The 5′ and 3′ termini of RNA play important roles in many cellular processes. Using Förster resonance energy transfer (FRET), we show that mRNAs and lncRNAs have an intrinsic propensity to fold in the absence of proteins into structures in which the 5′ end and 3′ end are ≤7 nm apart irrespective of mRNA length. Computational estimates suggest that the inherent proximity of the ends is a universal property of most mRNA and lncRNA sequences. Only guanosine-depleted RNA sequences with low sequence complexity are unstructured and exhibit end-to-end distances expected for the random coil conformation of RNA. While the biological implications remain to be explored, short end-to-end distances could facilitate the binding of protein factors that regulate translation initiation by bridging mRNA 5′ and 3′ ends. Furthermore, our studies provide the basis for measuring, computing and manipulating end-to-end distances and secondary structure in RNA in research and biotechnology. It was previously suggested that formation of RNA secondary structure tends to bring the 5′ and 3′ ends of RNA into close proximity. Here the authors use experimental and computational approaches to show that mRNAs and lncRNAs have an intrinsic propensity to fold into structures in which the 5′ end and 3′ end are ≤7 nm apart irrespective of length. RNA termini are recognized by a number of protein factors that mediate RNA processing and mRNA translation4. The binding of protein factors to RNA termini, rates of RNA degradation by exonucleases and translation regulation are affected by the intramolecular secondary structure of RNA8.The sequence and secondary structures at the 5′ and 3′ termini of RNA have important roles in various cellular processes11. One study predicted that the 5′ to 3′ end distance in RNAs is 3 nm, on average10. These theoretical predictions were tested by single-molecule Förster resonance energy transfer (smFRET) measurements of end-to-end distances in several viral RNAs and mRNAs from the fungus Trichoderma atroviride, which varied in length between 500 and 5000 nucleotides and were folded in vitro in the absence of any protein factors12. Experimentally derived end-to-end distances in RNA molecules, in which FRET was detected, ranged between 5 and 9 nanometers12.Recent theoretical analyses of a number of randomized and natural RNA sequences suggested that the 5′ and 3′ ends of long  RNAs are always brought in the proximity of few nanometers of each other regardless of RNA length and sequence because of the intrinsic propensity of RNA to form widespread intramolecular basepairing interactions11. The propensity of human mRNAs and lncRNAs to fold into structures with short end-to-end distances has also not been examined. In a published smFRET study12, end-to-end distance was measured only in molecules that showed FRET, which might have represented only a minor fraction of the total population of RNA molecules. It is further unclear to what extent end-to-end distance may vary between different transcripts. Sequence features that define RNA potential to fold into structures with short end-to-end distances are unknown.The intrinsic closeness of RNA ends may have a number of biological implications for various aspects of mRNA metabolism including translation, splicing or degradation. However, the hypothesis that the closeness of RNA ends is a universal property of all natural transcripts remains to be systematically tested. Previous computational studies explored end-to-end distances in a limited number of natural sequencesHere, we use FRET measurements and computational analysis of RNA structure to examine the end-to-end distances in mRNAs and lncRNAs from several species, including humans. Our study focuses on natural mRNA and lncRNA sequences because of their biological importance. We find that most, if not all, mRNAs and lncRNAs have an intrinsic propensity to fold into structures with short end-to-end distances irrespective of their length and sequence.13) to distance changes matches the theoretically predicted array of distances between the 5′ and 3′ ends of structured RNAs11. We selected yeast and human mRNAs that encode abundant housekeeping proteins and have well-annotated 5′ and 3′ UTR sequences, such as yeast RPL41A  and human GAPDH   cytoplasmic Mg2+ in human cells (0.5–1 mM)16. Energy transfer between fluorophores attached to the 5′ end of the 5′ UTR and 3′ end of the 3′ UTR was detected in all eight tested mRNAs. The average end-to-end distances, which were determined for each transcript from ensemble FRET data, were in the range of 5–7 nm irrespective of mRNA length  tail, with donor (Cy3) and acceptor (Cy5) fluorescent dyes, respectively. Computational prediction of RNA secondary structure suggests that all examined mRNAs can form extensive intramolecular basepairing interactions Fig. . mRNAs wory Fig. .We next tested whether mRNA ends are brought into close proximity by basepairing interactions. Refolding of human GAPDH and rabbit β-globin mRNAs in the presence of a 50-nucleotide-long DNA oligonucleotide complementary to the 3′ end of the respective mRNA led to a marked reduction in the efficiency of energy transfer between fluorophores attached to RNA ends Fig. . The obs53GAPDH mRNA variant. Likewise, 53 CA repeats were inserted at the 3′ end of the 202 nucleotide-long 3′ UTR of GAPDH mRNA in place of 106 nucleotides of the original sequence, to make the 3′UTR(CA)53GAPDH mRNA variant 53GAPDH mRNAs  NAs Fig. . These r19. Therefore, the poly(A) tail is unstructured and not involved in basepairing interactions with the 5′ UTR.mRNAs in eukaryotic cells undergo 5′ capping (attachment of 7-methyl-guanosine to the 5′ end) and polyadenylation of the 3′ end. In the experiments described above, we measured the distance between the 5′ end of the 5′ UTR and the 3′ end of the 3′ UTR of model mRNAs in the absence of the 5′ cap and the poly(A) tail because neither the 5′ cap nor adenosine repeats are likely to significantly affect secondary structure of mRNAs that lack extended uridine repeats. We tested the validity of this assumption by attaching donor and acceptor fluorophores to the ends of β-globin and GAPDH mRNAs transcribed with a 30 nucleotide-long poly(A) tail. Addition of a poly(A) tail led to a significant reduction in FRET efficiency Fig. , corresp22 and our own computational predictions suggest that mRNAs fold into an ensemble of structures with comparable thermodynamic stabilities rather than into a single structure. To test this prediction, we examined end-to-end distance in individual GAPDH, β-globin, and MIF mRNA molecules by measuring smFRET using total internal reflection fluorescence (TIRF) microscopy. smFRET reveals the structural dynamics of individual molecules that are masked in ensemble (bulk) FRET measurements because of signal averaging in the heterogeneous and non-synchronized population13. A previous smFRET study, which examined end-to-end distances in long transcripts, did not provide insights into mRNA structural dynamics because smFRET was measured in freely diffusing molecules12. To immobilize mRNAs to the surface of the microscope slide and, thus, to extend the observation time, a 20-nucleotide-long DNA oligonucleotide conjugated to biotin was annealed in the middle of the RNA where it was computationally predicted to have a minimal effect on the overall secondary structure and end-to-end distance of the RNA23  fluorescence with the green (532 nm) laser. smFRET traces acquired for GAPDH, β-globin and MIF mRNAs exhibited single-step photobleaching of both donor and acceptor fluorophores, indicating that we observe intramolecular rather than intermolecular energy transfer between mRNA ends  or three (β-globin and MIF mRNAs) Gaussians Fig. . The dis26. Consistent with FRET distribution histograms, individual GAPDH mRNA molecules predominantly fluctuated between ~0.4, 0.6, and 0.8 FRET states at frequencies of ~0.1–0.03 s−1  of the dynamic smFRET traces showed fluctuations between three  or all four  FRET states  in bringing mRNA ends in close proximity.Interestingly, FRET between the 5′ and 3′ ends in β-globin and MIF mRNAs showed stronger dependence on Mg33 and a freely jointed chain polymer theory19, we developed a new algorithm for modeling the distribution of end-to-end distances for the folding ensemble in natural RNAs to test the hypothesis about the proximity of RNA ends at a transcriptome-wide level. In this algorithm, a representative thermodynamic ensemble of structures is selected by stochastic sampling34, and then the distance between the 5′ and 3′ ends is estimated for each member of the sample in nanometers. The calculation employs two segment sizes (unpaired nucleotides and helix ends), which are estimated based on the freely jointed chain model of polymer theory19. We do not consider the presence of the poly(A) tail of mRNAs because the poly(A) tail is unlikely to make base-pairing interactions with the rest of the mRNA . For each %GC value, we calculated average end-to-end distance over 100 sequences, each of which was generated randomly. The ratios A/U and G/C were fixed to the same value as those in GAPDH. Our computational analysis shows that variation in GC content does not substantially affect the end-to-end distance in RNA .Although we find that the ends of most RNA sequences are inherently close, we have also demonstrated that the introduction of CA-repeats, which are known to have low basepairing potential, increase end-to-end distance in RNA. To further investigate the relationships between sequence properties, basepairing potential and end-to-end distance of RNA, we evolved the human GAPDH mRNA sequence in silico using a genetic algorithm. In this newly developed algorithm, populations of sequences are evolved either by random mutation or by crossover (combination of two sequences from the population), and then sequences with the lowest mean basepairing probabilities are selected for subsequent iterative refinement (details can be found in Methods). We performed 500 independent in silico evolution transformations of the GAPDH mRNA sequence; each of these transformations entailed 1000 mutation/sequence selection iterations. For each iteration of sequence evolution, we estimated RNA end-to-end distance and sequence linguistic complexity43.In silico evolution transformations of the GAPDH mRNA sequence revealed that a reduction in average basepairing probability leads to an increase in end-to-end distance of RNA Fig. . In addiA reduction in average basepairing probability is also accompanied by a decrease in sequence linguistic complexity Fig.  leading Although the decrease in sequence complexity levels off and sequences become completely depleted of guanosines after ~200 iterations, basepairing probability and end-to-end distance continue evolving until they plateau after ~500 iterations. The maximal value of end-to-end distance (46 nm) achieved during in silico sequence evolution of the 1327-nt long GAPDH mRNA is equal to the end-to-end distance predicted for RNA of this length in the random-coil conformation. Therefore, guanosine depletion and diminishing of sequence complexity are necessary but not sufficient to convert structured RNA into a completely unstructured conformation. Only specific, low-complexity sequences of adenosines, cytosines and uracils adopt the random-coil conformation. Hence, if intrinsically unstructured RNA sequences occur in organisms, then they likely have an important biological role and emerged as results of intense natural selection.44. To overcome this problem, we employed our genetic algorithm to generate 500 sequences of human GAPDH mRNA, in which the last 106 nucleotides of the 3′ UTR were evolved into non-repetitive, intrinsically unstructured sequences  by translocating along the mRNA during the elongation of the polypeptide chain47. However, RNA interactions with the ribosome and RNA-binding proteins are dynamic and, thus, at least transiently, mRNA and lncRNA likely fold in vivo. Indeed, several recent transcriptome-wide chemical probing studies in yeast, plant and human cells showed that mRNAs adopt extensive intramolecular secondary structure in vivo51. A number of structured elements within the mRNA, including bacterial riboswitches52, frameshift-inducing hairpins and pseudoknots of eukaryotic viruses53, Internal Ribosome Entry Sites (IRES)54, Iron Response Elements (IRE) in the 5′ UTR of transcripts coding for proteins involved in iron metabolism55, and Cap-Independent