The chemical probing and MS data for the free riboswitch show high exposure to solvent of the uridine nucleobases U7, U8, U13, U14, U18 as part of the proposed internal and apical loops, but those of U10 and U21 as part of the proposed internal loop were found to be far less exposed than expected. Thus, our data are in better agreement with the proposed secondary structure of the riboswitch in complexes with aminoglycosides than with that of free RNA. For the riboswitch in complexes with neomycin B, ribostamycin, and paromomycin, we found highly similar CMC+‐modification patterns and excellent agreement with previous NMR studies. Differences between the chemical probing and MS data in the absence and presence of the aminoglycoside ligands were quantitative rather than qualitative  and can be rationalized by stabilization of both the proposed bulge and the apical loop by aminoglycoside binding. Our study shows that chemical probing and mass spectrometry can provide important structural information and complement other techniques such as NMR spectroscopy.High‐resolution mass spectrometry was used for the label‐free, direct localization and relative quantification of CMC High‐resolution top‐down mass spectrometry can directly localize and quantifiy nucleobase modifications from chemical probing reactions of RNA, providing important structural information. This study shows that high‐resolution mass spectrometry can be used for the localization and site‐specific, relative quantification of CMC+‐labeled RNA to within ∼5 %. We attribute this finding to a far higher ionization efficiency of the CMC+‐labeled products with fixed positive charge ,1 and 2 have the same stem with canonical Watson‐Crick base pairing  are highly stable,[UUCG being fully exposed to solvent[GCAA showing relatively slow exchange with solvent.2 (UUCG‐loop) than RNA 1 (GCAA‐loop) in the labeling reaction with CMC+. Consistent with this prediction, ESI MS of a ∼1 : 1 mixture of RNA 1 and 2 after reaction with CMC+ for 90 min at room temperature indicated 0.4 % and 6.9 % labeled products, respectively (Table +‐labeled RNA 2 and 1 decreased from ∼18 (6.9 % to 0.4 %) at room temperature to ∼2 at 70 °C and 90 °C, which reflects the unfolding of both hairpin structures and the 2‐fold higher number of U in RNA 2 (4) compared to that of RNA 1 (2).To investigate the use of ESI and CAD for the site‐specific, relative quantification of CMCy stable,32, 33+‐labeled RNA 2 (from reaction at room temperature) with a net charge of −4, (RNA 2CMC+‐5H)4−, at 60 eV laboratory frame energy produced 15.1 % c and y fragments from phosphodiester backbone cleavage and 1.8 % a and w fragments , with zero net charge (2.1 %), loss of unlabeled, uncharged nucleobases  (10.1 %), and loss of both (CMC+‐H+) and nucleobase (0.4 %) from (RNA 2CMC+‐5H)4− ions was observed  decreased with decreasing energy used for CAD . Since CMC+ carries a fixed positive charge, deprotonated CMC+ must be a zwitterion with a net charge of zero. Therefore, the loss of (CMC+‐H+) from (RNA 2CMC+‐5H)4− ions leading to (RNA 2–4H)4− ions (measured Δm 251.198 Da) must be accompanied by proton transfer from CMC+ to the RNA. Because CMC+ does not carry any acidic protons (Scheme +‐H+) at all energies used (Table +‐H+) and nucleobase, which we attribute to preferential labeling of U and the relatively high stability of its glycosidic bond.2CMC+‐5H)4− ions at 60 eV, that from G was most frequent (∼73 %), followed by C (∼16 %) and A (∼11 %); nucleobase loss from U was not observed in any of the spectra in this study.Low‐energy CAD of CMC−4, RNA 2CMC+‐5H4−+‐H+)  during CAD. For example, 76 % of the y11 fragments from CAD of (RNA 2CMC+‐5H)4− ions at 60 eV laboratory frame energy showed labeling with CMC+  and no CMC+‐label could originate from dissociation of both labeled and unlabeled fragments. Since for RNA, nucleobase loss and phosphodiester backbone bond cleavage into c and y fragments are independent dissociation channels,[+‐H+) losses, phosphodiester backbone bond cleavage of CMC+‐labeled RNA should produce pairs of complementary c and y fragments with the CMC+‐label either on the c or the y fragment. Thus for each backbone cleavage site, the fractions of CMC+‐labeled c and y fragments should add to 100 % such that the data points for c and y fragments should lie on top of each other when plotted with reversed ordinate axes, similar to the fractions of methylated c and y fragments from CAD of RNA with N6‐methyladenosine (m6A), 5‐methylcytidine (m5C), 3‐methyluridine (m3U), and 5‐methyluridine (m5U) modifications.+‐labeled c and unlabeled y fragments are plotted on the same ordinate axis.+‐labeled c and y fragments from CAD of (RNA 2CMC+‐5H)4− ions at 56 eV laboratory frame energy versus cleavage site, with values for c fragments plotted from 0 % to 100 % (left axis) and values for y fragments from 100 % to 0 % (right axis). The good agreement between the values for c and y fragments  loss .The loss of (CMC) Figure A is detrD of RNA CMC+‐5H4D of RNA CMC+‐5H4D of RNA CMC+‐5H4+‐labeled RNA 2 at 56 eV, the fraction of CMC+‐labeled c fragments  structures of UUCG loops, N1 of G (but not N3 of the first U) is involved in noncanonical hydrogen bonding between the first U and G.[UUCG loop of RNA 2 is somewhat dynamic, and that the reactions of N1 of G9 and N3 of U6 with CMC+ are limited by solvent exposure rather than intrinsic nucleobase reactivity. At elevated energy (60 eV) used for CAD, larger disagreements between fractions of CMC+‐labeled c and y fragments were observed  loss  loss affects mainly c7‐c14 and y9‐y14. Nevertheless, the data in Figure U7 as the preferred site for CMC+‐labeling.For CAD of CMC3, 5′‐GGCUGCUUGUCCUUUAAUGGUCCAGUC‐3′) at room temperature. Reaction time and concentrations were chosen such that mostly singly labeled RNA was formed. For CAD experiments at three different energies , ions of singly labeled RNA with a net charge of 7‐, (RNA 3CMC+‐8H)7−, from ESI were isolated in the mass spectrometer prior to dissociation. The 15 nt (RNA 1CMC+‐5H)4−, 15 nt (RNA 2CMC+‐5H)4−, and 27 nt (RNA 3CMC+‐8H)7− ions studied carry very similar charges per nucleotide , so that we can compare the energies used for CAD. For CAD of (RNA 1CMC+‐5H)4− and (RNA 2CMC+‐5H)4− ions, we used 56 eV, 58 eV, and 60 eV, which corresponds to 3.73 eV/nt, 3.87 eV/nt, and 4.00 eV/nt, respectively (Table 3CMC+‐8H)7− ions, the energies per nucleotide were 3.34 eV/nt, 3.47 eV/nt, and 3.60 eV/nt, which is lower than the energies per nucleotide used for CAD of (RNA 1CMC+‐5H)4− and (RNA 2CMC+‐5H)4− ions. Accordingly, (CMC+‐H+) and nucleobase losses were lower in CAD of (RNA 3CMC+‐8H)7− ions (Table 2CMC+‐5H)4− ions 7− ions of singly labeled RNA 3 at 90.3 eV, 93.8 eV, and 97.3 eV were virtually the same; average values with standard deviations are shown in Figure We then used our MS approach to study the structure of an artificial, neomycin‐sensing riboswitch aptamer domain5 nt RNA CMC+‐5H45 nt RNA CMC+‐5H43 , unreactive. Structures of RNA 3 in the absence of aminoglycoside ligands are not available, but NMR data suggest that the neomycin‐sensing riboswitch aptamer domainU4, U10, U13, U14, U18 and U26 at 30 °C ,+‐modification at 20 °C calculated from the data in Figure U14 (25 %)≈U7 (22 %)>U13 (17 %)>U8 (12 %)≈U18 (11 %)>U4 (6 %), agrees well with high solvent exchange rates and is consistent with the predicted secondary structure in Figure U10, U15, and U21.The CAD MS data for RNA 3 in complexes with aminoglycosides  at pH 6.2 were previously reported by Wöhnert and colleagues, along with dissociation constants (KD) of the complexes with neomycin B (10±2 nM), ribostamycin (330±30 nM), and paromomycin (5.13±0.26 μM) at pH 6.8.3 in complexes with paromomycin and ribostamycin  in the complexes with paromomycin.3 with neomycin B are structurally and dynamically very similar to those with ribostamycin,3  is also indicated by very broad imino proton signals observed in an earlier NMR study of free RNA 3 at 10 °C.U15 of free RNA 3, even though U15 is fully solvent‐exposed in the NMR structures 2MXS and 2 N0 J. Possible interactions of U15 are likely dynamic and include Wobble base pairing with G9 or hydrogen bonding to a phosphodiester moiety. Overall, our data for free RNA 3 which show high exposure to solvent of uridine nucleobases in the internal and apical loop regions  and dynamic base pairing of U4 agree well with the NMR data, and add the additional information that U10 and U21 are less exposed than expected for a fully dynamic internal loop , the overall fractions of labeled c8 and y19 were 39 % and 61 % (adding up to 100 %) in the absence of ligand, respectively, and 58 % and 33 % in the presence of neomycin B (adding up to 91 %).The CAD spectra of singly labeled RNA +‐labeled c and y fragments from CAD of singly labeled RNA 3 from reaction with CMC+ in the presence of neomycin B, paromomycin, and ribostamycin, respectively, along with the data for free RNA 3 from Figure 3 in complexes with all three aminoglycosides,3 with CMC+ in the presence of aminoglycosides, the data points for c and y fragments at sites 4–12 show relatively large gaps instead of lying on top of each other  loss from (RNA 3CMC+‐8H)7− ions was higher when RNA 3 was reacted with CMC+ in the presence of aminoglycosides , along with a corresponding decrease at sites 14 and 18  and a smaller increase at site 4 (∼9 %), the latter of which was, however, not observed for c fragments  and the apical loop  in the free RNA 3. Apparently, the exposure to solvent of U8 is not affected by aminoglycoside binding. Finally, our data did not reflect the up to ∼7‐fold higher exchange rates of U10 and U13 in the complexes with paromomycin when compared to ribostamycin.Figure r Figure A–C. Alth8 Figure D. The das Figure D. The da+‐labeled fragments in the presence and absence of aminoglycoside ligands  solution used for electrospray ionization. For example, after removal of small molecules and ions  using centrifugal concentrators, the ESI spectra indicated 32 % singly labeled RNA 3 for the reaction in the absence of aminoglycoside ligands, and 20–23 % for the reactions in the presence of aminoglycoside ligands ethylcarbodiimide p‐toluenesulfonate (CMCT), 5′‐phosphate mononucleotides of A (adenosine), C (cytidine), G (guanosine), and U (uridine), piperidine, imidazole, acetic acid, ammonium acetate, ammonium bicarbonate, magnesium citrate, and sulfate salts of neomycin B (C23H46N6O13 ⋅ xH2SO4), ribostamycin (C17H34N4O10 ⋅ xH2SO4), and paromomycin  were purchased from Sigma‐Aldrich . H2O was purified to 18 MΩ⋅cm at room temperature using a Milli‐Q system  and CH3OH  was HPLC‐grade. Hairpin RNAs 1 and 2 were prepared by solid phase synthesis, purified by HPLC, and desalted by diluting ∼100 μl RNA solution in H2O with ∼400 μl aqueous ammonium acetate (100 mM) solution, followed by concentration to ∼100 μl using centrifugal concentrators ; the concentration‐dilution process was repeated 5 times and followed by 6 cycles of concentration and dilution with H2O. RNA 3 was purchased from Dharmacon (USA), purified by HPLC, and desalted as described above. RNA concentration was determined by UV absorption at 260 nm using an Implen Nano PhotometerTM .