With the goal to generate and characterize the phenotypes of null alleles in all genes within an organism and the recent advances in custom nucleases, genome editing limitations have moved from mutation generation to mutation detection. We previously demonstrated that High Resolution Melting (HRM) analysis is a rapid and efficient means of genotyping known zebrafish mutants. Here we establish optimized conditions for HRM based detection of novel mutant alleles. Using these conditions, we demonstrate that HRM is highly efficient at mutation detection across multiple genome editing platforms ; we observed nuclease generated HRM positive targeting in 1 of 6 (16%) open pool derived ZFNs, 14 of 23 (60%) TALENs, and 58 of 77 (75%) CRISPR nucleases. Successful targeting, based on HRM of G0 embryos correlates well with successful germline transmission (46 of 47 nucleases); yet, surprisingly mutations in the somatic tail DNA weakly correlate with mutations in the germline F1 progeny DNA. This suggests that analysis of G0 tail DNA is a good indicator of the efficiency of the nuclease, but not necessarily a good indicator of germline alleles that will be present in the F1s. However, we demonstrate that small amplicon HRM curve profiles of F1 progeny DNA can be used to differentiate between specific mutant alleles, facilitating rare allele identification and isolation; and that HRM is a powerful technique for screening possible off-target mutations that may be generated by the nucleases. Our data suggest that micro-homology based alternative NHEJ repair is primarily utilized in the generation of CRISPR mutant alleles and allows us to predict likelihood of generating a null allele. Lastly, we demonstrate that HRM can be used to quickly distinguish genotype-phenotype correlations within F1 embryos derived from G0 intercrosses. Together these data indicate that custom nucleases, in conjunction with the ease and speed of HRM, will facilitate future high-throughput mutation generation and analysis needed to establish mutants in all genes of an organism. Manipulation of the genome in cells and in model organisms has become mainstream in biomedical research. While the mouse has prospered from advances in ES cell technology, mutant generation has been limited/more cumbersome in most other organisms. The ultimate goal is to generate mutants in all genes or in combinations of genes, and characterize the associated phenotypes; however even with ES cell technology, this is limiting. High-throughput tilling approaches to generate large collections of null alleles have alleviated this in many organisms, such as the zebrafish, C. elegans, and drosophila There are a number of techniques used for detection of genome editing derived mutations. Initially, approaches utilized the destruction of a restriction enzyme site m of a particular PCR product. While a homoduplex product generated from a homozygous DNA sample will have a particular Tm, a heteroduplex product generated from a heterozygous individual will have an additional Tm, generally a much lower Tm signature  analysis ignature . It is tTo facilitate the use of HRM in high-throughput mutation detection and rapid phenotype analysis in G0 zebrafish, we established the optimal parameters and workflow for reliable detection of heterozygous alleles. We demonstrate that HRM can detect chimerism as low as ∼5% in G0 animals, and we validate that HRM is extremely efficient at mutation detection in ZFN, TALEN and CRISPR genome editing systems. Our analysis demonstrates that somatic mutations from G0 tail DNA weakly correlate with germline mutations; yet, small amplicon HRM can distinguish between individual alleles in complex backgrounds facilitating desired mutation isolation. Utilizing HRM, we determined that injection-based CRISPR genome editing produces relatively few off-target mutations; and based on HRM curve profiles, we have been able to make genotype-phenotype correlations between mutant embryos derived from G0 intercrosses, rapidly accelerating the pace of mutant phenotyping.m change between the different homoduplexes and heteroduplex PCR products. While the small amplicon will allow for greatest resolution of Tm differences it has a limitation in that small amplicons may not detect larger alterations (i.e. large deletions). On the converse, larger amplicons are more likely to encompass all possible mutant alleles but suffer from poor resolution of Tm differences. Therefore, to test the impact of amplicon size on mutation detection, we tested 50 bp (base pair), 100 bp and a 300 bp amplicon on three different mutations (heterozygous p53 mutant I166T (T>C) point mutation, heterozygous RB (retinoblastoma 1) 2 bp deletion, and heterozygous RB 13 bp deletion) designed such that the mutation was in the middle of the amplicon. For the p53 T→C point mutation, HRM could only distinguish the mutant allele with the 50 bp amplicon  with Cas9 mRNA into one cell embryos and then generated genomic DNA from 24 hpf (hours post fertilization) embryos. From this G0 genomic DNA, we determined that the Esco11, Cdca5, CHEK2 and PTGS2b CRISPRs generated HRM positive curves while the Esco21 and IFT881 CRISPRs did not  of G0 animals derived from TALEN or CRISPR injected embryos crossed to AB wild-type animals. For each clutch derived from a single G0 animal, genomic DNA from 24–48 F1 embryos was generated. HRM was performed and the percentage HRM positive (+) was determined  and 2. Im change in the heteroduplex curve.While analyzing the data from 2 CRISPR. From each tail, a 300 bp amplicon was generated, cloned and mutations were sequenced. We also isolated genomic DNA from 24 F1 progeny, for which we identified the mutation produced. Interestingly, from these data, we observed a lower number of alleles in the germline than in the soma  might facilitate identification of animals with a desired allele. To test this, we generated genomic DNA from tail clippings of 8 different G0 fish that had been injected with an Esco2the soma . In most2 mutant alleles ; while the other Δ72 was identified in 7 of 8 G0 based on tail DNA and 4 of 8 G0's based on F1 germline contribution. Among the total mutant alleles identified from the 8 G0, the two Δ7 alleles made up 39 of 61 alleles , while it only occurred in 1 of 8 of the G0's progeny (F1). When we align the sequence of these preferential deletions, we observe that they often occur between micro-homology regions (2 or 4 nucleotides on the PAM (Protospacer Adjacent Motif) side of cleavage, and 4 nucleotides on the other side of cleavage; Through the analysis of the Esco2 alleles  we obser alleles . In addiTo evaluate this observation, we made predictions of the prevalent allele in our BARD1, p107 and Atad5b gene targeting, based on target sequence and the following rules: that the CAS9 cuts 3 nucleotides upstream of the PAM sequence; and larger micro-homologies (3–5 nucleotides) are preferential to smaller homologies (1–2 nucleotides) . Using thttp://crispr.mit.edu/) online tools. From this, we selected 5 guides that range in score from 97 (Ptgs1) to 45 (Bub1bb) and generated 4 off-target  HRM amplicons for each of the 5 guides to determine if these sites are being targeted  we did observe the background SNPs , while Oft 2 clearly had 11/48 embryos with clear HRM positive curves (2 different curves). Sequencing of these two curves revealed a Δ15+3 mutation and a 2 base pair (bp) insertion at the CRISPR off-target cut site, consistent with a CRISPR derived mutation. For Bub1bb, which has the worst overall score, only Oft 1, which has a single nucleotide change in the target site at position 3, produced off-target hits in 7 of 48 F1 embryos. Sequencing revealed this to be a 3 bp insertion, at the CRISPR cut site. Interestingly in both off-target cases, we did not observe the off-target hit in G0 embryos, but did in the F1 progeny; suggesting that off-target analysis needs to be performed on the F1 progeny not G0 injected embryos. Furthermore, in both cases, the germline frequencies for the off-target mutation were lower than the on-target germline frequencies, suggesting that we can easily segregate these alleles apart. Together these data indicate that off target hits are low  and preferentially target “off target” sites with NGG PAM sequences not NAG (2 of 6 with NGG verses 0 of 14 with NAG). In addition, higher scoring guides (>78) generally did not have off- target hits while lower scoring (<61) did. These data suggest that HRM can be used to identify off-target frequencies and can be used to select embryos/fish without off-target mutations or delineate phenotypes that are due to off target hits.One concern of genome editing, in particular with CRISPR genome editing, is the potential for off-target cleavage targeted . To excl2 guides, and performed HRM analysis of the 3 targets in 86 F1 adults. From this, we were able to identify 18 Gas8; 12 Ptgs1, and 14 IFT882 animals that contain single gene mutations 1 or Δ72 alleles . For G0#9 X Esco22865/+ we observed 6 of 147 embryos (4%) displayed a mutant phenotype http://crispr.mit.edu/)Utilizing HRM, we have successfully targeted sites with 1 of 6 (16%) open pool derived ZFNs, 14 of 23 (60%) TALENs , and 58 19-GG, at times we have substituted the 5′ one or two nucleotides with G's to allow for ideal in-vitro transcription. Amongst perfect matches (GG-) we observe a 80% (44/55) success rate for any designed guide. Our data suggest that changing position 1 (NG-) has minimal effect and results in a 75% (3 of 4) success; changing position 2 only (GN-) decreases the success to 60% (6 of 10); and changing both position 1 and 2 (NN-) reduces the success to 37.5% (3 of 8). Therefore our criteria for generating null alleles are to select target sites with at maximum one mismatch at position 1 or 2. If a particular location is required, mismatches at 1 and 2 can be designed but may require multiple guides to identify an efficient one. Of guides with 2 mismatches that function, they all cleave well and therefore it is not a matter of reduced efficiency.While the ideal target sequence is “GG-NOur observation of disconcordance of somatic mutations with germline mutations most likely reflects the timing of cleavage and the timing of primordial germ cell (PGC) differentiation. At the 1000 cell stage there are 4 PGC. While it has been assumed that DNA cleavage happens very early (1–4 cell stage), our data suggest that some cleavage events do not occur until later developmental stages when the PGC differentiate. Further, the fact that we observed identical alleles from different G0 individuals suggest that many of the high frequency alleles may not be a derivative of an earlier nuclease cleavage but a preponderance for generation of a particular allele later in development within different cells.As far as biallelic targeting, based on our germline contributions of TALEN-derived alleles, we rarely observed a germline transmission frequency greater than 50%, suggesting the best case scenario is that they are heterozygous; whereas with CRISPRs we often observe greater than 50% germline contribution. However, this may be biased depending on if the target gene is essential or not. In fact, with genes we know are homozygous non-viable, we often observe more in-frame mutations in G0s with greater than 50% contribution. Our data also indicates that among guides that do produce off-target cleavage, the off-target cleavage event is infrequent and less efficient compared to the target site cleavage. Further, such low frequency off-target hits can be segregated out more quickly using off-target HRM genotyping.While traditionally the bottleneck has been the lack of efficient techniques for custom nuclease cleavage, the new genome editing techniques have made this step proficient and readily available. Now the major bottleneck exists in mutation detection. We demonstrate that HRM can be used to alleviate this bottleneck. HRM is extremely unrestrictive, in that as long as you can PCR across a target site, HRM can be used. HRM is rapid; from genomic DNA to mutant identification only takes 1 hour. Furthermore, once the HRM equipment is in place, HRM is low cost and can detect low level chimeric animals, which other techniques often cannot. In our hands, multiplexing CRISPR guides also facilitates mutant generation by reducing the number of G0 animals to raise. HRM can also be used to cleanup undesired off-target alleles if they occur.m change and can be genotyped even using 100 base pair amplicons. In addition, for phenotypic analysis