A network of strongly coupled residue pairs is identified. Helix α18 is part of this regulatory network and connects several NS3 functional elements involved in RNA replication. Among all genotypes we found distinct sequence diversity at helix α18 in particular for the most difficult-to-treat genotype 3. Our data suggest sequence diversity with implications for virus replicative fitness due to natural variants in helicase helix α18.High replicative fitness is a general determinant of a multidrug resistance phenotype and may explain lower sensitivity to direct-acting antiviral agents (DAAs) in some hepatitis C virus genotypes. Genetic diversity in the molecular target site of peptidomimetic NS3 protease inhibitors could impact variant replicative fitness and potentially add to virologic treatment failure. We selected NS3 helicase residues near the protease natural substrate in the NS3 domain interface and identified natural variants from a public database. Sequence diversity among different genotypes was identified and subsequently analyzed for potential effects of helicase variants on protein structure and function, and phenotypic effects on RNA replication and DAA resistance. We found increased replicative fitness in particular for amino acid substitutions at the NS3 helicase C-terminal helix α They demonstrated that cross-resistance among antiviral inhibitors may come about not only through RAVs that confer resistance to more than one drug but also through a general increase in viral fitness. High level replicative fitness allows HCV to maintain mechanisms to shutoff host cell protein synthesis by multiple viral expression products that interact with host factors. Moreover, high levels of replicating viral RNA and RNA expression products may confer a selective advantage in competition with the number of inhibitor molecules that reach the target viral or cellular proteins at the replication complexRAVs display reduced drug susceptibilities, however, due to large scale conformational changes between the open and closed conformation of NS3, helicase mutants are unlikely to have a direct impact on peptidomimetic PI binding to the protease active siteTo date, genotype 3 has become the most difficult-to-treat with DAA-based regimens and displays a specific clinical phenotype with more rapid progression of liver disease and a higher incidence of hepatocellular carcinoma12We used the protease-helicase complex structure PDB 1CU1 to identify amino acid residues in NS3h within close structure proximity to the natural substrate of NS3p-mediated proteolysis. Eighteen residues neighboring the NS3p substrate were identified: residues 438, 488, 524–532, 534, 619–624 , subsequImportantly, some of the variants were observed more frequently in the database than others. Most abundant variants in genotype 1b were S534G, A621T and S624A that were identified 74, 35 and 10 times respectively. Some variants were observed only once in the database, including F438L, Q526M, D527V, H528Y, S534A, S534D, C622S and S624W. A comparison of the sequence diversity for all genotypes is given in The replicative fitness of NS3h domain-interface mutants was assessed by quantitative RNA measurement of Huh7.5 cells harboring respective Con1 replicons. Our data demonstrate that NS3h polymorphisms can have a modulatory effect on RNA replication but do not generally have a consistent effect. We found three mutants  with a positive effect on RNA replication and seven mutants  with a negative effect on RNA replication, whereas three mutants  showed no effect on replicative fitness . We did 3 (E628) (3 site (E628). A positive effect on RNA replication is observed for I619V and A621T, both located in NS3h C-terminal helix α18  preceding the natural substrate of proteolysis. I619 is oriented towards the protein interior with its side chain close to the functionally important Phe-loop residues T443 and F444, whereas A621 is surface exposed and close to the NS3p peptide substrate P6 site (A625) . Helix α14 is oriented anti-parallel to helix α18 in the protein structure. The wild-type residue W532 is involved in a T-shaped π-π stacking interaction with the aromatic ring of residue F444. Mapping the comprehensive panel of mutational sites on the 3D protein structure of NS3, we found two functionally important sites with modulating effect on RNA replication, the NS3 protease-helicase allosteric site and NS3h C-terminal helix α18. Increased replicative fitness is found in particular for mutations at or close to helix α18.Some regulatory residues were located at the domain interface allosteric site that is V524, C525, Q526 and D527. Here a positive effect on RNA replication is observed only for Q526M with its side chain pointing towards the NS3p natural substrate residue P3 (E628) . All othe (A625) . A negat18, as well as helicase and protease functional sites. Six residue pairs consist of NS3h residues, one pair consist of NS3p residues and five pairs connect NS3p with NS3h residues  and helix α14 (residues 532 and 534) in NS3h. In contrast, residues of the protease-helicase allosteric site were found highly conserved throughout all genotypes (low sequence diversity). Physicochemical properties within the selected NS3h domain-interface residues were highly conserved and similar among all genotypes  with a maximum of 0.44 compared to genotype 1a (0.12), 1b (0.30) and 2 (0.17). Noticeable diversity is found in particular for the C-terminal helix αenotypes . For var50 values and fold changes (FC) were determined for the selected variants. Our data show no clinically significant effect for the selected NS3h variants on the inhibition of NS3p by telaprevir  with the protease amphipathic helix α0 (residue I18), required for efficient MAVS cleavage and RIG-I pathway control, which, in turn, is coupled to the helicase C-terminal helix α18 that we identified in our study with a regulatory role in RNA replication. Some additional functionally important sites were found associated to this closed I18-K371-V630 residue circuit, i.e. protease residue I170, involved in MAVS cleavage, helicase residue Y418, involved in intramolecular rearrangements and RNA interaction, as well as a subset of residues that connect helices α14 and α18 via the helicase Phe-loop. The respective residue side chains show potential molecular interactions that allow for conformational changes in variant structures that are likely to explain their modulatory impact on RNA replication  changes throughout the viral genome may add to RAV selection and may relate to virologic treatment failure. The structure element that we describe here is probably a novel functional site likely contributing to variant replicative fitness. High sequence diversity of i.e. genotype 3 at helix αhttps://euhcvdb.ibcp.fr/euHCVdb/)http://bip.weizmann.ac.il/correlated_mutations/). Sequence logos were computed using WebLogo (http://weblogo.berkeley.edu/logo.cgi)http://indra.mullins.microbiol.washington.edu/DIVEIN/index.html)i,j) is the genetic distance between sequences i and j:From the European HCV database (www.rcsb.org)in silico structure analysis. The structure contains the complete NS3 and NS4A sequence of genotype 1b (isolate BK) in a single polypeptide chain with NS3p and NS3h co-crystallized in closed conformation. The NS3p active site is occupied by the NS3h C-terminus as one product of NS3-mediated cleavage at the HCV polyprotein NS3-NS4A junction. Residues within a distance of ≤7.0 Å from the NS3p natural substrate of proteolysis were identified and denoted “NS3h domain-interface residues” with the cutoff based on previous publications. PyMOL and Chimera were used for protein structure analysis and visualization.The crystal structure 1CU1389neo/NS3-3′/ET  contains HCV subgenomic replicon sequences derived from HCV genotype 1b and an upstream T7 promoter for in vitro RNA synthesis. The point mutations were generated with the QuikChange Lightning Site-Directed Mutagenesis Kit  and a set of primers given in The plasmid pFKIin vitro transcribed subgenomic replicon RNA was performed using a standardized procedure . A wild-type sequence of pFKI389neo/NS3-3′/ET was used as positive control to compare with a replicon containing a lethal mutant (GDD-) as negative control. All mutants were tested at least in ten replicates.Huh7.5 cells were cultured in L-glutamine containing Dulbecco’s modified Eagle’s medium  containing 10% fetal bovine serum . Transfection of Huh7.5 cells with the 5 cells in DMEM with 10% FBS. For telaprevir  resistance analysis, 48 h later, the culture medium was replaced with DMEM + FBS containing DMSO as a control or the indicated concentrations of telaprevir . After an additional 48 h incubation, intracellular RNA was extracted with an RNeasy Mini kit (Qiagen). The level of HCV RNA was determined by two-step reverse transcription quantitative real-time PCR (RT-PCR) assay including cDNA synthesis  according to the manufacturer’s instructions and SYBR Green based RT-PCR  with a pair of HCV-specific primers  on a StepOnePlus RT-PCR System − replicons do not generate additional HCV RNA, the GDD− replicon was used to normalize data obtained with other replicons. Semi-quantitative HCV RNA replication was calculated using the DDCT method. Relative mRNA levels of the helicase variants were acquired and compared to wt, which was set to 1.Following transfection, HCV replicon cells were plated in duplicate or triplicate in 6 cm dishes at densities of 4–4.76 × 1050 was defined as the concentration of compound at which the HCV RNA level in the replicon cells was reduced by 50%, calculated by nonlinear regression analysis with GraphPad Prism.Relative replication efficiencies were displayed in relation to the wild type replicons replication capacity. Values were analyzed by student’s t-test for unpaired samples with a P value < 0.05 considered statistically significant. The ICHow to cite this article: Stross, C. et al. Natural HCV variants with increased replicative fitness due to NS3 helicase mutations in the C-terminal helix α18. Sci. Rep.6, 19526; doi: 10.1038/srep19526 (2016).


