In recent years,RNA has emerged as a multifaceted biomoleculethat is involved in virtually every function of the cell and is criticalfor human health. This has led to a substantial increase in researchefforts to uncover the many chemical and biological aspects of RNAand target RNA for therapeutic purposes. In particular, analysis ofRNA structures and interactions in cells has been critical for understandingtheir diverse functions and druggability. In the last 5 years, severalchemical methods have been developed to achieve this goal, using chemicalcross-linking combined with high-throughput sequencing and computationalanalysis. Applications of these methods resulted in important newinsights into RNA functions in a variety of biological contexts. Giventhe rapid development of new chemical technologies, a thorough perspectiveon the past and future of this field is provided. In particular, thevarious RNA cross-linkers and their mechanisms, the computationalanalysis and challenges, and illustrative examples from recent literatureare discussed. Therefore, direct measurements of RNA structuresin cells have been critical for understanding RNA behavior in variousbiological and pathological processes.13 A variety of chemical reactions have been developed and exploitedthat can modify RNA at certain positions  selectivelyalkylates the N1 position of adenine and N3 position of cytosine onunpaired nucleotides15 and the 2′-OHin flexible regions can be acylated with Selective 2′-HydroxylAcylation analyzed by Primer Extension (SHAPE) reagents.18 Resulting reactivity profiles have been useful to improve secondaryand tertiary structure modeling;21 however, the 1D informationobtained with these experiments is not necessarily definitive evidencefor specific structures. More recently, correlated chemical probingcoupled with computational deconvolution has been used to discoverpotential contacts and alternative conformations in relatively shortRNA regions and simple conformations.24To dissectthe critical roles of RNA in biology, to study diseasemechanisms, and to develop RNA-targeting therapeutics, structuralanalysis of RNA has played an essential role.ositions 1 dependi28 demonstrated this principle using psoralen, a duplex-specific agentthat cross-links opposing pyrimidine nucleobases with two consecutive[2 + 2] photocycloadditions.29 Subsequentapplications provided the first physical evidence for snRNA-dependentpre-mRNA splicing, and snoRNA-guided rRNA processing.32 Rapid progress in both cross-linking chemistry andsequencing technology in the past few years have led to several newhigh-throughput methods for the analysis of RNA structures and interactions.In theory, the structure of any object can be uniquelydeterminedby the coordinates of their components, which should be equivalentto the distances among the components. Therefore, measuring the spatialdistances between nucleotides should allow de novo determination ofRNA structures in any biological sample. Chemical cross-linking ofRNA in cells using compounds of defined sizes and subsequent identificationof cross-linked nucleotides represents a practical path toward thisgoal. Pioneering work by Hearst and colleagues in the 1970s and 1980s35 a criticalanalysis and evaluation of the chemical mechanisms, computationaltools, and applications in biology have been lacking. Simultaneousconsideration of these three aspects is necessary to solve increasinglychallenging problems in RNA chemistry and biology. In this perspective,we focus on these topics together, to inspire chemists to furtherdevelop specialized chemical cross-linking agents necessary to tackleoutstanding questions in RNA biology and provide a guide for biologiststo choose the most appropriate methods for addressing specific biologicalquestions.While other recent reviews have summarized these methods,22.136 which hasbeen successfully demonstrated with caging agents to control RNA function.38 Gillingham and co-workers showed that terminal phosphates are moreprone to O-alkylation with diazo compounds than internal phosphatediesters, for which usually a large excess of reagent is required.This was attributed to the substantial difference in pKa (∼6–7 for phosphate monoester and ∼1for phosphate diester).36 The 2′-OHposition chemical reagents to form cross-links 1 of whic yellow, 1 can be nd blue, 1.28 This orange, 1 can reae green, 1 can actne pink, 1 can act52 carbazoles,45 thionucleotides,53 diazirines,54 and platinum complexes55 among others and have recently been reviewed.56We make a distinction between external and internalcross-linking reagents. External cross-linking reagents are the mainfocus of this perspective and can be added exogenously to sampleswithout the need of first modifying the RNA under investigation, whichallows the study of native RNA. Other advantages are that they aregenerally more accessible and pan acting, thus enabling transcriptome-wideinterrogations. Conversely, internal cross-linking reagents are installedin the RNA scaffold prior to the study either chemically or enzymaticallyand include coumarins,Four classes of external cross-linkingreagents 2are pre2.225 This natural product can undergotwo consecutive [2 + 2] photocycloadditions to cross-link opposingpyrimidine bases  products and LIGation of interacting RNA followed by high-throughputsequencing (LIGR-seq) used AMT cross-linking to map transcriptome-wideRNA structures and discover previously unknown RNA–RNA interactions.64Over 100 psoralen derivativeshave been reported with improvedphotophysical, physicochemical and biochemical properties as comparedto the parent compound.ple,AMT 3b bears60 The limited solubility of AMT at ∼1 mg/mL in water was hamperingthe efficiency in capturing RNA–RNA interactions. Amotosalenbears a primary amine and ether group and exhibits markedly increasedsolubility in water of 230 mg/mL. In vivo, it was found that a 10-foldincrease in concentration resulted in a 7-fold increase in cross-linked RNA. This overall improvedcross-linking allowed for establishing the first whole genome structureof enterovirus D68 and dynamic interaction networks for the U8 snoRNA,where genetic mutations cause a neurological disorder.To further improve the analysis of dynamic RNA structuresand interactions,PARIS2 uses amotosalen 3b instea65 A different azido derivative bears the azidegroup at the end of a triethylene glycol linker attached to the primaryamine of AMT and forms the basis of Cross-linking Of Matched RNA AndDeep Sequencing (COMRADES).66 Using thispsoralen derivative, cross-linked RNA can be selectively capturedand enriched using a biotin ligation and streptavidin pulldown.69 The presence of the azide group did not affect the cross-link efficiencyand using this method the researchers determined the architectureof Zika virus inside cells.66To increasethe functionality of psoralens, azido modified derivativeswere designed that can undergo azide–alkyne cycloadditions.For example, Hall and co-workers used Psoralen Azide 3b to app70 This was ligated to an amine bearing miRNA-29a mimic using standardamide-coupling conditions to afford conjugated RNA in quantitativeyields. After transfection into HeLa cells, S-Pso labeled miRNA-29aefficiently silenced luciferase gene expression of a reporter plasmidcontaining a miRNA-29a target site in its 3′ UTR to ∼15%,showing that the psoralen group did not affect miRNA silencing. ThemiRNA mimic was then applied to identify targets in live cells. Afterphoto-cross-linking, captured transcripts were quantified by RT-qPCR.Tet2 RNA was identified as a miRNA-29a target with 20-fold enrichmentafter cross-linking. This study highlights the potential use of psoralencross-linkers in RNA target identification.Toconjugate psoralen to an RNA of interest, Rana and co-workersdesigned the NHS-ester bearing derivative S-Pso 3b.70 Thi71 developed Sequencingof Psoralen cross-linked, ligated and Selected Hybrids (SPLASH). Inparticular the sensitivity of their method increased from ∼0.45with psoralen to ∼0.75 with biotinylated psoralen. Using SPLASHthe authors identified hundreds of known and unknown snoRNA-rRNA bindingsites. One disadvantage of this protocol is that cellular uptake ofbiotinylated psoralen was low, and 0.01% digitonin was added to increaseuptake. The psoralen derivative used in this study was modified atthe C8 position with biotin. Lin and co-workers found that when biotinis appended to the 4′-position of AMT  treatmentis used for preservation for long-term storage and preservation ofpatient samples. Glutaraldehyde . It was first attempted to cross-link 16S and 23S RNAusing UV cross-linking, but no interactions were found. HN2 did efficiently cross-link 16S-23S RNA as analyzed by gel electrophoresis,which led to the conclusion that there are several RNA–RNAinteractions within the ribosomal particle and that these can be exploredwith chemical cross-linking methods. Datta and Weiner applied thisprinciple to investigate higher order RNA structures and tertiaryinteractions.91 Nuclear extracts were subjectedto 20 mM solutions of HN2 and analyzed using sequencinggels. Intramolecular cross-links in U2 snRNA were apparent and couldbe localized within regions of a few nucleotides. Exact pinpointingof cross-link sites was hampered by monoadducts. Nevertheless, thedata clearly supported a tertiary structure model for U2 snRNA.In one of the first reports, the authors applied HN2 5c to stuHN2 cross-linking sites in HIV-1 SL1A RNA.92 This structured RNA contains a large flexible loop andan internal bulge. Cross-linking was performed with 250 μM HN2and subsequently digested with RNase A. Using MS, cross-linked fragmentswere observed that originate from both the loop and bulge region.Interestingly, guanine-adenine cross-links were observed as well,implying that nitrogen mustards do not exclusively react with guanine.Using mass spectrometry (MS), Fabris and co-workers analyzed 93 a naturallyoccurring nitrogen mustard isolated from Streptomyces griseoluteus.94 Bis-3-chloropiperidines, including B-CeP 1  with SPR. Anti mC antibodiesdo not recognize 5-mC in duplex DNA, but do bind to 5-mC located inbulged dsDNA and the KD was determinedto be 7.70 × 10–3 using SPR. Interestingly, L1 cross-linked and immobilized DNA showed a similar KD of 5.60 × 10–3 towardanti-mC antibody enabling the analysis