of uncharacterized alleles, HRM is very advantageous in segregating what HRM profiles correlate with a specific phenotype; or more importantly if they do correlate.We have demonstrated that HRM can be used to efficiently distinguish particular mutant alleles. In a practical sense, periodically we observe a rare allele, amongst other more common alleles  that have been described in the literature. However these large deletions are rare and are not necessarily more advantageous that small out of frame deletions. The major drawback to HRM is the setup cost for the equipment required for HRM detection. While traditionally performed in the highly sensitive Lightscanner instrument, a number of other PCR based systems now describe HRM capabilities.It has been proposed that CRISPRs can be used for biallelic phenotypic analysis in the G0 animals, thereby overcoming the need to breed to the F2 generation While we have demonstrated the ease in detection of new mutant alleles using HRM, future detection techniques will need to be devised to rapidly identify properly targeted single stranded oligo-directed homologous (ssoHR) recombination alleles Merging the ease of CRISPR targeting with the efficiency of HRM, high-throughput genome editing can be achieved rapidly and cost effectively. Utilizing a two person team, 30 guides (pools of 3 guides) can be tested and raised per week. Once these G0's are adult then the same two person team can quickly, identify high percentage chimeras through HRM of 12 embryos from G0 x AB. If HRM positive, the remaining F1's embryos will be raised for future allele identification and sperm frozen. High chimeric G0's can then be intercrossed and phenotypes determined. As we have demonstrated HRM genotype of mutants and wild-type embryos can confirm genotype-phenotypes correlations. In addition to analyzing 0–5 dpf phenotypes, the embryos from the G0 intercross will be raised and if the HRM profiles within the embryos do not occur in the adults (∼3 months), then there is a lethality between 5 dpf and the adult stage. We envision with a staggered generation approach that over a 52 week period ∼1500 mutants can be generated and phenotypes analyzed between 0 and 3 months of age.All zebrafish work was performed at the facilities of the University of Alabama at Birmingham (UAB) in the Zebrafish Research Facility (ZRF). Adult fish and embryos are maintained as described by Westerfield et al (1995) http://zifit.partners.org/ZiFiT/ChoiceMenu.aspx) The ZFN OPEN Pools, pMLM36 (#21871), pB1H2w2-zif268 (#18045) and pH3U3-zif268 (#18046) plasmids were purchased from Addgene. The zinc fingers were designed and selected using the online tool ZiFit Targeter  TALENs, targeting 23 different genes , were designed and selected using the online tool TAL Effector Nucleotide Targeter 2.0 (http://zifit.partners.org/ZiFiT/ChoiceMenu.aspx). The pDR274 (#42250), pT3T3-nCas9n (#46757), and MLM3613 (#42251) plasmids were obtained from Addgene TGATTGCAGTCCAGTTACGC and Reverse: GGAGGCTTTTGACTTTCTGCT. The PCR product was used as template for RNA synthesis. We further modified the protocol again by amplifying two approximately 300 bp PCR products  off of the pDR274 plasmid using primers that could then be joined together in a second round of PCR with an overlapping reverse primer that contained the desired guide sequence (GCCTTATTTTAACTTGCTATTTCTAGCTCTAAAAC - N20 reverse complement of guide-TATAGTGAGTCGTATTAGCTAGCGGTG). This eliminated the cloning step all together and ensured that the guide sequence was present in the 600 bp PCR product. Guide RNA was synthesized off this purified product.CRISPR guides were designed and selected using the online tool ZiFit Targeter (ZFN and TALEN mRNA was transcribed using the mMessagemMachine SP6 kit (Life Technologies). CAS9 mRNA was transcribed from the linearized pT3TS-nCas9n plasmid (Addgene) using the mMessage mMachine T3 kit (Life Technologies). Each RNA was purified using the RNeasy Kit (Qiagen). The CRISPR guide RNA was synthesized using the MegaShortScript T7 Kit (Life Technologies) and purified using the MegaClear Kit (Life Technologies). RNA concentration was quantified using the Nanodrop spectrophotometer.AB wild-type one-cell stage embryos were collected for microinjection by using a regulated air-pressure micro-injector . For ZFN and TALEN injections, equal amounts of the Left and Right mRNAs were mixed (starting at 100 ng/ul each and increasing the concentration as needed). For CRISPR/Cas9 injections, 150 ng/ul of Cas9 mRNA and 30 ng/ul of gRNA were mixed together in all experiments. ZFN, TALEN, and CRISPR nucleases were all injected into the yolk of the embryos. These embryos were then used for genomic DNA isolation or raised to obtain G0 adult fish.Individual embryos or tail clippings were placed in 100 uL ELB  in 96 well plates. Embryos/tail clips were incubated at 55°C for 4 hrs to overnight depending on sample size to generate genomic DNA. To inactivate Proteinase K, plates were incubated at 98°C for 10 minutes.http://biotools.umassmed.edu/bioapps/primer3_www.cgi). All primer sets are available upon request. PCR reactions contained 1 ul of LC Green Plus Melting Dye (BioFire Defense), 1 ul of Ex Taq Buffer, 0.8 ul of dNTP Mixture (2.5 mM each), 1 ul of each primer (10 uM), 0.05 ul of Ex Taq (Takara Bio Inc), 1 ul of gDNA, and water up to 10 ul. PCR was performed in an Eppendorf Mastercycler Pro S, using black/white 96 well plates (BioRad cat. No. HSP9665). PCR reaction protocol was 98°C for 30 sec, then 40 cycles of 98°C for 10 sec, 59°C for 20 sec, and 72°C for 15 sec, followed by 95°C for 20 sec and then rapid cooling to 4°C. Melting curves were generated with a Lightscanner HR 96 (Idaho Technology) over a 65–95°C range. Curves were analyzed with LightScanner Instrument and Analysis Software.Primers were designed using Primer3 (Embryos were dechorionated by hand using Dumont #5 tweezers and anesthetized using Tricaine. Embryos were positioned in methyl cellulose prior to image acquisition. Brightfield imaging was observed using Nikon AZ100 microscope with 2x objective (0.2 NA) and 2x digital zoom. Z-stacks at 25 µm intervals were taken to encompass the entire embryo. Z-stacks were aligned and focused to create one image. Scale bars denote 500 µm.S1 TableTALEN targets and primers. This table contains the gene name, TALEN target sites and primer sequence for HRM analysis. Gene names in red were HRM negative.(XLSX)Click here for additional data file.S2 TableCRISPR targets and primers. This table contains the gene name, CRISPR target site and primer sequence for HRM analysis. Gene names in red were HRM negative. NT in red in target sites was altered to “G” for targeting.(XLSX)Click here for additional data file.


The nonenzymatic replication of RNA is a potential transitional stage between the prebiotic chemistry of nucleotide synthesis and the canonical RNA world in which RNA enzymes (ribozymes) catalyze replication of the RNA genomes of primordial cells. However, the plausibility of nonenzymatic RNA replication is undercut by the lack of a protocell-compatible chemical system capable of copying RNA templates containing all four nucleotides. We show that short 5′-activated oligonucleotides act as catalysts that accelerate primer extension, and allow for the one-pot copying of mixed sequence RNA templates. The fidelity of the primer extension products resulting from the sequential addition of activated monomers, when catalyzed by activated oligomers, is sufficient to sustain a genome long enough to encode active ribozymes. Finally, by immobilizing the primer and template on a bead and adding individual monomers in sequence, we synthesize a significant part of an active hammerhead ribozyme, forging a link between nonenzymatic polymerization and the RNA world.DOI:http://dx.doi.org/10.7554/eLife.17756.001 Though defining what makes something “alive” has proved challenging, one crucial feature of living things is the ability to copy genetic information and pass it on to the next generation. Nowadays, enzymes called polymerases copy genetic information encoded within the DNA of living cells. However, when life on Earth began approximately four billion years ago, polymerases had not evolved yet. This means that the genetic information of the first cells had to be copied some other way.The earliest life on Earth is unlikely to have used DNA to store its genetic information, and probably used a closely related molecule called RNA instead. Like DNA, RNA is made up of four smaller building blocks joined together to form long chains. The building blocks of RNA are commonly referred to using single letters: A, C, G and U. Previous studies have shown that it is possible to copy RNA without enzymes, but for only two of the four RNA letters, namely C and G.Prywes et al. wanted to know if it was possible to create a chemical system, without polymerases, in which all four RNA letters could be copied. The experiments showed that strings of RNA that were three letters long could catalyze RNA copying, just as long as they were chemically activated. That is to say, these short RNA strings allowed RNA to be copied without enzymes if they had a chemical group at one end that made them more reactive.Each short catalyst helped copy one of the four RNA letters, and adding several into one reaction meant that longer sequences containing all four RNA letters could be copied.Prywes et al. then used these short catalysts to copy an RNA molecule that itself acts a bit like an enzyme, and confirmed that a significant portion of this molecule could be copied without any polymerases. Further work is now needed to see if it is possible to copy other RNA sequences, and especially longer ones, without enzymes. Another challenge for the future would be to attempt to copy an RNA sequence multiple times without enzymes; a challenge that the earliest ancestors of cells on Earth must have overcome to pass their genetic information down through the generations.DOI:http://dx.doi.org/10.7554/eLife.17756.002 In order to serve as a bridge from prebiotic chemistry to the RNA world , the nonHere we show that the presence of a leaving group at the 5′ end of a helper oligonucleotide can be a source of significant catalysis. Activated helper oligonucleotides facilitate the addition of all four RNA monomers individually and in sequence in a single reaction. Finally, when a template is immobilized by attachment to a bead, sequential addition of activated monomers and helper oligonucleotides successfully promoted the synthesis of a significant part of an active hammerhead ribozyme.Given the historical and continuing problems in demonstrating efficient nonenzymatic template directed primer extension, one might wonder whether this biologically inspired model is appropriate for replication within primordial cells. An alternative scenario that might seem more reasonable in the context of prebiotic chemistry involves template copying by the initial formation of short oligonucleotides, followed by ligation events that generate longer oligonucleotide intermediates and eventually a full length copy . To testIn order to directly test the possibility that a 2-methylimidazole leaving group on the 5′-phosphate of a downstream monomer or oligonucleotide  would inTo systematically study the rate of nonenzymatic primer extension as a function of the length of the downstream activated ‘helper’ oligonucleotide, we synthesized a series of activated oligonucleotides of different lengths . At satuWe then tested the ability of a downstream 2-methylimidazole-activated AGC trimer to catalyze template-directed RNA primer extension with all four individual 2-methylimidazole activated monomers – A, G, C and U. We also tested the 2-thiouridine monomer, which we have previously shown to be superior to uridine in nonenzymatic primer extension in terms of both increased rate and improved fidelity . In eachIn order to assess the fidelity of nonenzymatic trimer-assisted primer extension, we measured the rates of monomer addition for all monomer-template combinations, including both matches and mismatches . We calcEncouraged by the relatively fast and accurate addition of all four monomers to a primer, we then attempted to copy short RNA templates containing all four nucleotides. In order to iterate the process of trimer assisted monomer addition, after a downstream activated trimer catalyzes the addition of the first monomer to the primer, the helper trimer must dissociate to allow for the binding of the next monomer-trimer pair. To test the feasibility of this mode of primer extension, we designed a template that contained binding sites for all four monomers and synthesized the appropriate activated trimers . We used2U or s2T might offset some of the discrepancy. The final product was released from the bead by hybridization of an excess of a DNA oligonucleotide of identical sequence to the immobilized template. After DNase treatment, the hammerhead substrate, HH1, was added to the crude synthesized pool of oligonucleotides in the presence of 200 mM MgCl2 for 16 hr . 