Translational Enhancers (CITEs)56, were shown to regulate translation initiation. Studies have also shown that accessibility of protein binding sites on mRNA and mRNA polyadenylation are also governed by RNA secondary structure58. Hence, at least to some extent, the secondary structure of mRNA can be maintained in the cell despite the presence of RNA helicases and other RNA-binding proteins51. Moreover, experimental evidence suggests that the thermodynamics rather than kinetics of co-transcriptional folding appears to determine the predominant secondary RNA structures in live cells59. In addition, in vivo mapping of RNA–RNA interactions using psoralen cross-linking in yeast and human cells detected intramolecular basepairing interactions between distant segments of mRNA, including interactions between the 5′ and 3′ UTRs51. These data indicate that the 3′ end of the 3′ UTR may be brought near the 5′ end of mRNA through intramolecular basepairing interactions in live cells.At least to some degree, the intrinsic mRNA and lncRNA propensity of folding into structures with short end-to-end distances is likely realized in live cells. It is possible that co-transcriptional RNA folding in vivo might be different from the folding of full-length RNA in vitro in terms of both the folding pathway and final formed structure. Furthermore, RNA secondary structure may be disrupted by RNA-binding proteins and RNA helicases6. The intrinsic closeness of mRNA ends may also influence eukaryotic translation initiation, which involves protein-mediated interactions between mRNA ends. The recruitment of the small ribosomal subunit to the 5′ end of the mRNA during translation initiation is stimulated by the interaction between the 5′ mRNA cap-binding protein eIF4E and the 3′ poly(A) tail binding protein PABP, which is mediated through their binding to different parts of the translational factor eIF4G61. The eIF4E•eIF4G•PABP complex is thought to enhance translation initiation by circularizing the mRNA and forming the “closed-loop” structure64. The mechanism by which the mRNA closed loop enhances protein synthesis is not well understood.The inherent closeness of mRNA and lncRNAs ends may have important implications for many aspects of mRNA biology, including RNA decay and translation. For example, basepairing interactions between RNA ends may affect RNA susceptibility to degradation by exonucleases65. The pervasiveness of protein bridges between mRNA UTRs in the evolution of translation regulation is puzzling because of the significant entropic cost expected for protein-mediated mRNA circularization10.Remarkably, translation initiation of many eukaryotic mRNAs is also regulated by sequences in their 3′ UTRs and controlled by the formation of protein bridges between the 5′ and 3′ UTRs. For example, the 3′ UTR regulatory sequences recruit protein complexes , which inhibit translation by interacting with either eIF4E or eIF4E•eIF4G bound to the 5′ end of mRNAThe entropic penalty for the formation of protein bridges between mRNA ends may be partially mitigated by mRNA compaction through intramolecular basepairing interactions. The protein complexes, which regulate translation by simultaneously interacting with the mRNA 5′ and 3′ ends or UTRs may have emerged during evolution to exploit the intrinsic closeness of mRNA ends. Thus, mRNA secondary structure, which brings mRNA ends in close proximity, may stabilize the binding of translation factors bridging mRNA ends.8. It is possible that during translation initiation, the 5′ end of the 5′ UTR undergoes partial unfolding while the rest of mRNA remains folded and compact, enabling recruitment of the small ribosomal subunit to the 5′ mRNA cap.Spontaneous fluctuations of mRNA between different structural states, which were observed in our smFRET experiments, might also have a role in translation. The presence of stable secondary structure near the 5′ mRNA cap and the start codon was previously shown to inhibit translation initiationIn the course of this work, we developed approaches and tools for measuring, computing, and manipulating mRNA end-to-end distances and the secondary structure of mRNA UTRs. This methodology can now be utilized to study unknown roles of mRNA end-to-end distance and secondary structure in mRNA UTRs in protein synthesis and other facets of mRNA biology.2, and 0.8 mM each of ATP, UTP, GTP, and CTP. The reaction was initiated by adding homemade T7 RNA polymerase to a final concentration of 2 μM and then incubated at 37 °C for 4–6 h. After the transcription reaction, the synthesized RNA was precipitated with 0.3 M sodium acetate pH 5.3 and 2.5 volumes of ethanol. The precipitated RNA was purified from a denaturing RNA gel (20 cm × 16 cm × 1.5 mm) in 7 M Urea, 1× TBE, and 5% acrylamide. The gel was pre-run at 20 mA for 30 min. An equal volume of formamide was added to the RNA before electrophoresis to aid denaturation of the RNA sample. RNA was run on the gel at 20 mA for at least 2 h until the tracking dye, Bromophenol blue, migrated three-fourths of the way through the gel. RNA bands were visualized on a TLC plate by briefly exposing the gel to short wave (254 nm) UV light. The RNA was eluted/recovered from the gel slab in gel extraction buffer  followed by phenol–chloroform extraction and ethanol precipitation.To prepare mRNAs and lncRNAs, we employed run-off in vitro transcription catalyzed by 6-His-tagged T7 RNA polymerase. With the exception of the pcDNA3-FLUC plasmid containing the T3 promoter for transcription, all mRNA encoding sequences were cloned downstream of a T7 promoter. Cloning of RNA-encoding sequences is described in Supplementary Methods. To obtain the transcripts with or without a 30-nt poly(A) tail, plasmid DNAs were digested by EcoRI or SacI, respectively, and precipitated with ethanol. To obtain the rabbit β-globin transcript with or without a 30-nt poly(A) tail, plasmid DNAs were digested by AgeI or SacI, respectively. 10 μg of linearized plasmid DNA was added to a 1 mL transcription reaction mixture containing 80 mM HEPES-KOH pH 7.5, 2 mM spermidine, 30 mM dithiothreitol, 25 mM NaCl, 8 mM MgCl (i) the 5′ γ-phosphate of RNA was reacted with 1-Ethyl-3-[3-dimethylaminopropyl]carbodiimide hydrochloride  and imidazole; (ii) the phosphorimidazolide derivative of RNA was reacted with cystamine; (iii) the product was reduced with TCEP to release the thiophosphate group, which was subsequently modified by Cy5 (or Cy3) maleimide for 2 h at room temperature (RT). Labeled RNA molecules were purified using a 1 mL G-25 spin column equilibrated with ddH2O. We can reproducibly achieve 100% yield of 5′ phosphate labeling. The 5′-labeled RNAs were then subjected to 3′ end labeling. The RNA 3′ OH group was conjugated to pCp-Cy3  by T4 RNA ligase I in 20 mM MgCl2, 3.3 mM DTT, and 50 mM Tris-HCl pH 8.5 in the presence of 5 mM ATP and 10% DMSO. The efficiency of Cy3/5-pCp labeling of transcripts typically does not exceed 15–30%. To perform ensemble FRET experiments, the 5′ end of mRNAs was labeled with Cy3 to ensure that all acceptor (Cy5)-labeled RNAs were also labeled with a donor fluorophore. To perform single-molecule FRET experiments, the 5′ end of mRNAs was labeled with Cy5 to ensure that all donor (Cy3)-labeled RNAs, imaged using the green (532 nm) laser, were also labeled with an acceptor (Cy5) fluorophore. All labeled RNA molecules were gel purified by denaturing PAGE as described above and stored in ddH2O after desalting via a 1 mL G-25 spin column.The 5′ phosphate of the RNA was labeled using cystamine and a maleimide derivative of Cy5  in the following steps as previously described2 was added to a final concentration of 0.5 to 8 mM depending on the experiment and cooled to RT for 5 min. In most experiments, folding buffer contained 1 mM MgCl2. In the experiments shown in Supplementary Fig. 2, PEG-8000 was added to a final concentration of 0–16% (wt/vol). To disrupt the basepairing interactions between the 5′ and 3′ UTR in GAPDH or β-globin mRNAs  RNA samples were refolded in 30 μL of folding buffer (50 mM HEPES-KOH pH 7.5 and 100 mM KCl) by first heating RNA at 90 °C for 2 min and slowly cooling to 37 °C. At 37 °C, MgCl GAPDH: 5′-biotin/GATGATCTTGAGGCTGTTG-3′; β-globin: 5′-biotin/TAGGATTGTTCATAACAGCA-3′; and MIF: 5′-biotin/CATGTCGTAATAGTTGATGT-3′.For single-molecule experiments, 100 nM doubly labeled RNA samples  and 150 nM biotinylated anchor DNA oligomers in 5 μL folding buffer were annealed as described above. Anchor DNA oligomers were designed to have a minimal effect on the overall secondary structure using OligoWalk software2 depending on the experiment. Cy3 emission spectra (555–800 nm) were taken by exciting fluorescence at 540 nm. Cy5 emission spectra (645–800 nm) were taken by exciting fluorescence at 635 nm. The slit-widths for excitation and emission were set to 5 nm of spectral bandwidth. FRET efficiencies (E) between the 5′ and 3′ end-labeled mRNAs were determined from Cy3 and Cy5 emission spectra using the ratioA method67. RatioA for each experiment was calculated from the ratio of the extracted integrated intensity of the acceptor (Cy5) fluorescence, which is excited both directly by 540 nm light and by energy transfer, divided by the integrated intensity of the acceptor excited directly by 635 nm light. FRET efficiency (E) was determined according to the following:d+ is the fraction of molecules labeled with donor. The donor labeling efficiency was determined from absorbance spectra. 1/d+ indicates the fraction of acceptor-labeled RNA that is also labeled with donor by assuming that the labeling of each fluorophore was random. ε is the extinction coefficient at the indicated wavelength, and the subscripts D and A denote donor or acceptor. The distance between donor and acceptor (R) was calculated from experimentally determined E values using:R is the inter-dye distance and R0 is the Förster radius at which E = 0.5. Calculations of R were performed assuming R0 = 56 Å68.The fluorescence emission of Cy3 and Cy5 were measured using a FluoroMax-4 (Horiba) spectrofluorometer at RT. A 12.5 mm × 45 mm quartz cuvette with a 10 mm path length (Starna Cells) was used for a sample volume of 30 µl. All measurements were performed in folding buffer (50 mM HEPES-KOH pH 7.5 and 100 mM KCl) in the presence of 0.5 to 8 mM MgCl2, 0.625% glucose, and 1.5 mM Trolox) to a final concentration of 50 pM and immobilized on quartz slides coated with biotinylated BSA  and pre-treated with NeutrAvidin . Imaging buffer with an oxygen-scavenging system  was injected into the slide chambers before imaging to prevent photobleaching.100 nM biotin-conjugated Cy3/Cy5 doubly labeled RNA samples were diluted in imaging buffer  and 642 nm laser (Spectra-Physics) for Cy3 and Cy5 excitation, respectively. Fluorescence emission was collected by a water immersion objective . Fluorescence signals were split into Cy3 and Cy5 channels by a 630 nm dichroic beam splitter and recorded by EMCCD camera . Movies were recorded using Single software )13 with the time resolution of 0.1 s for 10 min. All experiments were performed at RT.smFRET traces were recorded using a prism-based total internal reflection fluorescence (TIRF) microscope as previously describedhttps://cplc.illinois.edu/software/. Apparent FRET efficiencies (Eapp) were calculated from the emission intensities of donor (ICy3) and acceptor (ICy5) as follows: Eapp = ICy5/[ICy5 + ICy3]. The FRET distribution histograms were built from more than 200 trajectories that showed single-step disappearance for both Cy3 and Cy5 fluorescence intensities using a Matlab script provided by Prof. Peter Cornish . Single-step photobleaching of the acceptor dye resulting in a reciprocal increase in donor fluorescence indicated the presence of an energy transfer before acceptor photobleaching. FRET histograms were fitted to Gaussians using Origin (OriginLab). Among all collected traces, 20% of β-globin and GAPDH individual smFRET traces showed spontaneous interconversions between multiple FRET states. The state-to-state transitions in each fluctuating trace in GAPDH mRNA (N = 266) were determined using hidden Markov modeling (HMM) via HaMMy software25. smFRET traces showing apparent fluctuation were fit using HMM to 2, 3, and 4-state models. 