of 5-mC in genomic DNA. Ina later study,97 the authors reported thedesign and synthesis of a biotin bearing nitrogen mustard L2 , acyl adducts were left on flexible positions ofRNA that were shown to stall reverse transcriptase. Using primer extension,the exact position of these adducts could be determined, which helpedto deduce RNA secondary structures.16 Thispioneering method has become widespread in the field and several newversions of acylating SHAPE reagents have been reported in the pastfew years.99 Furthermore, continued interestin these chemistries have provided new insight into differences inRNA reactivity toward 2′-OH acylating reagents.100Early workby Knorre and co-workers40 The bifunctional probes bear twocarbonylimidazoles that can react with the 2′-OH of opposingnucleotides. Depending on linker length between the reactive groups,cross-linking efficiencies between 45% and 84% were observed on amodel self-complementary RNA duplex. To enable downstream analysisof cross-linked RNA, azide trigger groups were installed to reversethe cross-link. Azides could be reduced to amines using phosphines,promoting lactam formation and cross-link reversal. Reversal efficienciesranged between 2% and 70% depending on phosphine, with 20 mM tris(hydroxypropyl)phosphine (THPP) being most efficient. The applicability of this cross-linkingmethod was demonstrated by protecting RNA from nuclease digestion.A model RNA was fully degraded by S1 nuclease and RNase T1, whereasBINARI cross-linked RNA remained intact. Cross-link reversal by THPPliberated the model RNA strand, illustrating the potential use forchemical cross-linking for temporary RNA preservation.Two consecutive acylating reactions onopposing nucleotides should result in a cross-link 6. Kool a41 This method, named Spatial 2′-HydroxylAcylation Reversible Cross-linking (SHARC), used simple dicarboxylicacids that could be activated with CDI in a single step to cross-linkRNA. In particular, DPI ,66 or antibody-based immunoprecipitationof protein-bound RNA  , hiCLIP) 7b.102,10Each approach has its own advantagesand problems. rRNA depletion or oligo(dT) enrichment of mRNAs maynot be sufficient to isolate low-abundance RNAs. Biotinylated antisenseoligos are expensive, making it hard to scale up the experiments.Antibody enrichment of ribonucleoprotein (RNP) complexes results inhighly specific RNA conformations but depends on prior knowledge ofthe complex composition and the availability of high-quality antibodies.Centrifugation-based fractionation is very crude and highly variable,and often does not achieve sufficient specificity and purity. APEX-basedenrichment introduces another irreversible chemical modification stepthat impedes reverse transcription (see further discussion below),reducing the efficiency of detecting proximally ligated RNA fragments.3.260 The 2D gel methodis applicable to any chemical cross-linker, such as psoralens, nitrogenmustards and bifunctional acylators, since the separation only dependson RNA geometry.60 However, 2D gels arevery laborious and difficult to scale up. Exonuclease digestion ofnon-cross-linked fragments is easier to perform, but also enrichesnon-cross-linked RNAs that are highly structured, have chemical monoadducts,or are cross-linked to proteins.64 Biotinylatedcross-linkers allow facile enrichment of reacted RNAs using the biotin–streptavidinsystem , exonuclease digestion,and streptavidin selection of biotinylated cross-linkers. The 2D gelmethod, including both native-denatured 2D and denatured-denatured2D, separates cross-linked fragments from non-cross-linked based onslower migration of its extended “X”-shape, which intheory provides 100% purity 7a.60 The3.342 This approachalso improves the resolution in defining the cross-linked sites. However,this method has only been tested in simple RNA samples in vitro, andthe efficiency is even lower than proximity ligation. Given that monoadductsaffect both exonuclease trimming and template switching, further developmentof cross-linkers that produce minimal monoadducts is needed to improveresolution in the identification of cross-linking sites.Fragmented RNAs range in lengthfrom a few to several hundred nucleotides.While selection of shorter fragments increases the resolution of structuremodeling, it only helps duplex modeling, where base pairing rulescan be used to build the secondary structure model. Cross-linkingof fragments that form tertiary contacts or spatial proximity doesnot provide sufficient resolution for structure modeling. To resolvethis issue, two approaches have been developed. Exonucleases can trimoff nucleotides from either end ,until blocked by the cross-link, leaving a tail of a defined length7c. Such 3.4105 Given that each protocol has several other steps that affect theperceived ligation efficiency, such as the purity of the cross-linkedfragments (see the section above on enrichment of cross-linked fragments)and RNA damage levels, none of the improvements have been convincinglydemonstrated to outperform others in side-by-side comparisons. Newchemical and enzymatic approaches that overcome damages of RNA andsteric hindrance of short fragments are needed to improve the ligationefficiency.Proximity ligationis the most widely used approach to join two cross-linked fragments.The ligation reaction can occur on either end, leading to differenttypes of sequenced reads. Ligation of both ends leads to circularproducts that can no longer be ligated to adapters and are thereforelost during library preparation. However, given the low ligation efficiency,such double ligation events are rare and can be mostly ignored. Thecovalent linkage between the two fragments dramatically increasesthe likelihood of ligating them, compared to non-cross-linked onesin solution; however, the cross-linked stable structures and shortnessof the fragments create steric hindrance, limiting ligation efficiencyto typically below 15%. While longer fragments may be subject to lowersteric hindrance and more efficiently ligate, they reduce the resolutionof structure analysis. Several different protocols have been usedin the last 10 years, including direct enzymatic ligation by T4 RNARnl1, Rnl2, CircLigase, Mth Rnl, and RtcB and the indirect ligationby incorporation of linkers, such as pCp-biotin and short oligos.3.5106 UV-induced lesionsin RNA are commonly observed and include base oxidation (primarily8-oxoguanine),107 pyrimidine dimers,108 and adducts with proteins110 and other cellularcomponents  extraction of information from readsincluding classification and clustering, and (2) inference of structuralconformations, including 2D and 3D structure modeling. The first stepprocesses the data, without the need for any prior knowledge or assumptionsabout the structure, whereas the second step models the structuresbased on principles of RNA folding.4.1114 Proteinase treatment after cross-linking can exclude the protein-mediatedproximities.60 Careful comparison of data fromdifferent types of cross-linkers will provide deeper insights intothe organization of the RNP complexes.In theory, cross-linking and ligation can occuron any RNA in physical proximity (as long as the chemistry of thecross-linker permits). Therefore, such experiments can join many differenttypes of arrangements of RNA fragments into a single read. The chemicalreactivities of the cross-linkers determine the types of structuralinformation obtained 9a. For e115 Classification of these reads reveals the fragmentarrangements and therefore the underlying structural conformations.Recent exhaustive classification results in 5 major read types  suggest a singleconstraintin the structure, either a double helix cross-linked by psoralens,or tertiary contact/proximity cross-linked by SHARC or TBIA and othertypes of cross-linkers 9c. Reads4.2116 The clusteringof multiple different DGs provides direct evidence for the existenceof alternative or dynamic conformations. Such conformations are easilydetected for psoralen cross-linked RNA fragments, given the mutuallyexclusive base pairing (except the triplexes and G-quadruplexes whereeach stretch of nucleotides can participate in multiple consecutivecontacts). Other clustering approaches have been developed simplybased on overlap of arms among reads.118High-throughput sequencing produces verydense gapped reads that come from various structural units and conformationsin the transcriptome, making it difficult to interpret the data. Basedon the assumption that each structure unit produces a set of readsthat are highly similar to each other, the reads can be clustered,where each group can be used to infer a specific contact , enablingtight packing of the reads in genome browsers  demonstrated their authenticity.At a lower level, the inference of individual secondary and tertiarystructure units from cross-linking data remains an unsolved problem,for several reasons. First, the low cross-link-ligation efficiencyand strong bias led to incomplete data for modeling .Second, conventional computational modeling tools were not optimizedfor the incorporation of cross-link-ligation data, so it remains unclearhow to make best use of experimental constraints. Third, current modelingtools can only be applied to short RNAs due to the prohibitive computationalcost. Despite these challenges, several general approaches have beenimplemented.Protein-mediated proximities and in situ proximityligations can join any RNA fragments as long as they are close toeach other in space, but does not require direct contact, making itdifficult to determine the RNA conformations 9a. Direc4.3.163 Whole transcript structures can then be establishedby combining all the structure models. This method is fast, sinceonly cross-linked regions are modeled, however, the resulting globalconformations cannot be clearly deconvolved. Typically, one structuremap is produced for each RNA as a result, including all the predictedhelices, some of which may be mutually exclusive (124 The gapped reads (andthe assembled DGs) are then mapped onto the clustered conformations.This approach outputs complete global conformations, however, it alsosuffers from several caveats. The structures may be overfolded, andnot all duplexes in such models are necessarily supported by experimentalconstraints. The folding step may not be feasible for long cellularand