Caenorhabditis elegans locomotion mutants, we identified a gain-of-function (gf) mutation in dnj-17 closely linked to the widely used e156 null allele of C. elegans GAD (glutamic acid decarboxylase) unc-25. dnj-17 encodes a DnaJ protein orthologous to human DNAJA5. In C. elegansDNJ-17 is a cytosolic protein and is broadly expressed in many tissues. dnj-17(gf) causes a single amino acid substitution in a conserved domain, and behaves as a hypermorphic mutation. The effect of this dnj-17(gf) is most prominent in mutants lacking GABA synaptic transmission. In a seizure model caused by a mutation in the ionotropic acetylcholine receptor acr-2(gf), dnj-17(gf) exacerbates the convulsion phenotype in conjunction with absence of GABA. Null mutants of dnj-17 show mild resistance to aldicarb, while dnj-17(gf) is hypersensitive. These results highlight the importance of DnaJ proteins in regulation of C. elegans locomotor circuit, and provide insights into the in vivo roles of DnaJ proteins in humans.The highly conserved cochaperone DnaJ/Hsp40 family proteins are known to interact with molecular chaperone Hsp70, and can regulate many cellular processes including protein folding, translocation, and degradation. In studies of  Cells have molecular mechanisms to protect themselves from the stress caused by misfolded or aggregated proteins. DnaJ/Hsp40 family proteins are highly conserved through evolution and act as cochaperones by interacting with and activating the ATPase activity of Hsp70 chaperone proteins  causes a premature termination codon (Trp383amber) in the enzymatic domain; e156 mutants completely lack GABA immunoreactivity and have been widely used as representative of complete loss of GABA function.Functions of neural circuits depend critically on balanced activity between excitatory and inhibitory transmission. In 9/GABAAR  are highacr-2 is expressed in the cholinergic motor neurons. A gain-of-function mutation of acr-2 causes increased cholinergic motor neuron activity accompanied by decreased GABAergic motor neuron activity, generating excitation–inhibition (E/I) imbalance in locomotor circuit. acr-2(gf) animals exhibit a characteristic repetitive convulsion behavior, the frequency of which provides a quantitative measure of E/I imbalance (The nicotinic acetylcholine receptor subunit acr-2(gf) animals, we unexpectedly found a gain-of-function mutation in a cochaperone protein dnj-17 to be present in the widely used strain CB156unc-25(e156). We show that the DNJ-17 gain-of-function mutation behaves in a hypermorphic manner, and exacerbates excitation–inhibition imbalance in acr-2(gf). Null mutations of dnj-17 exhibit mild resistance to aldicarb, suggesting a role in modulating neurotransmission. Homologs of DNJ-17 include human DNAJA5, which is expressed in the brain and other tissues. Our findings provide insights into the in vivo function of these cochaperone proteins.Through studying the effects of defective GABAergic transmission on C. elegans strains were kept at 22.5° according to standard procedures. Supplemental Material, Table S1 lists strain information with alleles and transgenes. Galaxy platform (unc-25(e156) dnj-17(ju1162)III; acr-2(n2420)X and CZ19995 unc-25(e156) dnj-17(ju1162)III; acr-2(n2420)X, obtained by Beijing Genomics Institute . Subsequent analyses based on chromosomal linkage and recombination mapping identified the ju1162 missense mutation in dnj-17. We verified the presence of dnj-17(ju1162) in CB156, and generated CZ22168 unc-25(e156) that lacks dnj-17(ju1162) through multistep recombination as follows: We verified that the Caenorhabditis Genetics Center (CGC) strain SP1104unc-25(e156) bli-5(e518)III is wild type for dnj-17. We outcrossed SP1104 to N2, and isolated recombinant animals that showed unc-25(0) shrinker phenotype without blister phenotype. We performed genotyping on isogenic strains of the recombinants, and confirmed the presence of unc-25(e156) and the loss of bli-5(e518). In this process, we also found SP1104 has another mutation linked to chromosome III that caused egg-laying defects. Through further outcrossing to N2, we reisolated unc-25(e156) based on behavior and genotyping and established strain CZ22168 which does not exhibit the egg-laying defects. Primers used for PCR and genotyping were as follows: YJ10801 CCGTAGAAACCATTCACAGTTTGC and YJ10802 CTATGAAATGCCATTACGAAGTGCTC for dnj-17(ju1162), YJ11985 CATTGGCGCAGACTATTGCTTC and YJ11986 AATTGCTCACCGAAACTCACATTCT for unc-25(e156), YJ10799 TACTTGGTATCCAGCTCCTTCC and YJ10800 ATTATTTGGACAGTTTAGCCCACC for bli-5(e518). The information on the alleles and CB156 is deposited in CGC and Wormbase. Several researchers noted that unc-25(e156) appeared to behave differently from other unc-25 alleles or GABA mutants, in a number of behavioral and pharmacological assays . For future experiments on unc-25 mutants, we recommend CZ22168, as well as other unc-25 alleles.Table S2 describes the details of constructs generated in this study. We amplified 3.5 kb genomic sequences of dnj-17 with 0.9 kb 5′ upstream sequences to 0.1 kb 3′ downstream region using the following primers: YJ11121 AAACTCCATCAACCTGACTTCCCTG and YJ11122 TTGCCCATTATTCTTCCCGAAAC. To determine the gene structure of dnj-17, we isolated mRNAs from mixed-stage animals of N2 wild type and CB156unc-25(e156) dnj-17(ju1162) using Trizol (ThermoFisher Scientific). Complementary DNA (cDNA) synthesis was performed using SuperScript III (ThermoFisher Scientific), with random primers according to the manufacturers’ instructions. We performed RT-PCR using SL1 primer GTTTAATTACCCAAGTTTGAG and a reverse primer p3 GCGACCAGATTCCTAATTTGCTCGTTC designed on the junction of exon 3 and exon 4 to determine the first exon of dnj-17 mRNA, and p2 ATGAAATGCCATTACGAAGTGCTC and p4 AATGTTTCACCAATCCTCATCATCC primers designed on the first and sixth exon to verify the coding sequence. Sequences of all clones were verified by Sanger sequencing. Protein domain analysis was performed using NCBI domain database  was used for expression vectors. dnj-17(ju1239) and dnj-17(ju1276) deletion alleles were generated by CRISPR-Cas9 editing in the germline, using modifications of previously described methods  animals.dnj-17(ju1239), we examined the growth and locomotion of N2 and CZ21429 dnj-17(ju1239) under different temperature conditions. Briefly, 10 gravid adults of each strain were allowed to lay eggs for 6 hr at 22.5°. Then, adult animals were removed, and the plates with embryos were kept under 15°, 22.5°, or 25°. Hatched progeny were kept under the same temperature, and their growth and general locomotion were visually scored once within 16−24 hr. When the progeny reached L4 stage, animals from each condition were placed onto individual plates. Number of eggs laid by each animal was scored to compare the brood size. The experiment was repeated twice.To analyze the temperature effects on Pdnj-17-dnj-17(+) and Pdnj-17-dnj-17(ju1162) were generated at Chromosome II site ttTi5605 using modified vectors . Briefly, N2 young adult animals were injected with the following constructs: a construct (pCZGY3031 or pCZGY3032) containing dnj-17 sequence with ttTi5605 homology arms and a copy of hygromycin resistance gene, a construct (pDD122) which drives expression of Cas9 and sgRNA targeting ttTi5605 in the germline, and a Pmyo-2-mCherry fluorescent co-injection marker. F2 animals were selected for the resistance to hygromycin. Single-copy insertion lines were confirmed by PCR using primers designed outside of the homology arms. Loss of extrachromosomal array was confirmed by PCR and the loss of co-injection marker. Each insertion line was outcrossed twice before being used in experiments.Single-copy insertion transgenes of Escherichia coliOP50. On the following day, young adults were transferred to fresh plates with OP50 and visually scored for convulsion behavior under a dissecting microscope. The observer was blinded to the genotype of the animals tested. A convulsion event was defined as a shortening of the animal’s body length. The assay was repeated at least twice per genotype in two different generations. Two independent transgenic lines were used for each construct.Scoring of convulsions was performed as previously described . Animals were immobilized by 1 mM levamisole and placed on 4% agar pads. Images are maximum-intensity projections of z stacks obtained at 1 µm intervals. ImageJ was used to process the images obtained.Table S1 and Table S2 respectively, and are available upon request.Strains and constructs are described in acr-2(n2420gf) animals show spontaneous convulsion behavior, due to increased cholinergic excitation and reduced GABAergic inhibition (acr-2(gf) animals. We generated double mutants of acr-2(gf) with genes essential for GABA signaling, using canonical or null alleles of unc-25/GAD, unc-47/VGAT, unc-49/GABAR. We used three null mutations of unc-25: e156, n2324, and n2328, which cause amber stop codons at Trp383, Trp291, and Glu486, respectively, and which are all predicted to encode truncated proteins that lack the cofactor binding site and enzymatic activity site at the C-terminus. All double mutants showed increased convulsion frequency compared to acr-2(gf) single mutants (unc-25(n2324) and unc-25(n2328) enhanced acr-2(gf) behavioral defects to similar degrees as unc-47(gk192) and unc-49(e382), unc-25(e156) increased the convulsion frequency significantly more than these four mutations. Further outcrossing of unc-25(e156); acr-2(gf) (MT6648) did not eliminate this enhancement. We thus hypothesized that the ancestral CB156 strain may contain additional modifier mutation(s) linked to unc-25(e156). mutants . While uunc-25(e156); acr-2(gf). Following chromosomal linkage mapping, we identified a single nucleotide transversion from thymine to adenine in the coding sequence of the gene dnj-17, approximately 0.5 map units right of unc-25 on chromosome III (dnj-17(ju1162). The ju1162 mutation was present in the CGC strain CB156unc-25(e156), but not in SP1104unc-25(e156) bli-5(e518) III, which was generated in about 1987 through recombination from trans-heterozygous animals of unc-25(e156) with a chromosome containing bli-5(e518) . dnj-17(ju1162) was also not present in MT5957 unc-25(n2324) III and MT5969 unc-25(n2328) III. Therefore, dnj-17(ju1162) did not arise as a spontaneous mutation in strain passage in our laboratory, but was inherited from the original CB156 stock.We performed whole-genome sequencing analysis of MT6648 and of an outcrossed strain CZ19995 some III , and herdnj-17 contains seven exons, generating a mature mRNA predicted to encode a protein of 510 amino acids. To verify the dnj-17 gene structure we performed cDNA analyses using mRNA isolated from N2 and CB156unc-25(e156) dnj-17(ju1162). RT-PCR analyses using SL1 and gene-specific primers revealed that the 5′ end of dnj-17 mRNA contained an SL1 leader, but predicted exon 1 was not present in the mature mRNA. We obtained full-length dnj-17 cDNA and found that DNJ-17 protein consists of 485 amino acids  dnj-17(ju1162) contained a single nucleotide change, which