99% of smFRET traces were best fit by 2-state models. Idealized FRET traces obtained by HMM were examined using transition density plot (TDP) analysis. To obtain TDP, the range of FRET efficiencies from 0 to 1 was separated into 200 bins. The resulting TDP heat map was normalized to the most populated bin in the plot. The lower-bound and upper-bound thresholds were set to 5% and 100% of the most populated bin, respectively.Collected datasets were processed and trajectories for individual molecules were extracted with IDL, using scripts downloaded from 19 for each structure in a Boltzmann ensemble of structures. We generate 1000 structures using stochastic sampling34 (program stochastic) in RNAstructure33. In stochastic sampling, structures are selected at random with the probability equal to their Boltzmann probability. Because the sample is Boltzmann weighted, the mean of a quantity across the sample has the proper Boltzmann weighting. For each structure, we count the number of branches and unpaired nucleotides in the exterior loop, i.e., the loop that contains the 5′ and 3′ ends, and use:D is the end-to-end distance, n is the number of unpaired nucleotides, m is the number of helical branches, a = 6.2 Å, and b = 15 Å, where a and b were from a previous parameterization19. The mean end-to-end distance is the arithmetic mean across structures in the sample. mRNA sequences of HeLa cells transcriptome were downloaded from the UCSC Genome Browser . Human lncRNA sequences were downloaded from the LNCipedia database 36.To estimate end-to-end distance distributions and mean end-to-end distances for each RNA sequence, we used a two-scale freely jointed chain approximationThe genetic algorithm and computational analyses of the dependence of end-to-end distance on GC content and sequence complexity are described in Supplementary Methods.https://rna.urmc.rochester.edu/RNAstructure.html). This package is provided under the GPL V3 license, and is therefore open source and free.The genetic algorithm will be provided for free download as part of the RNAstructure software package (Supplementary InformationPeer Review File


The feasibility of self-assembly of a translation system from prebiotic random RNA chains is a question that is central to the ability to conceive life emerging by natural processes. The spontaneous materialization of a translation system would have required the autonomous formation of proto-transfer RNA (tRNA) and proto-ribosome molecules that are indispensable for translating an RNA chain into a polypeptide. Currently, the vestiges of a non-coded proto-ribosome, which could have only catalyzed the formation of a peptide bond between random amino acids, is consensually localized in the region encircling the peptidyl transferase center of the ribosomal large subunit. The work presented here suggests, based on high resolution structures of ribosomes complexed with messenger RNA (mRNA) and tRNAs, that three types of L-shaped RNA building blocks derived from the modern ribosome, alongside with an L-shaped proto-tRNA, each composed of about 70-mer, could have randomly occurred in the prebiotic world and combined to form a simple translation system. The model of the initial coded proto-ribosome, which includes the active sites of both ribosomal subunits, together with a bridging element, incorporates less than 6% of the current prokaryotic rRNA, yet it integrates all of the ribosomal components that are vital for synthesizing the earliest coded polypeptides. The modern translation system is a complex assembly of biomolecules that co-operate to produce proteins, the principal constituents of every organism. Synthesis of polypeptides, which in turn can fold into proteins, takes place at the ribosome and is directed by the instructions that are held in a copy of the gene coding for the protein sequence, i.e., by the messenger RNA (mRNA). The ribosome is an enormous complex of RNA and proteins, composed of two subunits, the large subunit (LSU) and the small subunit (SSU), having a total molecular weight of approximately 2.5 MDa in bacteria. About two-thirds of the bacterial ribosome mass consists of RNA, inclusive of the active sites of both subunits, classifying the ribosome as a ribozyme. Proteins, which constitute the remaining third of the mass, serve mostly in auxiliary roles. The active site of the large subunit, the peptidyl transferase center (PTC), is the location in which new amino acids are incorporated into the growing peptide chain, while the small subunit accommodates the mRNA and contains the decoding center.The genetic code is applied via the mediation of transfer RNA (tRNA) molecules, which link the mRNA codons with their matching amino acids. The modern tRNA is an L-shaped molecule. One end of the molecule is the universally conserved single stranded NCCA tail, which carries the cognate amino acid (aa), while the anticodon (AC) loop is located at the other end. Prior to peptide bond formation, two tRNA molecules, the aminoacyl tRNA (A-tRNA) carrying the incoming amino acid, and the peptidyl-tRNA (P-tRNA) carrying the peptidyl chain synthesized up to that stage, are accommodated at the A- and P-sites of both subunits. The AC loops of the A- and P-tRNAs are base-paired to adjacent codons on mRNA, while their 3′ ends position the reacting amino acids in the PTC, in a stereochemistry that is suitable for peptide bond formation, resulting in the lengthening of the nascent chain by one amino acid at each elongation cycle.The advent of the elaborate contemporary translation system by mere chance is highly unlikely. A prebiotic system possessing the capability to translate RNA chains into peptides could have emerged spontaneously only if it was far less complex. The core elements of the modern translation system, i.e., the catalytic regions of the ribosome and the tRNAs, consist of RNA. Evolutionary continuity entails that models of the prebiotic translation system should thus be composed of RNA elements as well. RNA possesses idiosyncratic characteristics: 1.) Oligonucleotides tend to fold spontaneously into stable 3D structures, a feature that can grant them with catalytic capabilities. 2.) RNA helices possess intrinsic flexibility, allowing the formation of kinks that can be used to store energy in biological motors. 3.) The replication mode of RNA, via nucleotide complementarity, may enable reliable copying, even under primitive conditions. Taken together, these features could have promoted the formation and sustainability of a prebiotic translation system.Various hypotheses, aimed at presenting simpler versions of the components of the modern translation system and of its mechanism, were put forward. The contemporary tRNA molecules were proposed to be preceded by hairpins ,3,4,5,6,Hypotheses putting forward simplified versions of the contemporary ribosome have consensually located its vestige in the region encircling the current PTC ,15,16,17The work presented here uses high-resolution X-ray structures of bacterial ribosomes complexed with mRNA and three tRNA molecules, to extract basic components that could have assembled the prebiotic coded translation system. Geometrical restrictions are shown to imply that the simplest tRNA that could have been involved in the prebiotic translation would be an L-shape molecule. This molecule, together with three different types of building blocks derived from the modern ribosome, all being L-shape structures composed of RNA sequences of about 70-mer, are suggested to have provided the necessary components for translating RNA chains into polypeptides in the prebiotic world. The minimum prerequisite from aminoacylated tRNAs involved in the prebiotic translation, would be their ability to line up side by side, being base-paired to an oligonucleotide serving as mRNA, while positioning the reacting amino acids in a proximity that allows for the formation of a coded peptide bond. The stereochemistry of a complex of two charged tRNAs attached to an mRNA was studied, using the high resolution structures of the modern 70S bacterial ribosomes . The length of a nucleotide-triplet, as obtained from measurements carried out on the mRNAs, lay in the range 13.8–18.2 Å, depending on the curvature of each codon, while the range of the maximal width of the double stranded AC stem, as obtained from measurements carried out on the tRNAs, is 20.6–21.7 Å . ParalleReplacing the A-, P-site tRNAs by hairpins, in order to test the hypothesis that two hairpins attached to adjacent codons on mRNA could have induced the prebiotic polypeptide synthesis ,7,8,9, aThese observations, which are independent of any element that is specific to the contemporary translation system, indicate that hairpins would have failed to take part in the primitive translation. Avoiding the collision of the stems by a kink in the translated RNA or by deflection of the stems a,b, woulThese geometrical restrictions, combined with evolutionary continuity, entail that the proto-tRNAs involved in the prebiotic translation process would have had an L-shape conformation. However, the intricate elbow region of the modern tRNA, having an angle of about 90° adjusted to the current stereochemistry of the ribosome, could have possibly evolved later. An elemental shape made up of two helices connected by a simpler elbow region, possibly similar to the elbow region of the DPR monomer encapsulating the PTC a, would The universal nature of the contemporary ribosome, which employs a common mode of action in all life domains, together with its considerable level of structural and phylogenetic conservation, implies that the essence of the current translation mechanism should have already been present in the Last Universal Common Ancestor (LUCA). It follows that the vestige of the stand-alone primordial proto-ribosome, which is assumed to have continuously evolved into the modern ribosome, may still be inferred from the contemporary structure. A model of a coded proto-ribosome, i.e., an entity possessing the capability to translate a code embodied in an RNA template into a polypeptide, should therefore include the two active sites; an RNA element that accommodates mRNA and contains the decoding center, which is derived from the ribosomal RNA (rRNA) of the SSU i.e., a proto-SSU, and an element that forms the PTC pocket, derived from the rRNA of the LSU. The spatial gap between these elements necessitates the existence of a bridging element that guarantees the structural continuity of the model. Adherence to the current translation mechanism entails that the model should also retain the stereochemistry of the interactions of the two L-shape tRNA molecules with the active sites of both subunits. The minimal model for an initial system involved in a processive translation of RNA chains into polypeptides, will thus include three types of building blocks derived from the rRNA of the modern ribosome a–c, two The prebiotic PTC pocket will be approximated by the DPR  derived The ancient tRNA is assumed, according to the results of E. coli numbering throughout), and 1505–1531 from h45 , each containing two molecules in the asymmetric unit. The atomic distances pertaining to the ancient tRNA model were obtained with COOT [The building blocks of the initial translation system model, were derived from the X-ray structures of the bacterial 70S ribosome determined at resolution higher than 3.1 Å, which contain cognate A- and P-tRNAs in a canonical conformation, paired to an mRNA, and an E-tRNA at the exit site. To avoid structural changes caused by entities that could not have existed in the prebiotic environment, structures that include factors, antibiotics, and unusual codons were excluded. Measurements were performed on two 70S ribosomes from ith COOT , by averThe conservation level of individual nucleotides was obtained from the CRW site . NucleotThe secondary structures of RNA oligonucleotides were predicted by applying free energy minimization using the program Mfold  version The feasibility of the spontaneous emergence of life via natural processes is highly controversial. A central claim against the scientific approach emphasizes the improbability that the initial stages of emergence could have occurred autonomously. Here, the spontaneous folding of RNA sequences derived from the structure of the modern ribosome, into stable L-shape entities that can assemble to form a compact proto-ribosome, is demonstrated. This autonomously-materializing prebiotic entity, that contains all the RNA components crucial for translating a code into a polypeptide, presents a feasible starting point, obtained via natural processes, for a continuous evolutionary path leading from the prebiotic era to life as we know it.