+ with mononucleotides, CMCT (1 mM) and 5′‐phosphate mononucleotides of A, C, G, and U (300 μM each) were dissolved in H2O with 20 mM ammonium acetate and 12 mM ammonium bicarbonate at pH 8.0. After variable reaction times (0–170 min), reaction quenching was initiated by lowering the pH to 4.7 (100‐fold dilution with 20 mM acetic acid and 20 mM ammonium acetate in H2O). After another 25 min to allow for complete hydrolysis of CMC+, the solutions were diluted (1 : 1) in H2O/CH3OH (1 : 1) with 20 mM ammonium bicarbonate and electrosprayed in positive ion mode. The final composition of the solution for ESI was 1.5 μM per mononucleotide in 3 : 1 H2O/CH3OH with 10 mM acetic acid, 10 mM ammonium acetate, and 10 mM ammonium bicarbonate as well as unreacted, hydrolyzed CMC+ (up to 5 μM).To monitor the reactions of CMC+‐labeling of hairpin RNAs, aqueous solutions of RNA 1 and 2 (10 μM each) with CMCT were incubated for 90 min at 20 °C, 15 min at 50 °C, 6 min at 70 °C, or 2 min at 90 °C. The CMCT concentration for the reaction at 20 °C was 4 mM, and the pH adjusted to ∼8 with 15 mM ammonium acetate and 6 mM ammonium bicarbonate. For the reactions at 50 °C, 70 °C, and 90 °C, the CMCT concentration was 6 mM, and ammonium acetate and ammonium bicarbonate concentrations were 41 mM and 9 mM, respectively. Reactions were stopped by removing CMCT using the desalting procedure described above, and the RNA (1 μM each) was electrosprayed in negative ion mode from solutions in 1 : 1 H2O/CH3OH with 10 mM piperidine and 20–25 mM imidazole as additives.For CMC+‐labeling of the riboswitch aptamer domain, 15 μM RNA 3 and 6 mM CMCT were incubated in H2O with 41 mM ammonium acetate, 9 mM ammonium bicarbonate, and 0.1 mM magnesium citrate at 20 °C for 120 min in the absence or presence of aminoglycoside ligands . Reactions were stopped by removing CMCT using the desalting procedure described above, and the RNA (1 μM) was electrosprayed in negative ion mode from solutions in 1 : 1 H2O/CH3OH with 2 mM piperidine and 9 mM imidazole as additives.For CMCAll MS experiments were performed on a 7 T Fourier transform ion cyclotron resonance (FT‐ICR) instrument  equipped with an ESI source, a linear quadrupole for ion isolation, and a collision cell for CAD. ESI spectra were obtained by operation of the linear quadrupole in transmission (radiofrequency‐only) mode. For CAD, ions of interest were isolated in the quadrupole and dissociated in the collision cell using the laboratory frame collision energy indicated. Data reduction utilized the SNAP2 algorithm  or FAST MS, a software programmed by the first author, as well as manual inspection of the spectra.The authors declare no conflict of interest.1As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.Supporting InformationClick here for additional data file.


RNA catalytic and binding interactions with proteins and small molecules are fundamental elements of cellular life processes as well as the basis for RNA therapeutics and molecular engineering. In the absence of quantitative predictive capacity for such bioaffinity interactions, high throughput experimental approaches are needed to sufficiently sample RNA sequence space. Here we report on a simple and highly accessible approach to convert commercially available customized DNA microarrays of any complexity and density to RNA microarrays via a T7 RNA polymerase-mediated extension of photocrosslinked methyl RNA primers and subsequent degradation of the DNA templates. RNA microarrays have many potential applications, but are difficult to produce. Here, the AUs present a method for converting commercial, customizable DNA microarrays into RNA microarrays using an accessible three-step process involving primer photocrosslinking, extension, and template degradation. These interactions are essential in all aspects of post transcriptional gene regulation from splicing to localization and translation, as well as in RNA virus infection and host defense mechanisms5. Despite its importance, the RNA interactome remains largely unexplored due to our inadequate understanding of the sequence dependence of RNA binding interactions7. Unlike DNA, which mostly exists as double-stranded structures that are well defined and exhibit low structural and binding diversity, RNA is typically single-stranded and naturally assumes complex three-dimensional structures. The combination of this conformational heterogeneity of RNA and the composite of ionic and hydrogen bonding, hydrophobic effects, π interactions, and van der Waals forces acting on binding targets, puts predictions of these interactions outside of our current reach and requires experimental approaches8.RNA is a key actor in many biological processes and participates in complex bioaffinity networks involving nucleic acids, proteins, and small-molecule metabolites11, while affinity-based selection methods, such as SELEX, use sequencing or DNA microarrays to identify strong nucleic acid ligands after selection cycles15. These select-and-identify approaches have the advantage over on-array assays in that they can start with larger oligonucleotide pools17. However, they do not simultaneously and directly measure the affinity parameters relevant to biological function and are biased towards strongly binding sequences. In nature, low- and medium-affinity binding sites are both used by cells to enhance specificity and are relevant to therapeutic RNA-binding ligands and bioengineering applications due to the need to minimize and account for off-target effects in the presence of millions of these weaker binding sites20.Massively parallel experimental assays, particularly DNA microarrays and sequencing, have revolutionized genomics research in the last decades. These same assays have also been leveraged for highly parallel quantitative investigations of the structure-function relationships of nucleic acid interactomes. For example, double-stranded DNA microarrays are used to elucidate the binding site specificities of transcription factors and other DNA-binding molecules24. Quantitative analysis of RNA on a massively parallel array (RNA-MaP)23 starts with ssDNA sequencing libraries including an RNA polymerase promoter region, a stall sequence, and a variable region complementary to the desired RNA. After the DNA library is sequenced on the Illumina flow cell, it is enzymatically double stranded by extension of a 5′ biotinylated primer. The RNA polymerase uses this template to generate the RNA. The resulting RNA stays attached to the surface since the RNA polymerase remains stalled on the DNA template at the terminal biotin-streptavidin roadblock. High-throughput sequencing-RNA affinity profiling (HiTS-RAP)22 is conceptually similar to RNA-MaP, but uses the E. coli replication terminator protein Tus to stall the RNA polymerase after transcribing the variable section of the DNA library. Similar sequence complexity can be achieved by combining chemical DNA synthesis and enzymatic fabrication using nucleic acid photolithography25. In this approach, maskless array synthesis is used to synthesize both the template DNA library 3′ to 5′ in situ on a surface and 2′-O-methyl RNA primers 5′ to 3′ using reverse synthesis. The primers, synthesized stochastically via partial photodeprotection on 50% of the surface hydroxyl groups, are then extended enzymatically using the T7 RNA polymerase according to an adjacent DNA template. At much lower density, but with relaxed length limitations, template DNA libraries may also be spotted onto surfaces for enzymatic transcription. Including the sequence for a streptavidin-binding RNA aptamer on the template allows for the released RNA to be captured on an adjacent parallel streptavidin-coated substrate while preserving the original spatial organization26.Several techniques have been developed aiming to produce high-density RNA microarrays suitable for quantitative RNA-binding assays. The highest throughput RNA microarrays are based on capturing, sequencing, and transcribing chemically synthesized DNA libraries―with a randomized variable region to be transcribed to RNA―in repurposed Illumina sequencers28. Such direct synthesis can also accommodate much higher chemical complexity through the position-specific substitution of other nucleic acid monomers, both natural, such as DNA and 2′-O-methyl RNA, and unnatural nucleosidic and non-nucleosidic monomers31. However, direct chemical synthesis of RNA microarrays is quite inaccessible, requiring maskless photolithography equipment and supplies that are not commercially available, and the chemistry is difficult and inefficient, with an oligonucleotide length limit of roughly 30 nt30.The most chemically versatile approach is to use nucleic acid photolithography to directly synthesize RNA microarrays in situ using the appropriate RNA phosphoramiditesO-methyl RNA primers32. Our approach allows for DNA microarrays of any density and complexity to be converted to RNA with minimal time and effort and using only standard molecular biology equipment and supplies. We apply this method to create complex, high density RNA microarrays from Agilent SurePrint DNA microarrays as well as from DNA microarrays made via maskless photolithography.While all these high-throughput approaches result in powerful platforms for measurements of RNA interactions, they are also highly complex and require specialized equipment and know-how beyond the practical reach of almost all researchers. In this work, we introduce a far simpler approach based on the unusual ability of the T7 RNA polymerase to synthesize RNA from a DNA template via extension of RNA or 2′-33, electrochemistry34, or photochemistry35, the end products are quite similar, with the 3′ termini of the DNA attached to the substrate via a short linker, and a molecular surface density of ~5 pmol/cm2 due to an initial surface functionalization with silane chemistry36. From these similarities, we expect that DNA microarrays of almost any source can be easily converted to RNA microarrays using our approach. For conversion to RNA, the DNA sequences on these microarrays are specified to include, in addition to the template sequences, the complement to a shared 2′-O-methyl RNA primer, and a short 3′ dT homopolymer linker to the substrate 41 or 2′-deoxy-2′-fluoro-RNA (2′-F-RNA)42 may provide similar protection while increasing selectivity. The photocrosslinking approach has been described in detail elsewhere29 and the ideal conditions were found to be the use of 5′-psoralen-labeled oligonucleotides forming a TA base-pair adjacent to the psoralen moiety for proper intercalation and photocrosslinking, which is performed under 365 nm UV light at ~4 °C (see “Methods” section). We then focused on the degradation of the DNA template without cleaving the linker to the surface, a pivotal aspect of the method as it is necessary to retain the polymerized RNA immobilized to the surface.The in situ transcription assays performed on commercial and custom-made microarrays are the fruit of preliminary tests aiming at investigating the critical parameters involved in the process of transformation of a DNA microarray into RNA Fig. . The priode Fig.  indicate43, but dU-containing microarrays are not available commercially, limiting the general usefulness of this strategy. We also experimented with template degradation with the E. coli lambda exonuclease. This exonuclease removes nucleotides 5′ to 3′ in single- and double-stranded DNA44, and we speculated that it might also work in DNA-RNA hybrids and would be unable to bypass the crosslink. However, we were unable to observe DNA template degradation using this exonuclease. Finally, we were successful with TURBO DNase, an optimized variant of the DNase I endonuclease. This endonuclease is less active on DNA-RNA hybrids (vs dsDNA), but is even less active on ssDNA, and preferentially cleaves at purine-pyrimidine junctions, favoring the integrity of the ssDNA homopolymer linker45. We also speculated that steric interference by the glass surface would prevent endonuclease activity in the case of sufficiently short linkers. To verify this, we considered various linker types and linker lengths, from homopolymeric dT (1–20 nt in length) to non-nucleosidic hexaethylene glycol (HEG), and treated both DNA and RNA with TURBO DNase in a system mimicking successful enzymatic extension of the primer  nucleotides in the template sequence, followed by incubation with uracil DNA glycosylase (UDG) after conversion to RNA is effective and unproblematic in the context of our own microarray synthesisAcknowledging the lower efficiency of TURBO DNase when acting on DNA-RNA hybrids, we became interested in studying how far