causes Asp77 to Lys amino acid substitution (N77K) in the region immediately adjacent to the DnaJ domain (Gene structure (Wormbase WS251) showed that no acids . From NCosophila . The J dproteins . Yeast JJ domain .ju1162 is a gain-of-function mutation of dnj-17. First, we examined the effect of a dnj-17 deletion allele dnj-17(tm570), which removes the C-terminal half of the protein (dnj-17(tm570) homozygous animals showed normal growth rate, wild-type locomotion, and did not affect convulsion frequency of acr-2(gf) (unc-47(gk192) dnj-17(tm570); acr-2(n2420) triple mutants and found that they resembled unc-47(gk192); acr-2(n2420) double mutants in their convulsion frequency. As dnj-17(tm570) mutants potentially produce mRNAs encoding a truncated protein with intact DnaJ domain, we next generated a deletion allele targeting the DnaJ domain using CRISPR-Cas9-mediated genome editing technology (dnj-17(ju1239) removes a large portion of the DnaJ domain and is predicted to cause a frameshift and premature stop after amino acid 34  mutants. The mutant animals had similar brood size as wild type under three temperature conditions (dnj-17(ju1239) did not affect the convulsion frequency of acr-2(n2420)  by itself or when GABA transmission is eliminated in unc-47(null) animals.Several lines of evidence support that  protein . dnj-17(cr-2(gf) . We also acid 34 . Since tnditions . Their g2(n2420) . These odnj-17(ju1162) from unc-25(e156) background would eliminate the increased convulsion frequency phenotype of acr-2(gf). As dnj-17 is located 0.5 map unit apart from unc-25, it is challenging to separate unc-25(e156) and dnj-17(ju1239) by genetic recombination. We therefore generated another deletion allele in the unc-25(e156) dnj-17(ju1162) background using CRISPR editing (dnj-17(ju1276) removed the DnaJ domain and the region including ju1162(N77K), and eliminated the increased convulsion (unc-25(e156) recombinants after outcrossing SP1104unc-25(e156) dnj-17(+) bli-5(e518), we obtained CZ22169 unc-25(e156) dnj-17(+); acr-2(n2420). Animals of genotype unc-25(e156) dnj-17(ju1276); acr-2(gf) and unc-25(e156) dnj-17(+); acr-2(gf) showed convulsion frequencies lower than unc-25(e156) dnj-17(ju1162); acr-2(gf), and instead resembled acr-2(gf) double mutants with unc-25(n2324) or with other GABA mutants (dnj-17(ju1162) showed semidominant effects on convulsion frequency in the acr-2(gf); unc-25(0) background (dnj-17(ju1162) is a semidominant gain-of-function mutation, designated as dnj-17(ju1162gf).We further examined if removing  editing . dnj-17 reporter using 0.9 kb promoter region of dnj-17. GFP was seen throughout the body with enrichment in the intestine and several cells around the pharynx, and the expression pattern was similar in both wild type and acr-2(gf) background  (acr-2(gf) background, suggesting that the presence of acr-2(gf) does not largely affect the localization of DNJ-17.We next analyzed the expression pattern of ckground . We thenthe body . A weakeDNJ-17(N77K) using transgenic overexpression. Overexpression of wild-type dnj-17 by genomic sequence of dnj-17 including 0.9 kb upstream promoter region caused increase of acr-2(gf) convulsion frequency (unc-47(0) mutant background, suggesting that the increase in convulsion by overexpression of dnj-17 is independent of the effect caused by defects in GABAergic transmission. Interestingly, this enhanced effect was also observed by overexpression of dnj-17(ju1162gf). ACR-2 is expressed specifically in neurons (dnj-17 wild type or ju1162(gf) using the Prgef-1 pan-neuronal promoter did not affect convulsion frequency of acr-2(gf) (Pmyo-3 promoter did not affect acr-2(gf) convulsion frequency (dnj-17 on convulsion frequency likely requires its expression in multiple tissues.We next examined the nature of requency . This trcr-2(gf) . Also, orequency . These rdnj-17(ju1162gf) to wild-type dnj-17, we generated a single-copy insertion transgene expressing full-length genomic dnj-17(ju1162gf) or dnj-17(+) on chromosome II. Animals with Pdnj-17-dnj-17(ju1162gf) expressed from a single-copy transgene showed overall normal locomotion, growth speed, and brood size. We found that acr-2(gf)Pdnj-17-dnj-17(ju1162gf); increased convulsion compared to acr-2(gf) single mutants, whereas Pdnj-17-dnj-17(+) single-copy expression did not (dnj-17(ju1162gf) acting semidominantly in unc-25(e156) background (DNJ-17(N77K) mutation has higher activity than wild-type DNJ-17, implying that the increase in convulsion by overexpression of wild-type dnj-17 is caused by excess levels of the protein.To precisely compare the effect of  did not , consistckground . These rdnj-17 mutations on neurotransmission at the neuromuscular junction, we examined the sensitivity of the mutant animals to an acetylcholine esterase inhibitor aldicarb. dnj-17(ju1239) null animals showed mild resistance to aldicarb, which was rescued by single-copy insertion of dnj-17(+), implying that dnj-17 affects cholinergic transmission at the neuromuscular junction (dnj-17(ju1162gf) caused mildly increased sensitivity to aldicarb, reaching statistical significance at one time point, consistent with this allele being a hypermorph mutation. These results raise a possibility that the function of dnj-17 is required for folding and/or function of proteins in multiple tissues that are involved in cholinergic transmission. Overexpression of wild-type DNJ-17 may also lead to a high level of cholinergic transmission by contributing to folding of the proteins in the pathway.To further assess the effect of junction . Expressdnj-17(ju1162). The N77K mutation may make DNJ-17 protein prone to form aggregates. DnaJ/Hsp40 proteins bind to misfolded proteins and bring them to Hsp70 (DNJ-17 to detach from the protein(s) it binds to, and prevent the misfolded protein from being degraded, resulting in accumulation of misfolded proteins that cause cellular stress. Such cellular stress could alter neuronal and muscular functions. Another possibility is that the mutation disrupts certain cellular functions. Recently it was reported that an Asn to Ser mutation in the DnaJ domain of human DNAJC13 was found in a family with Parkinson disease, where the disease was transmitted in an autosomal-dominant manner (C. elegansDNJ-17 may affect similar cellular functions such as endocytosis and subcellular trafficking, thus disrupting the coordination of the motor neuron circuit.Other mechanisms might account for the effects of to Hsp70 . The N77E. coli has only one gene coding DnaJ/Hsp40, whereas animals typically express multiple DnaJ family members. The DnaJ protein in E. coli has been well characterized, but functions of individual DnaJ/Hsp40 family proteins in animals remain largely unknown. DNAJA5, the closest human homolog of DNJ-17, shows enhanced expression in the brain (


The DEAD-box RNA helicase Ded1, which is essential in yeast and known as DDX3 in humans, shuttles between the nucleus and cytoplasm and takes part in several basic processes including RNA processing and translation. A key interacting partner of Ded1 is the exportin Xpo1, which together with the GTP-bound state of the small GTPase Ran, facilitates unidirectional transport of Ded1 out of the nucleus. Here we demonstrate that Xpo1 and Ran[GTP] together reduce the RNA-stimulated ATPase and helicase activities of Ded1. Binding and inhibition of Ded1 by Xpo1 depend on the affinity of the Ded1 nuclear export sequence (NES) for Xpo1 and the presence of Ran[GTP]. Association with Xpo1/Ran[GTP] reduces RNA-stimulated ATPase activity of Ded1 by increasing the apparent KM for the RNA substrate. Despite the increased KM, the Ded1:Xpo1:Ran[GTP] ternary complex retains the ability to bind single stranded RNA, suggesting that Xpo1/Ran[GTP] may modulate the substrate specificity of Ded1. These results demonstrate that, in addition to transport, exportins such as Xpo1 also have the capability to alter enzymatic activities of their cargo. Ded1 and its orthologs have been implicated in a variety of nuclear and cytoplasmic processes, from splicing to translation. Although essential for growth in yeast, the substrate specificities of Ded1 and the effects of binding partners on Ded1 activities have not been fully explored. In the cytoplasm, Ded1 has been shown to be required as a translation initiation factor . Studiesvia canonical mRNA export pathways that utilize mex67 and through protein export pathways using the exportin Xpo1 ) as a cofactor for cargo binding , 11. TheXenopus laevis Ded1 ortholog (An3) has been shown to interact with Xpo1, dependent on Ran[GTP] and the An3 nuclear export sequence (NES) , we find that Ded1 remains competent for the formation of stable, ATP-dependent complexes with single-stranded RNA (ssRNA), suggesting that RNA binding surfaces of Ded1 are not occluded. These results reveal that catalytic activities of a DEAD-box helicase can be modulated upon forming an exportin complex, which may be used to redirect Ded1 specificity in the context of an Xpo1 export complex.Helicase-type ATPases similar to Ded1 are commonly found to be regulated by protein segments outside the core motor . Given tS. cerevisiae genomic DNA. Amplified fragments of Ded1 and Ran were cloned into a modified pET28 vector containing a preScission protease site upstream of the multiple cloning site; Xpo1 was sub-cloned into a His-tagged pGEX vector using standard protocols. Modified versions of Ded1 (I13A and sNES) and RanQ71L were generated using a dual single-primer mutagenesis strategy Q71L fractions. Protein concentrations were determined by A280 and by Bradford assay.After resuspension in lysis buffer , cells were lysed using lysozyme and sonication. The lysate was clarified by centrifugation and the His-tagged proteins were purified by Ni-affinity chromatography. After desalting into lysis buffer containing 15 mM imidazole, His-tags were removed by treatment with preScission protease, and then further purified by a second passage over a HisTrap column. Proteins were then concentrated and applied to a Superdex 200 size exclusion chromatography column as a final step. The final buffer for Xpo1 and Ran proteins was 20 mM Tris (pH 7.8) and 300 mM NaCl. Due to poor stability in low salt, the final buffer for Ded1 proteins contained 1 M NaCl. For Ran[GTP]2 and 0.5mM TCEP). Xpo1 (10 μM), Ded1ΔC or Ded1ΔC variants (11 μM), and Ran[GTP]Q71L (11 μM) were run separately or in the combinations indicated, using a 500μL injection volume. Fractions were collected in 1 mL aliquots, and analyzed on 15% SDS-PAGE gels stained with GelCode Blue Safe Protein Stain (Pierce). Chromatograms and gels are representative of 3 or more experiments for each sample.For all size exclusion experiments, a Superdex 200 10/300 column  was used, pre-equilibrated in gel filtration buffer . Protein concentrations were 500 nM for full length Ded1 and Ded1 variants in all experiments. For the Xpo1/Ran[GTP] titration experiments, the concentrations of Xpo1 ranged from 0.5 μM to 11 μM, with the corresponding reactions containing 0.65 μM to 13 μM Ran[GTP]Q71L. Whole cell