2-thiouridine-5′-phosphoro-2methylimidazolide and 2′,3′-diacetyl-nucleosides were purchased from ChemGenes . Phosphoramidite nucleotides and all other oligonucleotide synthesis reagents were purchased from either ChemGenes or Bioautomation . Tris(hydroxymethyl)aminomethane (Tris)-HCl, ThermoScript reverse transcriptase as well as reaction buffer and NTPs were purchased from Thermo Fisher Scientific . DNA and RNA primers and were purchased from Integrated DNA Technologies . All oligonucleotide sequences are listed below. All other chemicals were purchased from Sigma Aldrich Corporation .Gels were prepared using the SequaGel – UreaGel system from National Diagnostics . Gels were prepared to 20% acrylamide and scanned using a Typhoon Scanner 9410 .RNA oligonucleotides were prepared by standard phosphoramidite oligonucleotide synthesis using a MerMade 6 DNA/RNA synthesizer  or starting with 2′,3′-diacetyl nucleosides using standard manual coupling procedures . 5′-phos4 in acetone. The precipitate was pelleted by centrifugation  and washed twice with a 1:1 mixture of acetone:diethylether and once with pure diethylether. After decanting the solvent, the pellet was dried under vacuum, resuspended in deionized water and purified by high-performance liquid chromatography (HPLC) over a C18 column  with 25 mM triethylammonium bicarbonate (TEAB) pH adjusted to 7.5 in 2% (v/v) acetonitrile for mobile phase A and acetonitrile for mobile phase B over a gradient beginning at 100% A and falling to 80% A over 20 min with a flow rate of 3 mL/minute. The fraction containing the product was verified by electrospray ionization mass spectrometry (ESI/MS) in negative mode (m/z = 996), frozen in liquid nitrogen and lyophilized overnight to yield a white powder. The powder was dissolved in water and the concentration of the activated trimer was determined using a NanoDrop 2000c spectrophotometer  and calculated assuming ε260 = 34,170 M−1 cm−1 29.Mononucleotide monophosphates and oligonucleotide monophosphates were activated using a modified published protocol . As an eMonomer stocks were adjusted to pH 7 before adding into the reaction mixture.2, 200 mM sodium N-cyclohexyl-2-aminoethanesulfonic acid (CHES) pH 9, 50 mM monomer, 1 mM trimer, 10 μM primer and 11 μM template. The primer sequence was the same for all reactions (6-carboxyfluorescein (FAM)-5′-GAC UGG-3′ for kinetics, cyanine 3 (Cy3)-5′-GCG UAG ACU GAC UGG-3′ for gels). The templates used in Nonenzymatic RNA primer extension reactions exploring the effect of downstream nucleotides and oligonucleotides on 2-MeImpG addition were conducted under the following conditions: 200 mM MgCl1) 5′-AAC CCC CCA GUC -3′2) 5′-G CUC CCA GUC -3′3)5′-AA CUC CCA GUC -3′The templates in For GGG:5′-AA CCC CCA GUC -3′For GCG:5′-AA CGC CCA GUC -3′For GAG:5′-AA CUC CCA GUC -3′For AGC:5′-GCU GCU GCU GCU CCA GUC AGU CUA CGC-3′The templates in a lanes 1–4:Part 5′-G CUC CCA GUC -3′a lane 5:Part 5′-GCC UCC CAG UC -3′b:Part N CCA GUC -3′5′-GCU The templates in The template in 5′-CCC GCU ACC AGU C -3′The template in 5'- GCU C GCU C GCU C GCU C CCAGUCAGUCUACGC -3'The templates in a:Part 5′-CCC GCU UCC AGU C -3′b:Part 5′-AUC AAC CAG UC -3′The template in 5′-biotin – AAC CCC GCG CCU CAU CAG CCA GUC -3′The template in 5′ - GCG CCU CAU CAG CCA GUC -3′kobs.Reaction progress was assessed by gel electrophoresis (20% acrylamide denaturing urea gel) after 10 min. Reaction rates were calculated by quantifying primer conversion to products using a Typhoon Scanner 9410 . Band intensities were quantified using ImageQuant TL software . The negative log of the fraction of unreacted primer was plotted against time, in hours. A linear regression was performed and the slope of the fit as plotted was reported as the pseudo-first order rate 2, 200 mM Tris-HCl pH 8, 25 mM monomer, 1 mM trimer, 10 μM primer and 11 μM template. The downstream helper oligomers were added in the following concentrations: 25 mM 2-MeImpA and 1 mM activated oligonuleotide . The reaction progress was assessed by gel electrophoresis (20% acrylamide denaturing urea gel) after 10 min. Reaction rates were calculated as above.Primer extension reactions exploring the effect of different monomers and different oligomers on the rate of polymerization were conducted under the following conditions: 100 mM MgCl2, 200 mM Tris-HCl pH 8, 25 mM monomers, 500 μM 2-methylimidazole-activated AGC, CGG and GGG, 100 μM activated GCG, 10 μM primer and 11 μM template. The reaction progress was assessed by gel electrophoresis (20% acrylamide denaturing urea gel) after 18 hr.Primer extension reactions exploring the addition of multiple monomers and trimers in one reaction had the following conditions: 100 mM MgCl2, 200 mM Tris-HCl pH 8, 25 mM monomer and 2 mM trimer. The beads were washed between steps in 2 M NaCl, 1 mM EDTA and 10 mM Tris-HCl pH 7. For steps 2, 5 and 7, 50 mM monomer and 4 mM trimer were added. Each step was monitored by gel electrophoresis until it reached >75% yield. Steps varied in length from 30 min to 22 hr; the total time required was 150 hr.30 μL of Dynabeads MyOne Streptavidin T1  beads were prepared as specified by the manufacturer. Primer (Cy3 - 5′- GCG UAG ACU GAC UGG - 3′) and template (biotin - 5′- AAC CCC GCG CCU CAU CAG CCA GUC AGC UCU ACG C - 3′) were bound to the beads at 250 μM and 275 μM, respectively, in 2 M NaCl, 1 mM EDTA and 10 mM Tris-HCl pH 7. Monomer additions were conducted under the following conditions: 100 mM MgCl2, 200 mM Tris-HCl pH 8 and 250 nM Cy5 labeled HH1 RNA (Cy5 - 5′ - CGC GCC GAA ACA CCG UGU CCC AGU C - 3′) for 20 hr. The products of both the bead immobilized reactions and the hammerhead reaction were analyzed by gel electrophoresis (20% acrylamide denaturing urea gel).10% of the product of the bead-immobilized reactions was washed twice in 100 μL water containing 0.01% (v/v) Tween 20. 174 μM DNA complement was added in 0.01% (v/v) Tween 20 and the beads were incubated at 95°C for 1 min. The solution was removed from the beads and 2 units of DNaseI along with DNaseI buffer (NEB) were added. Finally, the reaction was incubated at room temperature with 200 mM MgCl In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by Timothy Nilsen, Reviewing Editor and John Kuriyan as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Gerald Joyce (Reviewer #2); Christopher Switzer (Reviewer #3).Thank you for submitting your article "Catalysis of nonenzymatic template copying by activated oligonucleotides allows synthesis of an active RNA enzyme" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Here Szostak and coworkers describe a major advance in the non-enzymatic template-directed polymerization of RNA, achieving dramatically faster reaction rates and much broader sequence generality compared to what has been achieved over the past 40 years of investigation. The authors uncover and exploit a heretofore unrecognized aspect of the templated polymerization of nucleoside 5'-phospho-2-methylimidazolides, involving catalysis by the nucleotide at the +1 position relative to the reacting nucleotide. Remarkably, the same 2-methylimidazole moiety that is the leaving group on the reacting nucleotide also has a catalytic effect at the +1 position. Furthermore, this catalytic effect can be provided by an adjacent oligonucleotide that has the same modification, thereby ensuring template occupancy of the adjacent catalyst. Employing a set of trinucleotide catalysts that cover successive reading frames, it now is possible to add sequentially all four nucleotides in good yield. Furthermore, if the trinucleotide catalysts are provided sequentially rather than as a mixture, even longer sequences can be synthesized, including 12 nucleotides that constitute a portion of the hammerhead ribozyme.All of the referees felt that this work was an important contribution to nucleic acid chemistry and origins of life research.Despite their enthusiasm all of the reviewers felt that the paper could be improved and each has spelled out a number of points that should be addressed via revision. In particular, all thought the statement in the manuscript that reacting nucleotides are the same for reactions 1 and 3 in Reviewer #1:A long-standing question in origins research, and in the efforts to test/support the RNA World hypothesis specifically, is how RNA monomers  could have polymerized into polymeric RNA. This was the focus of the works of Orgel, Ferris, and several others and still remains unsatisfactorily solved. The current paper proposes a possible mechanism that partially addresses some of the chemical problems inherent to abiotic polymerization of nucleotides, namely that certain nucleotides  are recalcitrant towards non-enzymatic polymerization, and that in general such polymerization is slow, to the point of being ineffectual in the face of the back reaction (hydrolysis).Here, the authors provide data that nucleotide activation can serve not only the canonical activation role that provides the free energy for polymerization, but also a catalytic role in that "downstream" activating groups can actually boost the rates up "upstream" ligation (polyermization) reactions. Specifically, the authors show that helper activated trinucleotide oligomers are particularly effective in enhancing rates of polymerization. In the extreme, they show that an RNA of sufficient length to be a catalyst itself, i.e., a ribozyme, can be made using this methodology, albeit with some help.not the case: the oligomer in reaction #3 has an A on its 5´ end. This is particularly problematic because the authors make a big point about the lowered ability of A nucleotides to participate in ligation  reactions compared to G. At first I thought it might be just a typo, but the same 5´-A appears in all of the subsequent helper trinucleotide oligomers. Unless I am reading this wrong, it appears as though the rationale for the rest of the project was thus based on a flawed premise.When I started reading the manuscript I immediately ran into a conceptual flaw that temporarily tempered my enthusiasm for the work. In the first paragraph of the Results, the authors use an (apparent) observation that, when activated with a specific "high-energy" leaving group (2-methylimidizole), the efficiency of mononucleotide polymerization is greater than that of oligonucleotide ligation. This would be somewhat unexpected because of several reasons including a perceived enhanced stability of the oligo on the template strand during the ligation reaction, compared to the stability of a single nucleotide on the template strand. But to show this, the authors compare the reactions #1 and #3 depicted in Nevertheless, the balance of the manuscript did serve to convince me of the main result: that the activating group, and especially when placed on the 5´ ends of helper trinucleotides, can greatly facilitate monomer polymerization. This is indeed a significant result that should ultimately be meritorious of publication. I am always troubled by the artificiality of such imidazole-based activating groups, and thus I would ask the authors to comment on this more explicitly, and perhaps try other such activating groups. Would this work with a triphosphate or even with a 2´-3´-cyclic phosphate, the later has a clear prebiotic route to its synthesis as shown by Sutherland?Obviously the flaw mentioned above about the G vs. A should also be addressed; this could be done for example by reformulating the rationale for the study .On another point, the mechanism suggested by these data is reminiscent of "substrate assisted catalysis", which at one point was posited to be involved in the mechanism of RNA-directed peptide-bond formation in the PTC of the ribosome. This could be discussed.The fact that a trinucleotide emerges as the best catalyst  never existed. With substrate-assisted non-enzymatic template-directed RNA replication, one could envisage moving from a abiotic RNA monomer world to a protein world in a manner that obviates the need for an RNA replicase ribozyme.Reviewer #2:Prywes et al. describe a major advance in the non-enzymatic template-directed polymerization of RNA, achieving dramatically faster reaction rates and much broader sequence generality compared to what has been achieved over the past 40 years of investigation. The authors uncover and exploit a heretofore unrecognized aspect of the templated polymerization of nucleoside 5'-phospho-2-methylimidazolides, involving catalysis by the nucleotide at the +1 position relative to the reacting nucleotide. Remarkably, the same 2-methylimidazole moiety that is the leaving group on the reacting nucleotide also has a catalytic effect at the +1 position. Furthermore, this catalytic effect can be provided by an adjacent oligonucleotide that has the same modification, thereby ensuring template occupancy of the adjacent catalyst. Employing a set of trinucleotide catalysts that cover successive reading frames, it now is possible to add sequentially all four nucleotides in good yield. Furthermore, if the trinucleotide catalysts are provided sequentially rather than as a mixture, even longer sequences can be synthesized, including 12 nucleotides that constitute a portion of the hammerhead ribozyme.eLife, subject to the following modifications.This manuscript is an important contribution to nucleic acid chemistry and origins-of-life research. It will have appeal to a broad audience of chemists and biologist who are interested in the origin of genetic replication systems. The manuscript is highly suitable for publication in 1) In the first paragraph of the Results. A reference should be added to the 1999 paper by James and Ellington (Origins Life Evol. Biosph. 