Small non-coding RNAs are essential for transcription, translation and gene regulation in all cell types, but are particularly important in neurons, with known roles in neurodevelopment, neuroplasticity and neurological disease. Many small non-coding RNAs are directly involved in the post-transcriptional modification of other RNA species, while others are themselves substrates for modification, or are functionally modulated by modification of their target RNAs. In this review, we explore the known and potential functions of several distinct classes of small non-coding RNAs in the mammalian brain, focusing on the newly recognised interplay between the epitranscriptome and the activity of small RNAs. We discuss the potential for this relationship to influence the spatial and temporal dynamics of gene activation in the brain, and predict that further research in the field of epitranscriptomics will identify interactions between small RNAs and RNA modifications which are essential for higher order brain functions such as learning and memory. Cells produce vast amounts of RNA which lack protein-coding potential, including many functional RNA molecules less than 200 nucleotides in size. These small non-coding RNAs arise through a multitude of distinct biogenesis pathways, and are involved in cellular processes including transcription, splicing, translation, RNA modification, and regulation of gene expression through several mechanisms . Some smSmall non-coding RNAs have important regulatory roles in all mammalian cell types, but seem to be particularly important in the brain ,2. HighePost-transcriptional modifications can profoundly influence the structure, stability and base-pairing properties of RNA, and are increasingly recognised as a mechanism for regulating RNA localisation, longevity, translation, and interactions with other molecules ,8. SeverIn this review, we explore several classes of small non-coding RNAs which are known to be expressed in the mammalian brain, discuss their roles in brain function, and consider how post-transcriptional modifications of small RNAs and their targets can increase the information-carrying capacity of neuronal RNA. We predict that as new technology permits the profiling and functional interrogation of the epitranscriptome with improved temporal and spatial resolution, new mechanisms of gene regulation and cellular signalling will be identified at the interface of small RNA biology and RNA modification and shown to be essential for higher-order neurological function, including learning and memory. MicroRNAs are a class of small regulatory RNAs which negatively regulate gene expression through interactions with mRNA. Mature microRNAs are incorporated into a ribonucleoprotein known as the RISC (RNA-induced silencing complex), which is guided to specific sites by the base-pairing of part of the miRNA with complementary regions in the 3′ untranslated region (UTR) of mRNAs ,14. DepeIn mammals, the majority of miRNAs are derived from hairpin-containing precursor RNAs (pri-miRs) which are transcribed by RNA polymerase II. These precursors are processed in the nucleus by the endonuclease DROSHA which trims the RNA to a single hairpin (pre-miR) which is exported from the nucleus. Final miRNA processing and maturation occurs in the cytoplasm, where the endonuclease DICER removes the loop region from the hairpin, with several enzymes then participating in strand selection and loading of the miRNA into the RISC  occur in synapses of the adult mouse brain, and many miRNAs are strongly enriched in the synaptic compartment compared to whole cell lysate ,26. It iMammals have over one thousand miRNA sequences, almost all of which target dozens or hundreds of genes ,15,22. MHowever, there are also many examples of individual miRNAs which have profound impacts on neuronal function in isolation, particularly in the context of learning and memory. For instance, miR-132 is regulated by the neuronal transcription factor CREB (cAMP response element binding factor); this miRNA is upregulated in the mouse hippocampus in response to a spatial memory task, and mild overexpression of this miRNA enhances cognitive performance . MiR-182There is a growing recognition that miRNAs are commonly packaged into extracellular vesicles as a means of communication between cells . Much reRecent research has identified the presence of modified bases in miRNA precursors and mature miRNAs. Several papers have focused on N6-methyladenosine (m6A), which is often considered a functional switch on RNA. Yuan et al. showed that methylation of miR-125b in HeLa cells inhibits the function of this miRNA at all three stages of its biogenesis; the presence of m6A inhibits the processing of pri-miR-125b2 into pre-miR-125b2 by Drosha, decreases the cleavage of this pre-miR by Dicer, and attenuates incorporation of the mature miRNA into the RISC . HoweverMicroRNAs can also be modified by the addition of non-templated nucleotides to the 3′ end, which can occur at the miRNA precursor stage as well as to mature miRNAs ,55. MicrAnother form of miRNA modification is adenosine-to-inosine (A-to-I) RNA editing catalysed by enzymes of the ADAR (adenosine deaminase acting on RNA) family, which target double-stranded RNA templates including miRNA precursors. Adenosine-to-inosine RNA editing profoundly changes the base-pairing properties of the RNA molecule; adenosine base-pairs with uridine, whereas inosine preferentially pairs with cytidine but can also pair with adenosine or uridine. This can cause mature miRNAs containing inosine to target different mRNAs from their unedited counterparts , and A-tModification and editing of mRNAs could affect their potential to be regulated by miRNAs by creating or ablating miRNA binding sites, or by affecting the structure of the mRNA molecule in a way that makes it more or less accessible to the RISC. Editing of A-to-I by ADAR enzymes occurs in mRNA, particularly in the brain . InosineOther RNA modifications have less drastic effects on the mRNA sequence than RNA editing, but could affect miRNA regulation through other mechanisms, such as altering mRNA structure to reveal or mask miRNA binding sites. For instance, m6A destabilises RNA duplexes, but stabilises RNA structure in the single-stranded context, and can act as a conformational switch . InteresAn exciting new possibility for miRNA function was demonstrated by Chen et al., who found that miRNAs can act as guides to specify the location of m6A modification on mRNA in several mouse cell lines . In thisO-methylation of the terminal nucleotide [Piwi-interacting RNAs are a class of small regulatory RNAs defined by their interaction with Piwi-like proteins, which are a subset of the Argonaute family. Characteristic features of piRNAs include a length of 26–31 nucleotides (in vertebrates), occurrence in genomic clusters, a bias towards uracil as the first base, and 2′-cleotide . The priO-methylated on the 3′ terminal base; this modification is applied by the enzyme HENMT1 [The biogenesis and maturation of piRNAs has been thoroughly reviewed by Iwasaki et al. . Brieflye HENMT1 ,75,76 ane HENMT1 ,78,79,80Drosophila [In addition to the degradation of piRNA-complementary transcripts by the endonuclease activity of Piwi proteins, piRNAs can modulate gene expression through epigenetic activation and epigenetic silencing. Although most steps of piRNA production are cytoplasmic, Piwi proteins can re-enter the nucleus and are guided by piRNAs to complementary regions of genomic DNA. In the vast majority of cases, this results in epigenetic silencing by recruitment of chromatin modifiers . Howeveosophila . The Piwosophila . PIWIL2 osophila .Piwil1 in particular has several known functions in neuronal precursors which affect their migration and differentiation. Knockdown of Piwil1 in newborn cortical neurons in the developing mouse brain produces a defect in neuronal polarisation and radial migration, partly through regulation of microtubule-associated proteins [Piwil1 knockout mouse model, neuronal precursors show increased cell cycle re-entry and delayed differentiation, and neuronal migration and neocortical architecture are aberrant [Piwil2 knockout mice are hyperactive, with altered anxiety-like behaviour; this phenotype is likely neurodevelopmental as the absence of Piwil2 is present from conception [There is a growing recognition that the Piwi pathway is involved in cell fate decisions during development and regeneration . Piwil1 proteins . In a Piaberrant . Anothernception . These fnception , which aAplysia californica express the only Piwi-like protein found in this species, and several dozen piRNAs [O-methylated at their 3′ termini) to demonstrate that the small RNAs detected were bona fide piRNAs. In 2012, Rajasethupathy et al. reported that neurons of the sea slug n piRNAs . They foPiwil1 in cultured mouse neurons and reported that depletion of a specific putative piRNA alters dendritic spine morphology [MeCP2 to model Rett syndrome [Other authors have reported that the Piwi pathway occurs in mammalian neurons. Lee et al. detected expression of rphology . Other arphology , in the rphology , and in syndrome . These ssyndrome . The majsyndrome . HoweverPiwil2 knockout mice and found that LINE1 promoters were broadly hypomethylated in the hippocampus and prefrontal cortex, suggesting a defect in transposon control. This mouse line also showed hyperactivity and reduced anxiety, which implies a functional role for neuronal piRNAs in regulating behavioural responses to novelty.Despite this setback, two recent studies have profiled piRNA expression in the mouse brain using stringent bioinformatic criteria to classify small RNAs as piRNAs. Ghosheh et al. sequenced small RNAs in the size range of piRNAs from the mouse brain . The autPiwil1 and Piwil2 in cultured mouse neurons; both genes are dynamically upregulated by neuronal