yeast RNA concentration for these Xpo1/Ran[GTP] titration experiments was 320 μg/mL. For RNA titration experiments used to calculate KM, concentrations of Xpo1 and Ran[GTP]Q71L were 5.5μM and 6.5μM, respectively. For whole cell yeast RNA titration experiments, RNA concentations ranged from 750 μg/mL to 183 ng/mL in four-fold dilution steps. For the poly(A) and poly(U) titration experiments, substrate was purchased as the lyophilized product of polynucleotide phosphorylase action from Midland Certified Reagent Company (www.oligos.com). As with whole cell RNA substrate, seven RNA concentrations of poly(A) and poly(U) were used to calculate KM, ranging from 2.5 mg/mL to 610 ng/mL in four-fold dilution steps. Non-linear curve fitting, using the equation v = Vmax[S]/KM+[S], was conducted to calculate Vmax and KM values.ATP hydrolysis was monitored using a NADH-coupled assay in a microplate reader as previously described . Reactio5’ CGA AAG CAC CGU AAA CGA AAA CUA GCA CCG UAA AGC AAG CU) annealed with a FAM-labeled 13mer (5’ CGU UUA CGG UGC U) in a 1.1:1 ratio in 10 mM Tris (pH 7.5), 50 mM NaCl, 1 mM EDTA by heating to 95°C for 3 minutes and cooling slowly to room temperature. Duplex unwinding experiments were conducted at room temperature with 25 nM FAM-labeled duplex and 500 nM “trap” 13mer RNA, complementary to the labeled strand, in buffer containing 50 mM Tris (pH 7.8), 120 mM NaCl, 2 mM MgCl2, 5% glycerol, 1 mM DTT, and 0.5 units/μL RNasin Plus RNase inhibitor (Promega) 1mer RNA  μM in 5%Q71L:Xpo1 ternary complex.To determine whether the binding of yeast Ded1 to Xpo1 is dependent on Ran[GTP] and the NES of Ded1, we analyzed the association of purified proteins by size exclusion chromatography (SEC). Since high concentrations of full-length Ded1 are poorly behaved in low salt conditions, we used a C-terminally truncated version of Ded1  for co-migration experiments. To maintain yeast Ran in a GTP-bound form, the Q71L variant was used (corresponding to Q69L in human Ran), which is deficient in GTP hydrolysis and has been used by others to stabilize karyopherin:cargo complexes . In the X. laevis ortholog An3 [When Ded1ΔC and Xpo1 were incubated together in the absence of Ran[GTP], however, the resulting SEC profile resembled that of the individual components. SDS-PAGE analysis of the fractions revealed that the migration pattern of Ded1ΔC was unaffected by Xpo1 alone , indicatolog An3 , 14, depolog An3 , 30.To date, structural information for how cargos bind to Xpo1 is limited to complexes containing snurportin 1 , 13 and Q71L. We then separated unbound components from the complex by preparative SEC. Fractions containing the ternary complex were collected and concentrated for SAXS experiments. Several dilutions of concentrated samples were used (from 6 mg/mL to 0.65 mg/mL), with the Rg remaining consistent for dilutions 0.65 mg/mL to 2.6 mg/mL. Analysis of the linear region of the Gunier plot for these data indicated that samples were free from aggregation  . As abovregation .g and Dmax for Xpo1 alone agreed well with published values [g and Dmax of Xpo1 bound to Ded1 and Ran[GTP] were significantly larger . In thed DAMMIF . An analQ71L. Similar to previous observations [D306N variant failed to yield RNA-dependent ATPase activity alone or in the presence of high concentrations of Xpo1 or Ran[GTP] (column 2).Although it was previously shown that Ded1 orthologs bind to Xpo1, the effect of karyopherin binding on Ded1 activity has not been reported. To investigate if the interaction between Ded1 and Xpo1 modulated Ded1 ATPase activity, we purified full-length Ded1 and conducted ATPase assays in the presence and absence of Xpo1 and Ran[GTP]rvations , 34, we et al. [sNES. When ATPase reactions containing Ded1sNES were titrated with increasing amounts of Xpo1 and Ran[GTP], the ATPase activity was reduced to the same extent as wild-type Ded1, approximately 2-fold. However, maximum inhibition was reached at lower Xpo1/Ran[GTP] concentrations with Ded1sNES . However, RNA-dependent ATPase activity of Ded1 was reduced when Xpo1 and Ran[GTP] were both present (columns 8 to 12). At approximately equimolar concentrations of Xpo1 and Ran[GTP], the reduction in activity was small (less than 1.5-fold) but significant. Increasing the molar ratio of Xpo1 and Ran[GTP] further reduced activity up to 2-fold, with saturation apparent at a ~20-fold molar equivalent of Xpo1 and Ran[GTP]. The relatively high concentrations of Xpo1 and Ran[GTP] required to show maximal repression suggested that ATPase inhibition was limited by weak binding of Ded1 with Xpo1 and Ran[GTP]. To test this, we constructed a Ded1 variant with an NES designed to have a high affinity or “supraphysiological” nuclear export sequence (sNES) based on principles outlined by Güttler et al. , which wDed1sNES , consistI13A variant, which fails to stably bind to Xpo1 and Ran[GTP]  and RNA (320 μg/mL) sufficient to saturate Ded1 alone, high concentrations of excess Xpo1 and Ran[GTP] may have reduced ATPase activity through sequestering RNA substrates away from Ded1. To determine whether Xpo1 and Ran[GTP] could reduce Ded1 ATPase without forming a ternary complex, we tested the Ded1Ran[GTP] . In contDed1I13A , demonstI13A variant demonstrated that Xpo1 and Ran[GTP] did not independently compete with Ded1 for RNA substrates, it was still possible that Xpo1/Ran[GTP] could sequester RNA substrates in a Ded1-dependent manner. As mentioned above, Xpo1 undergoes a conformational change upon binding of cargo and Ran[GTP], which bind cooperatively  could be titrated away with a fragment of Ded1 that should be competent for forming a complex, but should be unable to bind to RNA substrate or hydrolyze ATP. To effectively compete for Xpo1/Ran[GTP] binding, we used a C-terminally truncated protein that only includes the first 368 residues, Ded1(1–368), which excludes the second RecA-like lobe of the ATPase motor and therefore lacks ATPase activity. To ensure that this truncated Ded1 was an effective competitor for Xpo1 binding, the supraphysiological NES was introduced. Compared with Ded1 ATPase activity in the presence of 20-fold molar excess of Xpo1/Ran[GTP], preincubation of the reaction with saturating amounts of Ded1(1–368)sNES yielded ATPase rates similar to that of Ded1 alone . This higher concentration of RNA reflects an approximate 50 fold increase in KM for the Ded1:Xpo1:Ran[GTP]Q71L complex compared to Ded1 alone. In contrast, we observed saturation kinetics similar to wild-type Ded1 for the Ded1I13A variant alone and in presence of the Xpo1 and Ran[GTP] Q71L. Because saturation of ATPase activity could not be observed for the Ded1:Xpo1:Ran[GTP] Q71L complex, it is difficult to confidently assign a Vmax to the ternary complex. However, at high concentrations of whole cell RNA, the ATPase activity of the Ded1:Xpo1:Ran[GTP] Q71L complex was reproducibly higher than Ded1 alone. It appears that binding to Xpo1 and Ran[GTP] reduces the ability of Ded1 to be readily stimulated by mixed substrates, such as those present in whole cell yeast RNA. Because we were unable to observe saturation for the Ded1 ternary complex, it was possible that the Ded1 ternary complex is specifically stimulated by particular RNA species that may be present at low concentrations in whole cell extracted yeast RNA, and the higher KM value reflects limiting concentrations of these species. To test whether limiting concentrations of RNA species in our whole cell RNA samples were responsible for the observed shift in KM, we repeated our Michaelis-Menten analysis of Ded1 using single stranded poly(A) and poly(U) RNA substrates Fig 5a). bstrates . As repoGTP]Q71L , suggestsNES, lacking the second RecA-like lobe critical for RNA binding, was incubated with Xpo1 and Ran[GTP] (lanes 4 and 5).A simple mechanism by which Xpo1:Ran[GTP] might modulate ATPase and helicase activities of Ded1 is by directly effecting the substrate binding: Xpo1 and Ran[GTP] may occlude Ded1 RNA binding sites and reduce stable association of Ded1 with stimulating RNA substrates. To determine if Xpo1 and Ran[GTP] directly occlude the RNA binding surfaces of Ded1, we analyzed ATP-dependent binding to ssRNA with and without Xpo1/Ran[GTP]. To visualize RNA binding by Ded1, a 25mer FAM labeled RNA oligomer was incubated with full length Ded1, and native PAGE was used to separate bound and unbound species . BindingsNES alone bound RNA to the same extent as wild-type Ded1 (lane 15), when incubated with Xpo1 and Ran[GTP]Q71L additional super-shifted species were observed that migrated more slowly than bands corresponding to Ded1sNES:RNA complexes (compare lanes 15 and 17). In fact, nearly all of the Ded1sNES:RNA complexes were converted to these more slowly migrating super-shifted species when incubated with Xpo1 and Ran[GTP]Q71L. In contrast, the I13A variant of Ded1 did not yield additional super-shifted species in the presence of Xpo1 and Ran[GTP] (compare lanes 11 and 13). Slower migrating super-shifted species were also observed for wild-type Ded1 when incubated with Xpo1 and Ran[GTP], although unlike the Ded1sNES experiments, bands corresponding to Ded1:RNA complexes were still visible (lane 9). Given the NES-dependent behavior of these slower-migrating species, we interpret these bands to contain Ded1:Xpo1:Ran[GTP]:RNA complexes. The presence of super-shifted Ded1:Xpo1:Ran[GTP] complexes demonstrates that Ded1 is still capable of binding ssRNA in an ATP-dependent manner when bound to Xpo1. We also find that that overall ssRNA binding is reduced with tight association of Ded1 with Xpo1 and Ran[GTP] (M for non-specific substrates in our Michaelis-Menten analysis.RNA super-shifts dependent on Ded1 and AMP-PNP were also observed in the presence of Xpo1/Ran[GTP]. Interestingly, although Ded1Ran[GTP] . This reExportins such as Xpo1 have a number of functions associated with their nuclear pore trafficking activities. In addition to maintaining nucleo-cytoplasmic gradients, exportins can also prevent aberrant association of binding partners to their cargos , 39, 40,Binding and solution scattering data presented here demonstrate that Ded1 binds canonically to Xpo1 Figs . We founsNES, an ATPase dead fragment of Ded1, also blocked Xpo1-mediated repression. In agreement with diminishing ATPase activity of Ded1, the presence of Xpo1 and Ran[GTP] also reduced RNA helicase activity of Ded1 (ATPase repression by Xpo1/Ran[GTP], observed at moderate concentrations of whole cell yeast RNA extract, was sensitive to the nature of the Ded1 NES, which appeared tunable based on affinity . Weakeni of Ded1 . Affinitmax, but instead an increased KM of Ded1 for RNA in the presence of Xpo1 and Ran[GTP] (The apparent repression we observed was not due to a reduced VRan[GTP] . AlthougM of the Ded1:Xpo1:Ran[GTP] complex for RNA substrates suggests a reduction in affinity for RNA. For the DEAD-box helicases Dbp5 and eIF4A, RNA binding is regulated by Nup214 and PDCD4, respectively, which directly block RNA-interacting surfaces on the helicase domains and inhibit ATPase activity  complex alters Ded1 action.