the enzyme had processed the DNA substrate and how thoroughly the primer sequence of the DNA template was degraded Fig. . Indeed,O-methyl RNA primers crosslinked to ssDNA templates, we replicated the array conversion in solution using commercially synthesized oligonucleotides: a DNA template, a 5′-psoralen 2′-O-methyl RNA primer, and a chimeric sequence consisting of the primer and the full-length RNA product. The first two of these were photocrosslinked and either digested directly with DNase or first used to synthesize RNA and then digested. Polyacrylamide gel electrophoresis (PAGE) analysis  mix supplemented with fluorescent Cy3-UTP, yielding fluorescent RNA products Fig. . After aO-methyl RNA primers photocrosslinked to ssDNA template arrays, resulting in DNA–RNA hybrids; (ii) TURBO DNase degradation of the DNA template results in RNA bound to the original position of the template via the 2′-O-methyl RNA primer crosslinked to the original short dT linker; and (iii) the combination of primer photocrosslinking and DNase degradation results in a universal strategy that enables the conversion of standard commercially-available DNA microarrays of any density and complexity to complementary RNA. Thus, functional high-density RNA microarrays can be generated overnight with minimal effort and using only equipment, supplies and skills commonly found in molecular biology research environments. Although RNA is likely to remain the most useful product, the approach can be extended through the use of engineered polymerases47 to other primer chemistries such as DNA, RNA, and LNA, but also to the production of complex high-density arrays of stably-linked dsDNA, 2′-fluoro- and 2′-azido-substituted analogs for aptamer and siRNA applications48, as well as to the conversion of RNA with 5-methylcytosine and pseudouridine substitutions for research in modified mRNA therapies49.In summary, we have shown that: (i) the T7 RNA polymerase efficiently extends 2′-DNA sequences intended for conversion to RNA consist of a 3′ dT linker to the surface, a segment complementary to the primer, and a variable segment that serves as a template for transcription. The optimal dT linker length for our own microarrays synthesized via photolithography was identified being 5 to 10 nt, whereas the optimal length for the Agilent microarrays was found to be 10 nt , TCAACCCAGGTCCAATTTCC (green), and ACAGTGGATCGTACTCAGGTCTCA (blue). Intensity levels are achieved by 5′ truncations to these sequences n, n = 5, 10, 15, 20), permutation of the three 3′ terminal positions of the sequence complementary to the primer, and permutations of three central positions of the template sequence to generate mismatches. These changes vary the efficiency of transcription and, after transcription, hybridization efficiency between the RNA and a Cy3-labeled complementary DNA oligonucleotide. The Agilent microarray design also includes DNA sequences complementary to this fluorescent oligonucleotide, allowing direct hybridization as a reference for hybridization signal intensities for the detection of RNA product as shown in Fig. A 4 × 44 K SurePrint custom DNA microarray (AMADID 086693) was designed following the aforementioned criteria. Design characteristics for the Agilent microarray are provided in Supplementary Table O-methyl RNA, 5′-Ps-UAGGGACACGGCGAA, Eurogentec) in MES 1× buffer  supplemented with 0.44 mg/mL acetylated BSA (Promega R3961) in self-adhesive chambers (Grace Bio-Labs) for 30 min at 37 °C with rotation (rotating bubble-based mixing), followed by washes with: 1– non-stringent wash buffer (NSWB)  for 1 min, 2– stringent wash buffer (SWB)  for 30 s and 3– 5 s in final wash buffer (FWB) (0.1× SSC). The primer was then crosslinked to the DNA template at 4 °C in 1× MES buffer by exposure to 25 J/cm² of 365 nm UV light. Crosslinking was performed using a custom-built light source based on the same high-power Nichia NVSU333A 365 nm UV LED used for the DNA template microarray photolithographic synthesis. The radiant power of the crosslinking light was determined using SÜSS Model 1000 UV intensity meter with a 365 nm probe. A more detailed description of the light source and the setup for photocrosslinking is given in Supplementary Fig. 29.DNA template arrays where hybridized with 89 nM primer oligonucleotide  1× RNA Pol Reaction Buffer with 0.2 mg/mL acetylated BSA and 0.005% Triton X-100 (Sigma-Aldrich) was applied to the hybridization chamber, followed by incubation for 30 min at 37 °C with rotation. After removal of this solution, a mix of 3 units/µL T7 RNA polymerase (NEB M0251) in 1× RNAPol reaction buffer supplemented with 0.005% Triton X-100 (Sigma-Aldrich), 0.5 mM of each NTP (Thermo Scientific R0481), 1 unit/µL RNase inhibitor (NEB M0307) and 4 mM DTT (Sigma-Aldrich D5545) was applied to the array. For incorporation of a fluorescent label into the RNA product, Cy3-UTP (Jena Bioscience NU-821-CY3) was added at a final concentration of 0.0175 mM and UTP at 0.2 mM. The enzymatic primer extension reaction was stopped after 16 h at 37 °C with rotation by exchange of the solution with a 0.1 units/µL mix of TURBO DNase (Invitrogen) in 1× buffer supplemented with 1 unit/µL RNase inhibitor for degradation of the DNA template (5 h at 37 °C with rotation). The degradation reaction mix was pipetted out and discarded, and the respective array briefly washed with NSWB by pipetting in and out two volumes of buffer within the hybridization chamber. After removal of the hybridization chamber, the entire slide was washed briefly in FWB and dried with a microarray centrifuge.50. After drying in a microarray centrifuge, microarrays were scanned with a GenePix scanner (Molecular Devices) at 2.5 or 5 µm resolution. Fluorescent signal intensities were extracted using NimbleScan 2.1.68 (NimbleGen), followed by data analysis in Microsoft Excel. For maximum comparability between effects of differing reaction conditions, the layout of the microarray was adjusted to divide the synthesis area in four parts with identical sequences. Custom-made self-adhesive chambers (Grace Bio-Labs RD475732-M) allow to individually address each subarray. The efficiency of the conversion procedure was determined by parallel hybridization to control sequences of DNA in an untreated and RNA as product in a treated subarray on the same surface.Hybridization with a fluorescently-labeled oligonucleotide probe complementary to the RNA generated was carried out for RNA detection. The hybridization mix consisted of 12.2 nM probes  in an adhesive hybridization chamber for 1 h at 37 °C with rotation. As a control, another sub-array with RNA on the same slide was treated in parallel with 1× buffer. After discarding the reaction mix, washing was performed in the same way as after DNase degradation. In order to assess the completeness of the degradation, the initial hybridization-based detection with Cy3-labeled complementary DNA was repeated, and the original presence of RNA was confirmed by a near complete loss in hybridization signal following RNase H treatment  in 1× buffer   for 5 min at 70 °C, followed by a gradual cooling to room temperature for 1.5 h. Crosslinking was performed at 4 °C and 50 J/cm² 365 nm light  consisting of a 3′ dT 5mer followed by a sequence complementary to the primer, followed by a 30mer sequence serving as template for transcription was annealed with an equal amount of the 5′-Ps-2′-ter Fig. , lane 1.O-methyl RNA with an additional RNA section at the 3′ end 53. An Expedite 8909 nucleic acid synthesizer is coupled to the reaction chamber and pumps reagents and solvents in synchrony with the UV light exposures. The DNA synthesis cycle is a variant of the standard phosphoramidite chemistry, customized with phosphoramidites (Orgentis) with the photolabile BzNPPOC group on the 5′ hydroxyl55. Monomer coupling times were set to 15 s for BzNPPOC-dN, 300 s for NPPOC-protected hexaethylene glycol phosphoramidites (ChemGenes), and 120 s for DMTr-dT phosphoramidites. Photodeprotection exposure was 3 J/cm2 or 6 J/cm² to remove BzNPPOC and NPPOC protecting groups, respectively. The following solvents and reagents used in synthesis were purchased from Sigma-Aldrich: acetonitrile (34851), DCI activator (L032000), both kept dry under molecular sieves (Z509027), exposure solvent composed of 1% (m/v) imidazole (56750) in DMSO (34943), and 20 mM iodine in H2O/pyridine/THF (L060060) as oxidizer. TRIDIA Activated Slides (Surmodics) were used as substrates. After synthesis, all protecting groups were removed in 2 h in a 1:1 (v/v) ethylenediamine/ethanol solution in a staining jar.We use a custom-built system consisting of an optical imaging system that projects the mirror pattern of an XGA (1024 × 786) digital micromirror device (Texas Instruments) onto a functionalized glass slide in a reaction chamberx-axis category “7” (concerning the position of dA the template) in Fig. All analyses were performed in OriginPro 2020 (version 9.7.0.188) and Microsoft Excel 2020. No statistical methods were used to determine sample size and no statistical tests were performed on the data. No data were excluded from the analyses, except for two data points (out of 85) in the Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Reporting Summary


Hybrid RNA:DNA origami, in which a long RNA scaffold strand folds into a target nanostructure via thermal annealing with complementary DNA oligos, has only been explored to a limited extent despite its unique potential for biomedical delivery of mRNA, tertiary structure characterization of long RNAs, and fabrication of artificial ribozymes. Here, we investigate design principles of three-dimensional wireframe RNA-scaffolded origami rendered as polyhedra composed of dual-duplex edges. We computationally design, fabricate, and characterize tetrahedra folded from an EGFP-encoding messenger RNA and de Bruijn sequences, an octahedron folded with M13 transcript RNA, and an octahedron and pentagonal bipyramids folded with 23S ribosomal RNA, demonstrating the ability to make diverse polyhedral shapes with distinct structural and functional RNA scaffolds. We characterize secondary and tertiary structures using dimethyl sulfate mutational profiling and cryo-electron microscopy, revealing insight into both global and local, base-level structures of origami. Our top-down sequence design strategy enables the use of long RNAs as functional scaffolds for complex wireframe origami. Hybrid nucleic acid origami has potential for biomedical delivery of mRNA and fabrication of artificial ribozymes. Here, the authors use chemical footprinting and cryo-electron microscopy to reveal insights into nucleic acid origami used to fold messenger and ribosomal RNA into 3D polyhedral structures. The predictability of Watson-Crick-Franklin base-pairing together with crossover motifs derived from the Holliday junction renders nucleic acids amenable to fabricating a wide variety of 2D and 3D structures. Scaffolded DNA origami14, in particular, has been demonstrated to enable the fabrication of nearly arbitrary 2D and 3D dense, bricklike17 as well as porous, meshlike wireframe24 objects by folding a single-stranded DNA scaffold to user-specified geometries via annealing with shorter DNA staple strands. These discrete DNA structures are versatile and broadly useful for numerous applications in materials25, therapeutics2 and cellular biophysics27.Nucleic acid nanotechnology offers unique capabilities for applications ranging from therapeutics31. For example, modulation of immunostimulation by therapeutics or prophylactics32; tunable release kinetics via nuclease-specific degradation for nucleic acid or other payload delivery28; and organization of RNAs for structural and catalytic applications34. In addition, the use of RNA as a scaffold material also has the practical advantage over typical DNA scaffolds that naturally abundant long single-stranded RNA (ssRNA) such as ribosomal RNA (rRNA), highly prevalent