viral RNAs, many of which measure tens to hundreds of thousandsof nucleotides. As a result, folding is often performed in windowsof limited lengths , which excludes long-rangestructures. In the future, integration of these two approaches isneeded to increase the efficiency and accuracy of 2D structure modeling.To quickly validate and rank the biological relevance of these secondarystructure models, multiple sequence alignments and identificationof conserved and covaried base pairs are often performed, and comparedto experimental constraints.122Two different strategiesare used for 2D structure modeling based on experimental constraints:divide-then-fold 10c, and xclusive 10d.66,124.3.214 In addition to theprimary sequence and secondary structure models, experimental constraintsare typically incorporated into the modeling as pseudoenergy terms:predicted conformations are penalized where the constraint is notsatisfied. Compared to 2D modeling, the basic rules in 3D structuremodeling have not been thoroughly studied,125 and therefore, the modeling results are typically confounded bymultiple sources of error, both computational and experimental. Despitethat experimental constraints can be obtained for RNAs of any length,modeling of large RNAs remain impractical due to the high computationalcost.Computational modelingof 3D RNA structures is a rapidly progressing field, and many differentapproaches have been proposed, such as molecular dynamics, fragmentassembly, and deep learning 10e.14 In5Cross-link-ligation methods have a widerange of applications inRNA biology and medicine. The earliest applications of these chemicaltools were critical in establishing the structural mechanisms of pre-mRNAsplicing and rRNA processing. Here we discuss critical considerationsin applying these methods, and review some of the most interestingexamples in recent years, focusing on lncRNAs, ncRNA networks, geneticdisorders and RNA viruses, which will help researchers to properlyapply them to their biological problems.5.1127Recent development of sequencing-based strategies allowed deeperinterrogation of transcriptome-wide RNA folding principles, lowerabundance RNAs and low frequency alternative/dynamics conformations.While general properties of RNA folding can be extracted from transcriptome-widemeasurements, rigorous functional studies of the newly discoveredRNA structures and interactions have not caught up with the rapidlygrowing large lists of new data from high-throughput sequencing. Thechoice of chemical cross-linkers should be based on the needs of specificbiological questions. For example, detection of base pairing mediatedstructures and interactions require psoralens, whereas general spatialproximity can be studied using other cross-linkers 9a. Even 119 More abundant and reproducible structures are more likely to contributeto functions. Second, validation by various other methods, especiallystructure conservation/covariation increases the confidence in thefunctional significance.128 Third, directconnection of the structural elements to functional sequence motifs, protein binding sites, RNA modificationsites and processing patterns, etc. indicates potential functionsin these aspects. Last, linkage of the structures to human diseasesis a strong motivation for further mechanistic analysis. These principleshave been employed in several recent studies. After discovery of potentiallyimportant RNA structures, care should be taken in studies of theirfunction, since functions for one specific DNA and its RNA productscan be encoded on multiple levels, such as DNA sequences, RNA sequences,RNA–protein or RNA–RNA interactions, as well as RNAstructures. To demonstrate that functional consequences are indeeddue to structure formation, multiple types of mutation and compensatoryrescue tests are needed.To pursue discovery-driven studies of RNA structures, severalimportant aspects need to be considered even if the sequencing experimentwas designed to test a specific hypothesis as opposed to an unbiaseddiscovery. First, analysis of the relative coverage and statisticalsignificance is needed to predict the biological significance of thenewly discovered structures or interactions, as described above 9g.118,115.2131 noncoding RNA interactions116 and lncRNA functions.132Recent applicationsof the cross-link-ligation methods have been focused on several directions,including RNA virus genome structures and host–virus interactions,Flaviviruses, such as Zika and Dengue,122Coronaviruses, such as SARS-CoV-2,131 and Picornaviruses, such as EV-D68.60 These studies confirmed many previously predictedstructures, revealed new structural elements and new miRNA and snoRNA-mediatedhost–virus interactions that affect virus fitness.Single-stranded RNA viruses are a major targetof the cross-link-ligation methods, because of the strong dependenceof the viruses on their genome structures and RNA-mediated host–virusinteractions, and the therapeutic potential of targeting viral RNAgenomes. Recent studies have reported genome structures and host–virusinteractions for 133 eukaryotic miRNAs134 and snoRNAs.116 These studies dramatically expanded the known targetsof important ncRNA regulators. Given the low abundance of many ncRNAsand their targets, it is expected that future deeper sequencing, coupledwith RNA enrichment methods  have been only implemented in bulk samples.Alternative RNA structures are pervasive in cells, and likely contributeto cell-type-specific regulation of gene expression. Indeed, suchexamples have been demonstrated in RNA-structure-dependent alternativesplicing of cell adhesion molecules that determine neuronal connectivity,such as insect 6.442 not every base pair can be identifiedwith high confidence. On the other hand, 1D chemical probing data,such as from SHAPE and DMS-seq, provides detailed information on thestructure/interaction constraints on individual nucleotides, despitethe lack of confidence in their discovery of complex and long-rangestructures. New computational tools that carefully evaluates datafrom various experimental methods are needed to effectively take advantageof each method and avoid artifacts. With new computational modelingalgorithms, 1D accessibility, 2D base pairing and 3D spatial proximityconstraints should enable better modeling of RNA structures.The cross-link-ligation data provide constraintsfor global organization of RNA structures but lack sufficient resolutionon the details. Even though the exo trimming and template-switchingmethods can pinpoint some of the cross-linking sites ,6.5Thelong-term goal of developing cross-link-ligation and otherexperimental tools is to build high resolution and comprehensive structuremodels for RNA, which will hopefully provide new insights into theirfunctions in vivo. While many computational tools have been developedto build 2D and 3D structures, such tools are often developed basedon energy terms and parameters derived from a small number of in vitromodels. Furthermore, RNA structural dynamics is not only determinedby its primary sequence, but also cellular environments, such as proteins,other RNAs, ions, metabolites, temperature, and pH, most of whichcannot be incorporated into the modeling studies.141 Now,the cross-linking-derived in vivo constraints offer a unique opportunityto model 2D/3D RNA that represent true in vivo conformations. On theexperimental side, distance measurements are not always accurate.Exo trimming is effective but is can be problematic due to monoadductsblocking the exonuclease. The template switching strategy in SHAPE-Jumpis another approach but suffers from high noise, due to the low efficiencyand randomness of template switching.42 Even though chemical cross-linking indicates a probable distancebetween two nucleotides, the range of the distance distribution canbe quite large due to the natural dynamics of the RNA in cells. Furthermore,very few RNA molecules exist in their naked form; most RNAs are boundby a wide variety of proteins. Ignoring the proteins in the modelingis bound to introduce errors. On the computational side, current implementationof such approaches are still rudimentary, and only produce very simplemodels.42 New methods that consider the in vivo flexibilityand dynamics during modeling are needed to produce ensembles of structureconformations that are more biologically relevant. Conventional 3Dmodeling tools are extremely computationally expensive, currentlyonly able to handle RNAs within 200–300 nucleotides. Fasternew algorithms are needed for the vast majority of the large RNA moleculesin cells, which often span hundreds to tens of thousands of nucleotides.Earlier studieshave made use of in vitro constraints from correlated chemical probingto improve computational modeling.6.6142 Many more RNA-targeting therapeutics are either in preclinical studiesor clinical trials. Structural studies have played critical rolesin some of these RNA therapeutics and we expect that the increasingavailability of RNA cross-linking experiments will further assisttoward this goal in the future. For example, the discovery of intronicsequence and structure elements in the SMN2 gene led to the developmentof antisense oligo drugs to treat spinal muscular atrophy, one ofthe most prevalent pediatric genetic disorders.143Normal and abnormal functions ofRNA molecules have been implicated in many human diseases, such asnucleotide repeat disorders, RNA virus infections, and splicing mutations,which account for at least a third of all disease mutations. The pastdecade has witnessed a revolution in the field of RNA therapeutics,with the approval of multiple small molecule and antisense oligo drugsthat target a wide variety of RNA sequence and structural elementswith critical roles in human diseases.In summary, we hope that our critical review of chemicalcross-linking methods, including the chemistry, enzymology, computationalanalysis, and biological applications, will spur further improvementsof these methods and applications in chemistry, biology, and therapeutics.Improved structural information will bring conventional sequence motif-basedstudies of RNA regulation to higher dimensions in the future. Betterstructure models obtained with enhanced chemical cross-linkers willprovide essential guidance for the development of RNA-based and RNA-targetingdrugs.