In this paper I outline a fast method called KFOLD for implementing the Gillepie algorithm to stochastically sample the folding kinetics of an RNA molecule at single base-pair resolution. In the same fashion as the KINFOLD algorithm, which also uses the Gillespie algorithm to predict folding kinetics, KFOLD stochastically chooses a new RNA secondary structure state that is accessible from the current state by a single base-pair addition/deletion following the Gillespie procedure. However, unlike KINFOLD, the KFOLD algorithm utilizes the fact that many of the base-pair addition/deletion reactions and their corresponding rates do not change between each step in the algorithm. This allows KFOLD to achieve a substantial speed-up in the time required to compute a prediction of the folding pathway and, for a fixed number of base-pair moves, performs logarithmically with sequence size. This increase in speed opens up the possibility of studying the kinetics of much longer RNA sequences at single base-pair resolution while also allowing for the RNA folding statistics of smaller RNA sequences to be computed much more quickly. The prediction of the secondary structure of an RNA molecule has been a heavily researched area for the last few decades and still remains one of the important challenges in biophysics and computational biology today. Computational techniques for predicting the minimum free energy secondary structure of an RNA based on the Turner rules for RNA base-pair stacking interactions  were pioT = 3 plant virus, that the 3′ end of the viral genome transiently adopts different RNA structures which regulate translation by the RNA-dependent RNA polymerase (RdRp) (Plus-sense single-stranded RNA viruses (+ssRNA) provide a particularly salient example of the importance of the kinetics of RNA folding. The genomes of ssRNA viruses are under multiple evolutionary pressures to ensure that their genome is copied, that viral gene products are produced from the RNA genome  and that their genomes are selectively packaged during capsid assembly. Due to the multitude of functional roles that are required of ssRNA viral genomes during their life-cycle, RNA dynamics are expected to play a key role in regulating genome copying and viral protein production. For example, Simon and co-workers have recently demonstrated for Turnip Crinkle Virus (TCV), a small e (RdRp) . Similare (RdRp) . In addie (RdRp) –10. CompKinetic folding algorithms have been previously developed to probe the dynamics of RNA and its alternative structures which may be only occupied transiently –14. A keThis paper introduces several computational strategies which allow the Gillespie algorithm  to be apSi and Sj can be obtained from the free energy difference between the states ΔGij = Gj − Gi using:kij denotes the transition rate from state Si to state Sj. An alternative method for estimating transition rates used by Flamm, called Kawasaki dynamics  the transition rate for moving from S0 to Si, ki0, using Equation m). And second, the time to compute the m secondary structures Si which differ from S0 by an appropriate move along with the corresponding transition rate for the reaction ki0. When the difference between states Si and S0 is a single base pair, then the energy difference between states can be calculated in O(1) time and the computational cost to compute neighbours and transition rates will also scale as O(m), giving a total scaling of the basic algorithm as O(m) per update of the RNAs secondary structure.KFOLD implements the Gillespie algorithm  for compSi which neighbour a given RNA structure S0 into many smaller ones by finding neighbours of local secondary structures in the RNA. By doing this, only a small portion of the neighbour list will need to be updated between steps, decreasing the cost of calculating neighbours dramatically to approximately O(1). The second strategy uses a partial sum table to (i) compute the total flux Φ and, (ii) choose one of the reactions to fire in order Log2(N) time. The result of these two changes is a Gillespie algorithm for RNA kinetics in which the computational cost for computing updates to the secondary structure performs logarithmically with sequence size N. These two methods are discussed in the following sections.Although the KFOLD algorithm follows the same basic Gillespie protocol as KINFOLD, KFOLD achieves increased computational efficiency and a logarithmic cost per update of the RNA secondary structure by employing two strategies to reduce the computational costs described above. The first is to break up the problem of finding the structures L. The loop element can be characterized by the number of single WC base-pair elements in the loop, also called its degree d  with i < j of the loop which begin/end the loop. The sole exception to this rule is the special external loop which contains the first and last nucleotides and is labelled by . The inversion  allows the KFOLD programme to distinguish external loops from internal loops in the rare case when the last nucleotide of a sequence is base-paired to the first nucleotide by a lonely base pair. In this case, there will be both an internal loop labelled by  and an external loop labelled by . Figure NL = 4 loop elements, as illustrated in Figure L4 =  =  labels the special external loop which contains the nucleotides {1, 41, 42, 43, 44, 45}.The KFOLD algorithm represents a secondary structure of an RNA Figure  by a serdegree d , which dS0 represents the current RNA secondary structure while Si with i = {1, 5} represent the neighbours. Two neighbours (S1 and S2) can be associated with loop L1, while three  can be associated with loop L2 as illustrated in Figure S1 and S2 associated with loop element L1 and S0 is a base-pair addition/deletion in loop L1. In addition to breaking up neighbour computations, the KFOLD algorithm will also break up the computation of the total flux Φ by loop elements. For the example shown in Figure partial fluxes ϕ1 = k01 + k02 and ϕ2 = k03 + k04 + k05, and store these for later use in computing the total flux Φ = ϕ1 + ϕ2.The KFOLD algorithm breaks up the neighbour problem by computing neighbouring structures of the loop elements which make up the current RNA fold and storing the portion of the total transition flux that is due to possible transitions to these neighbours. Figure  S1 and S can be al associated with it as illustrated in Figure Si is selected during the Gillespie algorithm (i.e. S0 will transition to Si), new neighbouring structures of Si can be computed by looking at the base-pair additions/deletions that can occur in individual loop elements. The computational advantage stems from the fact that for the vast majority of loop elements in the RNA (i) the total number of reactions for the loop element, (ii) the transition rate for those reactions and (iii) the contribution to the total flux from that loop element, ϕl, will remain unchanged. Thus, one only needs to calculate new base-pair moves for a few (at most three) of the loop elements in the entire RNA structure after each secondary structure update. Figure L1 would not need to be recalculated when the structure S0, shown in Figure S5  opening of a base pair within the terminal helix; (v) helix morphing; and (vi) defect diffusion. The move set is the same as previously used by Flamm  . Since new neighbours only need to be recomputed for a couple of loop element after each update of the secondary structure, the total cost of updating the data structure of neighbours in the KFOLD algorithm should perform logarithmically with sequence size when averaged over a large number of steps.With this move set and strategy for computing neighbours, it can be shown that the computational cost to compute the partial flux and neighbours of a loop element appears to perform logarithmically over a long simulation (see Supplementary Table S1), while the growth for the total computational cost per Gillespie update is bounded by Log. However, since all but a maximum of three of the partial fluxes ϕl for each of the loop elements in an RNA structure will remain unchanged between Gillespie steps, a partial sum table can be used to reduce the computational cost of calculating the total flux Φ and selecting a transition to O(Log2N). Details of the partial sum table and how a specific transition is chosen can be found in the supplementary material with a specific example of the partial sum data structure illustrated in Supplementary Figure S2. The computational cost of calculating the total flux is demonstrated in Supplementary Figure/Table S1.In addition to determining neighbours, the Gillespie algorithm for RNA folding also requires that the total flux Φ = ∑r et al.  showed tExtract the total flux Φ from the partial sum table.r1 and r2 on the interval .Choose two random numbers r2)/Φ.Increment the time by τ = −ln or destroyed (such as when two helices merge), add or subtract these loops from the list of loop elements.If the move to state i for loop Li according to the move set as well as for any other loops that where created. Re-sum the partial sum table after the partial flux for each loop has been re-calculated. Goto STEP 1.Re-calculate reactions, transition rates and the partial flux ϕA generic description of the pseudo-code for the KFOLD algorithm is now given. Note that the pseudo-code makes no assumptions about the move set; i.e. the move set can be chosen to be the six moves shown in Figure S0 → S5 shown in Figure m possible ones. Supplementary Figure S1 demonstrates the runtime and performance of the KFOLD code. As can be seen in Supplementary Table S1, the cost of computing a Gillespie update in the KFOLD algorithm is expected to perform logarithmically according to the mathematical analysis - c.f. Supplementary Figure S1. The runtime analysis also shows that KFOLD can compute 107 RNA folding steps on large RNAs substantially faster than KINFOLD and in a similar time frame to small RNAs, while KINFOLD scales as O(N) for large N as expected.Supplementary Figure S2 illustrates the partial sum table and the process of choosing a reaction to fire in the KFOLD algorithm for the example transition https://github.com/edykeman/kfold or from the author's personal website at http://www-users.york.ac.uk/∼ecd502/.The KFOLD program is written in FORTRAN and the source code is available from GITHUB at Leptomonas collosoma. These two examples provide a simple illustration of the KFOLD algorithm and are used to benchmark its accuracy. The energy model used for the calculations is the Turner 99 energy model . Figure S4 as a function of time. As can be seen from the graph, KFOLD reproduces the correct equilibrium populations predicted using the partition function .To test the accuracy of the KFOLD algorithm and insure that it reproduces the equilibrium thermodynamics of an RNA at long times, the folding kinetics of the small 20nt RNA sequence UUGCUAAGCA ACCAUUGGUU was calculated. Using RNAsubopt from the ViennaRNA package, all possible structures satisfying canonical  base-pairing were calculated. The RNAsubopt program found 4127 different RNA states for the 20nt sequence. The energy of these structures were then computed using the Turner 99 energy model and the partition function calculated along with the probability of each state at thermal equilibrium. A total of 10S1) were also calculated. Figure In addition to calculating population kinetics, the first passage times for the RNA to fold from the completely denatured state to the MFE state (structure Leptomonas collosoma is a 56-nt RNA which adopts two different stem-loop structures (S1).The spliced leader RNA from ructures  and is pS1 or S2. Interestingly at around 100 ms, the structure S2 decays into the MFE structure, suggesting that S2 forms a temporary kinetic trap. This is further supported by the first passage times shown in Figure C. Here, one can see that there are two peaks in the distribution of folding times, one at around 1 μs and the other at around 100 ms. In combination with the kinetic trajectory shown in Figure B, this data suggest that there are two pathways to fold to the MFE state. The first pathway is fast and takes the structure directly into the MFE state. The second is a slow pathway which is interrupted by a temporary kinetic trap, the state S2. The time to resolve this kinetic trap and fold into the MFE state is roughly 100 ms. These results roughly match in vitro experiments  that many trajectories of the RNA are required to be computed in order to obtain reasonable statistics of the kinetics. The KFOLD algorithm addresses one of these issues by presenting an improvement to the scaling and performance of Gillespie-type RNA kinetics algorithms which model RNA folding in single base-pair addition/deletion resolution. As demonstrated above, the improved algorithm performs logarithmically with sequence size as opposed to the O(N)-O(N2) scaling of the traditional method. It should be noted that although KFOLD can compute updates to the secondary structure quickly, it still suffers from the remaining problem shared by all Gillespie-type folding models, i.e. the requirement for a large number of trajectories to compute accurate statistics. However, by speeding up the computation of RNA folding trajectories as demonstrated here, KFOLD should be capable of generating many more folding trajectories in the same CPU time as the traditional Gillespie procedure, thus reducing the overall time to generate the folding statistics for an RNA.Fast, efficient and accurate RNA secondary structure prediction and RNA folding kinetics algorithms remain one of the foremost challenges in computational biology. Gillespie-type models for RNA folding kinetics have suffered from two major drawbacks: (i) that the computational cost to compute a fixed number of changes to the secondary structure of the RNA scales with the number of secondary structure neighbours It is expected that through the use of additional computational techniques, such as coarse graining of RNA restructuring, memorization  or otherSupplementary Data are available at NAR Online.