29:375-390), which first described a prebiotic scenario for template copying based on ligation of short oligonucleotides.2) In the first paragraph of the Results. The description of the comparative addition of either a mono- or oligonucleotide to a template-bound primer is confusing because it states that the reacting nucleotides are the same, but the referenced reactions in 3) At the end of the Results. It is an exaggeration to say that "an active ribozyme was synthesized nonenzymatically". Of the 37 nucleotides that constitute the catalytic complex, only 12 were synthesized non-enzymatically, with 6 provided by the primer and 19 contained within the substrate portion of the complex. Although Wochner et al.  used similar artifice to "synthesize" a hammerhead ribozyme using a polymerase ribozyme, the present manuscript should strive for a higher standard. The title of the manuscript is similarly misleading and should be changed from "[…]Allows Synthesis of an Active RNA Enzyme" to something like "[…]Allows Synthesis of a broad range of RNA Sequences".4) In the second paragraph of the Discussion. Further explanation is needed regarding what is meant by "the lack of a leaving group one base downstream of the site of primer extension". The meaning is clear to a specialist, but a non-specialist needs to be reminded that the catalytic 2-methylimidazole is not present at the second nucleotide position of the helper trinucleotide (and in any case would not be a "leaving group") because this is an unmodified phosphodiester within the 5´-activated trinucleotide.5) In the second paragraph of the Discussion. The authors are being too coy when referring to the possibility of an imidazolium intermediate that is the basis for the catalytic effect. If they have evidence for such an intermediate in another study, then it should be referred to as "unpublished data" or "manuscript in press", as appropriate.6) In the third paragraph of the Discussion. It is an exaggeration to say that the non-enzymatic polymerization reaction reported here compares favorably in terms of efficiency with the tC19Z polymerase ribozyme reported by Wochner et al. . While the rates are comparable, the efficiencies are not even close, especially in batch reactions where Prywes et al. generate no more than 7mers and Wochner et al. generate products  of more than 90 nucleotides.7) 8) Reviewer #3:The manuscript reports nonenzymatic template directed copying reactions of activated monomers promoted by activated oligonucleotides. The system described enabled the template directed synthesis of an active hammerhead ribozyme. This work is the first to report the nonenzymatic synthesis of a catalytic RNA using activated monomers. Prebiotic chemists have sought the means to simply and robustly copy all four RNA monomers for decades, with mostly limited success, for A and U in particular. Moreover, it has become increasingly apparent that the limitations imposed by A and U are nuanced, extending beyond simply diminished binding affinities. In keeping with the subtle nature of these systems, the authors have taken a known, but poorly understood, feature of 2-Me-imidazolide activated nucleoside phosphate monomers noted by Orgel, and applied it in a heretofore unanticipated manner. The authors surprising initially discovered that the rate of 2-MeImpN oligomerization exceeded the rate of activated trinucleotide ligation by nearly 100-fold, despite the greater template binding affinity of the trimer. On further investigation it became evident that consecutive 2-MeImp groups in subsequent monomers led to the enhanced rate, and, ultimately, the unusual discovery that an 2-MeImp activated trinucleotide enhanced the rate of monomer addition due to the neighboring 2-MeImp group. Thus, while Orgel had earlier shown that at least two consecutive 2-MeImpN monomers were required for efficient template directed synthesis, it was not possible to anticipate the effectiveness of the presently reported system for a variety of reasons, not least because it involves an activated trinucleotide rather than activated monomers, and historically there appeared little hope for efficient synthesis with A and U, consecutive 2-MeImp activating groups notwithstanding. The prospects of simplifying the reported system even further in future work are very exciting for the field.Introduction, first and second paragraphs. It is awkward to offer template immobilization as a shortcoming, but then promote its use shortly afterwards, even though template immobilization in the first instance is one of several shortcomings.Results, first paragraph. This sentence states the reacting nucleotides are the same in both reactions 1 and 3 in Results, fifth paragraph. It would be extremely interesting to also know what effect the 2-thio U or rT has on the rate of the G:(s)U/rT mismatch reaction.Results, last paragraph. This should reference Discussion, second paragraph. In Wu and Orgel, 1992, Orgel notes in the Discussion that simple steric effects are unlikely, suggesting instead that the neighboring 2-MeIm might act as an acid/base catalyst. I believe this section should be revised to reflect this fact. Nevertheless, the suggestion by the authors of covalent bond formation is new and interesting. Despite their enthusiasm all of the reviewers felt that the paper could be improved and each has spelled out a number of points that should be addressed via revision. In particular, all thought the statement in the manuscript that reacting nucleotides are the same for reactions 1 and 3 in We would like to thank the Editor and all of the reviewers for alerting us to this critical oversight, which resulted from replacing an earlier experiment with more recent data. We have now included a set of experiments that provide a direct comparison between the addition of multiple G monomers and an oligonucleotide that begins with G. Reviewer #1:When I started reading the manuscript I immediately ran into a conceptual flaw that temporarily tempered my enthusiasm for the work. In the first paragraph of the Results, the authors use an (apparent) observation that, when activated with a specific "high-energy" leaving group (2-methylimidizole), the efficiency of mononucleotide polymerization is greater than that of oligonucleotide ligation. This would be somewhat unexpected because of several reasons including a perceived enhanced stability of the oligo on the template strand during the ligation reaction, compared to the stability of a single nucleotide on the template strand. But to show this, the authors compare the reactions #1 and #3 depicted in Nevertheless, the balance of the manuscript did serve to convince me of the main result: that the activating group, and especially when placed on the 5´ ends of helper trinucleotides, can greatly facilitate monomer polymerization. This is indeed a significant result that should ultimately be meritorious of publication. I am always troubled by the artificiality of such imidazole-based activating groups, and thus I would ask the authors to comment on this more explicitly, and perhaps try other such activating groups. Would this work with a triphosphate or even with a 2´-3´-cyclic phosphate, the later has a clear prebiotic route to its synthesis as shown by Sutherland?We use the 2-methylimidazole activating group because it is the best model system available for the study of nonenzymatic template copying, irrespective of its its prebiotic relevance. We have added a sentence to this effect to the manuscript: “Nucleotides activated with 2-methylimidzole on the 5′-phosphate have been used extensively to model nonenzymatic template copying , irrespective of their prebiotic plausibility, and were used in all experiments reported here.”We and others do think about possible prebiotic routes to this and other activating groups, and this is the subject of ongoing research in several labs. As far as we are aware, no nonenzymatic polymerization of nucleoside triphosphates or 2´-3´-cyclic phosphates has ever been reported, although the corresponding oligonucleotide ligation reactions have been studied.Obviously the flaw mentioned above about the G vs. A should also be addressed; this could be done for example by reformulating the rationale for the study .See response above to Editor/Reviewer #1.On another point, the mechanism suggested by these data is reminiscent of "substrate assisted catalysis", which at one point was posited to be involved in the mechanism of RNA-directed peptide-bond formation in the PTC of the ribosome. This could be discussed.While this is an interesting suggestion, we think that our findings are not really an example of substrate assisted catalysis, because the substrate (the activated monomer) is distinct from the catalyst (the activated downstream nucleotide or oligonucleotide).The fact that a trinucleotide emerges as the best catalyst : “approximately constant”I wonder what the effect of hot/cold or wet/dry cycles would have on polymerization as assisted in the proposed scheme.We have attempted to optimize the temperature of the reaction and have found that within a window of approximately 10-40 degrees Celsius there is no noticeable effect on the rate while outside of that window the reaction slows down precipitously. Thermocycling was similarly ineffective in improving the reaction product distribution. We did not test the effect of drying and rewetting our samples. Such experiments may be fruitful but are unfortunately outside of the scope of this study.My last major point is that the authors, in showing these data and proposing this chemistry, miss an opportunity to note that perhaps the elusive RNA-dependent RNA polymerase ribozyme (RNA replicase ribozyme) never existed. With substrate-assisted non-enzymatic template-directed RNA replication, one could envisage moving from a abiotic RNA monomer world to a protein world in a manner that obviates the need for an RNA replicase ribozyme.We have edited the text to reflect this possibility by adding the following statement: “In fact, if the rates and fidelities of nonenzymatic RNA polymerization were sufficiently high, the need for a ribozyme polymerase in the RNA world might be circumvented: RNA could be copied by nonenzymatic chemistry alone until the advent of protein polymerases.”Reviewer #2:This manuscript is an important contribution to nucleic acid chemistry and origins-of-life research. It will have appeal to a broad audience of chemists and biologist who are interested in the origin of genetic replication systems. The manuscript is highly suitable for publication in eLife, subject to the following modifications.1) In the first paragraph of the Results. A reference should be added to the 1999 paper by James and Ellington (Origins Life Evol. Biosph. 