Understanding complex biological events at the molecular level paves the path to determine mechanistic processes across the timescale necessary for breakthrough discoveries. While various conventional biophysical methods provide some information for understanding biological systems, they often lack a complete picture of the molecular-level details of such dynamic processes. Studies at the single-molecule level have emerged to provide crucial missing links to understanding complex and dynamic pathways in biological systems, which are often superseded by bulk biophysical and biochemical studies. Latest developments in techniques combining single-molecule manipulation tools such as optical tweezers and visualization tools such as fluorescence or label-free microscopy have enabled the investigation of complex and dynamic biomolecular interactions at the single-molecule level. In this review, we present recent advances using correlated single-molecule manipulation and visualization-based approaches to obtain a more advanced understanding of the pathways for fundamental biological processes, and how this combination technique is facilitating research in the dynamic single-molecule (DSM), cell biology, and nanomaterials fields. Biological systems go through complex and multicomponent events happening at the molecular level. These events establish key functions of biological systems. Precise observation of these molecular events provides a better understanding of the biological mechanisms and the behavior of biological systems. Techniques in structural biology ) provide deep insights into the structure of the biomolecules at the atomic level as snapshots. While providing details into the structures of biomolecules such as nucleosomes to whole cells to viruses as well as subsequent molecular interactions, cryo-EM provides limited dynamic mechanistic information ,3,4,5,6.Single-molecule techniques have emerged as a powerful tool to bridge this gap toward a better understanding of biomolecular processes ,10,11. TBroadly, single-molecule experimental technologies can be divided into two categories: manipulation and visualization-based technologies . Active Atomic force microscopes are great force spectroscopy tools for studying various biological mechanisms such as inter and intramolecular interactions in near-physiological conditions ,32,33. AMagnetic tweezers (MT) are simple and robust single-molecule force spectroscopy tools that offer manipulation based on a magnetic field gradient ,46. MTs Compared to AFM and MT, optical tweezers provide a balance of sub-piconewton force measurements with high resolution and sensitivity, essential for biophysical characterization . OpticalWith advancements in optical tweezers, they have been combined with other single-molecule methods for biophysical studies. An early investigation by Ishijima et al. (1998) successfully combined dual optical traps with TIRF microscopy to observe individual ATP hydrolysis steps by a single myosin molecule on actin . Lang etThe high complementarity of force and fluorescence-based methods, enabling simultaneous manipulation and visualization for probing mechanical changes and biomolecular interactions, makes them a robust combination duo . One sucThis review highlights applications of correlated optical tweezers and fluorescence microscopy combined with microfluidic systems to understand key mechanisms of action for a broad range of biological systems. The most commonly studied mechanisms involve DNA–protein interactions, namely during DNA replication, DNA damage and repair, helicase activity, chromatin dynamics, and DNA editing using CRISPR-Cas-based systems. Next, we will focus on RNA and protein-based studies such as manipulating the structure of RNA and protein molecules and their key insights into the conformational dynamics of these folded biomolecules in the free-energy landscape. Further, we will investigate the cases where the material and rheological properties of disordered proteins forming biomolecular condensates and nucleic acid-protein co-condensates are studied using force spectroscopy. Moving from molecular interactions to macromolecular interactions, we will illustrate the roles and applications of correlative optical tweezers and fluorescence microscopy in understanding cytoskeletal structure and function, both in vitro and in vivo. In the future directions section, we will highlight new avenues and future outlooks of such combined approaches in new applications such as RNA biology, the characterization and handling of nanomaterials, and mechanobiology and cell-based measurements at a larger scale.Many biological processes revolve around the interactions between protein machinery and DNA/RNA. DNA repair, DNA replications, gene editing and regulation of gene expression, and transcription are crucial to cells’ performance and depend on the interactions between proteins and DNA/RNA molecules ,81,82. TIn recent decades, RNA-guided gene editing techniques from bacterial defense mechanisms against viruses have been adapted for therapeutic purposes ,86. ThesChromatin organization is a dynamic process that plays a key role in DNA repair, recombination, genome replication, and silencing ,82. CoheDNA replication includes major molecular events such as initiation, DNA unwinding, primer synthesis, and elongation, which are the result of precise collaboration between different proteins and dsDNA . CorrelaDNAs are constantly exposed to endogenous and exogenous damaging agents . To ensuRNA plays a key role as an information transfer intermediate between DNA and protein while regulating gene expression. The RNA coding family, mRNA, is responsible for protein synthesis inside the cell; the non-coding family of RNA plays an essential role in regulating downstream gene expression processes and controlling protein production. Similar to proteins, some non-coding RNAs are highly structured and undergo thermodynamic and kinetically controlled conformational changes in the folding free energy landscape ,100,101.+ concentration with a rupture force of ~32 pN (RNA G-quadruplex motifs (RG4) are a group of guanine (G)-rich RNA sequences that can form stacked G-quartets with monovalent cations between them, such as DNA G-quadruplex structures. RG4 is speculated to regulate key biological functions, such as transcription and translation regulation, RNP formation, and splicing regulation ,111. Whef ~32 pN . They shRNA pseudoknots, another group of RNA structural elements, are specifically known for their functional role in RNA viruses . RNA pseInterestingly, while certain viral factors interact and influence viral RNA pseudoknots to increase viral infection, other antiviral proteins can reduce viral infection through a similar mechanism. Zimmer et al. (2021) identified a short isoform of the endogenous zinc-finger antiviral protein (ZAP-S) and showed that its overexpression and interaction with viral RNA pseudoknot can reduce the replication of the SARS-CoV-2 virus and hence its life cycle . During Cells are made of specialized compartments and organelles with specific functions and chemical compositions. These organelles are separated from the cytoplasm and other organelles by a membrane. However, there are other organelles that are membraneless. These organelles are formed and separated from their environment by liquid-liquid phase separation . To undeBiomolecular condensates consist of structured proteins, intrinsically disordered and unstructured proteins, and RNA. Molecular condensates tend to coalesce together, and their speed of fusion can reveal information about their packaging density and liquidity ,119. It Optical tweezers are great tools to study condensate material properties via active and passive rheology. In active rheology, two micron-sized beads are trapped inside a condensate. One bead is used to cause oscillatory movements inside the condensate, and the second bead is used to measure the condensate deformation caused by the oscillation. In passive rheology, fluctuations caused by the thermal energy of an optically trapped bead inside a condensate are measured over time ,128,129.It is known that condensates are present inside the nucleus and are involved in different processes such as DNA repair, transcription, and heterochromatin formation . Even thAnother type of condensation that occurs between protein and DNA molecules in the nucleus is called surface condensation. Based on a study by Morin et al. (2022), measurements using optical tweezers show that the presence of DNA molecules can induce transcription factor Klf4 to form condensations at a much lower concentration than the required concentration for the bulk phase separation of Klf4 . FurtherProteins play essential roles in all life processes, from accelerating various metabolic reactions to controlling signaling transduction. The regulatory and catalytic functions of enzymes require dynamic changes in protein structure ,136. TheSophisticated biophysical methods better elucidate the mechanisms of various biological processes. Emerging technologies give an understanding of protein variability, time-dependent variability (dynamic disorder), and the innate mechanistic behavior of an enzyme during individual binding, unbinding, or catalytic events. In addition to spatial arrangement, dynamic fluctuations are a driving force for several types of molecular interactions. In particular, the Rief laboratory pioneered protein nanomechanics with single-molecule fluorescence accuracy using GFP protein as a model system ,139,140.Accurate characterization of dynamic travel time between enzymatic states is important for understanding protein function. Protein dynamics are characterized not only by the timescale of the fluctuations (a kinetic component) but also by the amplitude and the directionality of the fluctuations . Consequently, the energy landscape representing a protein, which has numerous atoms, is highly multi-dimensional. Optical tweezers enable precise manipulation of biomolecules while simultaneously monitoring their response to force and displacement with nm resolution. For example, Maciuba et al. (2021) demonstrate a streamlined approach for investigating complex molecular assemblies with single-molecule force spectroscopy with optical tweezers . DevelopOverall, the intricate manipulation and monitoring provided by single-molecule force spectroscopy illuminate protein folding mechanisms