Togaviridae) has recently caused several major outbreaks affecting millions of people. There are no licensed vaccines or antivirals, and the knowledge of the molecular biology of CHIKV, crucial for development of efficient antiviral strategies, remains fragmentary. CHIKV has a 12 kb positive-strand RNA genome, which is translated to yield a nonstructural (ns) or replicase polyprotein. CHIKV structural proteins are expressed from a subgenomic RNA synthesized in infected cells. Here we have developed CHIKV trans-replication systems, where replicase expression and RNA replication are uncoupled. Bacteriophage T7 RNA polymerase or cellular RNA polymerase II were used for production of mRNAs for CHIKV ns polyprotein and template RNAs, which are recognized by CHIKV replicase and encode for reporter proteins. CHIKV replicase efficiently amplified such RNA templates and synthesized large amounts of subgenomic RNA in several cell lines. This system was used to create tagged versions of ns proteins including nsP1 fused with enhanced green fluorescent protein and nsP4 with an immunological tag. Analysis of these constructs and a matching set of replicon vectors revealed that the replicases containing tagged ns proteins were functional and maintained their subcellular localizations. When cells were co-transfected with constructs expressing template RNA and wild type or tagged versions of CHIKV replicases, formation of characteristic replicase complexes (spherules) was observed. Analysis of mutations associated with noncytotoxic phenotype in CHIKV replicons showed that a low level of RNA replication is not a pre-requisite for reduced cytotoxicity. The CHIKV trans-replicase does not suffer from genetic instability and represents an efficient, sensitive and reliable tool for studies of different aspects of CHIKV RNA replication process.Chikungunya virus (CHIKV; genus Alphavirus, family  Togaviridae) is a mosquito-transmitted virus and the causative agent of chikungunya fever, which has affected millions during the 2004–2008 Indian Ocean outbreak, and since 2013 in the Caribbean region and the Americas [Chikungunya virus (CHIKV)  tail and contains two open reading frames (ORF). In the alphavirus genome, there are four conserved sequence elements (CSEs), three of which are required for RNA replication: the 5′ untranslated region (UTR), a 51-nt replication enhancing element in the beginning of the first ORF, and the end of the 3′ UTR followed by at least 11 adenine residues . The fouThe alphavirus ns proteins have several known enzymatic functions: nsP1 acts as the viral RNA capping enzyme , nsP2 istrans-replication systems so far described for SINV and SFV. These systems have been used to study the biogenesis of spherules [trans-replication system has uncovered several new biological properties. First, it was found that the size of alphavirus spherules is determined by the length of replicating RNA [trans-complementation systems have also been successfully used to study the composition of the replicase complexes of flaviviruses, another group of positive-strand RNA viruses [During virus replication, the expression of ns proteins is coupled with RNA replication. This generates a negative feedback loop for mutations reducing RNA replication. As a result, such mutations are almost always reverted, pseudoreverted and/or compensated by second-site mutations ,39–41, epherules ,45 and fpherules . Furtherting RNA . Second,ting RNA . Similar viruses ,49.trans-replication systems. These systems were successfully used to develop CHIKV replicases and replicons containing enhanced green fluorescent protein (EGFP) insertion in nsP1 or with peptide tags attached to the C-terminus of nsP4. The tagged trans-replicases enabled efficient spherule formation confirming that the essential steps associated with RNA replication were correctly reproduced in this system. The effects of mutations, associated with noncytotoxic phenotype of CHIKV, on the trans-replicase were similar to those observed in the context of replicons and genomes. Thus, CHIKV trans-replication system represents a powerful tool applicable for functional studies of CHIKV nsPs, replicase complexes and virus-host interactions; it should also be useful for detailed analysis of inhibitory properties of compounds affecting CHIKV replication.Here we describe the construction, properties and use of CHIKV 2 atmosphere; 10% fetal bovine serum, 100 U/mL penicillin and 0.1 mg/mL streptomycin were added to growth media. BHK-21 cells (ATCC CCL-10) were grown in Glasgow's Minimal Essential Medium  containing 2% tryptose phosphate broth and 200 mM HEPES. BSR T7/5 (hereafter BSR) cells, a derivative of BHK-21 cells stably expressing T7 RNA polymerase [All cells were grown at 37°C in 5% COlymerase , were culymerase  and U2OSCHIKV sequences were based on the isolate LR2006 OPY1 representing the East Central South African genotype. The sequence encoding for ns polyprotein was optimized according to human codon usage (hereafter this coding sequence is referred to as P1234) and obtained as synthetic DNA . A construct, where only 120 codons from the 5′ end and 52 codons from the 3′ end of CHIKV ns ORF were to correspond to human codon usage, was made for comparison. It contains native codon usage in 93% of ns polyprotein encoding region and was designated P1234-NAT.GAA.In order to express ns polyprotein, two different approaches were used. First, expression of mRNA for ns polyprotein was driven by the RNA polymerase of bacteriophage T7. To achieve efficient ns polyprotein translation from non-capped transcripts, the P1234 was placed under control of the internal ribosomal entry site (IRES) of encephalomyocarditis virus (EMCV) . To incrA matching set of plasmids, designed to express template RNAs for CHIKV replicase from T7 and CMV promoter-based vectors, was constructed as follows. All template RNAs were designed to contain following elements: 1) the full-length 5′ UTR of CHIKV followed by the region encoding for the 77 N-terminal amino acid residues of nsP1 (this region contains the 51-nt CSE); 2) sequence corresponding to the SG promoter and intergenic region of CHIKV (spanning residues -78 to +69 with respect to the start position of SG RNA); 3) the 3′ end (110 residues) of the 3′ UTR of CHIKV followed by 60 adenine residues and HDV antisense strand ribozyme. The elements 1, 2 and 3 were separated from each other by short polylinkers that were subsequently used for insertion of sequences coding for marker proteins.Renilla luciferase (Rluc) was fused with ORF encoding the 77 N-terminal residues of nsP1 and the sequence encoding for Tomato fluorescent marker protein was inserted under the CHIKV SG promoter; the resulting plasmid was designated T7-Rluc-Tom (Gaussia luciferase (Gluc) were inserted using the same approach, generating T7-Fluc-Gluc  promoter and terminator of T7 RNA polymerase. Sequence containing all the elements was obtained as synthetic DNA and cloned into pUC57Kan vector. Subsequently, the sequence encoding for Rluc-Tom . Alternaluc-Gluc . To obtaluc-Gluc , as prevluc-Gluc .ACTAGTCTCGAGCCCGGG-3′5′- (sites for SpeI and SmaI underlined) was inserted using PCR-based mutagenesis into the following positions of T7-P1234 and CMV-P1234 plasmids: 1) after codon 492 (site 1A), 497 (site 1B), 516 (site 1C) or 525 (site 1D) of nsP1; 2) after codon 466 (site 2A) or 618 (site 2B) of nsP2; 3) after codon 383 of nsP3. The sequence encoding for EGFP flanked with Gly-Gly linkers was fused with adapters containing sites for SpeI (5′ end) and SmaI (3′ end) endonucleases, amplified by PCR and inserted into the positions listed above. The resulting constructs were designated (either CMV- or T7-) P1E234-A, P1E234-B, P1E234-C, P1E234-D, P12E34-A, P12E34-B, and P123E4. Plasmid T7-P123E4GAA was obtained from T7-P123E4 by changing the Gly-Asp-Asp motif in nsP4 to Gly-Ala-Ala. To fuse EGFP to the C-terminus of nsP4 the flexible linker with sequence Ser-Gly-Gly-Ser-Gly-Gly was added to the N-terminus of EGFP. This fusion was achieved by PCR-based mutagenesis, giving T7-P1234E and CMV-P1234E.Polylinker with sequence WSHPQFEKMDYKDHDGDYKDHDIDYKDDDDK; 2) HF-tag consisted of HA- (bold) and 3xFLAG-tag (underlined): YPYDVPDYAMDYKDHDGDYKDHDIDYKDDDDK; 3) HS-tag consisted of two copies of HA-tag (bold) followed by Strep-tag (underlined): YPYDVPDYAMYPYDVPDYAMWSHPQFEK. To attach these tags to the C-terminus of nsP4 a flexible linker with sequence Gly-Gly-Gly-Gly-Ser was added to the N-terminus of the tag. Sequences encoding for such tags were obtained as synthetic DNAs and fused with the 3′ end of the P1234 in T7-P1234 and CMV-P1234 plasmids resulting in (either CMV- or T7-) P1234SF, P1234HF, and P1234HS expression constructs.To insert sequences recognized by commercially available antibodies and/or purification systems three peptide tags with a similar length were designed: 1) SF-tag consisted of the sequences of Strep- (bold) and 3xFLAG-tag (underlined): EK34), Lys192 to Asn (CMV-P12KN34), insertion of Gly-Glu-Glu-Gly-Ser sequence after amino acid residue 647 (CMV-P125A34) and Pro718 to Gly (CMV-P12PG34). In addition, two constructs containing nsP2 region harboring combinations of mutations were made: CMV-P12EKPG34 and CMV-P125APG34.Point mutations, resulting in the following changes of encoded nsP2 protein, were made in CMV-P1234 using PCR-based site directed mutagenesis; designations of the constructs are provided in parentheses: Glu117 to Lys (CMV-P125′-ACTAGTCTCGAGCCCGGG-3′) into selected positions of Repl-wt: after codon 516 of nsP1, after codon 486 of nsP2 or after codon 383 of nsP3; sequence encoding for EGFP was inserted as described above. The resulting replicons were designated as Repl-1E, Repl-2E and Repl-3E.To construct CHIKV replicons expressing nsP4 with SF- or HF-tag at its C-terminus the coding region of nsP4 was fused with that of SF- or HF-tag as described above. In addition, the SG promoter of CHIKV was inactivated by synonymous changes introduced into the region encoding for the 27 C-terminal amino acid residues of nsP4. These replicons were designated Repl-4SF and Repl-4HF. pICRES1-SG-Rluc [SF and ICRES-4HF. All these manipulations were done by using synthetic DNA fragments and subcloning procedures.pChikRepl (hereafter referred to as Repl-wt), a plasmid containing the cDNA of CHIKV replicon vector , was usein vitro using the mMESSAGE mMACHINE SP6 Transcription kit (Ambion), to obtain RNAs for transfection of BHK-21 cells. These procedures as well as infectious center assay (ICA) were performed as previously described [Plasmids containing the cDNA of CHIKV replicons or genomes were linearized and transcribed Renilla luciferase assay lysis buffer (Promega) and Fluc and Gluc activities were analyzed using the Dual-Luciferase Reporter Assay kit and Glomax SIS luminometer (Promega); total amount of protein in cell lysates was measured using Bio-Rad protein assay system according to the manufacturer's protocols. In some experiments aliquots of growth media were collected at selected time points and Gluc activity was measured using Renilla Luciferase Assay kit (Promega).The minicircle forms of CMV-P1234 and MCC-P1234 were obtained as described . These mtrans-replicase transfected cells) post transfection with SDS gel loading buffer , and proteins were separated by 10% SDS-PAGE, transferred to nitrocellulose membranes, and detected using primary antibodies against CHIKV nsP1, nsP2 (recognizes amino acid residues 1–470), nsP3 (recognizes amino acid residues 1–320) and nsP4 (in-house), FLAG , EGFP (in-house) or β-actin . The membranes were then incubated with appropriate secondary antibodies conjugated to horseradish peroxidase  and proteins were visualized using ECL Immunoblot Detection kit .Cells were lysed at 24 h (virus/replicon RNA transfected cells) or 18 h (® reagent (Life Technologies). Equal amounts of total RNAs (1 μg) were denatured for 10 min at 70°C in 2-fold RNA loading dye (Thermo Scientific), cooled on ice and separated on 1% agarose 6% formaldehyde containing denaturing gel using 1xMOPS buffer. RNA was transferred to a Hybond-N+ filter  and fixed using a UV Stratalinker 1800 (Stratagene). A digoxigenin (DIG)-labeled RNA, complementary to the last 110 residues of the 3′ UTR region of CHIKV genome, was generated using a DIG hybridization kit (Roche) and used as a probe. Filters were hybridized overnight; blots were washed and developed according to the manufacturer's protocols .BSR or U2OS cells were co-transfected with plasmid DNAs coding for CHIKV replicase and RNA template as described above. At 18 h post transfection, total RNA was extracted