in cells35, may be used as a natural, albeit sequence-restricted source of scaffold, and scalable production of long single-stranded RNA with arbitrary sequence is also facile with in vitro transcription37. Finally, use of RNA scaffolds for origami enables base-level insight into secondary structure through chemical probing, offering insight into the impact of sequence design rules on local structural stability that is of significant interest to nucleic acid nanostructure design generally40.Incorporation of RNA in molecular origami with controlled target geometry offers additional applications in nanoscale materials synthesis and therapeutics that are not currently possible using purely DNA:DNA origami alone41. In addition, RNA is typically single-stranded in the cell, adopting complex tertiary folds with Hoogsteen and sugar edge base interactions, thereby rendering reliable de novo tertiary structure prediction and associated structural programmability challenging43. Nevertheless, knowledge gained from RNA tertiary structures has been used to generate RNA nanoparticles by engineering RNA fragments to self-assemble into programmed higher-order geometries using, for example, tRNAs and multi-way junctions to create complex shapes48. However, absolute control over the programmability of the final, target shape with this approach is constrained by the requisite sequences of the underlying folds.Unlike DNA, RNA carries an additional 2’-hydroxyl group on the sugar that forces a C3’-endo form, leading to an A-form double helix , when hybridized with either DNA or RNA, rather than the canonical B-form of duplex DNA 47 that leverages native RNA tertiary structures, tile-based assembly and RNA-scaffolded origami require specifically programming secondary structure to self-assemble target tertiary structures. Multicomponent tile-based assembly has been employed with either RNA:RNA or RNA:DNA interactions to form wireframe structures with single duplex51 or dual-duplex edges52. Other recent advances in programming structures have focused on enabling co-transcriptional folding using a single RNA strand that folds isothermally into the target 2D structure that may include predefined tertiary junctions such as kissing loops56. Bottom-up design of RNA-scaffolded origami has been demonstrated using RNA staples to form 2D structures57 and single-duplex-edged 3D wireframe structures58, and using DNA staples to form bricklike59 or 2D objects61. However, automated sequence design algorithms, which have greatly aided the dissemination of scaffolded DNA origami23, remain sparse62, and no studies have yet realized the design and fabrication of arbitrary dual-duplex wireframe 3D structures with and RNA scaffolds of varying sequence and length.As an alternative to the preceding tectonics approachHere, we explore design strategies for hybrid nucleic acid origami that use DNA oligo staples to fold in vitro transcribed RNA scaffolds of varying sequences and lengths into distinct 3D wireframe polyhedra with dual-duplex edges. Impacts of folding buffers, annealing protocols, and staple-to-scaffold ratios are first characterized with gel electrophoresis; target structures under suitable folding conditions are then validated using cryo-EM reconstruction. Secondary structure hybridization and stability are additionally assessed at single-nucleotide resolution using DMS-MaPseq, which provides insight into specific sources of structural instability in origami design. Our design strategy is distributed using a modified version of the open-source software DAEDALUS implementing A-form dual-duplex wireframe design rules.63, namely between adjacent scaffold and staple strand crossovers  that allow RNA to be used as the scaffold with DNA staples. To account for A-form duplex geometry in our hybrid RNA:DNA origami sequence design, we assumed 11 nt per helical turn and incorporated asymmetric spacing between adjacent crossovers of distinct strands64. For RNA:DNA dual-duplex wireframe origami, we adopted an analogous dual-duplex DNA wireframe origami annealing protocol18, albeit reducing incubation time at high temperatures, omitting divalent cations (300 mM KCl instead of MgCl2), and lowering the pH (10 mM HEPES pH 7.5 instead of 1x TAE pH 8.0) to minimize RNA instability. We compared our selected protocol to two others employed in published RNA:DNA origami designs, one reported to fold 2D structures61 and another to fold a 3D bricklike structure59. Gel mobility shift assays comparing these protocols as applied to two wireframe RNA:DNA polyhedra, an EGFP mRNA-scaffolded tetrahedron and a 23S rRNA-scaffolded pentagonal bipyramid with six helical turns (66 bp) per edge each, suggested that our selected protocol with 10 mM HEPES pH 7.5 + 300 mM KCl led to folded particles that were most compact. A fast folding protocol with a TAE + magnesium buffer reported for 2D RNA:DNA origami61 led to a comparable gel mobility shift, but slightly more dimerization in the tetrahedron and a slightly more diffuse monomer band for the pentagonal bipyramid ; and an in vitro transcript of the M13 viral genome frequently used to scaffold DNA origami. For an initial test we targeted the design and fabrication of a regular tetrahedral geometry with six edges of equal length and four three-way vertices. We used in vitro-transcribed 792-nt prokaryotic EGFP mRNA and 660-nt and 924-nt De Bruijn RNA sequences to scaffold tetrahedra with six, five, and seven helical turns per edge, respectively, corresponding to 66, 55, and 77 bp per edge .66 to characterize folding biochemically with single base resolution, enabling the evaluation of the degree of base pairing between scaffold and staples. Mean normalized DMS reactivity for each of the n = 64 double helical segments in the folded origami, and corresponding segments of nucleotides in the EGFP mRNA scaffold alone, showed DMS reactivity was 82% lower  in the folded origami (median = 0.63%) than in the scaffold without staples (median=3.4%) . No such change was observed for off-target nucleotides , thereby also confirming hybridization specificity of this omitted staple. For the rT55 and rT77, gel mobility shift assays again indicated compactly folded particles  Fig. . Lower DTurning to a more complex geometry with twelve edges of equal length and six four-way vertices, we used a 1056-nt transcript of the M13 phage genome to scaffold a regular octahedron with four helical turns per edge (rO44). The M13 transcript-scaffolded rO44 likewise formed a discrete shifted gel band Fig. , with cr67 from energy-minimized A-form duplex simulations. Although still generally consistent with expectations for A-form helices, this increase in average rise might indicate that the helices were slightly underwound67 or that the crossover junction geometry created space that modestly lengthened the edges. For both the rT66 and rO44, the two duplexes in the edges moderately twisted relative to one another , which are ~10–11% larger than the canonical A-form rise of 0.260 nm/bp and ~7–8% larger than theoretical rise of 0.267 nm/bpher Fig. . This di-transcribed 1980-nt fragment of the E. Coli 23S rRNA to scaffold two different A-form DX wireframe origami objects of varying complexity: a regular octahedron and a pentagonal bipyramid, each with six helical turns (66 bp) per edge , as well as a pentagonal bipyramid with five helical turns (55 bp) per edge (rPB55). Unlike the other geometries investigated, the pentagonal bipyramid has multiple vertex types, with both four-way and five-way vertices and corresponding variations in dihedral angles, making it a more complex target geometry in addition to using the longer, intrinsically structured ribosomal RNA scaffold. Gel mobility shift assays suggested each object folded properly , rather than being suppressed . We tested the ability of an in vitrorly Fig. , with adrly Fig. . In furt67. In both the rO66 and rPB66 reconstructions, we observed an offset in the duplex ends in each DX edge, likely corresponding to the pitch of A-form helices and the asymmetry in staple crossover designs.Cryo-EM micrographs for each particle also showed well-folded, monodisperse particles Fig.  and 10, 57, and optimal implementation of crossover asymmetry was not obvious for DX wireframe polyhedral origami. In contrast to single-stranded RNA tiles54 and 2D origami bundles or tiles57, DX designs for wireframe polyhedra are constrained by the helical position of the scaffold exiting and entering duplexes at vertices, which has the potential to affect optimal design of crossover asymmetry. We, therefore, tested several routing scheme variants for our DX wireframe origami, including (1) a negative control B-form design with no crossover asymmetry and 10.5 bp per helical turn, (2) a symmetric A-form (Sym A-form) design with no crossover asymmetry and 11 nt per helical turn, and (3) an alternative A-form (Alt A-form) design with asymmetry incorporated into scaffold crossovers and 11 nt per helical turn , the mRNA sequence used for SARS-CoV-2 vaccination70, a long replicon RNA followed by mCherry coding sequence71, ribosomal RNA72, and viral genomes (GenBank69 accession numbers GU131973.1 and KY008770.1) that could serve as scalable sources of long single-stranded RNA to fold larger objects for nanomaterials applications.The A-form design for DX wireframe origami was incorporated as the A-form option in the open-source pyDAEDALUS software, which generates scaffold and staple routing for polyhedral mesh surfaces to design DX-edge-based wireframe structures Fig. . 14 polyn = 5 characterized A-form origami objects  and computed the distributions of DMS reactivities at each position from 6 bp upstream to 6 bp downstream of the feature instance, where 6 bp corresponded to the shortest contiguous double helical segment in the origami objects investigated . The same was true for bases immediately upstream of staple double and single crossovers. However, by the same criteria for significance, none of these more distant bases was more reactive than corresponding bases further away from the structural feature, except for bases two positions upstream of vertices . Thus, crossovers and staple termini destabilized only the immediately adjacent bases, and vertices only destabilized bases within two positions.To gain base-level insight into how the placement of crossovers, strand termini, and vertex designs impact RNA-scaffolded origami stability, we analyzed DMS-MaPseq data for nucleotides near these features across the origami Fig. . For eacP-values generally lower than for cytosines alone. This result suggested that stabilities of A-T base pairs depended more on their proximities to structural features than do C-G base pairs, as might be anticipated due to their weaker hybridization free energy.To account for any biases caused by differences in innate DMS reactivities between adenines and cytosines, we repeated the analysis on each type of residue separately  were moderately anticorrelated with predicted melting temperature (ρ = −0.58) and GC content (ρ = −0.41) were no more reactive than those further upstream Fig. . All sca.58)Fig. , as wellP = 2 × 10−5 and P = 1 × 10−2, respectively, two-tailed Mann-Whitney U test). These findings are consistent with previous work with DNA origami motifs that showed mesojunctions, the geometry adopted by single crossovers in DX edges, are less thermally stable than the conventional junctions of double crossover motifs76.To further investigate the relative stabilities of different structural features, we divided the DMS reactivity of the base immediately downstream (or upstream) of the structural feature by the mean DMS reactivity among the interior bases in the adjacent segment, isolating the effects of each structural feature on local stability when located at the 5’ (or 3’) end of a segment, while controlling for factors that could affect the entire segment Fig. . Bases aP = 1 × 10−3, two-tailed