stimulation, and they promote activity-dependent chromatin relaxation at the Ppp3r1 locus which is required for binding of the regulatory factor ING1 and subsequent expression of Ppp3r1 [Piwil1 and Piwil2 in the hippocampus enhances contextual fear memory without affecting generalised anxiety [Other studies have implicated the Piwi pathway in gene regulation in adult neurons without directly examining piRNAs. Earlier work from our laboratory detected low-level expression of f Ppp3r1 . We have anxiety .Endogenous small interfering RNAs, known as endo-siRNAs, are 20–24 nucleotide small RNAs which participate in RNA interference. Endogenous small interfering RNAs arise from long double-stranded RNA (dsRNA) precursors, and the endo-siRNA system likely evolved as an immune response to undesirable dsRNAs such as viral genomes and transposon transcripts . HoweverO-methylated at their 3′ termini. This means that distinguishing them from both miRNAs and piRNAs is best done by examining the genomic context of putative endo-siRNAs to look for hallmarks of dsRNA formation and processing, such as the bioinformatic prediction of a large hairpin domain or the confirmed generation of sense and antisense transcripts at a potential endo-siRNA producing locus. Smalheiser et al. identified 20–23 nucleotide small RNA sequencing reads from mouse hippocampus that map within eight genes which contain intronic inverted repeats forming large hairpin structures that do not include any annotated miRNAs [Ctnna2 locus, where another gene, Lrrtm1, occurs within an intron and is transcribed from the opposite direction; these small RNAs probably represent endo-siRNAs derived from annealing of complementary RNAs [Sox4 mRNA and natural antisense transcripts produced from the Sox4 locus; a specific 24 nucleotide small RNA with Dicer-dependent origin was found to originate from these dsRNAs and has a potential role in the regulation of neurogenesis [The existence of endo-siRNAs in the mammalian brain remains controversial, partly because these small RNAs are difficult to unambiguously identify. They overlap in size with miRNAs and possibly with piRNAs; they can also be associated with transposons and repetitive elements, and in some species are characteristically 2′-d miRNAs . These sary RNAs . Ling etogenesis . Importaogenesis .To date, although putative endo-siRNAs have been described in the mammalian brain and are plausibly predicted to have a role in synaptic plasticity, there is no convincing evidence that they directly regulate gene expression or that they are functional components of gene regulatory networks at the synapse. Further experiments (such as specific deletion of siRNA-generating intronic inverted repeats) need to be performed in order to determine whether endo-siRNAs are important for synaptic function or for the development or function of the brain more broadly.Transfer RNAs are the molecular adaptors which recognise the sequence of mRNA and deliver the corresponding amino acid into the active site of the ribosome for incorporation into the nascent polypeptide chain. They range in size ~75–90 nucleotides and form a universally conserved “cloverleaf” shape, with three loops surrounding a central stem. The 3′ terminus of the tRNA molecule is the attachment site for an amino acid; structurally opposite this site is the anticodon loop, which base pairs with the appropriate mRNA codon to deliver the amino acid to the ribosome. Transfer RNAs have generally been overlooked as potential regulatory molecules and their fragments, when sequenced, have been interpreted as junk produced by the sample extraction and library preparation process. However, the growing recognition that tRNA fragments can have metabolic and regulatory roles is leading to renewed interest in tRNA biology.In eukaryotes, tRNAs are encoded at dozens of loci by both the nuclear and mitochondrial genomes and are transcribed by RNA polymerase III. Newly synthesised tRNA transcripts contain superfluous sequence at both the 3′ and 5′ ends, as well as introns, and undergo several processing steps to remove these non-functional sequences and add the invariant overhanging triplet, CCA, to the 3′ end of the tRNA (reviewed by Phizicky and Hopper ). In addFollowing tRNA processing and modification, tRNAs enter a cycle of charging and participation in translation. Charging, or aminoacylation, of tRNAs involves covalent attachment of the correct amino acid to the 3′ terminus of the tRNA by a protein known as an aminoacyl tRNA synthetase (aaRS). One aaRS is associated with each amino acid and this protein recognises all of the tRNAs which carry that amino acid . The funTransfer RNAs are often thought of as housekeeping genes, which are required by all cells in relatively constant quantity in order to carry out basic metabolic processes. However, there are several domains of tRNA function through which intact tRNAs affect the rate or fidelity of protein synthesis, both through established regulatory functions, and in cases where tRNAs or their cofactors are mutated.There are 20 universal proteinogenic amino acids, but 64 triplet codons, of which 3 are stops and 61 specify an amino acid. There are fewer than 61 unique tRNAs, because of wobble base pairing rules which allow the same tRNA to recognise codons that differ at the third position ; humans CFTR, the gene which causes cystic fibrosis when mutated. A synonymous single nucleotide polymorphism (SNP) in this gene causes detrimental changes to the stability of the encoded protein because translation through this SNP requires a low-abundance tRNA, tRNAThr(CGU), that is particularly rare in human bronchial epithelia [Gln(CUG); this tRNA is not rare, but its charged form becomes depleted in cells expressing mutant huntingtin due to translation of the repeat expansion poly(CAG) [Gln(CUG) at a lower level [Further examples of the subtle regulatory capacity of tRNAs are provided by cases where tRNA mutations cause disease, generally despite the presence of functional isodecoder tRNAs in the genome. For instance, mutation of a brain-specific tRNA contributes to neurodegeneration in mice due to stalling of the ribosome. Interestingly, the severe neurodegenerative phenotype is only unmasked when the ribosome rescue protein GTPBP2 is also mutated, revealing the potential interplay between variants in tRNAs and protein-coding genes . A similpithelia . Similaroly(CAG) . An impaer level . Kirchneer level ,115.NSun2 knockout mice causes cellular stress responses and neuronal apoptosis [The many post-transcriptional modifications applied to tRNAs strongly influence their folding, structure and properties , and thpoptosis . Althougpoptosis ,116. FurIt is increasingly recognised that fragmentation of tRNAs is a non-random process; specific endonucleases cleave specific tRNAs in response to cellular signals, and in many cases the fragments thus generated are functional signalling or regulatory molecules within the cell. Small non-coding RNAs derived from tRNA precursors or mature tRNAs are collectively referred to as tRNA fragments or tRFs; the term tiRNA (tRNA-derived stress-induced RNA) refers to tRNA halves produced by a single cleavage within the anticodon loop ,128. TheAPOER2) to reduce expression of this gene [APOER2 is implicated in Alzheimer’s disease [Several studies have linked regulated cleavage of mature tRNAs to the cellular stress response and have implicated this process in neurological disease  ,130. Somhis gene . Althoug disease  and the  disease . Other t disease  and inco disease ,138, altStrikingly, tRFs have also been implicated in transgenerational inheritance, a phenomenon by which metabolic, and in some cases behavioural, phenotypes are observed in the unexposed offspring of animals which underwent an environmental manipulation prior to mating . The stuO-methylated and pseudouridylated positions . These In eukaryotes, the majority of newly transcribed mRNAs and long non-coding RNAs contain introns, non-coding sequences which must be removed to generate the mature and functional RNA. Intron removal, or RNA splicing, is carried out by the spliceosome in nuclear compartments called splicing speckles or simply speckles. The spliceosome dynamically assembles on the precursor mRNA (pre-mRNA); removal of the intron requires a series of reactions which are sequentially catalysed by the various snRNPs which comprise the spliceosome, facilitated by base-pairing between the snRNAs and recognition sequences within the introns and exons of the pre-mRNA (reviewed by Hoskins and Moore ). The maRnu2–8 gene (one of the copies of the U2 snRNA) causes cerebellar ataxia and neurodegeneration [While splicing is necessary to generate functional RNA from the majority of genes, it can also be a means of gene regulation and the generation of genetic diversity through alternative splicing. This process involves the selective inclusion and exclusion of exons in order to generate proteins with different amino acid sequences. Alternatively-spliced transcripts are enriched in the brain and the regulation of alternative splicing is considered critical for brain development and function . Alternaneration . Surprisneration . HoweverPerturbations of the minor spliceosomal snRNAs result in cellular dysfunction which disproportionately affects the developing nervous system. Removal of U12 introns by the minor spliceosome is substantially slower than removal of U2 introns by the major spliceosome, and this has been proposed as a gene regulatory mechanism . U12 intO-methylated positions. The majority of modifications on snRNAs are applied in the Cajal body during snRNA maturation by small Cajal body specific RNAs (discussed later in this review). However, some snRNA modifications are applied in an RNA-independent manner by pseudouridine synthases including Pus7p and Pus1p [O-methylated bases at the 5′ end of U2 snRNA are