using TRIzol4 U2OS cells were seeded on glass coverslips and incubated overnight at 37°C prior to transfection. For replicon vectors, transfection was performed using 450 ng of in vitro transcribed Repl-wt, Repl-1E, Repl-2E, Repl-3E or Repl-4SF RNAs. For trans-replication system, cells were co-transfected using 250 ng of CMV-Rluc-Tom plasmid and 200 ng of CMV-P1234, CMV-P1E234, CMV-P12E34, CMV-P123E4 or CMV-P1234SF plasmids. At 18 h post transfection cells transfected with replicon RNAs or co-transfected with CMV-P1234+CMV-Rluc-Tom or CMV-P1234SF+CMV-Rluc-Tom were fixed with 4% paraformaldehyde buffer, quenched with NH4Cl and permeabilized with 0.1% Triton X-100. dsRNA and nsP4 with SF-tag were detected using mouse monoclonal antibodies J2  or M2 (Sigma-Aldrich) as primary antibodies respectively and Cy5-conjugated anti-mouse antibody (Abcam) as secondary antibody. Samples were mounted with ProLongGold containing DAPI (Molecular Probes). The cells co-transfected with CMV-Rluc-Tom and CMV-P1E234, CMV-P12E34 or CMV-P123E4 were fixed with 4% paraformaldehyde buffer and immediately mounted as described above. In all cases EGFP-tagged ns proteins were detected using EGFP fluorescence. Imaging was done with Leica TCS SP5 confocal microscope (HCX APO 63x/1.30 Corr glycerol objective) or Leica TCS Sp5II HCS A confocal microscope (HCX PL APO 63x/1.2 W Corr/0.17 CS water objective). The images were analyzed using ImageJ software.For immuno-fluorescence imaging, 2x104 BSR cells were seeded on 35 mm glass-bottom P35G-2-14-C-Grid dishes (MatTek) and incubated overnight at 37°C. The cells were then co-transfected using 1.25 μg of plasmids expressing the CHIKV replicase and 1 μg of T7-Tom-Rluc (for co-transfection with T7-P123E4GAA a T7-Rluc-Tom-Vis was used instead). At 16 h post transfection the cells were fixed with 2% glutaraldehyde (Sigma-Aldrich) in 0.1 M sodium-cacodylate buffer  for 20 min at room temperature, washed three times with 0.1 M NaCac buffer and left in the last wash. The cells were immediately imaged using a Leica TCS Sp5II HCS A confocal microscope with the HC PL APO 20x/0.7 CS (air) objective lens. Fluorescent and differential interference contrast (DIC) images of cells containing replicating template RNA (determined by presence of Tomato marker) were obtained for each sample except for cells transfected using T7-P123E4GAA plasmid; in this case cells expressing both nsP3-EGFP and mCherry were selected instead. The gridded dishes were marked in selected areas where positive cells were spotted during confocal imaging, and prepared for transmission electron microscopy as previously described [7.5x10escribed . PositivStatistical analysis was carried out using original datasets and GraphPad Prism software. Student’s paired t-test was used for comparison of two sets of data. To compare means of three or more samples one-way ANOVA Sidak’s multiple comparisons test was used.trans-replication systems for CHIKV that could be used in multiple cell types, to study basic biology of CHIKV as well as virus-host interactions. So far most alphavirus trans-replication studies have utilized bacteriophage T7 RNA polymerase to express the replicase and its template RNA [trans-replication systems.We set out to develop late RNA ,44–46. Alate RNA  but its The design of a cassette for T7 promoter-based expression of CHIKV ns polyprotein is shown in trans-replication systems [The codon usage of alphaviruses represents a compromise between codon usages of their vertebrate host and mosquito vectors. For SFV, both native and codon-optimized replicase expression constructs can be used as parts of  systems ,47; howetrans-replicase activity, we first compared CMV-P1234, which contains an intron in the leader sequence, with MCC-P1234 lacking introns. In U2OS cells co-transfected with CMV-P1234 + CMV-Fluc-Gluc or with MCC-P1234 + CMV-Fluc-Gluc the former combination yielded 3.2–3.8-fold higher Gluc activity. Second, the expression cassettes in MCC-P1234 and CMV-P1234 vectors can be converted into minicircles devoid of bacterial DNA; this has been shown to increase expression levels [To further maximize n levels ,57. CompNext, the expression kinetics of Gluc reporter in BSR cells transfected with CMV- and T7 promoter-based systems were compared. For both, Gluc activity was high already at 8 h post transfection and approached a plateau by 16–18 h post transfection . Based otrans-replication system was tested in two human  and three rodent  cell lines; BSR cells were also co-transfected with T7-P1234 + T7-Fluc-Gluc. Gluc is encoded by the second ORF of the template RNA  or Gluc (for SG RNA synthesis) activities.The analysis of viral RNAs revealed that the levels of full-length (“genomic”) transcripts were greatly boosted by active CHIKV replicases . The oriluc-Gluc  indicateluc-Gluc  and low luc-Gluc . In the luc-Gluc . Howeverluc-Gluc . Overallluc-Gluc . As the luc-Gluc  the Gluctrans-replication system, however, changes introduced into the replicase proteins cannot be reverted. This should offer possibilities to study the effects of tags and other modifications in ns proteins on the RNA replication as well as on the localization and other functions of these proteins.Recombinant alphaviruses carrying immunological, affinity, luciferase or fluorescent tags in their ns proteins have been used to study various aspects of the viral life cycle ,38,58,59E4) had little to no effect on the template RNA replication/transcription (E34-A); in contrast insertion of EGFP after amino acid residue 618 of nsP2 (P12E34-B) reduced template RNA replication and transcription at least 100-fold (E234-A), 497 (P1E234-B) or 525 (P1E234-D) resulted in prominent reduction of template RNA replication and transcription (E234-C) caused milder effects, revealing this to be the most suitable site for EGFP insertion. EGFP fused to the C-terminus of nsP4 allowed for RNA replication and transcription, confirming that nsP4 with such tag was functional. However, the activity of nsP4-EGFP fusion protein was severely compromised: replicase harboring such mutation yielded no more than 1% template RNA replication or transcription compared to wild type replicase (trans-replication systems in U2OS cells (trans-replicases (hereafter referred to as P1E234 and P12E34) for further characterization.EGFP was inserted into four different positions located in the C-terminal region of nsP1, into two positions in nsP2 corresponding to those previously used to tag SINV nsP2 , into thcription . The sam100-fold . The effcription . In conteplicase . All theOS cells , showingtrans-replication systems. Transfection of BSR cells with the T7 promoter-based vectors revealed that the negative effect of the SF-tag on template RNA replication/transcription was the smallest. The HF-tag greatly reduced the activity of the CHIKV trans-replication system, and the HS-tag reduced replication of template RNA to a background level /μg RNA in BHK-21 cells) was only one-log lower than that of ICRES-wt (~5.5x105 PFU/μg RNA). In contrast, the rescue of ICRES-4HF occurred at a much lower level (~9.1x102 PFU/μg RNA). However, the progeny of ICRES-4HF reached a titer of 2.0x108 PFU/mL; even higher than other viruses used in this experiment (1.2x108 PFU/mL for ICRES-wt and 6.3x107 PFU/mL for ICRES-4SF). Western blot analysis of infected cells revealed that all three viruses expressed ns proteins roughly at the same level  had no apparent effect on the ns protein levels (KN34) resulted in increased expression of all ns proteins (PG34) or in combination with EK mutation (P12EKPG34) (5A34); again this is coherent with reduced cytotoxicity of corresponding replicons [Mutations associated with noncytotoxic properties of nsP2 inhibit its ability to induce shutdown of RNA polymerase II mediated transcription . Thus, tn levels . KN mutaproteins , most li2EKPG34) ; these eeplicons .KN34 + CMV-Fluc-Gluc did not exceed background levels  or nsP2 NTPase/triphosphatase/helicase (P12KN34) were unable to replicate/transcribe the template RNA  that vi P1234HS : their i234HS  has already been used to visualize nsP4, which was not detectable by nsP4-specific antibodies in CHIKV infected cells [SF can also be used for analysis of interactions between CHIKV nsP4 and cellular proteins as has been done for SINV [The CHIKV proteins . Such tred cells . ICRES-4for SINV . CHIKV ifor SINV  making ifor SINV  and nsP3for SINV ,58.trans-replication system can be applied for the development of antiviral strategies. It has already been, to some extent, used for analyzing the molecular bases of attenuation of CHIKV Δ5nsP3 virus [trans-replication system is also suitable for the discovery and subsequent analysis of inhibitors affecting CHIKV replicase formation and function. Thus, with the T7 promoter-based version of the system, it can be analyzed which exact step of RNA replication  is affected by the compounds. The trans-replicase based assay would also simplify identification of the precise functions affected by different inhibitors. For example, in the context of virus infection, the amounts of ns proteins  may simply be too low to enable detection of the effect of an inhibitor on e.g. ns polyprotein processing, or on the intracellular localization of viral ns proteins. Uncoupling the replicase expression from RNA replication makes such assays feasible; the availability of mutant and tagged forms of trans-replicase provides further advantages for such studies.Finally, CHIKV P3 virus , a highlP3 virus . The tra


Long non-coding RNAs (lncRNAs) represent a numerous class of non-protein coding transcripts longer than 200 nucleotides. There is possibility that a fraction of lncRNAs are not functional and represent mere transcriptional noise but a growing body of evidence shows they are engaged in a plethora of molecular functions and contribute considerably to the observed diversification of eukaryotic transcriptomes and proteomes. Still, however, only ca. 1% of lncRNAs have well established functions and much remains to be done towards decipherment of their biological roles. One of the least studied aspects of lncRNAs biology is their engagement in gene expression regulation through RNA-RNA interactions. By hybridizing with mate RNA molecules, lncRNAs could potentially participate in modulation of pre-mRNA splicing, RNA editing, mRNA stability control, translation activation, or abrogation of miRNA-induced repression. Here, we implemented a similarity-search based method for transcriptome-wide identification of RNA-RNA interactions, which enabled us to find 18,871,097 lncRNA-RNA base-pairings in human. Further analyses showed that the interactions could be involved in processing, stability control and functions of 57,303 transcripts. An extensive use of RNA-Seq data provided support for approximately one third of the interactions, at least in terms of the two RNA components being co-expressed. The results suggest that lncRNA-RNA interactions are broadly used to regulate and diversify the human transcriptome. There are 145,331 lncRNAs known in the human transcriptome  loci in mammalian cells [Some of the mechanisms mentioned above, like modulation of pre-mRNA splicing, RNA editing, mRNA stability control, and abrogation of miRNA-induced repression might involve interactions between long non-coding RNA and other RNA molecules. Recently published data suggest a great potential in lncRNA-mediated regulation via base-pairing with complementary RNAs but we are only starting to understand its significance. For instance, there are several lncRNAs known to play a role in splicing regulation, presumably by splice-site masking and subsequent blocking of spliceosome assembly. They require an extensive complementarity with regulated pre-mRNA molecule ; such coan cells . In a sian cells  and giveFinally, lncRNAs have been implicated in both positive and negative regulation of mRNA stability. For instance, Alu repeat-containing lncRNAs are involved in targeting mRNA transcripts for Staufen-mediated decay (SMD) pathway . SMD is Motivated by a growing body of evidence that lncRNA-RNA interactions play crucial roles in driving transcriptome diversity, we performed a large-scale identification of human transcripts able to hybridize with lncRNA molecules. To this point, we used a similarity-search based approach with custom substitution matrix to score the alignments. Subsequent analyses showed that a number of interactions can be associated with lncRNA functions in pre-mRNA splicing, mRNA editing, Staufen-mediated decay, or modulating miRNA-dependent regulation; altogether, as many as 57,303 transcripts could be affected. We used an extensive set of RNA-Seq libraries to calculate transcript expression values, which enabled us to check whether the two components of RNA-RNA duplex are co-expressed, therefore able to interact. It occurred that in case of one third of all interactions both RNAs are co-expressed in at least one sequencing library. Taken together, our results suggest extensive roles of lncRNAs in transcript processing and gene expression regulation through base-pairing with both mRNA and pre-mRNA molecules.lncRNA-mRNA interactions, and 56,735,686 interactions between lncRNAs and pre-mRNAs. 