Mann–Whitney U test), relative to interior adenines and cytosines, respectively. Similarly, terminal adenines (relative to interior adenines) were more reactive than terminal cytosines (relative to interior cytosines) for segments with 3’ staple single termini and staple nicks. This finding suggests that A-T pairs immediately upstream of staple single crossovers, single termini, and nicks are particularly unstable, and that these sites in origami might be most important to stabilize with C-G pairs. Conversely, terminal cytosines were approximately two-fold more reactive than terminal adenines (relative to interior residues of the same type) for segments with 5’ staple nicks and 5’ staple double crossovers. Relative to interior bases of the same type, there were no significant differences in the reactivities of adenines versus cytosines adjacent to scaffold double crossovers and vertices. These results show that, after controlling for the type of residue and DMS reactivity of each segment, structural features destabilize adjacent A-T and C-G base pairs to different extents, which has implications for optimizing the sequence of the scaffold. For example, prioritizing placement of cytosines and guanines at and near structural features, when feasible based on sequence design and fabrication constraints, should enhance origami stability. While these base-level findings are limited here to RNA:DNA origami, they are likely to generalize to DNA:DNA origami as well.To glean insights for optimizing sequences of RNA scaffolds for folding polyhedral wireframe origami, we investigated differences between adenines and cytosines adjacent to each structural feature Fig. . Most no78, as well as the relative unpredictability of its tertiary structures. However, the presence of native secondary and tertiary structure present in target RNA scaffolds did not appear to prevent proper folding, given that the 23S rRNA fragment used to scaffold three different objects has a variety of secondary structural motifs and is approximately ~58% base paired on its own according to our DMS-MaPseq analysis. Following denaturing at high temperatures and re-annealing, this RNA scaffold bound preferentially to the staples and folded the target structure with high yield. The assumption of A-form helices in our sequence design algorithm may also apply to RNA staples with DNA scaffolds, or entirely RNA-RNA wireframe origami.We demonstrated folding of a variety of RNA scaffolds using DNA staples to self-assemble, via thermal annealing, distinct 3D polyhedral wireframe geometries based on DX-edge designs. Aside from the need to accommodate A-form helical geometry, a major concern in using long RNA strands to scaffold origami has been its tendency to be highly structured internally, as observed in long natural RNAs from rRNA to viral genomes39 and high-resolution atomic force microscopy to visualize missing staples directly in 2D tiles40, chemical probing to characterize base-level secondary structure has only been applied to simple 3-way and 4-way DNA junctions using hydroxyl radical footprinting76. The investigation of large-scale scaffolded origami using chemical probing was made possible in this work by the use of RNA scaffolds. Our observations of secondary structure stability might also generalize to scaffolded DNA origami. We can apply this protocol to investigate base pairing stability for improved sequence design—for example, our data suggest that placing C-G base pairs immediately upstream of staple single crossovers should increase origami stability. Complementing existing techniques81, the approach also holds promise for kinetic studies of nucleic acid origami folding, by probing samples either at various time points of isothermal co-transcriptional folding55 or at various stages of thermal annealing and comparing which sections of the scaffold are hybridized at each stage, which may improve mechanistic understanding of scaffolded origami folding.Scaffolding wireframe origami with RNA allowed us to study nucleic acid origami folding and stability with nucleotide-level precision. Further, although numerous studies have investigated the stability of and defects in DNA origami at the staple level, for example using fluorescent probes to estimate the average number of unpaired nucleotides in 3D helix bundles84, multiplex automated genome engineering (MAGE)85, and homologous recombination template86 delivery. The tunable degradation rates introduced by the combined use of RNA, modified RNA and DNA may also prove useful for material templating and etching. We additionally used ribosomal RNA to scaffold a pentagonal bipyramid that would leave domains V and VI of the 23S rRNA to fold freely. Future engineering might allow for the generation of synthetic nucleic acid assemblies that coordinate catalytic ribozymes88, test substrates of RNA modification enzymes90, and eventually even mimic or augment the functions of the ribosome during protein synthesis93.Beyond studies of nucleic acid origami itself, the use of RNA as a scaffold for DX wireframe origami enables a variety of applications, depending on the particular scaffold used. RNA has a number of useful features that are distinct from DNA, including the ability to modify nucleotides for stability, immunogenicity, and translatability, and to introduce riboswitches and aptamers, ribozymes, antisense oligos, and long RNAs. In particular, here we used mRNA as a scaffold for the assembly of a nanoparticle containing the sequence encoding a fluorescent protein. Targeted cellular delivery of such a nanoparticle could offer important potential for nuclease-specific release of scaffold or staples within the cell, with applications in antisense oligonucleotide (ASO) therapy2, magnesium acetate, acetic acid, and high-resolution agarose were purchased from Sigma-Millipore (MA). HiScribe T7 RNA polymerase kits and Q5 2x HiFidelity PCR mastermixes were purchased from New England Biolabs . Sodium cacodylate solution, pH 7.2, was purchased from VWR.Oligonucleotide staples and primers and gBlock synthetic DNA sequences were purchased from Integrated DNA Technologies . HEPES, Trizma base, EDTA, NaCl, KCl, MgCl54, scaffold crossover edges, which have adjacent crossovers occurring on different strands of the double helix (scaffold vs. staple) and thus must occur an odd number of half-twists apart, require that the crossovers be spaced asymmetrically on the two duplexes of the edge to be compatible with A-form helical geometry. We investigated two approaches to implementing this asymmetry (A-form and Alt A-form), in addition to testing a design with no asymmetry incorporated (Sym A-form).To generalize to A-form helical geometries to allow for RNA:RNA or hybrid RNA:DNA DX-based origami, edge lengths were discretized to multiples of 11 rather than rounded multiples of 10.5, and crossover positions were changed to be compatible with A-form helix crossovers. As described previouslyIn one approach to A-form, the required asymmetry is incorporated into the staple crossover position calculation Fig. . In this94 and subsequently automated. For the tetrahedron and octahedron, a Sym A-form design was also manually generated, which does not have the asymmetry in crossover position between the two duplexes, but instead directly crosses over as in the standard DNA DX design  incorporates asymmetry into the scaffold crossover position calculation for A-form  mirrors the format and naming conventions of DAEDALUS18. Briefly, the input target geometry file in the Polygon File Format (PLY) is parsed to identify relevant geometric parameters including coordinates of vertices, edge and face connectivities that form the graph of the shape, and edge lengths. Scaffold routing is achieved by calculating the spanning tree of the graph, and staples are added according to either standard geometric rules for B-form DNA or the A-form design rules, depending on user specification. The resulting outputs of the algorithm are plaintext and Comma-Separated Values (CSV) files that store the routing information, staple sequences, and nucleotide spatial coordinates. The positions and orientations of each nucleotide are represented as vectors following the convention from the software 3DNA95.We implemented the A-form design rules with staple crossover asymmetry in a top-down design algorithm that calculates sequences for folding an input target shape with wireframe DX edges Fig. . The cod96, which is used to generate the spanning trees required to route the scaffold strand, was used in both algorithms as built-in functions. However, for many structures the Python version generates a spanning tree different from the MATLAB version. Although this will affect the scaffold routing and staple sequences, the fidelity of the final design should not be affected, because each possible spanning tree of an object corresponds to a valid scaffold routing18. Third, in order to exploit the object-oriented structure that Python enables, the DNAInfo class was introduced, which packages together the many variables associated with the geometry, routing, and structure generated in intermediate sub-functions of the algorithm.While the overall architecture of DAEDALUS is preserved in pyDAEDALUS, several fundamental changes were required. First, the connectivities passed through the functions are stored in pyDAEDALUS as NetworkX Graph objects, rather than sparse matrices as in DAEDALUS. Second, Prim’s algorithmTo render the code more robust and offer a platform for further development by other contributors, additional frameworks were constructed. A style guide was implemented to help readability of the code, and linting, i.e. automatic checking of adherence to the style guide, is also enforced. In addition, unit tests were introduced to ensure that the functionality of the code is preserved as intended by the original authors. All tests and linting are evaluated automatically on each change to the current version on GitHub, with the results published within the readme.md of the repository.rrlB gene encoding the 23S rRNA from the pCW1 plasmid72. For the octahedron with 4 helical turns per edge, partial M13 DNA template was amplified from mp18 ssDNA (NEB). For the fragment of human immunodeficiency virus 1 (HIV-1) Rev response element (RRE) used as a control in DMS-MaPseq experiments, the sequence was synthesized as a gBlock (IDT) containing a 5’ T7 promoter, then PCR amplified using the Q5 High-Fidelity 2X Master Mix (NEB). For the tetrahedra with 5 and 7 helical turns per edge, we designed a random scaffold sequence with minimal self-complementarity  and again obtained the sequence as a synthetic gBlock (IDT), then amplified with Q5 High-Fidelity 2x Master Mix (NEB) to create dsDNA templates for 660 nt and 924 nt scaffolds, each with a 5’ T7 promoter.The full sequence of each DNA template is listed in Supplementary Data Using these dsDNA templates, RNA was transcribed using the manufacturers protocol for HiScribe T7 (NEB). RNA was treated with DNase I (NEB), then pre-cleaned on a ZymoClean RNA cleanup kit (RNA Clean-and-concentrator 5). Urea polyacrylamide gel (PAGE) was used to validate purity, and PAGE or HPLC was used to purify the RNAs if byproducts were present. With RNA pre-cleaned using the RNA clean-and-concentrator-5 kit (Zymo), and denatured by addition of 1x RNA loading dye (NEB) and 5–10 min incubation at 70 °C, PAGE purification was performed on a 6% gel containing 8 M urea. RNA was sliced from the gel after visualization with SYBR Safe (ThermoFisher) and eluted in 300 mM sodium acetate pH 5.2, precipitated in 70% ethanol at −20 °C for >2 h, and then pelleted at 14,000 RPM for 30 min at 4 °C.97). Buffer A was a solution containing 0.1 M TEAA, while buffer B included 0.1 M TEAA and 25% (v/v) acetonitrile. All HPLC purification of the RNA scaffold was run at 65 °C to prevent formation of secondary structure. Sodium acetate, pH 5.2, was added to a final