical pairing interactions as well as the disrupted base stacking of the C-C pair with the neighboring U-U pairs cause the internal 5′UCU3′/3’UCU5′ loops to be the least thermodynamically stable elements of the AUUCU repeat hairpin structure. Furthermore, as proposed by the MD simulation analysis, this dynamic feature of the internal loops affects the overall AUUCU A-form helix stability, causing its rearrangement into single-stranded conformations (quasistable hairpin structures). This 5′UCU3′/3’UCU5′ loop is thought to be a site where RNA unwinding starts.To date, higher-order RNA structures formed by pentanucleotide AUUCU repeats, which are present in intron 9 of the ) Figure . Recentl) Figure . In that) Figure . In the n and antisense (CCCCGG)n transcripts that both form different higher-order RNA structures.In recent years, numerous structural and functional studies have been carried out to understand RNA toxicity in newly described hexanucleotide repeat expansion which is implicated in C9ALS/FTD. In these diseases, the expanded repeats are transcribed bidirectionally, generating noncoding sense (GGGGCC)in silico computational analysis performed with a G-quadruplex prediction tool (QGRS mapper) and showed that an isolated (GGGGCC)3GGGGC RNA oligomer (C9Gru) is minimally required for the formation of a specific G-quadruplex structure  that connects laterally G-quadruplex phosphate backbones  or from the interaction of GGGGCC repeats from different C9orf72 molecules (intermolecular G-quadruplexes) is still a matter of a debate  can form stable G-quadruplex structures only through an intramolecular association 6 or 8, which is consistent with the formation of additional intermolecular G-quadruplexes (multimeric). Moreover, such an increase in heterogeneity was observed, as both additional intramolecular and intermolecular G-quadruplexes were formed when a native 5′ flanking sequence (15-nt long) from C9orf72 RNA was present upstream of the GGGGCC repeat tract. Hairpin formation may compete with or contribute to the formation of G-quadruplexes or other structures  forms stable multimeric G-quadruplex structures in U87 nuclear extracts  into a stable G-quadruplex structure is strongly influenced by the presence of monovalent cations (K+ promotes stable folding over Na+ and Li+ ions). Furthermore, at a physiological K+ ion concentration (pH), these structures were shown to be extremely thermodynamically stable  or a structure consistent with single-stranded bulges and hairpin conformations, depending on the presence or absence of K+ ions, respectively , these G-quadruplex forming regions were shown to be globally unfolded, presumably by a robust and effective machinery consisting of unknown RNA helicases and other ssRNA-binding proteins, that await to be fully characterized. Therefore it is predicted that in C9ALS/FTD patients this machinery could be either “switched off” or inefficient in the certain cell types, states or subcellular compartments thereby allowing G-quadruplex structures to form over time and exert significant pathogenic effects.The G-quadruplex structures formed by GGGGCC repeats have only recently been observed in cells 4, intermolecular multimers; (CCCCGG)10, intramolecular A-form like helixes. In the same study, the X-ray crystal structure of a model (CCCCGG)3(CCCC) RNA refined to 1.47 Å resolution was determined  interacted with either the carbonyl O2 atom (N4H⋅⋅⋅O2 hydrogen bond) or with the N3 atom of the other cytosine residue (N4H⋅⋅⋅N3 hydrogen bond) ) Figure . Moreovein vitro RNA structures formed by expanded repeats has significantly increased. However, to gain deeper insight into the role of RNA toxicity in the pathogenesis of repeat expansion-related diseases, the interplay between mutant RNAs and their binding proteins needs to be studied in more detail. In this section, we present a few examples of repeat RNA-protein interactions for which the secondary structure formed by simple expanded repeats seems to play crucial role. Other proteins identified as RNA repeat binders are reviewed elsewhere  protein and CUG repeat-containing RNA. It is commonly known that abnormal MBNL1 sequestration by RNA foci formed by a mutant Drosophila MBNL1 was first identified as a protein that binds the CUG repeat in a repeat length-dependent manner  assay was used, which confirmed the interaction between protein and RNA through detection of the reporter gene activities  alone and in combination with IF (FISH/IF) techniques were also employed to investigate CUG repeats targeting by MBNL, which demonstrated the accumulation of long CUG tracts in nuclear foci where MBNL1 co-localized , wherein ZnF1 with ZnF2 and ZnF3 with ZnF4 are paired to form two tandems connected by a linker region Figure . There aElectron microscopy demonstrated that MBNL1 binds to long CUG tracts as a ring-shaped structure  family of RNA-binding proteins, was one of the first proteins that was considered a factor potentially sequestered by expanded CUG repeats 30  or when antisense hairpin-forming (CCCCGG)4 repeats were studied. NCL directly binds to the G-quadruplex motif, as demonstrated by RNA pulldown with GST-NCL, and colocalizes with GGGGCC RNA foci. It is still unknown which domain of NCL is involved in the interaction with GGGGCC G-quadruplexes. However, based on relevant data from c-MYC G-quadruplex structures, it is likely that the GGGGCC G-quadruplex-binding domain might consist of RRM3, RRM4 and the arginine-glycine-glycine domain , a multifunctional protein involved in DNA metabolism, transcription, ribosome assembly, mRNA stability and translation 8 , a member of the arginine/serine-rich splicing factor protein family, which is involved in constitutive and alternative splicing, mRNA export and decay, or translation, represents another GGGGCC quadruplex-binding protein Figures . The GGG8  the exact structure of full-length repeat-containing transcripts in cells; (2) whether there are any alternative RNA structures that are formed in cells by the same repeat-containing transcripts; (3) the complement of proteins that bind to the specific RNA repeats; (4) the exact nature of these RNA-protein interactions; (5) which of these RNA-protein interactions exhibit toxic effects to cells; and (6) how this toxic effect is manifested (which cellular processes are affected).2+ ions) RNA structure probing. These biophysical studies shed light on the physical characteristics of the RNA structures formed by the repeated sequences, i.e., thermodynamic stabilities, detailed duplex/hairpin properties and hydrogen bonding status; however, these studies were performed only on isolated, short repeat-containing oligomers without native sequence context. Such studies were able to provide very detailed, but only partial, information on the structures formed by the full-length transcripts in cells. This finding also applies to the enzymatic and chemical RNA structure probing experiments in which relatively short 5′ and 3′ repeat-flanking sequences were analyzed, which are rather insufficient, in light of recent findings showing that extensive long-range intra- and intermolecular RNA-RNA interactions occur in cells  technologies. Currently, the focus should be to harness these in vivo RNA structural probing methods or to develop novel ones to solve the precise RNA structures of repeat-containing transcripts with single-nucleotide resolution.To date, the structural studies on simple repeat-containing transcripts were performed mostly under non-physiological conditions and relied on a range of biophysical methods, such as X-ray crystallography and NMR and CD spectroscopies or on traditional enzymatic  and chemical  or immunoblotting against proteins predicted to interact with repeat-containing transcripts (a biased “candidate” protein approach), EMSA, filter binding assay, in vitro RNA immunoprecipitation, UV-induced crosslinking and RNase footprinting assays, fluorescence polarization anisotropy and electron microscopy studies  can be of use, i.e., CLIP  and by the Polish Ministry of Science and Higher Education, under the KNOW program for years 2014–2019.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.