such as the GroEL-ES chaperone-assisted folding mechanism, in which enhanced collapse plays a vital role. This proposed unfolding model was directly observed through single-molecule optical tweezer experiments and further facilitates an understanding of the folding mechanism, which is distinct from current models . DelvingThe cytoskeleton is a critical cell component that regulates cell shape, cell migration, and intracellular organization . It consUsing a single-molecule approach enables the simultaneous study of the dynamics and mechanics of cytoskeletal processes a. SpecifUsing correlative IRM/TIRF technology, microtubules were imaged on the surface using IRM, while the motility of GFP-labeled kinesin motors on microtubules was measured using TIRF b. These A deep study of vimentin, a typical IF protein, using optical tweezers reveals crucial loading rate dependence of mechanical response, which further implies that IFs could serve to protect eukaryotic cells . FurtherSorkin et al. (2020) illustrated the flexibility and power of a system coupling optical tweezers with imaging capabilities provided when investigating Synaptotagmin-1 (Syt1), a calcium sensor protein, induced membrane remodeling . ResearcCorrelated force and fluorescence single-molecule approaches have emerged as great tools, not only for biophysicists but also for biologists and physicists, in understanding the missing details of structure-function relationships and materials’ properties. For example, employing correlated force-fluorescence approaches to look at biophysical and material properties of biomolecular condensates and measuring their micro-rheology has shown new possibilities for studying and understanding condensate properties. Similarly, looking at DNA-protein interaction through simultaneous manipulation and visualization in real-time has established new ways to understand complex, multi-component processes such as DNA replication, organization, damage repair, and editing. The adaptation of dynamic single-molecule approaches is increasingly benefiting various applications in the biology field. Thus, new generations of applications are anticipated, where the implementation of correlated force and fluorescence microscopy can aid in understanding complex biological processes and nanomaterial handling.RNA biology is a research area of increasing interest, where researchers are focused on understanding the structure-function relationships of different forms of RNA. In the past couple of decades, researchers have used optical tweezers and single-molecule fluorescence microscopy separately to understand different types of RNA structures  and their related functions  ,99,106. In earlier sections, we discussed the adaptation of correlated force and fluorescence techniques for studying RNA structures at different forces. Just like proteins, conformational dynamics and long-range interactions of regulatory RNA elements such as hairpins, riboswitches, and ribozymes can be studied with optical tweezers in correlation with smFRET. Duesterberg et al. (2015) reported correlated force-smFRET studies to measure secondary and tertiary structural changes in a TPP riboswitch during folding and ligand binding . RNA folThe combination of optical tweezers and fluorescence microscopy is a perfect tool for understanding RNA elements far beyond just their structures. For example, the transcription cycle in prokaryotes happens in two key steps: (1) initiation, where RNA polymerase recognizes the promoter site on DNA, binds to the DNA, and then unzips the DNA to form a bubble while recognizing the template strand; (2) elongation and termination, where elongating RNA polymerase scans over the DNA to decode the template into mRNA, followed by termination, often induced by certain factors, to signal the end of mRNA synthesis and release . Many reSimilar to transcription, the translation process uses templates of coding RNA (mRNA) to make proteins essential for gene regulation. Each of these translation steps involves template mRNA, ribosomal subunits, tRNAs, and a variety of factors that have been extensively studied using a wide range of single-molecule techniques, showing the precise kinetic control of each component and forces generated by the ribosome during this process ,176,177.Although electron microscopy techniques such as SEM and TEM are ideal tools to study nanomaterials, optical tweezers can be used for the manipulation and precise placement of nanoparticles such as semiconductor nanowires to assemble complex circuits and lab-on-a-chip devices ,181,182.Raman spectroscopy uncovers the structural fingerprint of materials according to their vibrational modes. Metallic nanostructures in bulk have been used to intensify the typically weak Raman signal through their plasmonic effects . Dai et At larger scales, correlated fluorescence microscopy and optical tweezers have a variety of applications in mechanobiology and nanomaterial handling and characterization . OpticalAt smaller scales, several labs have been using home-built and commercial optical tweezer systems with integrated microfluidic devices to investigate the behavior of bacteria for microbiology and biofilm studies. For example, bacteria’s response to chemical stimuli has been extensively studied based on their swimming behavior using optical tweezer systems. Optimal experimental parameters have been identified to decrease the IR radiation damage and increase the “killing time.” Moreover, it is shown that oscillating and dual-beam optical tweezers enable the horizontal alignment of bacteria, which is important for simultaneous manipulation and observation ,194,195.9–1012 W/cm are used to create optical traps with high stiffness. This can lead to local heating at the focal point, which can cause damage to the sample and alter temperature-dependent and enzymatic reactions [Although optical traps remain one of the most versatile force measurement and manipulation tools, they have drawbacks that must be considered during different measurements. As optical tweezers work like a Hookean spring, force measurements’ resolution depends on the accuracy of the calibration for obtaining the trap stiffness (spring constant) ,198,199.eactions ,205,206.There are still many challenges in this field that need to be addressed to make such correlated technologies applicable to broader applications. A key limitation of optical tweezers is their low throughput . OT obseMore recently, such technologies are getting adopted far beyond the single-molecule level. As we discussed in some cases in the mechanobiology sub-section, correlated tools are increasingly being adopted to detect, measure, and visualize molecular interactions at the single-cell level. The ability to measure lateral and axial forces on individual cells has helped researchers reveal mechanical complexities in a wide variety of cell-based systems, such as RBC  and mono


RNA-binding proteins (RBPs) form complex interactions with RNA to regulate the cell’s activities including cell development and disease resistance. RNA-binding proteome (RBPome) aims to profile and characterize the RNAs and proteins that interact with each other to carry out biological functions. Generally, RNA-centric and protein-centric ribonomic approaches have been successfully developed to profile RBPome in different organisms including plants and animals. Further, more and more novel methods that were firstly devised and applied in mammalians have shown great potential to unravel RBPome in plants such as RNA-interactome capture (RIC) and orthogonal organic phase separation (OOPS). Despise the development of various robust and state-of-the-art ribonomics techniques, genome-wide RBP identifications and characterizations in plants are relatively fewer than those in other eukaryotes, indicating that ribonomics techniques have great opportunities in unraveling and characterizing the RNA–protein interactions in plant species. Here, we review all the available approaches for analyzing RBPs in living organisms. Additionally, we summarize the transcriptome-wide approaches to characterize both the coding and non-coding RBPs in plants and the promising use of RBPome for booming agriculture. Owing to their sessile nature and fixed growing places, plants have evolved an adaptive mechanism to cope with changing environments . This meRBPs exert their function by forming a complex interaction with RNAs via single or multiple RNA-binding domains (RBDs) , such asThe available methods for studying RNA–protein interactions are mainly categorized into RNA-centric, protein-centric, in silico, and transcriptome-wide approaches . In thisCaenorhabditis elegans and humans to identify both coding and non-coding RBPs [The selection of the identification methods for RBPs relies on the type of RNA molecule . The proing RBPs .Arabidopsis to identify the mRNA targets [Protein-centric methods aim to identify RNAs that bind to proteins of interest . Interac targets ,17. ReceTo overcome the drawbacks associated with the “native purification methods a”, a “deRNA-centric approaches are used to identify proteins that bind with the RNA of interest . GeneralThe in vitro approach involves the biosynthesis of RNA bait, the binding of the tagged-RNA to resin, the formation of a complex of ribonucleoproteins (RNPs), and the washing, purification, and elution of the RBPs that are bound with the tagged RNA ,37. The The major drawback of the in vitro RNA-tagged method is the alteration of the secondary structure of RNA due to its interaction with the labeling dyes . For RNATo circumvent the drawbacks of different dyes, numerous natural and artificial aptamers are used to increase the affinity of RNA with the proteins ,41. StreProtein microarray is also an alternative in vitro approach . In thisGenerally, in vitro methods work specifically and efficiently for the individually known RNAs. However, it is difficult to know the insertion place of natural and artificial aptamer tags without any structural information about the RNA of interest, and the insertion of tags changes the RNA structure. Moreover, these aptamers are not resistant to endonucleases which could reduce the lifetime and recovery rate of RBPs ,46. The Arabidopsis [The in vivo method isolates and identifies the RNA–protein complexes inside the cell and retains the integrity of RNA–protein complexes by developing a strong covalent bond between them. The in vivo method has