concentration of 300 mM in the collected fraction, and the RNA was precipitated in 70% ethanol at −20 °C for >2 h, then pelleted at 14,000 RPM for 30 min at 4 °C.For HPLC purification, transcribed and column-purified (with ZymoClean RNA clean-and-concentrator-5 kit) RNA was diluted with nuclease-free water and injected into an XBridge Oligonucleotide BEH C18 column  under the following gradient, flowing at 0.9 ml/min: increasing from 38–40% solvent B over 1 min, increasing to 60% buffer B across 15 min, increasing to 66% buffer B across 6 min, increasing to 70% buffer B across 30 s, reaching 100% buffer B across 30 s, maintaining 100% buffer B for 1 min, decreasing to 38% solvent B over 1 min, where it was finally held for 2 min .We also tested two alternative published protocols with the A-form origami. Following the protocol from Wang et al.Gel mobility shift assays were performed using 2.5% high-resolution agarose (Sigma-Millipore) in 1x TAE and 2 mM magnesium acetate. Folded origami samples were prepared for loading with 1x purple DNA loading dye with no SDS (NEB). RNA scaffolds without DNA staples were prepared with 1x RNA dye (NEB) and denatured at 70 °C for 10 min or 95 °C for 2 min, followed by incubation on ice for at least 2 min immediately prior to gel loading. Gels were run on a Bio-Rad gel system in a cold room (4 °C) at 65 V for 4 h, then imaged using a Typhoon FLA 7000 scanner (GE).The size distribution of the origami nanoparticles was measured via DLS using a Zetasizer Nano ZSP . Purified nanoparticles were concentrated to 75 nM in 50 μl in 10 mM HEPES-KOH pH 7.5 and 300 mM KCl. The default procedure for DNA was used, only customizing the buffer to include 300 mM KCl. Three serial DLS measurements were performed on the same folded sample at 25 °C. The average nanoparticle diameter (nm) and polydispersity index (PdI) were computed using the associated Malvern software (Zetasizer Software v 7.12).2, maintained at 4 °C on ice.Biochemical stability in the presence of RNases A and H was also tested. 50 nM purified Alt A-form EGFP mRNA-scaffolded tetrahedron with 66-bp edge length was incubated for 5 min at 37 °C in the presence of buffer alone, 25 units of RNase H or 3.5 units of RNase A. Reactions were quenched at 4 °C and run at 65 V for 180 min on a high-resolution 2.5% agarose gel in 1X TBE with 2.5 mM Mg(OAc)g for 60 sec to extrude the gel slice into the 1.5 ml tube. Each gel slice was covered with 400 µl of gel elution buffer  and incubated in a thermomixer at 20 °C for 11 hr while shaking at 500 rpm. The slurries were decanted into Costar Spin-X Centrifuge Tube Filters (Corning) and spun at 16,000 × g for 1 min to remove gel particles. To each filtrate, 1 ml 100% ethanol was added, and the tubes were frozen at −80 °C for 1 hr. The tubes were then spun at 12,700 × g for 1 hr at 4 °C. The pellets were washed with 500 µl 75% ethanol at −20 °C and spun for another 10 min. The supernatants were removed and the tubes uncapped and placed on a 37 °C heat block to dry the pellets for 10–20 min. The pellets containing the RNA were resuspended in 10 µl nuclease-free water.The DNA template for each scaffold and the HIV-1 RRE fragment was generated, amplified, and transcribed into RNA as described above. Three denaturing polyacrylamide gels with 6 M urea (2.4 ml 5X Tris-Borate-EDTA (TBE), 4.32 g urea, 1.2 ml 40% 19:1 acrylamide:bis-acrylamide, 120 µl ammonium persulfate, 12 µl TEMED, nuclease-free water to 12 ml) were pre-run at 160 volts for 30 min. The RNAs were denatured in 2X RNA Loading Dye (NEB) at 70 °C for 10 min, immediately placed on ice, and run on the gels at 160 volts for 60 min in 1X TBE in a Mini-PROTEAN Tetra Cell (Bio-Rad). The gels were stained in 1X TBE containing 1X SYBR Safe (Thermo Fisher) for 5 min, and each band of expected molecular weight was excised and transferred to a 0.5 ml tube at the bottom of which a hole had been punctured with a needle. Each 0.5 ml tube was placed in a 1.5 ml tube and spun at 16,000 × The gel-purified RNA scaffolds were used to fold nanoparticles in folding buffer  using 20 nM scaffold and 400 nM for each staple with the temperature steps described above. Each RNA scaffold was also folded using the same protocol but without adding staples. The 23S scaffold was folded in two tubes each containing 85 µl; rT66 without staple 10 was folded in one tube containing 70 µl; all other nanoparticles and scaffolds were folded in two tubes each containing 60 µl.g for 30 min at 4 °C with 500 µl of the buffer used to fold the origami. To each pre-spun filter, 350 µl of 300 mM sodium cacodylate pH 7.2 (Electron Microscopy Sciences) was added, followed by 50–150 µl of the pooled folding product of one nanoparticle/scaffold. The samples were spun at 850×g for 30 min at 4 °C, after which the filtrate was decanted and 450 µl sodium cacodylate added to the filter, and these steps were repeated for a total of five filtrations. The fifth filtration was run for 50 min, after which each filter (containing approximately 50 µl) was inverted into a clean collection tube and spun at 1500 × g for 1 min at 4 °C to collect the sample of nanoparticles/scaffold. A 10 µl aliquot of each sample was transferred to a 1.5 ml tube.Folded nanoparticles/scaffolds were purified by five rounds of filtration through Amicon Ultra 100 kDa 0.5 ml filter columns. One Amicon filter for each of the 16 nanoparticle/scaffold samples was first spun at 2400 × As a control for normalization of the DMS reactivities, 1.3 μg of gel-purified RRE RNA was denatured in 8 μl of RNase-free water at 95 °C for 60 s and immediately placed on ice for 60 s. The denatured RRE RNA was mixed with 612 µl of 300 mM sodium cacodylate pH 7.2 (Electron Microscopy Sciences) and incubated at 37 °C for 20 min to refold its structure. A 38.5 µl aliquot of refolded RRE RNA was added into each of 16 tubes containing 10 µl of one nanoparticle/scaffold. To each sample, 1.5 µl of neat dimethyl sulfate  was added , stirred with a pipette tip, and incubated at 37 °C for 5 min in a thermomixer while shaking at 500 rpm. Each reaction was quenched by adding 30 µl neat beta-mercaptoethanol (MilliporeSigma). DMS-modified nucleic acids were purified using a Zymo RNA Clean and Concentrator-5 Kit (Zymo Research) and eluted in 10 μl RNase-free water.For each RNA sample, 4 µl was reverse transcribed in a 20 µl reaction containing 1 µl pooled reverse primers (10 µM each), 1 µl TGIRT-III enzyme (Ingex), 4 µl 5X First Strand buffer (Invitrogen), 1 µl 10 mM dNTPs (Promega), 1 µl 0.1 M dithiothreitol (Invitrogen), 1 µl RNaseOUT (Invitrogen), and 7 µl nuclease-free water. The reactions were incubated at 57 °C in a thermocycler with the lid set to 60 °C for 90 min. The RNA templates were degraded by adding 1 µl of 4.0 M sodium hydroxide (MilliporeSigma) to each reaction and incubating at 95 °C for 3 min. Each cDNA was purified using a Zymo Oligo Clean and Concentrator-5 Kit (Zymo Research) and eluted in 10 µl nuclease-free water.The cDNA from each of the 16 samples was amplified as a set of overlapping amplicons, each 250–556 bp , plus one amplicon spanning the entire RRE . For each amplicon, 1 µl purified cDNA was amplified with an Advantage HF 2 PCR kit (Takara) in a 25 µl reaction containing 0.5 µl forward primer , 0.5 µl reverse primer , 0.5 µl 50x Advantage-HF 2 Polymerase Mix, 2.5 µl 10x Advantage 2 PCR Buffer, 2.5 µl 10x HF dNTP Mix, and 17.5 µl nuclease-free water. The PCR entailed an initial denaturation step at 94 °C for 60 s, followed by 25 cycles of 94 °C for 30 sec, 60 °C for 30 s, and 68 °C for 60 sec, with a final extension at 68 °C for 60 s. All PCR products were validated using E-Gel EX-Gels with 2% Agarose (Thermo Fisher).All 47 PCR products from nanoparticles/scaffolds and 5 RRE products were consolidated into 5 pools such that no two amplicons from the same RNA sequence were pooled together. Pools 1 – 4 contained 6 µl each of 10 PCR products; pool 5 contained 5 µl each of 12 PCR products. For each pool, 30 µl was mixed with 6 µl 6X gel loading dye and run on a 50 ml gel containing 2% SeaKem Agarose (Lonza), 1x Tris-Acetate-EDTA (Boston BioProducts), and 5 µl 10,000X SYBR Safe DNA Gel Stain (Thermo Fisher) at 60 volts for 105 min. Bands at the expected sizes were excised and the DNA was extracted using a Zymoclean Gel DNA Recovery Kit (Zymo Research) and eluted in 12 µl 10 mM Tris pH 8.0 (MilliporeSigma). DNA libraries were generated and sequenced on an Illumina MiSeq using a 300 × 300 read length at the MIT BioMicroCenter sequencing core.66, using the default parameters except for a 90% coverage threshold for clustering. In order to control for variations in DMS treatment among different samples, the DMS reactivities were normalized using a custom script as follows. The median DMS reactivity among the top 50% (n = 46) of the 91 adenine (A) and cytosine (C) bases in the spiked-in RRE control was computed for each sample. For each other sample, the ratio of the median DMS reactivity of the RRE to the median DMS reactivity of the RRE in the sample of 23S scaffold without staples (the reference sample) was computed, and the DMS reactivity of the sample was divided by this ratio to normalize it.DMS-induced mutation rates (DMS reactivities) were determined using the Detection of RNA folding Ensembles with Expectation Maximization clustering (DREEM) pipeline version 1.098, Pandas 1.299, Matplotlib 3.3100, Seaborn 0.10101, and BioPython 1.7102. For each origami, ARIADNE was used to generate a table of all nucleotides in the scaffold and staple strands, indicating for each nucleotide the identity of its base  and the identity of the adjacent structural feature (if any), which could be one of seven types: double crossover of the scaffold strand (scaffold DX2), 5’ or 3’ terminus of the scaffold stand (scaffold nick), double crossover of the staple strand (staple DX2), single crossover (a.k.a. mesojunction) of the staple strand (staple DX1), 5’ or 3’ terminus of a staple stand that lies on the same double helix as and adjacent to that strand’s 3’ or 5’ terminus (staple nick), 5’ or 3’ terminus of a staple strand that abuts a single crossover of another staple strand (staple single term), or a vertex of the polyhedral origami. Scaffold nicks were excluded from further analysis due to insufficient coverage.We developed the software ARIADNE to determine the locations of these structural features using the outputs from pyDAEDALUS. ARIADNE was written in Python 3.8 and uses NumPy 1.20103. The DMS reactivities at the terminal scaffold bases in each segment, the mean DMS reactivity over the interior bases in each segment, their ratios, and the DMS reactivities of bases up to 6 nt upstream and downstream of each structural feature were computed and plotted with a custom Jupyter notebook written in Python 3.8, using Pandas 1.2, Matplotlib 3.3, and Seaborn 0.10. The melting temperature of each segment was predicted using a nearest neighbor model104 and salt correction105 for RNA/DNA duplexes, with 300 mM Na+, implemented in BioPython 1.7. All statistical significance tests and estimates of parameters were performed using SciPy 1.6106. Only non-parametric tests were used in order to avoid making assumptions about the underlying distributions. Each analysis was also repeated on the DMS reactivities of only adenines and of only cytosines separately in order to control for the covariate of base identity. A table of all DMS reactivities and structural features of every origami analyzed in this study is given in Supplementary Data ARIADNE was used to identify all double helical segments, defined as a set of contiguous scaffold-staple base pairs bordered by a structural feature on each end with no structural features in the middle, as in a previous work2. We used a defocus range of −1.5–−3 μm to collect images, which were subsequently motion-corrected using MotionCor2107; CTF was estimated using CTFFIND4108. The initial particles were picked manually