29:375-390), which first described a prebiotic scenario for template copying based on ligation of short oligonucleotides.We have added this reference.2) In the first paragraph of the Results. The description of the comparative addition of either a mono- or oligonucleotide to a template-bound primer is confusing because it states that the reacting nucleotides are the same, but the referenced reactions in See response above to Editor/Reviewer #1.3) At the end of the Results. It is an exaggeration to say that "an active ribozyme was synthesized nonenzymatically". Of the 37 nucleotides that constitute the catalytic complex, only 12 were synthesized non-enzymatically, with 6 provided by the primer and 19 contained within the substrate portion of the complex. Although Wochner et al.  used similar artifice to "synthesize" a hammerhead ribozyme using a polymerase ribozyme, the present manuscript should strive for a higher standard. The title of the manuscript is similarly misleading and should be changed from "[…]Allows Synthesis of an Active RNA Enzyme" to something like "[…]Allows Synthesis of a broad range of RNA Sequences".a significant portion of an active ribozyme was synthesized nonenzymatically.”We thank the reviewer for holding us to a higher standard and have edited the text to reflect this as follows: “[…]thus demonstrating that We have changed the title to: Nonenzymatic copying of RNA templates containing all four letters is catalyzed by activated oligonucleotides4) In the second paragraph of the Discussion. Further explanation is needed regarding what is meant by "the lack of a leaving group one base downstream of the site of primer extension". The meaning is clear to a specialist, but a non-specialist needs to be reminded that the catalytic 2-methylimidazole is not present at the second nucleotide position of the helper trinucleotide (and in any case would not be a "leaving group") because this is an unmodified phosphodiester within the 5´-activated trinucleotide.We have edited the text to improve clarity by adding the following: “[…]in this case the downstream position corresponds to the second monomer in the oligonucleotide which necessarily has no leaving group as it is linked to the upstream monomer by a phosphodiester linkage.”5) In the second paragraph of the Discussion. The authors are being too coy when referring to the possibility of an imidazolium intermediate that is the basis for the catalytic effect. If they have evidence for such an intermediate in another study, then it should be referred to as "unpublished data" or "manuscript in press", as appropriate.We have added  a reference to recent work describing such a covalent adduct, and a reference in the text to our ongoing work, “T. Walton and J.W. Szostak, unpublished data.”6) In the third paragraph of the Discussion. It is an exaggeration to say that the non-enzymatic polymerization reaction reported here compares favorably in terms of efficiency with the tC19Z polymerase ribozyme reported by Wochner et al. . While the rates are comparable, the efficiencies are not even close, especially in batch reactions where Prywes et al. generate no more than 7mers and Wochner et al. generate products  of more than 90 nucleotides.We have edited the text  to emphasize that our rates and efficiencies are close to those obtained by Wochner et al. on arbitrary RNA templates, as opposed to the specific sequence on which the Wochner polymerase was trained.7) We have added the actual numbers into 8) We thank the reviewer for the helpful comment and have edited Reviewer #3:Introduction, first and second paragraphs. It is awkward to offer template immobilization as a shortcoming, but then promote its use shortly afterwards, even though template immobilization in the first instance is one of several shortcomings.We have deleted the sentence on template immobilization.Results, first paragraph. This sentence states the reacting nucleotides are the same in both reactions 1 and 3 in See response above to Editor/Reviewer #1.Results, fifth paragraph. It would be extremely interesting to also know what effect the 2-thio U or rT has on the rate of the G:(s)U/rT mismatch reaction.We are currently pursuing additional experiments related to the fidelity of nonenzymatic primer extension, using both MS and deep sequencing methods to analyze reactions in which the different monomers can compete with each other for binding to the template. These studies, which will be published separately, will address the interesting question of how the 2-thio pyrimidines will affect fidelity.Results, last paragraph. This should reference We have edited the text to correct this mistake.Discussion, second paragraph. In Wu and Orgel, 1992, Orgel notes in the Discussion that simple steric effects are unlikely, suggesting instead that the neighboring 2-MeIm might act as an acid/base catalyst. I believe this section should be revised to reflect this fact. Nevertheless, the suggestion by the authors of covalent bond formation is new and interesting.We have edited the text in accordance with this suggestion as follows: “[…]though the authors ultimately concluded that such subtle effects are not likely to adequately explain the strength of the interaction. Wu et al. also suggested that the catalytic effect could be due to acid-base catalysis.”


Long noncoding RNAs (lncRNAs) form an abundant class of transcripts, but the function of the majority of them remains elusive. While it has been shown that some lncRNAs are bound by ribosomes, it has also been convincingly demonstrated that these transcripts do not code for proteins. To obtain a comprehensive understanding of the extent to which lncRNAs bind ribosomes, we performed systematic RNA sequencing on ribosome-associated RNA pools obtained through ribosomal fractionation and compared the RNA content with nuclear and (non-ribosome bound) cytosolic RNA pools.H19 and TUG1.The RNA composition of the subcellular fractions differs significantly from each other, but lncRNAs are found in all locations. A subset of specific lncRNAs is enriched in the nucleus but surprisingly the majority is enriched in the cytosol and in ribosomal fractions. The ribosomal enriched lncRNAs include Most studies on lncRNAs have focused on the regulatory function of these transcripts in the nucleus. We demonstrate that only a minority of all lncRNAs are nuclear enriched. Our findings suggest that many lncRNAs may have a function in cytoplasmic processes, and in particular in ribosome complexes. XIST.β-catenin [Human colon cancer cells carrying a doxycycline-inducible short hairpin RNA against B-catenin (LS-174 T-pTER--catenin ) were cuβ-catenin cells were lysed in polyribosome lysis buffer ) with help of a Dounce tissue grinder . Lysed samples were centrifuged at 1200 g for 10 min to remove debris and loaded onto the sucrose gradients. The gradients were ultra-centrifuged for 2 h at 120,565 g in an SW41 Ti rotor . The gradients were displaced into a UA6 absorbance reader  using a syringe pump  containing 60% sucrose. Absorbance was recorded at an optical density of 254 nm. Fractions were collected using a Foxy Jr Fraction Collector (Teledyne ISCO). Corresponding fractions from each of the three replicates were merged prior to RNA isolation.All steps of the mono- and polyribosome profiling protocol were performed at 4°C or on ice. Gradients of 17% to 50% sucrose (11 mL) in gradient buffer  were poured the evening before use. Three replicates of 15 cm dishes with LS-174 T-pTER-β-catenin cells were obtained by centrifugation at 1200 g after whole-cell lysis prior to ribosome fractionation (see previous section). To exclude the presence of rough endoplasmic reticulum and thus validate the purity of the isolated nuclei, nuclear staining and imaging were performed . RNA derived from triplicate mono- and polyribosome fractionation experiments was purified using TRIzol® LS reagent . Isolated RNA from the pooled triplicate fractions corresponded to the (A1 + 2) non-ribosome bound RNA, (B1) 40S subunit, (B2) 60S subunit, (C) 80S ribosome, (D) 2 ribosomes, (E) 3 ribosomes, (F) 4 ribosomes, (G) 5 ribosomes and (H) 6 ribosomes and (I) more than 6 ribosomes  primers and the high capacity cDNA reverse transcription kit . Three primer sets were designed per lncRNA. Quantitative PCR reactions were performed in 20 μl reactions using 2 ng of cDNA and iQ™ SYBR® Green Supermix  on a MyIQ2 Real-time PCR detection system (Bio-Rad).bp: Base pairs; CPM: Counts per million; lncRNA: Long noncoding RNA; NMD: Nonsense mediated decay; ORF: Open reading frame; PCR: Polymerase chain reaction; RNA-seq: RNA-sequencing; rRNA: Ribosomal RNA; RT: Reverse transcription; sncRNA: Small noncoding RNA; snoRNA: Small nucleolar RNA; snRNA: Small nuclear RNA.The authors declare that they have no competing interests.SvH, MvI, EC and MS wrote the manuscript. MvI, MS, SB and JJ performed RNA-seq data analyses. SvH performed cell culture, nuclei isolation and RNA-seq experiments. SvH and PBE performed polysomal fractionation experiments. WH and EdB performed next-generation sequencing. SvH, EC, MS and AWM designed the experiments. All authors contributed to scientific discussions, and read and approved the final version of the manuscript.Microscopy images of purified nuclei.Click here for fileTable showing the raw read counts of all sequenced fractions per gene.Click here for fileScatter plot illustrating the contribution of sncRNAs, protein-coding transcripts and lncRNAs to the observed correlation between the nuclear and >6 ribosome sample .Click here for fileBar plot depicting the contents of each sequenced sample in reads per kilobase per million instead of CPMs .Click here for fileTable showing the normalized read counts for each cluster in Figure 4A.Click here for fileFour heatmaps illustrating the effects on k-means clustering when 9 to 12 clusters are required.Click here for fileEffects on clustering and transcript localization when all sncRNAs are removed from the data.Click here for fileDistribution of lncRNAs over the polyribosomal fractions in relation to the number of ORFs detected per transcript.Click here for fileFigure showing the enrichment of lncRNAs in the nucleus or cytosol by qPCR analysis.Click here for fileTable with the results of the antisense lncRNA versus senseprotein-codingtranscript co-localization analysis.Click here for fileGraph showing the bimodal distribution of sequencing reads over all sequencing data.Click here for file


A general feature of Argonaute-dependent small RNAs is their base-paired precursor structures, and precursor duplex structures are often required for confident annotation of miRNA genes. However, this rule has been broken by discoveries of functional small RNA species whose precursors lack a predictable double-stranded (ds-) RNA structure, arguing that duplex structures are not prerequisite for small RNA loading to Argonautes. The biological significance of single-stranded (ss-) RNA loading has been recognized particularly in systems where active small RNA amplification mechanisms are involved, because even a small amount of RNA molecules can trigger the production of abundant RNA species leading to profound biological effects. However, even in the absence of small RNA amplification mechanisms, recent studies have demonstrated that potent gene silencing can be achieved using chemically modified synthetic ssRNAs that are resistant to RNases in mice. Therefore, such ssRNA-mediated gene regulation may have broader roles than previously recognized, and the findings have opened the door for further research to optimize the design of ss-siRNAs toward future pharmaceutical and biomedical applications of gene silencing technologies. In this review, we will summarize studies about endogenous ssRNA species that are bound by Argonaute proteins and how ssRNA precursors are recognized by various small RNA pathways. Caenorhabditis elegans. Therefore, it appeared that double-stranded structures were prerequisite to the initiation of this mysterious silencing mechanism. Subsequent studies on molecular mechanisms of RNAs clearly showed that silencing is mediated by small RNA species processed from dsRNA trigger molecules (Ever since the Nobel prize-winning discovery of RNA interference (RNAi), gene regulation mediated by double-stranded RNAs (dsRNAs) has been one of the most active areas of research in molecular biology . They deolecules . Furtherolecules . In nearolecules , endogenSmall RNA pathways generally involve two key components, RNase III enzymes and Argonaute proteins. RNase III enzymes are dsRNA-specific RNases, and Argonaute proteins are effector