two variants depending on whether UV cross-linking is needed ,45,46. Tbidopsis . Howeverbidopsis ,14,50. Mbidopsis .8−109) [The other variant of the in vivo method is formaldehyde cross-linking, which links together the macromolecules within 2 Å. Formaldehyde cross-linking can form protein–protein, RNA–protein, and DNA–protein interactions, and works efficiently on cells, tissues, and even whole organisms . Formald8−109) ; many pr8−109) .There are RNA-centric variants that do not need UV and chemical-based cross-linking. “Promiscuous” biotin ligase (BioID) is one of these RNA-centric variants . In thisArabidopsis [Despite the availability of several RNA-centric approaches, only the RIC RNA-centric approach was employed in bidopsis ,58,59,60Both protein-centric and RNA-centric approaches are useful for the identification of RBP in humans, yeast, and plants . HoweverMainly, computational methods are categorized into two categories: template-based and machine learning methods. Template-based methods, initially, find sequence similarity between query and template (known to bind RNA) for assessing the RNA binding preference of the protein sequences, whereas the machine learning method creates predictive models that can find a pattern in the input feature space to score the probability of the RNA-binding preference. Various features and algorithms are used in the machine learning approach for deciphering the RNA–protein interactions ,62. SomeIn plants, several studies have been conducted for the transcriptome-wide identification of coding RBPs by employing the RIC method ,59,65,667 cells are required for RBP enrichment [To overcome the drawback of RIC, Jackob and colleagues developed the XRNAX method for the identification of transcriptome-wide RNA binding proteins . XRNAX frichment . By emplrichment . Besidesrichment .6 cells) than the RIC approach [Salmonella Typhimurium [Beckman and colleagues developed PTex b for theapproach . Practichimurium .Similar to XRNAX and PTex, the CARIC method captures both poly(A) and non-poly(A)-dependent RBPs. It consists of a series of steps: the metabolic labeling of RNAs (mRNA and non-coding RNAs) with 4-thiouridine (4SU) and 5-ethynyl uridine (EU); in vivo RNA protein photo cross-linking; reaction with azide-biotin; use of biotin tags for the affinity enrichment; and isolation of RBPs by streptavidin beads. Due to its universal acceptability towards the eukaryotes, CARIC has been used in living organisms such as bacteria , animals6 cells for RBP-enrichment in OOPS [OOPS retrieves the free protein, protein-bound, free RNA, and cross-linked protein RNA in an unbiased manner, and enables the study of each component of the RNA–protein complex separately . It does in OOPS . OOPS ca in OOPS ,73, and Arabidopsis [Recent discoveries have revealed that RBPs have various functions and have shown great implications for crop improvement ,74. For bidopsis , while tbidopsis . The aboArabidopsis (Among the ribonomic approaches available to identify RBPs ,51 in otbidopsis , leadingbidopsis  providedAs a result of the above-stated conventional and modern ribonomics approaches such as RIC, CLIP, PtRIC, XRNAX, PTex, and CARIC, a wide range of coding and non-coding RBPs have been identified ,55,65,73Why is the identification of RBPs is important? In short, RNA and protein interactions are everywhere in living organisms and play a role in changing the fate of cells by regulating gene expression. It is compulsory to understand the regulatory roles of transcriptome-wide RBPs. Methods such as XRNAX, RIC, CARIC, and OOPS should be prioritized in plants. RNA biologists could also complement the interactome capture technologies such as RIC, eRIC, and ptRIC  with the


DB-TPE) exhibits a strong, 19-fold fluorescence enhancement upon binding to a short CAG RNA, and the binding and fluorescence response was found to be specific to the overall RNA secondary structure with A·A mismatches. These promising analytical performances suggest that the probe could be applied in pathological studies, disease progression monitoring, as well as diagnosis of related neurodegenerative diseases due to expanded CAG RNA repeats.Fluorescent sensing of nucleic acids is a highly sensitive and efficient bioanalytical method for their study in cellular processes, detection and diagnosis in related diseases. However, the design of small molecule fluorescent probes for the selective binding and detection of RNA of a specific sequence is very challenging because of their diverse, dynamic, and flexible structures. By modifying a bis(amidinium)-based small molecular binder that is known to selectively target RNA with CAG repeats using an environment-sensitive fluorophore, a turn-on fluorescent probe featuring aggregation-induced emission (AIE) is successfully developed in this proof-of-concept study. The probe ( HTT gene encodes the toxic and aggregation-prone mutant huntingtin (mHTT) protein with an expanded polyQ tract translated from the expanded CAG repeats, and the accumulation of the mHTT protein will lead to neuronal cell death due to altered neural circuitry, mitochondrial dysfunction, transcriptional dysregulation, disrupted protein homeostasis, impaired protein degradation, and aberrant activation of stress responses . Th. ThDB2132 . Thin layer chromatography was performed on silica gel 60 F254 (Merck) and column chromatography was carried out using silica gel 60F (Silicycle), neutral or basic aluminium oxide Brockmann I (Acros Organics). Detailed synthetic procedures and characterization of all other starting materials are described in the 1H and 13C{1H} NMR spectra were obtained from a Brucker DPX 400 or Brucker DPX 500 spectrometer and signals were referenced to solvent residues. LC-MS analyses were performed on a UPLC-MS system with a Waters UPLC coupled to a 2489 UV/Vis detector and an ACQUITY QDa MS detector. High resolution ESI-MS data was obtained from a Waters Micromass Premier Q-ToF tandem mass spectrometer.All reagents were purchased from commercial suppliers  and used without further purification unless otherwise specified. All solvents were of analytical grade . Dried solvents were distilled over CaHDB-Res was carried out as follows. Under an argon atmosphere, a mixture of 3DB-N , Res-alkyne , and [Cu(CH3CN)4](PF6)  in DMSO (3 mL) was stirred at room temperature for overnight. The resulting mixture was purified by a neutral alumina column with CH2Cl2/MeOH (v/v = 8:2) as the eluent. Fractions containing the product was combined and concentrated using a rotary evaporator, to which a saturated HCl solution in dry EtOH (1 mL) was added. The mixture was stirred at room temperature for 3 h and centrifuged . The solution was decanted and the remaining solid was washed with dry EtOH (10 mL × 1) and dry diethyl ether (10 mL × 3). The orange-red solid obtained was dried under vacuum. Yield = 15 mg, 73%. 1H NMR : δ 8.27 , 7.99–7.95 , 7.95–7.91 , 7.78 , 7.54 , 7.17 , 7.13 , 6.85 , 6.28 , 5.35 , 4.62 , 3.57 , 3.26 , 2.96 , 2.84–2.78 , 2.56 , 2.38–2.34 , 2.06 , and 1.85 . 13C{1H} NMR : δ 188.3, 164.9, 164.6, 164.2, 151.9, 147.1, 146.6, 143.9, 136.6, 135.0, 134.8, 134.7, 133.0, 130.1, 130.0, 130.0, 126.4, 115.7, 106.9, 102.3, 63.3, 57.2, 56.7, 55.1, 44.6, 44.5, 42.3, 42.3, 42.2, 26.2, and 25.5. HR-ESI-MS (+ve) calculated for C34H42N10O3 [M+H]+ (m/z): 639.3514, found: 639.3504.Synthesis of DB-Dan was carried out as follows. Under an argon atmosphere, a mixture of 3DB-N , Dan-alkyne , and [Cu(CH3CN)4](PF6)  in MeCN/MeOH  was stirred at room temperature for overnight. Solvents were removed using a rotary evaporator, and the residue was purified by a basic alumina column using a gradient mixture of CH2Cl2/MeOH (v/v = 9:1 to 8:2) as the eluent. Fractions containing the product were combined and concentrated using a rotary evaporator, to which a saturated HCl solution in dry ethanol (1 mL) was added. The mixture was heated at 60 °C for 3 h, cooled to room temperature, and centrifuged . The solution was decanted and the remaining solid was washed with dry ethanol (10 mL × 1) and dry diethyl ether (10 mL × 3). The resulting solid was dried under vacuum to obtain the product as a pale-yellow solid. Yield = 20 mg, 21%. 1H NMR : δ 8.52 , 8.32 , 8.15 , 7.71 , 7.60–7.48 , 7.25 , 4.31 , 4.11 , 3.33 , 3.18 , 2.87 , 2.74 , 2.54–2.38 , 2.27 , 2.25 , 1.87 , and 1.75 . 13C{1H} NMR : δ 163.8, 157.3, 153.1, 146.0, 139.0, 138.6, 137.2, 131.1, 131.0, 130.9, 130.2, 129.1, 128.5, 128.4, 124.8, 124.3, 120.6, 116.3, 58.2, 57.6, 56.0, 45.8, 45.4, 42.9, 42.5, 42.2, 39.2, 27.6, and 27.3. HR-ESI-MS (+ve) calculated for C34H49N11O2S [M+H]+ (m/z): 676.3864, found: 676.3870.Synthesis of DB-TPE was carried out as follows. Under an argon atmosphere, a mixture of DB-alkyne , 3TPE-N , and [Cu(CH3CN)4](PF6)  in MeCN/MeOH/CH2Cl2  was stirred at room temperature for overnight. The solvents were removed using a rotary evaporator, and the residue was washed with dry diethyl ether (10 mL × 2). A saturated HCl solution in dry ethanol (1 mL) was added to the residue, and the mixture was heated at 60 °C for 3 h, cooled to room temperature, and centrifuged . The solution was decanted and the remaining solid was washed with dry ethanol (10 mL × 1) and dry diethyl ether (10 mL × 3). The resulting solid was dried under vacuum to a obtain the product as a yellow solid. Yield = 42 mg, 93%. 1H NMR : δ 8.39 , 8.03 , 7.16–7.01 , 7.01–6.88 , 5.58 , 4.59–4.37 , 3.72–3.55 , 3.53–3.39 , 2.94 , 2.90 , 2.39–2.28 , and 2.28–2.18 . 13C{1H} NMR : δ 165.1, 144.8, 144.7, 143.1, 141.5, 134.8, 132.9, 132.3, 132.2, 130.3, 128.9, 128.8, 128.7, 127.7, 127.7, 56.5, 43.9, 41.7, and 24.2. HR-ESI-MS (+ve) calculated for C47H53N9 [M+H]+ (m/z): 744.4497, found: 744.4494.Synthesis of DB-Res, DB-Dan, and DB-TPE in water were diluted to 10 μM with H2O and/or THF to the required THF/H2O ratios. DB-Res, DB-Dan, and DB-TPE were excited at 475 nm, 330 nm, and 300 nm, respectively. Synthetic RNAs, 6-CCrGG-(CAG) (5′-rGG CAG CAG CAG CAG CAG CAG CC-3′), 3-CCrGG-(CAG) (5′-rGG CAG CAG CAG CC-3′), and 3-CCrGG-(CUG) (5′-rGG CUG CUG CUG CC-3′) were purchased from Integrated DNA Technologies, and stock solutions at 100 μM were prepared by dissolving the RNA in UltraPure™ DNase/RNase-free distilled water. For measurements in the presence of RNA, RNA sample were diluted with water, heated at 95 °C for 2 min, and slowly cooled to room temperature and added to a sample solution containing 10 μM of the fluorescent probe in 20 mM MOPS buffer (pH 7.0) in the presence of 300 mM NaCl.Fluorescence spectra were recorded on an Edinburgh Instruments FS5 Spectrofluorometer equipped with a 150 W CW ozone-free xenon arc lamp and a Photomultiplier R928P detection unit with spectral coverage of 200–870 nm. Fluorescence studies were performed in quartz cuvettes of 1 cm path length and 1.5 mL cell volume, and double distilled water was used in all measurement. Stock solutions of dK) of DB-TPE towards 6-CCrGG-(CAG) was determined by non-linear curve fitting of the fluorescence data using the following equation:DB-TPE (10 μM), and Dissociation constant  derivatives have been designed and synthesized as potential fluorescent probes for CAG RNA based on the structure of DB213 . In partA or RNA ,23, smalA or RNA ,25. HoweA or RNA ,17,18. IA or RNA ,27,28,29A or RNA . 