by e2boxer.py in EMAN2109. The particles were imported into cryoSPARC110 software for further 2D analysis and 3D refinement. For the A-form origami, the percentages of particles kept from initial picking and 2D analysis for final reconstructions were approximately 32.8% for rT66, 17.5% for rO44, 46.9% for rO66, and 40.2% for rPB66. The total number of images collected and total particles used for final refinement are listed in Supplementary Table 111. Correlation of each map with its corresponding atomic model is calculated by the UCSF Chimera fitmap function, with density simulated from the model at the same resolution as the corresponding reconstruction. Density map edge length measurements were performed with the tape measure tool in UCSF Chimera X112, measuring each edge and averaging the edge length measurements per object. For comparison, each A-form origami object was also reconstructed without symmetry imposed, and these maps are displayed in the supplement  were applied onto the glow-discharged 200-mesh Quantifoil 2/1 grid, blotted for four seconds and rapidly frozen in liquid ethane using a Vitrobot Mark IV (Thermo Fisher Scientific). All grids were screened and imaged on a Talos Arctica cryo-electron microscope (Thermo Fisher Scientific) operated at 200 kV at a magnification of 79,000× . Micrographs were recorded by EPU software (Thermo Fisher Scientific) with a Gatan K2 Summit direct electron detector in counting mode, where each image is composed of 24 individual frames with an exposure time of 6 s and a total dose ~63 electrons per ÅSequences of De Bruijn scaffolds were designed using a De Bruijn order of 8, such that no sub-sequence of 8 nucleotides was identical to any other sub-sequence of 8 nucleotides or its reverse complement. A single sequence of 1218 nt was generated; the first 660 and 924 nt were used as the scaffolds of rT55 and rT77, respectively.Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Reporting Summary


The structural transitions RNAs undergo during trafficking are not well understood. Here, we used the well-developed yeast Ty1 retrotransposon to provide the first structural model of genome (g) RNA in the nucleus from a retrovirus-like transposon. Through a detailed comparison of nuclear Ty1 gRNA structure with those established in the cytoplasm, virus-like particles (VLPs), and those synthesized in vitro, we detected Ty1 gRNA structural alterations that occur during retrotransposition. Full-length Ty1 gRNA serves as the mRNA for Gag and Gag-Pol proteins and as the genome that is reverse transcribed within VLPs. We show that about 60% of base pairs predicted for the nuclear Ty1 gRNA appear in the cytoplasm, and active translation does not account for such structural differences. Most of the shared base pairs are represented by short-range interactions, whereas the long-distance pairings seem unique for each compartment. Highly structured motifs tend to be preserved after nuclear export of Ty1 gRNA. In addition, our study highlights the important role of Ty1 Gag in mediating critical RNA–RNA interactions required for retrotransposition. Pseudoviridae), Ty3/Gypsy (Metaviridae), and BEL/Pao (Belpaoviridae)  or 40 µL DMSO alone (-). The modification reactions were carried out at 37 °C for 15 min. RNA modification reactions with NAI were additionally quenched by adding 1 M DTT at a 1:1 ratio to the reaction volume. Cells were collected by centrifugation at 8000× g for 5 min.A total of 100 mL of galactose-induced yeast culture (DG3408 or BY4742) was centrifuged at 7500× g for 5 min, supernatants were transferred to fresh tubes, and RNA was extracted twice with phenol (pH 8.0) and twice with acid phenol:chloroform (pH 4.5). RNA was recovered by LiCl precipitation overnight at −20 °C, pellets were washed twice with 70% ethanol, and then they were resuspended in an appropriate amount of water.RNA isolation was performed as previously described . BrieflyThe optimal amount of SHAPE modified (+) or control (−) RNA sample was combined with 1 µL of 10 µM fluorescently labeled primer [Cy5 (+) or Cy5.5(−)] and 1 µL 2 mM EDTA pH 8.0, 3.84 µL of 5 M betaine and water to a final volume of 12 µL. Primer-template solutions were initially incubated at 95 °C for 3 min, 37 °C for 10 min, and 55 °C for 2 min. A total of 8 µL of reverse transcriptase mix  was added to each reaction tube, followed by an additional 90 min incubation at 50 °C. Sequencing ladders were prepared using labeled primer: WellRed D2 (ddA) or IRD-800 (ddT) and a Thermo Sequenase Cycle Sequencing kit  as recommended by the manufacturer. Reverse transcribed samples and sequencing ladders were purified using ZR DNA Sequencing Clean-Up Kit  and analyzed on a GenomeLab GeXP Analysis System . Raw electropherograms were processed using ShapeFinder software  and norm−1, respectively) for each calculation. A partition function was computed in 1200-nt sliding windows with the increment of 100 nts, the pairing distance was limited to 600 nts, and the four additional calculations were performed on the 5′ and 3′ ends of the nuclear Ty1 gRNA. Moreover, 300 nts were trimmed from each window to exclude the end effect. Base-pair probabilities from multiple windows were combined. Shannon entropies were calculated from individual base-pairing probabilities and combined into a single, 55-nt sliding windows profile. The MFE structure was predicted with the SHAPE data as pseudo-energy constraints, and base pairs with >99% probability were added as hard constraints. Fold was run in 3000-nt sliding windows with 300 nt-increments, and the pairing distance was set to 600 nts. Four additional fold calculations were performed on the 5′ and 3′ ends, as described above. The final MFE structure was combined from multiple windows with the requirement that base pairs must appear in a majority of the windowed folds. Well-defined regions (lowSS) were identified by selecting regions with at least 40 nts with both median SHAPE and median Shannon entropy values below their respective medians. Some lowSS regions were combined or expanded to include the entirety of helixes predicted in MFE. RNA structures were visualized using VARNA [A SHAPE-derived minimum free energy (MFE) secondary structure model for nuclear Ty1 gRNA was predicted using an updated version of SuperFold (v1.1) . The preng VARNA . Additiong VARNA , in whicThe signal-to-background (S/B) ratio for NMIA and NAI modification in the yeast nucleus was calculated based on ShapeFinder raw output files. The signal and background peak area values for each nucleotide were averaged, and their medians were estimated. S/B was then calculated as the ratio between the medians of signal and background. Spearman’s correlations and linear regressions were computed with GraphPad Prism 8 software.Sensitivity and PPV values for the entire nuclear Ty1 gRNA MFE model were calculated relative to the cytoplasmic or in vitro Ty1 gRNA MFE using the Scorer function implemented in RNAStructure. To ensure that compared structures have identical sequence, the adenine at position 58 in the frameshift mutant Ty1fs was manually deleted from cytoplasmic and in vitro Ty1 MFE structures. For identified lowSS regions, sensitivity and PPV values were computed relative to the nuclear Ty1 gRNA MFE. If the region of interest holds only a half of the predicted base pairings, nucleotides from the disrupted helix were added manually to the calculations. SHAPE reactivities for Ty1 gRNA in virio were reported previously . For comThe absolute value of the SHAPE reactivity difference between nuclear and cytoplasmic compartments was summed over 75-nt sliding windows. Spans of at least 100 consecutive nucleotides in which absolute reactivity changes were above the global median change were characterized as regions with the largest SHAPE reactivity differences.S. cerevisiae strain BY4742 using NMIA and 2-methylnicotinic acid imidazolide (NAI)—SHAPE reagent previously shown to be suitable for RNA probing inside the nucleus of mammalian cells [SHAPE mapping using an appropriate electrophile to acylate the ribose 2′-hydroxyl groups efficiently interrogates the flexibility of local RNA structures in vitro and in vivo . Severalan cells . Using cTo determine the structure of Ty1 gRNA in the yeast nucleus, we used a previously-characterized yeast strain—DG3408—that naturally lacks chromosomal Ty1 elements, and expression of Ty1 occurs exclusively from a galactose inducible plasmid pGTy1fs   Figure C. Ty1fs To investigate how the structure of LTR-retrotransposon gRNA changes during replication in host cells, we performed a detailed comparison of SHAPE data for the nuclear and cytoplasmic Ty1 gRNA states . We can We compared the overall SHAPE reactivity distribution in different Ty1 gRNA states A. The diTo follow Ty1 gRNA structural changes between cell compartments, we calculated the position-dependent correlation between their SHAPE reactivities C. We fouGAG and POL ORFs. Such extensive reactivity alterations support compartment-specific folding of Ty1 gRNA rather than differences in RNA/protein interactions or RNA modification patterns that usually induce more local changes [Analysis of SHAPE reactivity profiles confirmed the substantial differences detected between many regions of the nuclear, cytoplasmic, or in vitro Ty1 gRNA states D. To est changes .To better understand Ty1 gRNA folding inside the nucleus, we used the SuperFold pipeline to perform SHAPE-directed windowed modeling of the minimum free energy (MFE) RNA structure  Figure A. ExaminTo consider the complete ensemble of possible Ty1 gRNA structures in the nucleus, we calculated the probability of each base-pairing in the MFE model A. HighlyTo better understand the structural heterogeneity of nuclear Ty1 gRNA, we determined the most compact and thermodynamically stable RNA regions. Based on low SHAPE reactivity and Shannon entropy values (lowSS framework) , we idenShannon = 0.09). Based on the lowSS approach, we were able to identify 4 lowSS regions that were partially shared in these states of Ty1 gRNA , where nucleotides at positions 1–7 and 256–262 form base pairs with nucleotides 264–270 and 319–325, respectively ,41. The Due to the rapid development of RNA probing techniques, the structures of several viral RNAs in distinct experimental conditions have been resolved, e.g., ,52,53,54Here, we took advantage of a well-developed Ty1 experimental system to resolve the first structure of a retroviral-like RNA in the nucleus. To avoid problems concerning inefficient purification of intact yeast nuclei and the low level of wild type nuclear Ty1 RNA, we utilized a genetically modified element that does not produce Ty1 Gag and accumulates GAL1-promoted Ty1fs RNA in the nucleus . In the In support of our previous findings that the cellular environment greatly impacts Ty1 RNA architecture , we obseAlthough Ty1 gRNA displays a higher degree of structural heterogeneity in the nucleus, we identified 11 thermodynamically stable regions (lowSS regions) that significantly overlap with those in the cytoplasm . Prior sThe exact mechanisms by which RNA structures are modulated in vivo are not well understood. While some studies suggest that translation is the primary force responsible for the RNA structural remodeling, others highlight the importance of RNA binding proteins or RNA modifications ,62. We pStudying RNA structures in cellular compartments is essential to gain a comprehensive view of the complex interplay between RNA structure and function. Our work is the first to present the nuclear structure of a viral-like gRNA, although it may be premature to conclude whether compartment-specific gRNA folding is a general feature of LTR-retrotransposons or other reverse-transcribing single-strand RNA viruses. However, additional RNA structural studies across cellular compartments are needed to define the common or specific mechanisms of viral and retrotransposon gRNA structure modulation.