proteins that bind to small RNAs and mediate target RNA regulation . Small RBecause RNase III enzymes are highly selective for particular RNA folding or duplex structures, they can act as gatekeepers of small RNA pathways by distinguishing guide RNA precursors and other cellular transcripts . On the Giardia and Kluyveromyces Dicers, respectively; Figure 1).Small RNA duplexes are usually produced from longer dsRNA precursors as products of Dicer-class RNase III enzymes . These DFigure 1).For small RNA duplex loading, Argonaute proteins are believed to first undergo a conformational change to open the small RNA duplex binding pocket . This coin vitro studies using cell lysate systems and by transfection of ss-siRNAs to cultured cells  identified both DNA and RNA molecules that are associated with the Argonaute protein, RsAgo . Similar to many classes of eukaryotic Argonaute-dependent small RNAs, RsAgo-dependent small RNAs showed a strong enrichment for uridine at the 5′ nucleotide. In addition, mild enrichment for pyrimidine was also observed at the second nucleotide counting from the 5′ end. The majority of small RNAs were derived from the sense strand of protein coding or non-coding RNAs, and the levels of small RNAs roughly correlated with the level of their host, long RNA species. However, detailed analysis of individual genes revealed mild depletion of non-coding RNAs and a strong enrichment of RNAs encoded by foreign DNAs such as plasmids, phages and transposons. Interestingly, the authors noted that these foreign DNAs exist as extrachromosomal DNAs at least at certain stages of their lifecycles.A recent study analyzing Argonaute-associated DNA/RNA molecules in n, RsAgo . FifteenFigure 2). It is not clear whether both small RNA and small DNA molecules are loaded in RsAgo as guide molecules or they bind to RsAgo as small RNA/DNA heteroduplexes. However, small RNAs were more abundant than small DNAs by ~twofold, which indicated that at least a fraction of RsAgo proteins may form complexes with sRNAs alone.Similarly, short DNAs associated with RsAgo showed enrichment for foreign DNA sequences . A compuE. coli. Furthermore, similar preferential loading of plasmid-derived small RNAs was also observed in a previous study with a bacterially expressed yeast Argonaute protein . The amplification-independent trigger RNAs were named priRNAs . In agreement with this model, a low level of small RNAs could be detected in mutants of dcr1 or rdp1, in which siRNA amplification is compromised. Small RNA cloning and computational analysis of priRNA showed that priRNAs were generated from a wide range of abundant protein coding/non-coding RNAs in addition to the known siRNA producing loci. However, the majority of reads mapping to protein coding mRNAs were in the sense orientation. priRNAs mapping to mRNAs were strongly enriched in the 3′ downstream regions of annotated protein coding sequences, or the immediate downstream of transcriptional termination sites.However, the mechanism that initiates the nucleation of RNAi at specific loci is not understood. In a recently proposed model , a Dcr1-dg and dh loci, where pericentromeric siRNAs are efficiently generated . Consistent with the active roles of priRNAs in heterochromatin formation, ago1Δ cells generally showed greater defects in heterochromatin formation at centromeric repeats compared to dcr1Δ cells.Conversely, a large fraction of antisense priRNAs were mapped to the bidirectionally transcribed enerated . Even thtri1Δ cells exhibited defects in priRNA-mediated heterochromatin formation. The remaining siRNAs and priRNAs were slightly longer in tri1Δ cells (22–25nt) than in wild-type cells (21–23 nt). In in vitro binding assays, Ago1 bound more tightly to 22 nt RNA than longer species, and it was not able to efficiently cleave targets when cleavage was guided by small RNAs ≥ 24 nt in length. Therefore, trimming of small RNAs by Tri1 is essential for their functions. It should also be noted that distinct classes of heterochromatin require distinct set of factors for the siRNA production and heterochromatin formation  was identified as an essential priRNA processing factor that trims Ago1-loaded small RNAs . Tri1 isormation .Figure 3B). Therefore, in mutants of exosome components, the priRNA pathway is more active due to the lack of competition . piRNAs are predominantly derived from the telomeric and pericentromeric regions that house fragmented TE copies . In the primary piRNA pathway, piRNA precursor ssRNAs are loaded to PIWI proteins to generate “primary piRNAs.” An amplification mechanism called the ping-pong amplification uses the primary piRNAs to direct cleavage of complementary TE sense transcripts . In the fly female gonad, germline cells have both the primary processing and ping-pong amplification pathways, while piRNAs are exclusively produced by the primary processing pathway in gonadal somatic cells . In fact, the silkworm PIWI protein that binds primary piRNAs exhibited 5′U preference . This enrichment of piRNAs in the 3′ UTR looks similar to the 3′ enrichment of genic priRNAs in S. pombe . 21U-RNAs are bound by the nematode PIWI ortholog PRG-1, which had been known to be essential for normal fertility .The clusters on chromosome IV are not the only source of 21U-RNAs. Other pol II transcripts starting at the YRNT motif also produce 21U-RNAs at lower efficiencies, even when the locus is not associated with the CTGTTTCA upstream motif . SequencFigure 4). The strategy also resembles the yeast siRNA pathway , where priRNAs processed from longer ssRNAs trigger siRNA amplification  to establish stable silencing of non-self sequences . Furtherfication . The appfication .Immunoprecipitation) analysis would be essential. Nonetheless, accumulating data indicate that miRNA-class small RNAs can be made from precursors without obvious duplex structures.MicroRNAs are a well-studied class of small regulatory RNAs in higher animals . Many mimir-451 is the only verified member of Dicer-independent, Drosha-dependent miRNAs. Although mir-451 precursor forms a hairpin structure, we will cover this miRNA in this review because the hairpin is not loaded as a duplex and, in theory, miR-451-like small RNAs could be generated in an RNase III-independent manner (see below). mir-451 was originally found as a conserved hairpin located in a vicinity of a known miRNA mir-144 and was subsequently shown to associate with Ago2 . However, the resulting hairpin with a 17 bp stem region is too short to be processed by Dicer because processing by Dicer requires > ~22 bp stem regions . Because the mir-451 hairpin has a highly paired stem region, Ago2 cleaves the 42 nt hairpin at the position complementary to 10th–11th nucleotides from the 5′ end of the hairpin, leaving a 30 nt half-hairpin (ac-pre-miRNA: Ago2-cleaved precursor miRNA).The  regions . Insteadmir-451-like hairpins, there appears to be no strict sequence restriction . Two recent studies identified miRNA loop species in Argonaute complexes, and demonstrated regulatory activity of overexpressed miRNA loops using luciferase sensor assays  were differentially sorted to dAGO1 and dAGO2. Differential sorting of miRNA loops was recapitulated within in vitro loading assays even when the loops were provided as pre-processed synthetic ssRNA oligonucleotides. These results raised a possibility that Argonaute proteins have previously unknown preferences for particular ssRNA species.Consistent with the 5′ U preference of Argonautes, loaded miRNA loop species often have a U at the 5′ end . HoweverThese observations challenge a general assumption that binding between guide RNAs and Argonaute proteins is sequence non-specific except for the 5′ nucleotide preference . HoweverThe ssRNA features that determine Argonaute loading efficiency will be a topic of future research. It also remains to be studied whether and the extent to which loaded loops influence endogenous gene expression. Some of the mammalian Argonaute-loaded loop species have evolutionarily conserved sequences , therefotRNAs are known to be versatile by playing various roles in gene regulation besides their main function in the translational machinery . In thisFigure 5C; tRNA genes are transcribed by RNA polymerase III (RNA Pol III) whose transcription is terminated by a series of Us . While at least some 3′ CCA tRFs are processed by a Dicer-dependent manner  RNAs . While TIn summary, a variety of endogenous ssRNAs are selectively loaded to miRNA-class Argonautes in animals. The mechanisms of precursor selection and the biological roles for such ssRNA-derived small RNAs will be an interesting topic of research.To maintain the integrity of gene regulatory networks, Argonaute proteins should not randomly sample all cellular transcripts to generate regulatory RNAs. The mode in which guide RNAs are selected in a majority of eukaryotic Argonaute pathways is through usage of dsRNA molecules as guide RNA precursors . HoweverS. pombe Ago1; 3′ trimming of loaded sRNA precursors is commonly seen in ssRNA loading pathways. 3′ trimming is essential for some Argonaute proteins . In Arabidopsis, mutations in 5′→3′ exoribonucleases or a nucleotidase/phosphatase result in the accumulation of miRNA loops. It has not been tested whether the accumulated loops are loaded to Argonautes, but the results suggested that there are active mechanisms removing miRNA loops after processing at least in plants . However, care has to be taken as Argonaute proteins have many direct contacts with RNA molecules including hydrogen bonds with 2′-OH groups . The introduction of a PS-linkage after the first nucleotide and 7 PS-linkages in the next 12 nt followed by uniform PS-modifications in the 3′ region further enhanced the stability of ssRNAs without impairing target cleavage activity . On the other hand, ssRNAs with uniform PS modifications in the 5′ half could not induce silencing, consistent with the tight and specific interaction between the 2nd and 10th nucleotides of the guide strand and the RNA binding groove of Argonaute -vinylphosphonate (5′VP), which is more stable but has chemically similar properties to the natural phosphate . The study demonstrated that efficient knockdown could be achieved in vivo and efficient gene silencing could be observed for at least 3 days after a single injection of ssRNAs chemically modified by this formulation , were tested for the ability to selectively silence the expanded allele . The expThese studies demonstrated the potential of chemically modified ss-siRNAs for animal knockdown experiments and opened a possibility to use such modified RNA molecules for drug development. By combining the power of advanced nucleic acid chemistry and structural information of Argonaute complexes, it would probably be possible to further improve ss-siRNA design in more directed ways. Furthermore, it will be interesting to see whether there are any natural chemical RNA modifications that promote or inhibit Argonaute loading. Although some of the modifications used for ssRNA-mediated RNAi have not been seen in natural RNA molecules, it has been recently recognized that cellular RNAs are often subjected to various chemical modifications . Future As described above, ssRNA loading pathways were generally revealed as atypical activity of Argonaute proteins in previous studies in eukaryotes. However, the importance of ssRNA loading pathway in unicellular organisms and the common features of ssRNA loading pathways suggest that the ability of eukaryotic Argonautes to incorporate ssRNAs as guide molecule is a universal activity that was inherited from the primordial ancestral Argonaute protein. Because previous studies were focused on roles for RNase III products in Argonaute-mediated gene regulatory pathways, biological significance of ssRNA products may have been overlooked. Therefore, it remains to be seen in future studies how many important ssRNA-derived small RNAs exist in higher organisms.Furthermore, the finding that particular ssRNA species can be selectively loaded to individual Argonautes raised new questions. How do Argonautes select small RNAs? Do they have sequence specificity, and if so, does the sequence specificity of Argonautes affects stability of guide RNA-Argonaute complexes or efficiency of loading even when the guide RNAs are derived from duplexes? Further molecular and structural biology studies will be needed to answer these questions.Sequence preference of distinct human Argonaute proteins  is partiThe 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.