1H NMR, 13C NMR, HR-ESI-MS, and UV–Vis. Fluorescent properties of the probes in response to environment changes were evaluated to assess their applicability in fluorescent RNA sensing. DB-Res, DB-Dan, and DB-TPE in water/THF mixtures of various ratios and ionic strengths (from 3 mM to 3 M NaCl). For DB-Res, weaker fluorescence was observed when there is an increase in the percentage of THF, and a 7.5-fold decrease in the emission intensity at 574 nm was found at 90% THF when compared to that at pure water. The weaker emission can be explained by the formation of non-emissive aggregates of the probe when the solvent becomes more non-polar. Consistent with this, weaker fluorescence was also observed when solvent ionic strength increased, and there was a 3.2-fold decrease in fluorescence in the presence of 3 M NaCl. On the other hand, an increase in fluorescence, along with a blue shift of the emission maximum, was observed for DB-Dan upon increasing the THF percentage. At 90% THF, a 6.8-fold emission enhancement and a blue shift of the emission maximum by 41 nm (from 562 nm to 521 nm) was resulted, and these solvatochromic and fluorogenic effects are consistent with an ICT mechanism [DB-Dan at different ionic strengths. Consistent with the AIE effect of TPE, a 10 µM solution of the aqueous soluble, cationic DB-TPE in water was weakly emissive and can be ascribed to the rapid non-radiative decay due to intramolecular rotations of the phenyl units [DB-TPE upon addition of THF likely resulted in the aggregation of the probe and restricted the intramolecular rotations that activated the TPE emission. Compared to the emission intensity in the presence of 3 mM NaCl, a 24-fold increase in fluorescence was observed in the presence of 3 M NaCl, showing that the salting-out effect at high ionic strength can also trigger the AIE.All the three probes have been characterized by echanism ,32. No syl units ,34. Upon6-CCrGG-(CAG) RNA as a model of CAG repeats. Previous studies have shown that this particular sCAG RNA will form a hairpin structure in solution with which DB213 can selectively bind with a strong affinity (Kd = 3.8 µM) [6 RNA for DB-Res and DB-Dan, suggesting that the change in the local environment upon binding may not be significant enough to result in an obvious fluorescent response. On the contrary, a 19-fold emission enhancement of DB-TPE was observed under the same condition, suggesting that the AIE probe has a promising analytical potential for CAG RNA.Fluorescence response of the probes was further tested using a synthetic RNA with the sequence  3.8 µM) ,35. FluoDB-TPE towards the (CAG)6 RNA was studied in more details. 6 RNA increased from 0.05 eq. to 1 eq. Binding strength of DB-TPE to the (CAG)6 RNA was obtained from the fluorescence titration data, and a Kd of 2 µM was found by fitting the binding isotherm to a 1:1 binding model. The Kd of DB-TPE is comparable to that of the binding of DB213 to the same (CAG)6 RNA, suggesting that both bis(amidinium) compounds share a similar binding mode that targets the major groove and overall secondary structure of the sCAG RNA with A·A mismatches in the hairpin structure. Consistent with this, a much weaker fluorescence, likely due to the non-specific electrostatic interactions between the cationic bis(amidinium) and anionic nucleic acid, was observed when the sCAG RNA was denatured by urea (3-CCrGG-(CAG) and 3-CCrGG-(CUG) with complementary A·U pairs  fluorescence enhancement upon binding to sCAG RNA with an apparent Kd of 2 µM. Comparative fluorescence studies showed that DB-TPE binds and reports the presence of sCAG RNA with a specific secondary structure. With this promising analytical performance, DB-TPE not only could be employed in the sensitive detection of CAG RNA for diagnostic applications of CAG repeats-related neurodegenerative diseases, but may also allow for the real-time monitoring of the CAG RNA for further understanding of the disease in cell models. Further works on applying the probe in biological samples and specimens are currently underway in our laboratory. In summary, a fluorescent turn-on probe that selectively binds to sCAG RNA with a strong fluorescence enhancement is successfully developed. Despite the various challenges in specific RNA recognition due to their dynamic structures, by using tetraphenylethylene as an AIE-active fluorophore to decorate


Large gaps in reef distribution may hinder the dispersal of marine organisms, interrupting processes vital to the maintenance of biodiversity. Here we show the presence and location of extensive reef habitats on the continental shelf between the Amazon Reef System (ARS) and the Eastern Brazilian Reef System (ERS), two reef complexes off eastern South America. Formations located 20–50 m deep include both biogenic and geogenic structures. The presence of diverse reef assemblages suggests the widespread occurrence of rocky substrates below 50 m. These habitats represent an expansion of both the ARS and ERS and the closure of the only remaining large-scale gap (~ 1000 km) among West Atlantic reef environments. This indicates that the SW Atlantic harbors a single, yet heterogeneous, reef system that stretches for about 4000 km, and thus, represents one of the largest semi-continuous tropical marine ecosystems in the world. Along the South Atlantic Ocean two main reef systems have been recognized to date: the Eastern Brazilian Reef System (ERS), which comprises shallow-water (< 30 m depth) and mesophotic (30–150 m) reefs along Brazil's eastern continental shelf4; and the Amazon Reef System (ARS), encompassing mesophotic and rariphotic (30–220 m depth) ecosystems located on the Brazilian Equatorial Margin10  is the Brazilian semi-arid coast (SAC)34. Biological and geological characterizations of these substrates are only beginning, but many sustain a diverse reef-associated biota , which play an important role in the economy and ecology of the region37. Furthermore, there are similarities between the SAC hard substrates and the biogenic reefs from the ARS and ERS38.Nevertheless, in the past decade a growing number of studies have reported the occurrence of hard substrates in this region, located from the intertidal zone to tens of meters below the surface40. In this context, the North Brazil Current (NBC), which flows northwestward off shelf, has surface velocities around 60–100 cm s−141 , thus confirming the occurrence of biogenic reefs along the SAC , black groupers (Mycteroperca bonaci), nurse sharks (Ginglymostoma cirratum) and stingrays (Hypanus) were present in more than 90% of the fishing grounds and accounted for 60.8% of the total captured biomass. Their abundance, along with the diverse benthic assemblages, is a strong indication of the occurrence of consolidated reefal substrates along the SAC outer continental shelf.Despite the lack of detailed scientific descriptions, the outer SAC continental shelf is intensely fished for reef-fish species Fig. . Three aMontastraea cavernosa and Siderastrea spp.)  Fig. a,d and cp.) Fig. f. Reef fp.) Fig. a and thep.) Fig. d, have sp.) Fig. b,c. ThesXestospongia cf. muta, Agelas dispar, Aplysina fulva, Aplysina lacunosa, and Ircinia strobilina) and soft- and hard-bottom dwelling octocorals (such as Neospongodes atlantica) also appeared in these areas , Bodianus sp. and Halichoeres sp. (Labridae), Holocentrus adscensionis (Holocentridae), Lutjanus jocu (Lutjanidae), Mycteroperca sp. and Epinephelus sp. (Epinephelidae)  Fig. a–d.Figur2, and which is clearly aligned with ARS (to the west), possibly providing a bridge to ERS (to the east) along the equatorial margin of the SW Atlantic Ocean  and the geographic distances of ARS, SAC, ERS and other South American biogeographic regions  has particularities that should not be disregarded in ecological studies Table . Overall2 of the middle-to-outer continental shelf of the SAC. This discovery of a spatial connection between ARS and ERS implies that this should be regarded as a single and extensive reef system, stretching for about 4000 km along the east coast of South America.The available data confirm that reefal seascapes associated with hard-bottoms are extensive and semi-continuous along 34.000 km29. Therefore, new reef areas along the SAC must be surveyed and validated, especially close to the shelf break. In addition, the shallower (< 10 m) and western sectors of the SAC continental shelf are generally more turbid33 and therefore more difficult to map with remote sensing techniques. The use of high spectral, spatial, and temporal resolution data, in addition to statistical methods and direct underwater assessments  are essential to refine our initial estimates of the reef distribution.The mapping and physical characterization of this reef system should be improved in future studies. Due to the limited penetration of light into water, analyzes based on satellite data are normally restricted to underwater features located no more than 40 m deep30 and limestones with well-developed coral communities 46. The only study that quantified the benthic cover on one of these formations32, a rocky plateau at 23 m depth, reported that live corals and calcareous algae covered 9.2% (4.6% each) of the substrate. This number is within the range commonly observed in Brazilian biogenic reefs56. However, maybe except for the mostly organic Açu reefs, it is generally not known how much these bioconstructors contribute to the framework of the SAC habitats. Therefore, ecosystems that develop on these hard substrates seem to range from deep and low-lying marginal biogenic reefs58 to non-framework building