required for splicing [Small nuclear RNAs contain a number of post-transcriptional modifications, predominantly pseudouridylated and 2′-nd Pus1p ,159. Sevnd Pus1p . Specifind Pus1p , while esplicing . Loss ofsplicing ). Howevesplicing .O-methylation at specific sites of their RNA targets, while H/ACA box snoRNAs guide isomerisation of specific uridine residues in target RNAs to pseudouridine. C/D box and H/ACA box snoRNAs are predominantly localised to the nucleolus, which is the site of ribosome biogenesis, and the vast majority of their target sites occur on the 18S and 28S ribosomal RNAs  are nuclear RNAs which are primarily involved in the post-transcriptional modification of other RNA species. There are two subclasses of snoRNAs, which are defined by specific sequence motifs. C/D box snoRNAs direct 2′-s et al.  and Reics et al. ). Convers et al. . Most scO-methyltransferase [O-methylation, which is almost always five nucleotides upstream of the D or D’ box [C/D box snoRNAs range in size from ~70 to ~160 nucleotides, and are defined by the presence of the C-box  and D-box (CUGA) motifs, which occur near the 5′ and 3′ ends of the RNA respectively . Most C/nsferase ,169,170.r D’ box ,164,171.Most C/D box snoRNAs are ubiquitously expressed, consistent with their function in guiding rRNA modifications that are necessary for proper function of the ribosome. However, some C/D box snoRNAs have tissue-specific expression patterns, including several that are expressed predominantly or only in the brain ,173. TwoHtr2c. This gene is essential for the regulation of appetite and feeding behaviour in humans and animals [Htr2c mRNA inhibits an alternative splicing event which drives the expression of a truncated isoform of Htr2c [Htr2c transcript also undergoes ADAR2-mediated A-to-I RNA editing which alters the amino acid sequence of the encoded protein; the presumed 2′-O-methylation of Htr2c mRNA by snord115 blocks editing by ADAR2 and promotes expression of the unedited protein sequence [HTR2C is expected to contribute to the human PWS phenotype in most cases; however, loss of snord115 alone is not sufficient to cause PWS in humans [To date, the most compelling example of C/D box snoRNAs with neurological functions is given by the contribution of snord115 and snord116 to Prader-Willi syndrome (PWS), a disorder characterised by intellectual disability and neonatal growth deficiency followed by hyperphagia and obesity . Prader- animals ,182,183.sequence . Throughsequence ,186. Snosequence , and dysn humans .Drosophila brain [In addition to the established functions of C/D box snoRNAs in the brain, ongoing research is suggesting new ways in which these small RNAs may regulate nervous system function. The expression of some snoRNAs has a daily rhythm in the la brain , and della brain . This mala brain  as well la brain ,190. Thela brain . Anotherla brain . Alternala brain , making la brain . Finallyla brain ,194. Givla brain  and 76 hla brain , continuHTR2C [H/ACA box snoRNAs are approximately 150–300 nucleotides long, and are defined by the H-box  and ACA-box  sequence motifs ,162,195.HTR2C . To dateO-methylation and pseudouridylation onto non-rRNA targets, most of which are small nuclear RNAs, consistent with the Cajal body’s role in the final stages of spliceosomal RNA maturation [O-methylation and pseudouridylation guides. Small Cajal body-specific RNAs are structurally and functionally indistinguishable from snoRNAs, but are defined by their localisation to the Cajal body. Unlike the nucleolus, the Cajal body is not involved in ribosome biogenesis, and lacks ribosomal DNA (rDNA) domains and RNA polymerase I machinery. Concomitantly, scaRNAs target 2′-turation . Small Cturation , whereasturation ,201. CABturation , indicatTo date, scaRNAs with brain specificity or neuron-specific functions have not been reported. However, the role of scaRNAs in the maturation of the splicing machinery suggests that neurons could be among the cell types most sensitive to disruption of scaRNA activity, given that alternative splicing is particularly prevalent in the brain. This hypothesis is supported by observations that decreased expression of 12 scaRNAs in congenitally abnormal human hearts is associated with dysregulated alternative splicing of several genes which regulate heart development ; althougCharacterisation of scaRNAs is also complicated by the mis-annotation of many scaRNAs as either C/D box or H/ACA box snoRNAs; in many databases, only those scaRNAs with an unusual structure (such as those containing both C/D and H/ACA motifs) are reliably annotated as such. Larger scaRNAs also fall into a size range which is often missed by library preparation for both small and large RNA sequencing, and targeted approaches such as RNA capture-seq may be necessary to better understand their function.O-methylation [The primary functions of snoRNAs and scaRNAs as guides for post-transcriptional RNA modification have been well established. However, many questions remain about the potential regulatory and adaptive functions of these modifications, as well as the growing list of non-canonical functions of snoRNAs and scaRNAs. Recent improvements have been made to the sensitivity and accuracy of biochemical profiling methods for both 2′-hylation  and pseuhylation , resultiO-methylation and pseudouridine on rRNA is universally conserved; humans share the core machinery of both the C/D and H/ACA snoRNPs with bacteria and archaea [The occurrence of 2′- archaea . The spe archaea ,206. Gen archaea ,207,208  archaea , providi archaea ,210,211. archaea .O-methylation of some mRNAs from HEK cells and a non-random distribution pattern for this mark, which appears to occur preferentially near splicing junctions [O-methylation of mRNA could affect splice site selection. There is evidence that 2′-O-methylation of mRNA attenuates the translation rate by affecting the interaction between the mRNA and tRNA [O-methylation of mRNA may affect its structure or stability, as is the case for rRNA, although there is currently no evidence to support this idea. Pseudouridine also occurs in eukaryotic mRNAs and long non-coding RNAs, and in the brain, it responds dynamically to stress [Another emerging possibility is that some snoRNAs or scaRNAs modify mRNAs. Some mRNAs are detectable in fibrillarin immunoprecipitates from HEK293T cells, indicating association of mRNA with the C/D box snoRNA machinery . A recenunctions . This imand tRNA . It is ao stress ,213. Whio stress . PseudouDICER and DGCR8 show altered snoRNA fragment profiles [Finally, it is likely that at least some snoRNAs are processed into smaller fragments which have regulatory roles. Sequencing of small RNAs from various mammalian tissues, including brain, reliably identifies a large population of snoRNA fragments in the 20–30 nucleotide size range ,214. Mouprofiles ,215,216.profiles ,217. TogO-methylation) at single-base resolution with high throughput has enabled unprecedented understanding of where, when and how these marks accumulate on small and large RNAs [Our understanding of many RNA modifications is hampered by the lack of technologies to detect them. Recently developed methods to profile some epitranscriptomic marks (including m6A, m5C, pseudouridine, and 2′-rge RNAs ,218,219.The RNA-guided RNase Cas13, and its RNase-deficient derivatives, can be engineered to modify RNAs with single-base precision. A fusion protein consisting of Cas13b and the adenosine deaminase domain of ADAR2 was used to drive A-to-I editing site-specifically while avoiding the sequence constraints of the wild-type enzymes . We predThere is a growing understanding that RNA trafficking and localisation are essential for neuronal function, where rapid and regulated protein synthesis may need to occur as far as one metre from the cell nucleus. New technologies are emerging to interrogate specific RNA molecules and RNA functionalisation with greater temporal and spatial resolution than ever before. Approaches such as bio-orthogonal labelling of nascent RNA using tagged nucleobase analogues  and spatThe majority of small RNA biotypes are represented in the mammalian brain, where they are an integral component of regulatory processes which underlie most nervous system functions . We are Epitranscriptomics is a discipline in its infancy. Hundreds of RNA modifications have been confirmed by mass spectrometry to exist in mammalian RNA , includiAnother lesson from the research described in this review is the potential functional relevance of small RNAs that are derived from larger RNA species, and which have typically been dismissed as degradation products arising from sample preparation and sequencing. Most small RNA sequencing analysis also rejects sequences which do not perfectly match the reference genome, which may mean that reads corresponding to modified or edited small RNAs are discarded at an early stage of data analysis and not considered further. Finally, a recent analysis has highlighted issues with small RNA classification in online databases  and provIn this review, we have discussed the functions of several classes of small non-coding RNA in the brain, and explored their roles as guides, recipients, and interacting partners for dynamic RNA modifications. The ability of RNA modification to immediately and dramatically affect RNA folding, base-pairing and stability functionalises RNA molecules to rapidly integrate information from changing environmental inputs. We have presented cases of the interplay between small RNAs and the epitranscriptome controlling state-dependent functions of neurons, as well as examples of regulatory mechanisms from other cell types. We expect that ongoing research will discover more ways in which this relationship increases the complexity of information processing in the brain, with particular relevance to higher-order processes such as learning and memory.


Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) are responsible for significant cassava yield losses in eastern sub‐Saharan Africa. To study the possible mechanisms of plant resistance to CBSVs, we inoculated CBSV‐susceptible and CBSV‐resistant cassava varieties with a mixed infection of CBSVs using top‐cleft grafting. Transcriptome profiling of the two cassava varieties was performed at the earliest time point of full infection (28 days after grafting) in the susceptible scions. The expression of genes encoding proteins in RNA silencing, salicylic acid pathways and callose deposition was altered in the susceptible cassava variety, but transcriptional changes were limited in the resistant variety. In total, the expression of 585 genes was altered in the resistant variety and 1292 in the susceptible variety. Transcriptional changes led to the activation of β‐1,3‐glucanase enzymatic activity and a reduction in callose deposition in the susceptible cassava variety. Time course analysis also showed that CBSV replication in susceptible cassava induced a strong up‐regulation of RDR1, a gene previously reported to be a susceptibility factor in other potyvirus–host pathosystems. The differences in the transcriptional responses to CBSV infection indicated that susceptibility involves the restriction of callose deposition at plasmodesmata. Aniline blue staining of callose deposits also indicated that the resistant variety displays a moderate, but significant, increase in callose deposition at the plasmodesmata. Transcriptome data suggested that resistance does not involve typical antiviral defence responses . A meta‐analysis of the current RNA‐sequencing (RNA‐seq) dataset and selected potyvirus–host and virus–cassava RNA‐seq datasets revealed that the conservation of the host response across pathosystems is restricted to genes involved in developmental processes. We have recently characterized KBH 2006/18 and KBH 2006/26, which are two resistant elite breeding lines with immunity to a mixed infection of CBSV and UCBSV  to characterize the transcriptome response at an early time point of CBSV and UCBSV co‐infection. We report an in‐depth characterization of the pathways and genes altered in compatible and incompatible cassava–ipomovirus interactions and present biochemical evidence to explain the inhibition of virus intercellular movement in the resistant breeding line KBH 2006/18. These data provide new insights into the cassava–CBSV interaction and identify commonalities in plant responses to virus infection.et al., Following successful grafting of 60444 and KBH 2006/18 virus‐free scions onto rootstocks with a mixed infection of CBSV (TAZ‐DES‐01) and UCBSV (TAZ‐DES‐02) (CBSV infection in short), we performed a time course sampling of the scions at 16, 22 and 28 days after grafting (dag) . We assessed virus titres in inoculated and mock scions at the selected time points. Virus infection reached homogeneous titre levels across the three biological replicates only at 28 dag in inoculated 60444 scions . No virus was detected in leaves of KBH 2006/18 scions , consistent with previous results (Anjanappa Manihot esculenta AM560–2 v6.0). The reads not mapped to the reference genome were assembled de novo using Trinity , were subsequently blasted against the National Center for Biotechnology Information (NCBI) nucleotide collection to provide gene descriptions. The dnATs were then used for differential gene expression analysis using STAR .Gene expression in 60444 and KBH 2006/18 from non‐inoculated and CBSV‐inoculated scions collected at 28 dag was analysed using Illumina HiSeq 2000 sequencing. Total RNA from the second emergent leaf immediately after the graft union was used for RNA‐sequencing (RNA‐seq) analysis, with three independent replicates per condition  and per plant variety. A total of 1 254 619 280 reads with 100‐bp paired ends was generated from the 12 samples, ranging from 77 to 121 million reads per sample. On average, 93.4% of the total reads were successfully mapped to the cassava reference genome . Over 68% of all differentially expressed genes (DEGs) were up‐regulated in variety 60444, whereas only 30% were up‐regulated in KBH 2006/18. A total of 158 DEGs were common between both varieties, and a major proportion (99 DEGs) of these were down‐regulated , CALRETICULIN 1B (CRT1B), HEAT SHOCK PROTEIN 17.6 (HSP17.6)] and one non‐significantly changed gene [CALRETICULIN 3 (CRT3)] were confirmed using reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR) on the same RNA samples as used for sequencing. Fold change values (comparing infected and non‐infected samples) for these RNAs were similar to those observed in the RNA‐seq analysis . We used unmapped reads to de novo assemble the full‐length virus genomes of CBSV (TAZ‐DES‐01) and UCBSV (TAZ‐DES‐02). Full‐length virus genome contigs were employed for read counts to estimate virus abundance in each sample used for RNA‐seq . Read counts detected for CBSV (TAZ‐DES‐01) and UCBSV (TAZ‐DES‐02) indicated that CBSV (TAZ‐DES‐01) was more prevalent than UCBSV (TAZ‐DES‐02) in two of the three inoculated 60444 scions. The read count analysis confirmed the absence of both CBSVs in the inoculated KBH 2006/18 scions .The RNA‐seq expression results of three significantly transcriptionally changed genes , whose expression was altered in different host–potyvirus interactions and at different time points after infection. Understanding the functions of these proteins in host–virus interactions might reveal conserved developmental responses to virus infections across different taxa. Our Pfam‐based comparison methodology also makes a larger scale comparison of crop RNA‐seq studies possible, with the aim of developing a more comprehensive understanding of conserved responses of non‐model plants to different biotic and abiotic stresses.Our study suggests that the analysis of early time points during virus–host interactions captures the emerging impact of virus replication on host gene expression. For example, our RNA‐seq dataset from scion leaves at 28 dag revealed a broad immune response (including SA and RNA silencing pathways) in the susceptible cassava 60444 variety which was not found in susceptible cassava plants after a long‐term infection , Dar es Salaam, Tanzania, and the susceptible variety 60444 from the ETH Zurich  cassava germplasm collection. Cassava plants were grown under glasshouse conditions . Infected 60444 rootstocks with mixed infection of the CBSV isolate TAZ‐DES‐01 (KF878104) and the UCBSV isolate TAZ‐DES‐02 (KF878103) were employed to inoculate KBH 2006/18 and 60444 plants using a previously described top‐cleft grafting method  RNA extraction protocol , and, subsequently Illumina HiSeq 2000 sequencing was performed to generate the reads.Library preparation and sequencing were performed as follows. Five micrograms of total RNA extract were treated with DNase according to the manufacturer's instructions , and subsequently column purified using an RNeasy Plant Mini Kit . RNA quality was assessed using a Qubit® (1.0) Fluorometer (Thermo‐Fisher) as well as a Bioanalyzer 2100 . Samples with an RNA integrity number (RIN) above six were used for sequencing. One microgram of total RNA was polyA enriched and cDNA libraries were synthesized using a TruSeq RNA Sample Prep Kit v2 . Cluster generation was performed using 10 pM. esculenta reference genome AM560–2 v6.0 available on Phytozome (www.phytozome.jgi.doe.gov) using the transcriptomics toolbox in CLC Genomics Workbench v8.5. Empirical analysis of differentially expressed reads was performed using default parameters to identify DEGs between control non‐infected and CBSVs‐infected scions. DEGs were then filtered based on an FDR‐corrected P value of <0.01 and a fold change of ≥2. DEGs were annotated in CLC Workbench using the Phytozome GFF3 annotation file (www.phytozome.jgi.doe.gov).The raw read files were trimmed using the trim sequence tool in CLC Genomics Workbench v8.5, and the settings are declared in Notes S1 (see Supporting Information). Unique trimmed reads were mapped to the et al., dnATs. Differential expression of dnATs between infected and mock‐infected samples was determined using STAR  and UCBSV (HG965222.1) genomes to identify full‐length virus genomes. Two full‐length genomes corresponding to CBSV  and UCBSV  were obtained as single assembled contigs. The two full‐length viral genomes were used to map reads from each individual sample  using the CLC Genomics Workbench read mapping to contigs tool in order to estimate virus read counts per sample and read count distribution across the virus genomes.Unmapped reads (described previously) were assembled into contigs using the CLC Genomics Workbench m HEPES, pH 8.0, 5 mm MgCl2 and 1 tablet/50 mL buffer of ethylenediaminetetraacetic acid (EDTA)‐free protease inhibitor] and quantified using the bicinchoninic acid assay (BCA) assay. The amount of glucose released by the activity of β‐1,3‐glucanase in a known amount of soluble proteins in the presence of the substrate laminarin  was then measured spectrophotometrically at 540 nm  using a previously described method . Commonly regulated Pfams were determined by constructing a five‐set Venn diagram, and the resulting Pfam overlaps between pairs of sets were used to calculate a pairwise similarity matrix.For Pfam‐based meta‐analysis, RNA‐seq DEG data were downloaded from published reports  Schematic representation of the workflow for the RNA‐sequencing (RNA‐seq) study. (b) Workflow for callose quantification, enzymatic assay and expression analysis for β‐1,3‐glucanase.Fig. S2Cassava brown streak virus (CBSV) quantification at three different time points after grafting. Reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR) quantification of virus titre [log2 fold change relative to reference gene Manihot esculenta protein phosphatase 2A (MePP2A)] from individual leaves from three independent biological replicates at three different time points after grafting.Fig. S3 Validation of RNA‐sequencing (RNA‐seq) data by reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR). RT‐qPCR for four genes was performed on the same samples as used for RNA‐seq analysis. MePP2A, Manihot esculenta protein phosphatase 2A.Fig. S4 Virus read counting from unmapped RNA‐sequencing (RNA‐seq) reads. Unmapped reads from each sample sent for RNA‐seq were mapped to the two de novo assembled virus genomes. (a) Read distribution across virus genomes for 60444 samples. (b) Read counts for all samples in the compatible (60444) and incompatible (KBH 2006/18) virus–host interaction.Fig. S5 Reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR)‐based RNA‐DEPENDENT RNA POLYMERASE 1 (RDR1) transcript expression across the three time points. dag, days after grafting; MePP2A, Manihot esculenta protein phosphatase 2A.Table S1 Primers used in this study.Click here for additional data file.Table S2 Significantly differentially expressed genes from RNA‐seq analysis.Click here for additional data file.Table S3 Identification and differential expression of de novo assembled transcripts.Click here for additional data file.Table S4 Gene set analysis results.Click here for additional data file.Table S5 Comparison of multiple virus–host RNA‐sequencing (RNA‐seq) studies.Click here for additional data file.Table S6 Differentially expressed genes (DEGs) in the study that match putative RNA‐DEPENDENT RNA POLYMERASE 1 (RDR1) targets based on Cao et al. (o et al. .Click here for additional data file.Notes S1 Settings used for transcriptomics analysis and visualisation.Click here for additional data file.