Viral evolution remains to be a main obstacle in the effectiveness of antiviral treatments. The ability to predict this evolution will help in the early detection of drug-resistant strains and will potentially facilitate the design of more efficient antiviral treatments. Various tools has been utilized in genome studies to achieve this goal. One of these tools is machine learning, which facilitates the study of structure-activity relationships, secondary and tertiary structure evolution prediction, and sequence error correction. This work proposes a novel machine learning technique for the prediction of the possible point mutations that appear on alignments of primary RNA sequence structure. It predicts the genotype of each nucleotide in the RNA sequence, and proves that a nucleotide in an RNA sequence changes based on the other nucleotides in the sequence. Neural networks technique is utilized in order to predict new strains, then a rough set theory based algorithm is introduced to extract these point mutation patterns. This algorithm is applied on a number of aligned RNA isolates time-series species of the Newcastle virus. Two different data sets from two sources are used in the validation of these techniques. The results show that the accuracy of this technique in predicting the nucleotides in the new generation is as high as 75 %. The mutation rules are visualized for the analysis of the correlation between different nucleotides in the same RNA sequence. The deoxyribonucleic acid (DNA) strands are composed of units of nucleotides. Each nucleotide is composed of a nitrogen-containing nucleobase, which is either guanine (G), adenine (A), thymine (T), or cytosine (C). Most DNA molecules consist of two strands coiled around each other forming a double helix. These DNA strands are used as a template to create the ribonucleic acid (RNA) in a process known as transcription. However, unlike DNA, RNA is often found as a single-strand. One type of RNA is the messenger RNA (mRNA) which carries information from the ribosome, which are where the protein is synthesized. The sequence of mRNA is what specifies the sequence of amino acids the formed protein. DNA and RNA are also the main component of viruses. Some of the viruses are DNA-based, while others are RNA-based such as Newcastle, HIV, and flu . RNA virOne of the important focuses in the field of human disease genetics is the prediction of genetic mutation . Having The prediction of the mutated RNA gives a clear understanding of the mutation process, the future activity of the RNA, and the help direct the development of the drugs that should be designed for it , 16. In This paper presents a proof of concept by applying this technique on a set of successive generations of the Newcastle Disease Virus (NDV) from two different countries, Korea and China , 18. In Predicting techniques have been utilized in the field of genetics for many years, and have been geared towards different directions. One of these directions is the detection of the resistance of the virus to drugs after its mutation , in whicAnother research direction is the prediction of the secondary structure of the RNA/DNA of the organism in the generation post-mutation. The ribonucleic acid (RNA) molecule consists of a sequence of ribo-nucleotides that determines the amino acids’ sequence in the protein. The primary structure of the RNA molecule is the linear form of the nucleotides’ sequence. The nucleotides can be paired based on specific rules that is: adenine (A) pairs with uracil (U) and cytosine (C) with guanine (G). Base pairs can occur within single-stranded nucleic acids. The RNA sequence is folded into secondary structure in which a pair of basis is bonded together. This structure contains a set of canonical base pairs, whose variation is considered as a form of mutation that can be predicted. Several researches have been focused on automating the RNA sequence folding  and predi in the genome data, the number of reads ai that match the reference genome and the number of reads bi that do not match the reference genome are counted. The total number of reads, depth, is given by Ni=ai + bi. A naïve approach to detect the SNV locations is to find the location i ∈  whose fraction fi=ai / Ni is less than a certain threshold  to . The reason being is that the distance between each nucleotide is the same, while the distance between [0–3] is not the same as that between [0–1]. The effect of this can be demonstrated by the following example: when applying neural networks to the numerically transformed sequence, the results show unsuccessful results. This is because the neural networks technique changes the values of the output based on the nucleotide values. Hence, the backward propagation in the case of moving from the value The disadvantage in using a neural network technique or support vector machine is the scaling of each nucleotide in the DNA sequence to four input states. This scaling process increase the computational complexity of the technique. On the other hand, the limited number of input instances could negatively affect the accuracy of the prediction process. Finally, the extraction of the rules in this technique is not possible, and hence, the prediction process is not feasible.This paper proposed a new algorithm for solving the evolution prediction problem that is based on the input time series data set. Each RNA sequence is mutated, i.e., evolution passage, to the next RNA sequence in the data set, as these sequences are sorted from old to recent dates. For each iteration in this learning phase of this algorithm, the input is an RNA sequence and the output is the next RNA sequence in the data set. The learned output is not the classification of the RNA virus; however, it is the RNA virus after mutation. Because, techniques like support vector machine, neural networks, and Bayesian belief networks have to deal with data in a numerical form, the proposed technique deals with alphabetical and numerical data in the same fashion.A,C,GorT] for each nucleotide. At this point, the training applied will consider each nucleotide as a target class of four values. The input that leads to one of the values of the target class is the sequence before the sequence containing the current value of the target class. The machine learning algorithm will learn what input will produce which output accordingly. The rules learned from the used machine learning algorithm will be used to predict the generated nucleotide corresponding to the input. The rule will be in the form of short sequences of nucleotides genotype and location that govern the mutation of a nucleotide from certain genotype to another. The number of iterations will be the number of nucleotides in the RNA sequence. After each iteration, the required rule for the nucleotide x corresponding to the current iteration will be extracted.The purpose of this technique is to infer the rules that governs certain value  precedes nucleotide x at position i of value A, and the sequence [CTGAAC] precedes nucleotide x′ at position i of value A. The nucleotide x in the position i corresponding to the current iteration does not change from sequence j+1 to sequence j+2. In this case, if the nucleotides in the sequence preceding to the one corresponding to the nucleotide x do not change, then these nucleotide values will be included in the rule of nucleotide x, otherwise they will be completely excluded. Hence, for Fig. A of the nucleotide at position i will be . A different case is presented in Fig. i is changed from value A to value C. In this case, if the nucleotides in the sequence preceding the one corresponding to the nucleotide x changes, then these nucleotide values will be included in the rule of nucleotide x, otherwise they will be completely excluded. Hence, for Fig. C of the nucleotide at position i will be .In each iteration, the algorithm detects the value of nucleotide N, and the number of nucleotides is K, the computational complexity of the calculations is as follows: The reason behind using this methodology in extracting the rule is that for each iteration in this algorithm is that two main cases are considered. The first case is that the value of the iterated nucleotide corresponding to this iteration does not change. In this case, if the neighbor nucleotides to this iterated nucleotide do not change, this will indicate that the values of the nucleotides are attached and leads to the value of the iterated nucleotide. If the neighbor nucleotides did change, then the variation of these values do not affect the iterated nucleotide, and hence they can simply be removed from the extracted rule. The second case is considered the opposite of the previous one where the existed nucleotides in the RNA sequence will cause the change of the genotype of a specific nucleotide in the following generation. In this case, the extracted rule of the genotype at this nucleotide location will include the set of neighbor nucleotides. While the unchanged behavior of some nucleotides means their unimportance or non-effect of changing the value of the of iterated nucleotide. As shown in Algorithm 1, if the number of sequences is The analysis of RNA mutations requires the gathering and preparing a set of aligned RNA sequences that go through different mutations over a long period of time. A set of time-series successive isolates of the Newcastle virus RNA are collected from two different countries, China and South Korea , 18. TheFigure The Chinese data set shows 33 % of the total number of nucleotides have been mutated, and this percentage in the Korean is 43 %. The rate of genome mutations over the time period applied shows variable number mutations.st instance. The testing will have the 21st RNA sequence as the input to the neural networks and the 22nd RNA sequence as the target output. The results show that after 3743901 learning cycles of back-forth propagation, the validation accuracy reaches 70 % percent as shown in Fig. In order to apply NN to the aligned time series RNA sequences, only a part of the sequence will be considered. The partial training of the RNA sequence is applied to ensure a reasonable training execution time. Applying neural networks to this number of target class labels will lead to a very high processing complexity. The training phase contains only 20 nucleotides, where each nucleotide will be scaled to only four input nodes. This will lead to a data set of 80 input nodes and 80 output nodes. For the Korean input data set, the in-out for the training is the first 20 out of 22 instances. The target 20 output instances for these 20 input instances started from the second instance in the input data set and ends at the 21The validation of the proposed rough set gene evolution (RSGE) is achieved through testing the total number of nucleotides. For the Korean input data set where the total number of nucleotides is 200, the number of correct nucleotide matches is 148, which is considered 74 % classification accuracy percentage. Also, only four nucleotides have shown incorrect matches, which corresponds to 2 % out of all nucleotides. 