communities58, including coral grounds and carpets60 which can be regarded as an integral part of the reef system along the SAC. At the same time, the prevalence of biogenic versus geogenic formations should be reassessed throughout the entire South American reef system.The geological composition of SAC hard-bottom formations is uncertain, but, as we have shown here, include sandstones cemented by calcium carbonate (i.e. beachrocks)61. The dominant taxon in these surveys was Porifera, which accounted for 90% of the total wet weight, especially due to the species Agelas dispar, Ircinia strobilina, Leucascus sp. and Monanchora arbuscula. Ascidians were the second most abundant group, with the species Stomozoa gigantea alone representing 5% of the total wet weight, followed by Cnidaria (3% of the biomass) and Bryozoa (2% of the biomass)61. Previous studies have shown that such assemblages are associated with the occurrence of geoforms, including reefs and associated habitats62. Additionally, similar biotic communities were found in the deeper zones of the eastern Brazilian continental shelf  and are also linked to the occurrence of mesophotic reef habitats63. Therefore, the presence of these assemblages is a strong indication of the occurrence of yet unmapped hard-bottom environments along the SAC, especially in the outer continental shelf.Outside the alignment of rocky-bottom habitats between 20 and 40 m deep, numerous localities along the SAC continental shelf support diverse epilithic biotas. For example, trawls made at mesophotic depths revealed a high species richness and biomass of reef benthic organisms, with biodiversity apparently increasing with depth46. In fact many formations along the ARS10 and ERS64 are flat and largely covered by marine sediment. Consequently, these relatively flat habitats seem to be another important component of the South American reef system, particularly at mesophotic depths64. Due to their apparent ubiquity across ARS, SAC and ERS, these mesophotic environments may form an extensive ecological corridor along most of the SW Atlantic coast.Habitats deeper than 40 m explored using ROV data show a relatively flat seascape and hard substrates can only be inferred from the presence of epilithic biotas. Such flat seascapes are not typical of reef environments, which, by definition, have three-dimensional profiles. Nevertheless, ROV data is localized, and sandy and rocky flats are a known feature of reefs along the SAC2, this reef system forms a seascape with other habitats, such as rhodolith beds, seagrass and seaweed meadows, marine animal forests, and unconsolidated sediment deposits65. Data on the structure and functioning of these ecosystems is scarce, but the few available comparisons, both from within and outside the SAC, indicate important differences in terms of species composition and ecological dynamics66. The recognition of these particularities is essential for the adequate management and conservation of these habitats. In parallel, the SAC reef system and neighboring habitats are all equally under the energetic oceanographic conditions across the equatorial Brazilian shelf67. As such, some of these environments may even be subject to seasonal cycles of burial and exposure, due to the transport of unconsolidated sediments and possible migration of subaqueous sand ripples and dunes69. This may explain why some of the hard-bottom habitats are dominated by few stress-tolerant and weedy reef-building corals adapted to sedimentation and moderate turbidity, such as M. cavernosa and Siderastrea spp.60.Therefore, at a broad spatial scale, the SAC continental shelf harbors an extensive network of different types of consolidated substrates, which form a complex and heterogeneous reef system. Furthermore, much like the ARS and ERS71. In this scenario, the SAC hard substrates effectively constitute stepping-stones between ARS and ERS, providing adequate substrates for at least some species, aiding larval dispersion, ontogenetic migration, and small-scale movements of adult animals, which are key processes connecting Western Atlantic reef systems73. It is noteworthy that both ARS and SAC reefs are typically composed of subsets of the Tropical Atlantic biota, as their environmental conditions seem to be challenging for many coral reef species confined to either the ERS or Caribbean. Nevertheless, the spatial connection provided by the SAC may help to explain the biogeographical affinities observed in previous studies among SW Atlantic reef species, including sponges74, corals75, anemones76, gastropods77, and reef fish78. Furthermore, a multi-taxa study with reef organisms reports a relatively low beta diversity and high nestedness among Brazilian biogeographical provinces, suggesting considerable interconnectivity along the South American reef system51.Due to their large spatial and depth distribution, the hard-bottom formations along the SAC connect ARS and ERS. Together, these reef systems may also link the Caribbean and Brazilian biogeographic provinces. Hence, recognizing the presence and extension of the SAC hard bottoms implies closing the only remaining broad scale gap among Western Atlantic reef habitats. This physical connectivity is mediated by the shelf currents and the NBC, both of which flow primarily from east to west Fig. . However45. Such human pressures are threatening the biodiversity of both shallow and mesophotic habitats and, thus, urgently require conservation and mitigation actions79. To be successful, such actions need to consider the biogeography and dynamics of metapopulations among SW Atlantic reefs, especially given the wide spatial distribution of such habitats78. Further study is urgently required to characterize the ecological dynamics of these tropical reef habitats at multiple spatial and temporal scales in order to sustainably maintain the numerous ecosystem services provided.The connectivity between ARS and ERS provided by the SAC may affect the resilience of the SW Atlantic reefs against environmental and anthropogenic stressorsUniversidade Federal do Ceará, Universidade Estadual do Ceará, Universidade Federal do Rio Grande do Norte, and Universidade Federal de Pernambuco), governmental agencies , and all-purpose search engines . Search terms included combinations of “reef”, “beachrock”, “continental shelf”, “Northeast Brazil”, “fisheries”, “fishing grounds”, “corals”, “octocorals”, and “sponges”, with their respective Portuguese translations  location of known hard-bottom habitats—i.e. rocky substrate topologically distinct from the surrounding sediment deposits, (b) occurrence of sponge, scleractinian or octocoral assemblages typical of hard-bottom habitats recorded by trawling or other indirect methods, and (c) coordinates of fishing grounds used to catch reef fishes, whose bottoms had not been characterized, but which may include reefs, marine animal forests, and rhodolith beds. The literature survey included publications in English and Portuguese, but only primary data sources were considered . A relevant proportion of the data was only available through gray literature, so we focused on institutional repositories of Brazilian universities  were performed to assess the occurrence of sponges and corals  along the SAC continental shelf, particularly near the shelf break (Supplementary Table 78) closer to the shelf break. The fishing campaigns targeted exclusively mesopredators and predators, particularly of the Lutjanidae and Epinephelidae families, and elasmobranchs. Therefore, these data do not represent the entire fish diversity on the SAC outer continental shelf. Nevertheless, the eventual occurrence of typical reef-fish assemblages should reflect the distribution of hard-bottom environments63, thus meeting the objectives of the present study.This literature survey was complemented by new information produced during this study. Surveys of scientific collections’ databases  and western sectors of the SAC continental shelf had higher sediment inputs and resuspension29, and thus were more difficult to map with satellite images.Based on these published and unpublished data, submerged rocky substrates were mapped using satellite imagery and bathymetric data. Landsat 8 (OLI sensor) and Landsat 5 (TM sensor) digital images were processed  through bands 1 and 2 (0.45–0.52 µm), and RGB compositions (4-3-2 and 4-2-1) were produced to highlight the occurrence and distribution of hard substrates. Bathymetric contours were created to corroborate and complement satellite information, using bathymetric data from the Brazilian Navy (DHN), retrieved form board pages  and nautical charts . Owing to the clear oceanographic conditions along most of the tropical Brazilian coast, satellite data can be used effectively to map submerged reefs and other hard-bottom habitatsGround-truthing of compiled data was performed for selected reef formations by Scuba diving and Remotely Operated Underwater Vehicle (ROV) assessments  for 8375 species  distributed across six marine ecoregions encompassing the Brazilian, Guianan, and Caribbean coasts50. Both datasets were originally used to identify and describe connections among marine biogeographical regions along their studied coastlines, mainly through cluster analysis and the construction of dendrograms. In the present study, to highlight the interconnections among reef systems, we opted for an ordination analysis. A Sammon mapping80, which is similar to a Multidimensional Scaling putting emphasis on the neighborhood of points, was used to visualize the data. Additionally, we have superimposed a minimum spanning tree, constructed with Prim’s algorithm81, on the Sammon mapping to aid the visualization of connections. Variations of minimum spanning trees have been used in biogeography to investigate putative historical pathways of connection among marine areas53. Considering the mostly unidirectional flow of oceanic and shelf currents along ERS, SAC and ARS the minimum spanning tree should also be able to reflect the interconnection among reef systems in a parsimonious way. The ordination analyses and the algorithm for the minimum spanning trees were executed in R 4.1.2, with packages vegan and MASS.To investigate possible interconnections among ARS, SAC and ERS we re-analyzed two recently published datasets on the distribution of marine species along the tropical SW Atlantic coastSupplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.