Excessive adiposity caused by high-fat diets (HFDs) is associated with testicular metabolic and functional abnormalities up to grand-offspring, but the mechanisms of this epigenetic inheritance are unclear. Here we describe an association of sperm small non-coding RNA (sncRNA) with testicular “inherited metabolic memory” of ancestral HFD, using a transgenerational rodent model. Male founders were fed a standard chow for 200 days (CTRL), HFD for 200 days (HFD), or standard chow for 60 days followed by HFD for 140 days (HFDt). The male offspring and grand-offspring were fed standard chow for 200 days. The sncRNA sequencing from epidydimal spermatozoa revealed signatures associated with testicular metabolic plasticity in HFD-exposed mice and in the unexposed progeny. Sperm tRNA-derived RNA (tsRNA) and repeat-derived small RNA (repRNA) content were specially affected by HFDt and in the offspring of HFD and HFDt mice. The grand-offspring of HFD and HFDt mice showed lower sperm counts than CTRL descendants, whereas the sperm miRNA content was affected. Although the causality between sperm sncRNAs content and transgenerational epigenetic inheritance of HFD-related traits remains elusive, our results suggest that sperm sncRNA content is influenced by ancestral exposure to HFD, contributing to the sperm epigenome up to the grand-offspring. The adoption of high-fat diets (HFDs) associated with increased adiposity, often from early life, is considered one of the major contributors for the present “fat pandemic”. Concurrently, the prevalence of non-communicable diseases, such as type 2 diabetes (T2D), has increased proportionally. The most recent figures by the World Health Organization (WHO) and by the International Diabetes Federation (IDF) estimate that more than 500 million people worldwide have obesity, and 463 million suffer from T2D ,2. TheseThe role of sperm small non-coding RNA (sncRNA) in epigenetic inheritance has been suggested by several authors ,6. RecenObesity, T2D, and diet alter sperm sncRNA content ,12,13, aIn this study, we describe sperm sncRNA response to lifelong exposure to HFD and exposure to HFD until early adulthood. We further investigate if ancestral exposure to HFD is reflected in the sperm sncRNA profile in the offspring. This work was conducted by using the same animal model as our recent studies ,17,18,19n = 36) were randomly divided in three groups: control (CTRL) (n = 12), HFD (n = 12), and HFDt (n = 12). Each group was assigned to a diet regimen: CTRL—standard chow  during 200 days; HFD—fat-enriched diet  during 200 days; and HFDt—fat-enriched diet  during 60 days, then switched to standard chow  during 140 days. When animals reached 120 days post-weaning age, F0 mice were mated with normoponderal, chow-fed, same-age, randomly selected females to generate the unexposed offspring (Generation F1). Mating was performed in mating pairs, without access to water and food for 6 h a day. The process was repeated over 8 days. After weaning, the F1 mice were assigned to the same experimental group as their fathers: CTRL_F1—Offspring of CTRL (n = 12), HFD_F1—Offspring of HFD (n = 12), and HFDt_F1—Offspring of HFDt (n = 12), but all mice were fed with standard chow  during 200 days. F1 mice were mated in the same scheme as their progenitors to generate the unexposed grand-offspring (Generation F2). F2 mice were assigned to experimental groups in the same way as their fathers , and fed with standard chow for 200 days after weaning. Food and water were supplied without restrictions to all generations. Mice from all generations were killed by cervical dislocation 200 days after weaning, and tissues were collected for further analysis. Total body weight, water, and food intake were monitored weekly, from weaning to sacrifice. The animal model is compliant with the ARRIVE guidelines, was internally reviewed by the Organization for Animal Welfare (ORBEA) and approved and licensed by the Portuguese Veterinarian and Food Department (DGAV) with the registration number 0421/000/000/2016. All animal experiments were conducted in the Animal Facility of the Research Center in Health Sciences (CICS) of the University of Beira Interior , according to the “Guide for the Care and Use of Laboratory Animals” published by the US National Institutes of Health  and European rules for the care and handling of laboratory animals (Directive 86/609/EEC). None of the interventions performed on the animals required the use of anesthetics.We designed a transgenerational ancestral exposure model based on three generations of C57BL6/J mice ,19. Normg for 5 min at room temperature, and the supernatant was discarded, according to the manufacturer’s instructions (protocol for cells grown in suspension). RNA pellets were resuspended in 20 μL of DEPC-treated water and stored at −80 °C until library preparation.Epididymides were isolated and placed in pre-warmed (37 °C) Hank’s Balanced Salt Solution (HBSS), pH 7.4. Then small incisions were made using a scalpel blade, and the suspension was incubated for 5 min (37 °C) to allow spermatozoa to swim out of the epididymis. The purity of the sperm solution was accessed in sperm swabs stained by eosin–nigrosin and observed by an optical microscope . The sol® Small RNA-Seq Kit v3 for Illumina  according to the manufacturer instructions. Pooled libraries were sequenced by using Next-Generation Sequencing (NGS), in single-end mode, on NextSeq 500 with NextSeq 500/550 High Output Kit version 2, 75 cycles . All pooled libraries passed Illumina’s default quality control.Before library preparation, RNA concentration and integrity were screened by using an Agilent 2100 Bioanalyzer . The RNA integrity number (RIN) was globally low (ranging 2–5), a normal value for RNA obtained from mature spermatozoa, which lacks 18S and 28S rRNA peaks [https://github.com/junchaoshi/sports1.1; accessed on 1 June 2020), a perl-based analytical workflow tweaked for the annotation of sncRNAs [https://hgdownload.soe.ucsc.edu/downloads.html#mouse; accessed on 1 June 2020), miRNA from miRbase 22 , rRNA-derived small RNA (rsRNA) from NCBI/Nucleotide (available at SPORTS repository), tRNA-derived small RNA (tsRNA) from GtRNAdb , and piRNA from pirBase 2.0 . Fragment counts for specific sequences and for sncRNA biotypes , per sample, were based on the default annotations in SPORTS result output files.Cutadapt version 2.10  was used sncRNAs . SPORTS https://www.smallrnagroup.uni-mainz.de/piCdb/; accessed on 3 June 2020), and interspersed repeats to their genomic region in to Dfam 3.1 database [https://www.dfam.org/home; accessed on 3 June 2020), using featureCounts to aggregate the final sequence counts.SPORTS 1.1 is unable to annotate piRNAs and repRNAs ; therefore, an alternative annotation using HISAT2 , SAMtooldatabase   [p-value cutoff = 0.01. Differently expressed piRNA clusters were added to the list of potential miRNA and tsRNA targets. This list was uploaded to R 4.1.0 [Differently expressed sncRNAs were selected for term enrichment analysis based on gene ontology (GO) terms ,31. Firsst 2020) , based ost 2020)  and RNAhst 2020)  interact R 4.1.0  and anno R 4.1.0  and GO.d R 4.1.0 . Target p < 0.1. A fragment was considered differently expressed whenever log2 Fold Change (FC) > |1.5| and adjusted p < 0.1. GO term enrichment analysis was tested by Fisher Exact test. GO term annotations were sorted according to their “weight01” score. GO terms were considered significant when p < 0.1, regardless of the statistical test. Whenever more than 10 GO terms met the criteria, only the top 10 terms were considered.Raw sequence counts obtained by SPORTS and featureCounts were imported as dataframes into R 4.1.0 . A non-cTo understand how the sperm sncRNA profile responds to chronic (200 days) exposure to high-fat initiated at weaning, we collected mature spermatozoa from chow-fed (CTRL) and HFD-fed mice (HFD) for small RNA-sequencing. We also analyzed sperm from mice on transient HFD  to study if the exposure to HFD and adiposity cause irreversible changes in sperm sncRNA content. To get a general view on the mapping of sperm RNA reads into different RNA biotypes, annotated RNA sequences were categorized as miRNA, tRNA-derived small RNA (tsRNA), mitochondrial tRNA-derived small RNA (mtRNA), Piwi-interacting RNA (piRNA), rRNA-derived small RNA (rsRNA), repeat-derived small RNA (repRNA), and Y RNA, and their total counts were normalized by using DESeq2 based on total genome-matched sequences. We compared only animals which have lived during the same period in order to limit the influence of uncontrollable variables that may affect sperm sncRNA content, such as seasonal and environmental variation. This analytical strategy has been commonly adopted in transgenerational inheritance models ,40.p = 0.0013) and compared to HFD  (p = 0.0128). The size distribution of small RNA reads was as expected (HFD or HFDt did not cause major changes in the relative fraction of the different RNA biotypes in sperm in any of the generations (F0–F2). Only rsRNA reads were slightly increased in F0 sperm after transient HFDt compared to CTRL  A. Contra 0.0945) A,B  analysis between groups to identify any changes in the levels of individual RNAs. We analyzed separated miRNAs and two distinct groups of tsRNAs: transcription initiation RNAs (tiRNAs), also known as tRNA halves, and tRFs (tRNA-derived fragments). The tiRNAs are 29–50 nucleotide sequences resulting from the cleavage of mature tRNAs at the anticodon loop by angiogenin, thus producing a 3′-tRNA half and a 5′-tRNA half. The tiRNAs are involved in the post-transcriptional gene expression regulation via base complementarity to transcription start sites, to RNAse II recognition patterns, and to the ribosome ,42,43. NTo study the intergenerational effect of exposure to HFD in sperm sncRNA content, mice founders (Generation F0) were randomly assigned to a normoponderal female in mating pairs 120 days after weaning. The resulting male offspring (Generation F1) were exclusively fed with chow diet for 200 days, independently of the diet regimen of its male progenitor. Littermates were assigned to the same experimental group (lineage) as its progenitor.p < 0.0001 and 3068-5p, log2FC = −6.78, p = 0.0701) and one tiRNA  compared to the CTRL F1 offspring  of the male founders.An ancestral chronic HFD did not leave any detectable RNA signatures in F2 sperm, since no differentially expressed RNAs were identified A. HoweveTo estimate the potential role of the sncRNA sequences in testicular function and sperm parameters, targets of differently expressed miRNAs and tsRNAs were predicted by using bioinformatic tools. These targets and the differently expressed piRNA clusters were then annotated according to gene ontology (GO) terms for biological processes , moleculThe most significant GO terms resulting from the targets of the differently expressed sncRNAs between HFDt and CTRL mice are the sensory perception of smell and the G-protein-coupled receptor signaling pathway , indicatInterestingly, this term is also prominent, considering the differences between the offspring of HFDt compared to the offspring of HFD. Compared to the offspring of CTRL, sperm sncRNAs from the offspring of HFD have several changes in GO terms of biological processes linked to cell motility, cytoplasm projections, and even sperm activation . Comparing the potential impact of differently expressed sperm sncRNAs between the offspring of HFD and the offspring of HFDt, the most relevant biologic process terms are related to antioxidant response and cell proliferation, especially of bone-related cells. However, in this comparison, relevant molecular function terms are related to ATP binding and energy-sensing receptors , whereasThe targets of the differently expressed sperm sncRNAs between the grand-offspring of HFDt and grand-offspring of CTRL mice are mostly associated with metabolic regulation, cell adhesion, and cell differentiation . The estThe increasing prevalence of obesity and associated comorbidities is primarily associated with risk behaviors, such as excessive caloric intake and physical inactivity. However, several studies have suggested a modulation of the predisposition to weight gain and the onset of non-communicable diseases due to ancestral exposure HFD ,48,49, eIn previous works ,17, we hAnother striking difference between the results of this study and our previous studies is related to the offspring of the mice exposed to HFD ,19. The An interesting finding from our previous transgenerational studies ,19 was tWith this project we have demonstrated the conditional inheritability of phenotypes related to ancestral exposure to HFD B. The exIn summary, we have shown that HFD causes a “rippling effect” in HFD-related phenotypes of testicular function and sperm sncRNA content. The “inherited metabolic memory” of ancestral exposure HFD results from a complex interaction between the inherited epigenome and stochastic events that creates a new epigenetic landscape that may not be associated with an evident phenotype, yet produces a new sperm epigenetic signature which will influence the epigenome of the following generation B. Howeve