48 nucleotides have shown no matching results, which indicates that none of the four rules of each of these nucleotides is applied. These results show the predicted and actual target RNA sequence of nucleotides.Actual : ATGGGTTCCAAATCTTCTACCAGPredicted : ATGGGNNCCANANCTTCTACCANFor Korea Data Set Newcastle disease virus strain Kr-XX/YY [1982–2012]: Actual : ATGGGCTCCAAACCTTCTACCAGPredicted : TGGGCTCCAAACNTTCTACCNGFor the Chinese input data set where the total number of nucleotides is 240, the number of correct nucleotide matches is 180, which corresponds to 75 % classification accuracy. Also, only four nucleotides, i.e., 1.6 %, have shown incorrect matches. And, 56 nucleotides have shown no matching results, which indicates that non of the four rules of each of these nucleotides is applied. The results for the China Data Set Newcastle disease virus isolate JS XX XX Ch [2011–2012] is: If Genotype is A then P47=C, P57=AIf Genotype is G then P23=AFor Nucleotide P131: If Genotype is C then P6=T, P118=CIf Genotype is T then P6=G, P118=AFor Nucleotide P101: A sample of the generated rules is figured as follows: This sample is composed of two base nucleotides only in the RNA sequence, which are 131 and 101. The first rule shows that the nucleotide at position 131 will take the genotype value “A” in the following generation if the nucleotide at position 47 in the current generation is ’C’ and the one at position 57 is of type “A”. These rules show the existence of a correlation between the three nucleotides, i.e., those at positions , in the first rule and . The genotype values of some specific nucleotides could affect the alteration/mutation of the RNA sequence. The input Chinese and Korean data sets contain different genotypes, AA, AB, and BB. The nucleotides of the genotypes that have the value AA and BB can be excluded from the resulted rule set. These genotypes need not to be predicted as the values are the same over all the generations. Table N37 is C, the genotype of the nucleotide at position N33 is T. And when the genotype of the nucleotide at position N33 is T, the genotype of the nucleotides at positions N53 and N68 are T and G respectively. The is applied on the rules generated for the Korean data set as shown in Fig. Finally, the correlation between the nucleotides can be visualized after extracting the prediction rules from the RSGE technique. This form of exploring the effect of nucleotides on one another can provide a better understanding of the mutation mechanism existing in the virus’s RNA. An example of this correlation visual is shown in Fig. Figure The contribution of machine learning techniques in the RNA mutation was limited to the prediction of the activity of the virus of resulted RNA. This work paves the way to a new horizon where the prediction of the mutations, such as virus evolution, is possible. It can assist the designing of new drugs for possible drug-resistant strains of the virus before a possible outbreak. Also it can help in devising diagnostics for the early detection of cancer and possibly for the early start-of-treatment. This work studies the correlation between the nucleotides in RNA including the effect of each nucleotide in chaining the genotypes of other nucleotides. These rules of these correlations are explored and visualized for the prediction of the mutations that may appear in the following generations. The prediction rules are extracted by a proposed technique based on RSGE, and is trained by two data sets extracted from two different countries. This work proves the existence of a correlation between the mutation of nucleotides, and successfully predicts the nucleotides in the next generation in the testing parts of two used data sets with a success rate of 75 %. On the other hand, the proposed rough set (RSGE) based technique shows a better prediction result than the neural networks technique, and moreover, it extract the rules used in the prediction.


Tossa jute is an important natural fiber crop of Southeast Asian countries including India, Bangladesh, China, Thailand, Myanmar etc. Traditional industrial application of jute fiber is limited to the packaging products like hessians, sacks, etc. and the fiber found unsuitable for textile industries largely due to significantly high lignin content. Therefore, understanding genetic factors underlying lignin biosynthesis in tossa jute holds promise for jute based product diversification. The major limiting factor in undertaking such study is unavailability of efficient protocol for RNA extraction at secondary growth active stage of tossa jute. Here we report a simplified, swift and cost effective protocol for isolating fairly good quality RNA from bark tissue of 65-days-old field grown tossa jute plant with active secondary growth. The purity, concentration and integrity of extracted RNA ascertained. To confirm downstream amenability, isolated RNA samples were reverse transcribed and PCR analysis done by using CCoAMT1 primer. Results established that method of RNA extraction presented here is an improvement over the other methods, particularly for bark tissue of field grown tossa jute at advance developmental stage. Therefore, present study will enhance our ability to understand expression pattern of fiber formation and maturation related genes in mature bark tissue that holds key for much talked genetic manipulation of fiber quality via lignin optimisation in the crop. Tossa jute (Corchorus olitorius L.) is an annual herbaceous dicot plant, belongs to family Malvaceae and mostly cultivated in Southeast Asian countries as a fiber crop. Besides, traditional applications in hessian and packaging industries, jute fiber valued for potential diversified industrial applications including yarn, ethanol and different grades of high quality pulp production , Barrackpore, India experimental field  during March–July, 2014 following the recommended cultural practices. Fertilizer were applied at the rate of 40 kg N, 20 kg P2O5 and 20 kg K2O per hectare at sowing time, with N 50 % as basal dose and 50 % a top dress at 21 days after sowing. Adequate measures were taken to avoid abiotic and biotic stresses that may affect plant growth and phloem fiber development. The seeds were germinated and grown for 120 days in the experimental field .tossa jute plants since 30 days after showing. The section was stained with safranine dye without fixation and observations were made under a Zeiss Axioskop 40  bright field microscope and a Canon PowerShot A80 camera system.Fresh free-hand transverse sections were prepared at 5 days interval from lower stem segment of Bark tissue of the cultivar were taken at optimum phloem fiber cells increment percentage stage (65 days after sowing) as revealed from histological study of transverse section of basal stem Fig. . SamplesCorchorus spp. seedling was modified for effective RNA isolation from 65-days-old field grown bark tissues. 1 g of bark tissues frozen in liquid nitrogen were taken in a pre-chilled RNase-free mortar and pestle. The sample finely grounded by using liquid nitrogen through crushing and quickly divided into four aliquots. Each of them was transferred to a 2 ml RNase-free microcentrifuge tube and 1 ml of RNA extraction buffer  added into each tube. The mixture was shaken vigorously for 1 min, and then kept at room temperature for 10 min, followed by addition of 0.2 ml chloroform and mixing. The content was centrifuged at 10,000 rpm for 10 min at 4 °C to carefully collect upper aqueous phase. To this, 2X volume of absolute alcohol and 0.1X volume of 5 M NaCl was added, mixed well, allowed precipitation of the pellet for 3 h. The pellet was collected following centrifugation at 12,000 rpm for 10 min at 4 °C. Initial steps of RNA extraction were repeated again after dissolving the pellet in RNase-free distilled water. 0.2 ml chloroform is added into each tube, mixed well by inversion, vortexed briefly and incubated at room temperature for 5 min to allow the nucleic acid to precipitate, followed by removal of residual phenol. The tubes were then centrifuged at 13,000 rpm for 10 min at 4 °C and the aqueous phase was transferred to a fresh micro centrifuge tube using a sterile transfer pipette. An equal volume of 7.5 M LiCl was added to each tube, mixed well by invert mixing and incubated for 10 min at room temperature to allow the nucleic acid to precipitate. The pellet was collected by centrifugation at 13,000 rpm for 10 min at 4 °C and washed twice with 0.5 ml of 70 % ethanol followed by centrifugation at 12,000 rpm for 10 min at 4 °C. The supernatant was discarded and RNA pellet dried at room temperature inside a laminar flow clean air work station. The dried RNA pellet re-suspended in 20 μl RNase-free distilled water and kept at 4 °C for immediate use or at −20 °C for long term storage.RNA isolation protocol developed by Mahmood et al.  for in vPurity and concentration of RNA samples were assessed using a spectrophotometer . Integrity of total RNA was evaluated on a 1 % denaturing formaldehyde-agarose gel by using 28 S rRNA and 18 S rRNA universal markers . Primers of two genes namely 18S rRNA gene  and phenypropanoid pathway gene i.e. CCoAMT1  designed  in the presence of 1 μg oligo (dT)tossa jute (C. olitorius L.) at optimum increment percentage of phloem fiber cells so that phloem fiber development and maturation specific gene expression study can be precisely undertaken.The aim of this study was to develop a simple, swift and cost effective protocol for RNA isolation from mucilage, phenol and secondary metabolite rich bark tissue of tossa jute.Histological analysis Fig.  suggeststossa jute at 65-days-old plant. It was evident that the protocol was reported only for 3-day-old seedling plants which are obviously developmentally totally different than a 65-days-old adult plant with high amounts of mucilage as well as secondary metabolites. Next, we investigated the protocol suggested by Samanta et al. (white jute (C. capsularis L.). Despite of very long and complex procedure involving 3 h centrifugation and costly chemicals like CsCl, the protocol yielded poor quality and quantity of RNA from 65-days-old plant bark. Plant growth stage and species difference may contributed to the RNA yield. However, both the protocols were able to extract good quality RNA at 3-days-old seedling stage  and yielded good amount of RNA with better quality then HBIC method and SDS/phenol method, suggested by Samanta et al.  and Mahmin Table  indicate+ mRNA isolated from bark tissue of 65-days-old plant. RT-PCR was performed for CCoAMT1 transcript of lignin biosynthetic pathway as lignin is being considered as one of prime factor involved in fiber cell maturations + mRNA istossa jute plant has largely been missing. Unlike to pre-existing RNA isolation protocols from secondary metabolite, phenol (Ghawana et al. tossa jute bark tissues with active secondary growth stage. Therefore, present study will enhance our ability to understand expression pattern of fiber formation and maturation related genes in the mature bark tissue that holds key for much talked genetic manipulation of jute fiber quality suitable for diversified products.A suitable method for extraction of RNA from mature bark of