3,788,306 interactions between lncRNAs and pre-mRNAs span at least one exon-intron junction and they were dubbed lncRNA-pre-mRNA interactions. These numbers refer to the transcript level and therefore different splice forms of a single gene may come into identical interactions with splicing isoforms of another gene. At the gene level there are 8,796,210 unique gene pairs that interact. Taking into account that 38,225 distinct Ensembl genes and 45,517 lncRNA genes were considered in the analysis, this corresponds to 0.098% of all possible gene-gene pairs. 0.21% of lncRNA-mRNA interactions and 0.82% of lncRNA-pre-mRNA interactions are in cis i.e. they occur between genes that occupy the same genomic loci but are transcribed from the opposite strands  and pre-mRNAs . Half of the interactions are formed between lncRNAs and non-coding transcripts. Those involving protein-coding transcripts most frequently occur within 3' UTRs, constituting 39.22% and 37.76% in lncRNA-mRNA and lncRNA-pre-mRNA interactions, respectively.The analysis revealed 15,082,791 interactions between lncRNAs and human transcripts, referred to as  strands . The intmRNA interactions that could bear regulatory roles.The interactions were checked against occurrences of mRNA editing sites as well as miRNA and splicing factor binding regions that could be masked by complementary lncRNA molecules. We also searched for Alu repeats within lncRNA-pre-mRNA interactions, 2,692,097 overlap at least one alternative splice site. Altogether 21,456 alternative splice sites across human genome could be affected in this way, which involves 24,020 distinct transcripts. An example of such interactions is presented in Out of 3,788,306 lncRNA-mRNA interactions , followed by those located in non-coding transcripts (38.78%), 5' UTRs (4.61%) and coding regions (2.72%). Finally, using RepeatMasker we found 24,886 transcripts with Alu repeat in their 3' UTRs. In case of 7,439 of them, Alu was entirely located within lncRNA-mRNA interaction region. Such a configuration was shown to target protein-coding transcripts to Staufen-mediated decay pathway [Then we investigated potential regulatory roles of ractions . Using m pathway .lncRNA-mRNA interactions and 28.84% of lncRNA-pre-mRNA interactions both RNA components are co-expressed in at least one library.In order to estimate what fraction of identified interactions are possible in terms of the two RNA components being co-expressed, we calculated transcript expression values using 63 RNA-Seq libraries, listed in In this work we applied a similarity-based approach to identify RNA-RNA interactions across the human transcriptome. Ideally, one would apply thermodynamic functions to this task in order to calculate energies of RNA-RNA interactions and take into consideration secondary structures of both RNA components. An RNA molecule might fold in a manner that makes the complementary region inaccessible for the other component. However, the analyzed sequences are quite long  and secondary structure prediction for them would be highly ineffective. The problem could be ameliorated by exploiting evolutionary conservation data for RNA structures, however lncRNAs are poorly conserved across species . MoreoveTo test the accuracy of our pipeline, we followed a recently proposed method, with modifications . First, lncRNA-mRNA interactions and 1,092,516 (28.84%) lncRNA-pre-mRNA interactions both RNA components are co-expressed in at least one library. These numbers suggest that a large proportion of found interactions may indeed exist in a cell. It might be, however, that the values are underrated, as we applied quite stringent criteria for expression calculation, taking into consideration only those sequencing reads that map uniquely to a given transcript, especially that analyzed genes have on average 6.62 isoforms and they overlap extensively. For the same reason the actual number of transcripts that get transcribed might be significantly higher. Then we calculated the expression values in a modified manner, where a read was required to map uniquely to a gene (instead of a transcript). With this approach we were able to detect expression of 170,798 (57.09%) transcripts. However, this procedure, alike other popular approaches, e.g. RSEM [In order to support the predictions with transcriptomic data, we calculated transcript expressions values across 63 human RNA-Seq libraries, spanning a number of human tissues and cell lines. Products of RNA polymerase II possess a polyA tail at their 3' end, a feature being exploited in RNA-Seq technology to deplete ribosomal RNA fraction in the sequencing library. However, a number of non-coding transcripts are products of RNA polymerase III and lack polyA tail. Therefore, we took advantage of 27 RNA-Seq libraries without polyA selection, i.e. where RiboMinus depletion of rRNA was applied. Altogether, out of 299,154 distinct human transcripts (lncRNAs from NONCODE and Ensembl transcripts), 139,645 (46.68%) were expressed in at least one library. 24.1% of transcripts were expressed in libraries without polyA selection but only 1.7% of all sequences were expressed uniquely in these libraries. Next, we found that in case of 5,480,029 (36.33%) .g. RSEM , does notrans and only 0.21% and 0.82% of them are in cis, in lncRNA-mRNA and lncRNA-pre-mRNA interactions respectively. A higher proportion of cis interactions in the latter group can be explained by the fact that transcripts being close each other in a genome have higher chance to interact and, additionally, they base-pair without mismatches, thus providing higher hybridization energies. Both features might be critical for efficiency of base-pairing and could have functional consequences in splicing regulation, owing that this is a fast process, occurring co-transcriptionally. Regarding protein-coding transcripts, the lncRNA-mRNA interactions are predominantly located in 3' UTRs (39.22%) versus 5.19% in 5' UTRs, 4.10% in coding sequences and 2.19% spanning both CDS and UTR; the remaining interactions are found in non-coding transcripts (49.30%). This observation can be partially explained in terms of region lengths. For example, the cumulative length of all human 5' UTRs and 3' UTRs is 20,989,925 and 73,183,804 nucleotides respectively, thus there are higher chances a lncRNA will interact with a 3' UTR. Moreover, 3' UTRs bear higher proportion of repetitive elements (11.88%) than 5' UTRs (8.88%) and the whole transcriptome (8.43%), which adds up to the preference of interactions to occur in 3' UTRs, especially that lncRNAs possess even higher proportion of repeats (25.83%). Notably, the observed preference to base-pair with 3’UTRs is exactly what one would expect from the biological point of view, as 3' UTRs play critical roles in gene expression regulation. Still, however, in case of lncRNA-mRNA interactions spanning miRNA binding sites, there is preference towards coding sequences (37.59%), compared to only 29.78% of interactions located in 3’UTRs. We postulate this could be linked to lncRNA functions in preventing RISC complex from binding to the coding regions, leading to increased target specificity of microRNAs. In lncRNA-pre-mRNA interactions, alignments within 3’ UTRs (6.57%) are outnumbered by those within 5’ UTRs (16.2%). This cannot be simply explained by the requirement that alignments span splice sites, because generally almost equal numbers of splice sites can be found within 5’ and 3’ UTRs in transcripts of interest, 34,949 and 33,141 respectively. Keeping in mind that protein-coding transcripts have almost eightfold more introns in 5' UTRs than in 3' UTRs, while disfunctional transcripts, like those targeted for nonsense-mediated decay (NMD) pathway, tend to have an elevated number of introns downstream coding region, we hypothesize that the preferential occurrence of interactions within 5' UTRs may indicate involvement of lncRNAs in RNA stability control mechanisms in a cell.The interactions are predominantly found in Our analysis indicated altogether 57,303 transcripts that could be regulated by means of lncRNA-RNA interactions. This would be achieved in the following ways: i) masking splice sites and other splicing signals, ii) competing with miRNAs for binding sites on transcripts, iii) promoting mRNA editing events, and iv) hybridizing with 3' UTRs of Alu-containing transcripts and targeting such mRNA molecules for degradation through Staufen-mediated decay pathway. Genome and transcriptome sequences as well as corresponding annotation data were retrieved from Ensembl 75  using Bilastal from LAST package [lastal is that other popular similarity-search tools, like BLAST, do not allow user-supplied scoring matrices, although BLAST has already been used in a similar task [Lastex, from the same package, enabled us to estimate a threshold value for alignment scores. We set this threshold to 107, which corresponds to less than one alignment expected to occur by chance. In the interaction search procedure, lncRNAs from NONCODE constituted a database, while transcript sequences were used as a query. When looking for lncRNAs base-pairing with pre-mRNAs, the query transcripts contained intron sequences; any intronic sequences distant by more than 250 bases from 3' or 5' splice sites were masked with N characters using Python scripts and based on exon coordinates from Ensembl. Here, the threshold value for alignment score was set to 108, as estimated with lastex. Having the lastal results in MAF format, we applied a set of in-house Python scripts to process the data and prepare them for subsequent steps: (i) the coordinates of intermolecular alignments were converted to genomic positions, (ii) the coordinates were merged to unique positions in the genome, (iii) the MAF files were converted to BED format.We used  package  to identlar task . In the lar task . AdditioInteractions between lncRNAs and pre-mRNAs were filtered to keep only those that spanned exon-intron borders. These alignments, after converting to BED format with genomic positions, were superimposed with StarBase 2.0 coordinates for human splicing factors. It was required that both features occupied the same DNA strand and putative splicing factor binding site was located entirely within the interaction region. Alternative splice sites were identified based on exon coordinates from Ensembl using Python scripts.merge [StarBase 2.0 coordinates of putative miRNA binding sites were put into a single file and converted to non-overlapping coordinates with BEDTools merge  tool to merge  was perfhttp://www.repeatmasker.org). They were required to be entirely located within the lncRNA-mRNA alignment region and additionally in a 3' UTR of protein-coding transcripts.Coordinates of Alu elements in human transcripts were identified with RepeatMasker  lncRNA NONHSAT001705 base-pairs with pre-mRNA of ENST00000413854 in a way that the alignment spans an alternatively spliced exon as well as parts of surrounding introns. b) NONHSAT001705 gets expressed predominantly in white blood cells and SK-N-SH cell line, which was originally isolated from a bone marrow. On the other hand, ENST00000413854, a transcript of RHCE gene coding for Rh blood group antigens is located on chromosome 1 close to NONHSAT001705, suggesting the interaction could have functional consequences.(PDF)Click here for additional data file.S1 FileThe file contains a list of all human transcripts putatively affected by lncRNAs through one of the following mechanisms: i) masking splice sites and other splicing signals, ii) competing with miRNAs for binding sites on transcripts, iii) promoting mRNA editing events, and iv) hybridizing with 3' UTRs of Alu-containing transcripts and targeting mRNA molecules for degradation through Staufen-mediated decay pathway.(TXT)Click here for additional data file.S2 Filelastal behavior.The matrix is constructed in a way that enables identification of G:T (G:U) pairs, which is distinct from default (TXT)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.