ST = 0.145***). Further differentiation within the Pacific included a West and East cleavage as well as North-Central and South-Central Pacific clusters. No genetic differentiation was detected within archipelagos. These results highlight the legacy of past climate changes and the effects of large ocean expanses and circulation patterns on contrasting levels of connectivity at global, regional and local scales. Our results indicate a need for regional conservation units for gray reef sharks and pinpoint the isolation and vulnerability of their French Polynesian population.Human activities have resulted in the loss of over 90% of sharks in most ocean basins and one in four species of elasmobranch are now listed at risk of extinction by the IUCN. How this collapse will affect the ability of populations to recover in the face of continued exploitation and global climate change remains unknown. Indeed, important ecological and biological information are lacking for most shark species, particularly estimates of genetic diversity and population structure over a range of spatial scales. Using 15 microsatellite markers, we investigated genetic diversity and population structure in gray reef sharks over their Indo-Pacific range . Clear genetic differentiation was observed between the Indian and the Pacific Ocean specimens (F Collapse of shark populations has had profound effects on ecosystem functioning and resilience6 and potentially threatens their capacity to maintain demographic connectivity and genetic diversity across their ranges7. Reef sharks are of particular concern as they are a primarily reef-associated group that plays an important structural role in coral reef ecosystems as apex or meso-predators10. Recent work has reported striking declines in reef shark densities associated with the size of adjacent human populations8. More information on basic evolutionary and demographic processes are urgently needed to ensure conservation of individual reef shark populations and the ecosystem services that they provide across the world’s tropical and sub-tropical oceans10.Anthropogenic pressures, including over-fishing and habitat destruction, have resulted in the loss of over 90% of sharks and large predatory fishes across all ocean basins7. Molecular tools are, in many cases, the only means available to estimate essential parameters for populations, and this is certainly the case for rare and elusive species. Genetic methods have been used to infer dispersal patterns, demographic trends and important reproductive traits in many sharks. Indeed, mitochondrial sequences and microsatellite markers have revealed genetic structure and recent declines in whale sharks11, a strong trans-Pacific break and the need for regional conservation units in the Galapagos shark12, and panmixia throughout the Indo-Pacific range of the highly migratory tiger shark13. Furthermore, reef shark studies have demonstrated significant genetic structure and variable demographic histories for blacktip reef sharks over their Indo-Pacific range14, and female blacktip reef sharks were shown to be philopatric in French Polynesia15. Genetic differentiation is also apparent in whitetip reef sharks across the Indo-Pacific but populations are more homogeneous at the regional scale16. Taken together, these studies illustrate that spatial and temporal variability in genetic differentiation among populations often reflect important components of the movement ecology of elasmobranch species.The application of molecular DNA techniques in conservation biology is well establishedCarcharhinus amblyrhynchos) is a reef-associated species distributed throughout the Indian Ocean and West and Central Pacific18. Gray reef sharks are among the most abundant reef sharks in the Indo-Pacific and can comprise up to 50% of the upper trophic level biomass on coral reefs in some areas19. Yet possible collapses of gray reef shark populations have been documented, even on reefs with relatively low human impacts20. Without a pelagic larval phase in their life cycle, population connectivity in gray reef sharks occurs exclusively through movements of adults and juveniles24. These movements and residency patterns are complex and vary among reefs and life stages and between sexes24. Gray reef sharks have been shown to change territory often at some locations  while at other places they have been documented to stay up to two years within the same territory . Low residency was also recorded on the semi-isolated reefs of the Great Barrier Reef23 whereas on isolated habitats, gray reef sharks seem to exhibit longer residency on a single reef28. The few genetic studies undertaken to date on gray reef sharks have shown high migration frequency along the Great Barrier Reef29, a barrier to gene flow across large expanses of ocean, and an isolation-by-distance pattern  along the Australian continental shelf30. So far, no study has investigated the genetic composition of gray reef shark populations across the species’ range. Therefore, while reef characteristics such as geography and oceanographic context likely play an important role, more specific factors regulating dispersal of gray reef sharks remain unknown.The gray reef shark . Therefore, all individual Fst values including the Indian Ocean were significant and high 36. Moreover, the large oceanic distances are now likely hindering widespread genetic exchange between the gray reef shark populations of each ocean basin as large stretches of deep open water have been suggested to create a barrier to gene flow for this species30. The strong genetic differentiation that we found .The western Indian Ocean population of the gray reef shark is clearly separated from the rest of the samples collected in the Pacific Ocean Table  and 3A. nd Table  and 3A i40 as well as in the sedentary whitetip sharks16. Large ocean expanses between these two regions likely reduce the probability of long-distance dispersal. Schultz et al.41 revealed moderate genetic differentiation (FST = 0.07) between Australian and French Polynesian populations of the Sicklefin lemon shark Negaprion acutidens and proposed a stepping stone mechanism for rare long-distance dispersal events between West and Central Pacific islands. Additionally, genetic differentiation between the Line Islands and French Polynesia has been demonstrated in the three-spot damselfish, Dascyllus trimaculatus42 and the brown surgeonfish Acanthurus nigrofuscus43. This genetic differentiation on either side of the equator in the Central Pacific likely arose due to isolation maintained by the major currents in the zone 45. A similar pattern of genetic differentiation in gray reef sharks suggests that dispersal seems to be dependent, to some extent, on the ocean circulation and the major currents in the area likely limit migration of sharks across this boundary. Gray reef sharks are viviparous and therefore, contrary to most reef fishes, population connectivity occurs through movements of adults and juveniles rather than dispersal of eggs and larvae. It is therefore likely that the same barriers to dispersal are acting for species both with and without larval dispersal. However, gray reef sharks have strong and complex reef residency behaviors24 that, when combined with the large expanse of deep open ocean between the regions, apparently reduces the frequency of long-distance movements. Thus, the genetic structure of gray reef sharks appears somewhat higher than that of reef fishes, that are more homogenous across their range43. We did identify a pattern of isolation-by-distance in our dataset when including all samples, samples from the Pacific only, and when removing the small size sample , indicating that dispersal probability in gray reef sharks is proportional to geographic distance among populations. Similar patterns of isolation-by-distance were described by Momigliano et al.30 and highlight the low probability of adult gray reef sharks migrating long distances across expanses of open ocean.At a regional scale, gray reef shark samples from the Pacific Ocean were clustered in distinct groups, with the Coral Sea specimens forming one cluster , the North-Central specimens forming another cluster  and the South-Central specimens (French Polynesia) comprising a third cluster Fig. . Additioet al.29 similarly detected no genetic differentiation in gray reef sharks over the 1200 km of the Great Barrier Reef system. In contrast, blacktip reef sharks show differentiation both among and within the archipelagos of French Polynesia46. Blacktip reef sharks must, therefore, either home to natal reefs at much higher frequencies, or move among reefs at much lower frequencies, than gray reef sharks. Interestingly, inbreeding coefficients from Eastern Australia, Phoenix, Society and Tuamotu samples were significant, suggesting somewhat limited exchange among reefs that went undetected by more traditional statistical analyses based on Fst. Overall, our results suggest that a small number of gray reef sharks make infrequent long-distance movements between reefs across open water. White et al.28 came to a similar conclusion based on a small sample of satellite-tagged gray reef sharks at Palmyra Atoll in the North tropical Pacific. Two from a total of six sharks were detected outside of the 200 NM limit MPA (Marine Protected Area) boundary surrounding Palmyra Atoll for 3% and 46% of their daily location estimates. The shark that traveled the furthest reached a maximum linear distance of 908 km from the 12NM MPA boundary surrounding Palmyra Atoll28.At a local scale, we collected sufficient numbers of samples to investigate genetic differentiation at the scale of a single archipelago  or several close archipelagos . No significant differences among reefs were found in either comparison. Momigliano 47. In our study, observed heterozygosity values were comparable for all the samples analyzed and also to those from the gray reef sharks of the Great Barrier Reef (0.79 to 0.829). These values were higher than in blacktip reef sharks28, where observed heterozygosity ranged from 0.47 to 0.67 but comparable to that of other shark species also analyzed with microsatellite markers7. Noticeably, heterozygosity levels did not correlate with the level of isolation of a reef, as all reefs show similar values. Thus, we found no evidence for recent genetic bottlenecks, as suggested for other reef shark species28. In our study, we further revealed clear genetic groupings across the Pacific region, with genetic differentiation among broader geographic clusters  or several closely related archipelagos (French Polynesia), gray reef sharks appear to represent quasi-panmictic units with free movements of individuals across reefs. Juhel et al.50 also showed that human-linked behavioral alterations should be considered in management strategies to ensure the persistence of gray reef shark populations. Furthermore, rare long-distance dispersal across open ocean barriers seem to be an important process driving genetic diversity and structure in gray reef sharks. Open ocean movements through “high-seas” corridors therefore represent an important component of the life history of at least some coastal sharks that functions to reduce local inbreeding. “High-seas” are currently the subject of much debate at the United Nations, and the first-ever “high-seas” conservation treaty is expected to be finalized in 2020. Momigliano et al.28 went so far as to suggest a move from discontinuous networks of MPAs on the GBR to MPAs connected via protected corridors to better protect these sharks with larger home ranges. A conservation plan for these gray reef shark populations should therefore include several conservation units with the potential for migration corridors in the high seas that would serve to connect regional reefs within each conservation unit. The Indian Ocean gray reef sharks clearly represent a conservation unit on their own while another conservation unit can be identified for the West Pacific and two others for the North and South-Central Pacific populations  ID number 18417. Sampling protocols for Palmyra Atoll collections were certified by the IACUC, University of California, Santa Barbara, Protocol no. 856  under U.S. Fish and Wildlife Service special use permits . Samples from the Great Barrier Reef were provided by collaborators from Australia in accordance with local regulations.A total of 407 sharks were sampled at 9 locations in the South West Indian Ocean, and the West and Central Pacific  to be run on an Applied Biosystems 3730 sequencer and were genotyped employing GeneMapper software version 4.0 .Total DNA was extracted from fin clips using the PureGene protocol . A total of 15 microsatellite markers developed for gray reef sharks were amplified using the primers and cycling parameters from Momigliano Micro-checker v2.2.358. The mean number of alleles (A), observed (Ho) and expected (He) heterozygosity, the inbreeding coefficient (Fis) and the fixation index (Fst) were computed in Genetix v4.05.0259. The number of private alleles (Ap) was computed in GenAlEx v6.560. The correction for multiple tests of Benjamini & Hochberg61 was applied.The presence of null alleles, scoring errors and large allele drop-out was verified using enAlEx. Additionally, Structure v2.362 was used to search for the most likely number of clusters. This analysis was run with no priors by location. After initial runs, the parameters were set as follows: a burn-in period of 100 000 iterations followed by 500 000 recorded iterations for K = 1 to K = 9 clusters and 15 iterations per K values. We ran a first analysis with all specimens and a second analysis with the specimens from the Pacific Ocean only. In this last analysis, we used sampling locations as prior (model LOCPRIOR63), known to be able to reveal subtle differentiations. The most probable number of clusters present in this dataset was determined using the Evanno’s ΔK approach64 and computed with Structure Harvester online65.To investigate population structure, a Principal Coordinates Analysis (PCoA) on populations was first computed in Genetix between the matrix of genetic distances [Fst ⁄ (1 – Fst)]66 and the matrix of log coastal geographical distances (in km) of each pair of localities. Significance was tested using a random permutation procedure implemented in Genetix (5 000 permutations). This analysis was performed on the whole dataset and on the Pacific samples only with or without the site with small sample size .We also tested for  a pattern of isolation-by-distance using a Mantel test in GSupplementary TablesTable S4