CRISPR‐Cas systems are a form of prokaryotic adaptive immunity that employs RNA‐guided endonucleases (Cas effectors) to cleave foreign genetic elements. Due to their simplicity, targeting programmability, and efficiency, single‐effector CRISPR‐Cas systems have great potential for application in research, biotechnology, and therapeutics. While DNA‐targeting Cas effectors such as Cas9 and Cas12a have become indispensable tools for genome editing in the past decade, the more recent discovery of RNA‐targeting CRISPR‐Cas systems has opened the door for implementation of CRISPR‐Cas technology in RNA manipulation. With an increasing number of studies reporting their application in transcriptome engineering, viral interference, nucleic acid detection, and RNA imaging, type VI CRISPR‐Cas systems and the associated Cas13 effectors particularly hold promise as RNA‐targeting or RNA‐binding tools. However, even though previous structural and biochemical characterization provided a firm basis for leveraging type VI CRISPR‐Cas systems into such tools, the lack of comprehension of certain mechanisms underlying their functions hinders more sophisticated and conventional use. This review will summarize current knowledge on structural and mechanistic properties of type VI CRISPR‐Cas systems, give an overview on the reported applications, and discuss functional features that need further investigation in order to improve performance of Cas13‐based tools. Class 2 type VI CRISPR‐Cas systems are characterized by Cas13 effector proteins that exclusively cleave single‐stranded RNA. This review article summarizes current knowledge on structural and mechanistic properties of type VI CRISPR‐Cas systems, gives an overview on reported applications of Cas13‐based tools, and discusses functional features that need further investigation in order to improve their performance. Adjoining the CRISPR array are multiple genes encoding CRISPR‐associated (Cas) proteins. Cas proteins perform different tasks in the three phases of CRISPR‐Cas‐driven immunity: adaptation, CRISPR RNA (crRNA) biogenesis, and interference. During the adaptation phase, Cas1 and Cas2 select and modify segments of foreign nucleic acids (termed protospacers), eventually adding them to the CRISPR array. Upon subsequent infection, spacers are transcribed along with the rest of CRISPR array into a long precursor crRNA (pre‐crRNA). pre‐crRNA is then processed either by Cas effectors or other endogenous endonucleases into mature crRNAs  containing a direct repeat and a spacer sequence. Some systems also require a second small RNA known as transactivating crRNA, which binds with crRNA to form functional gRNA. gRNAs are then used by Cas interference module as a template that guides the effector to cleave complementary nucleic acid sequences in MGEs, thereby curbing infection.CRISPR‐Cas systems are adaptive immune systems that protect bacteria and archaea against phages and other invasive mobile genetic elements (MGEs).3, 4 Currently known CRISPR‐Cas systems can be grouped into class 1 and class 2 systems, which are further divided into types and subtypes. Class 1 CRISPR‐Cas systems  utilize a wide assortment of smaller Cas proteins to form a multi‐subunit interference complex. By contrast, class 2 systems  use a single, comparatively larger Cas effector protein for interference and, in certain cases, crRNA biogenesis.The unceasing arms race between prokaryotes and MGEs has led to evolutionary development of a great variety of CRISPR‐Cas systems.19 Cur Engineered and certain naturally occurring variants of Cas9 have also been used for RNA targeting and binding, thus initiating the use of CRISPR‐Cas technology in RNA manipulation and potentially advancing this field by overcoming limitations of conventionally used RNA‐targeting methods. However, the fact that Cas9 also retains its ability to target DNA involves risk from undesired off‐target effects on genes. Moreover, Cas9 effectors may not necessarily be efficient in all RNA‐targeting applications, so expanding the CRISPR‐Cas toolbox with new and diverse effectors would allow greater flexibility and more sophisticated RNA manipulation.In the years following the discovery of Cas9, the DNA‐targeting type II and type V CRISPR‐Cas effectors have been successfully harnessed for a variety of applications in genome editing and nucleic acid detection.33 Eng Four subtypes (A–D) have been identified to date, of which subtypes VI‐A, VI‐B, and VI‐D have been functionally characterized along with respective effectors, i.e., Cas13a, Cas13b, and Cas13d  domains that mediate ssRNA cleavage. As opposed to Cas9 that specifically cleaves crRNA spacer‐complementary dsDNA sequences  in cis, the activated Cas13‐crRNA interference complex cleaves nonspecifically both the crRNA‐bound complementary ssRNA sequence (henceforth referred to as activator RNA) in cis and any other encountered RNA  in trans   or adenosine (A)  have been discovered.40 Fou) Figure . Currently known Cas13a orthologs are grouped into two subfamilies (U‐cleaving and A‐cleaving) based on their cleavage preferences and the aforementioned functional exchangeability of noncognate crRNAs. Activation of ssRNA cleavage appears to be restricted, at least for certain orthologs, by a 3′‐H (non‐G) protospacer flanking sequence (PFS). Pre‐crRNA processing is not a prerequisite for RNA interference, but enhances the activity by releasing crRNAs from CRISPR array, thus allowing optimal use of individual crRNA guide sequences.Cas13a is a large protein (>1000 aa) and currently the most well‐understood type VI effector. Its primary sequence lacks appreciable similarity to other known Cas effectors.37 Cur2.1Leptotrichia shahii Cas13a (LshCas13a), (2) binary and ternary complex of the U‐cleaving Leptotrichia buccalis Cas13a (LbuCas13a), and (3) binary complexes containing pre‐crRNA/crRNA of the A‐cleaving Lahnospiraceae bacterium Cas13a (LbaCas13a).To date, several structures of Cas13a homologs and their complexes with crRNA and/or activator RNA have been reported: (1) apo protein and binary complex of the U‐cleaving hCas13a),52 (2)α‐helical and comprises two lobes, namely, the crRNA recognition (REC) lobe and the nuclease (NUC) lobe. However, its structure highly differs at architectural and domain organization level  lobe.54 Howl Figure . The RECl Figure ,B. The Nl Figure ,B. HEPN‐2.2 All of these subregions have distinct subfamily‐specific characteristics in terms of sequence, length, and conformation, and therefore cannot be used interchangeably between the two Cas13a subfamilies. For instance, one crucial distinction between crRNA repeat regions is the sequence of the dinucleotide bulge, which reads AC in the U‐cleaving systems and AA in the A‐cleaving systems. crRNA repeat region is generally intolerant to most sequence modifications, including base changes, altering the length of the stem region, inversion of the stem‐loop sequence and shortening of the loop. Single mutations of the dinucleotide bulge or interacting residues abolish both RNA cleavage and pre‐crRNA processing, which underscores the importance of the dinucleotide bulge in crRNA recognition and thereby both RNase activities of Cas13a.Repeat region of mature type VI‐A crRNAs (often referred to as 5′ handle) adopts a comparatively simple structure divided into a stem‐loop with a 3′ dinucleotide bulge, a 5′ and a 3′ single‐stranded flanking region Figure ,D.534 Cas13d was discovered by further improving the search strategies of previous computational pipelines and expanding the search to smaller effectors. Outside the two HEPN domains, the primary structure of Cas13d bears little overall similarity to other type VI effectors and shows only distant relation to Cas13a. Nevertheless, its ternary structure bears close resemblance to Cas13a effectors , which makes it useful for application in broad range of hosts. Moreover, most of the VI‐D loci have an adjacent WYL domain‐containing accessory protein that augments ssRNA cleavage in a dose‐dependent manner. The reported structure of Ruminococcus sp. WYL1 (RspWYL1) accessory protein provides insights into mechanisms underlying specific binding of ssRNA substrates by WYL1 and modulation of Cas13d activity.Like other Cas13 effectors, the bipartite HEPN motif‐mediated RNase activity of Cas13d relies on the presence of spacer‐complementary activator RNA and Mg2+ ions.40 Cas4.1Eubacterium siraeum Cas13d (EsCas13d) and high‐resolution binary structure of uncultured Ruminococcus sp. Cas13d (UrCas13d or RspCas13d) show that Cas13d roughly adopts bilobed architecture reminiscent of larger class 2 effectors  a pentahydrated Mg2+ ion located at the center of the U‐shaped turn formed by the 3′ nucleotides of the crRNA repeat region   Interaction between Cas13d and spacer region is maintained mostly through sugar‐phosphate backbone and is responsible for stabilizing the spacer conformation and arranging it for activator RNA binding.In the binary complex, the crRNA spacer region adopts a conformation with three U‐shaped turns.67 Int4.3 Concurrently, new interactions between Cas13d  and phosphate backbones of crRNA spacer and activator RNA are formed. Mutating conserved Cas13d residues that contact crRNA and activator RNA abolishes ssRNA cleavage, implying importance of Cas13d‐mediated stabilization of the crRNA‐activator RNA duplex for HEPN nuclease site activation.Upon activator RNA binding, the spacer abolishes most of its previous interactions with Cas13d and reorganizes to form a double‐stranded A‐form RNA helix with activator RNA.67 Con Activation of the HEPN nuclease active site is strongly interlinked with activator RNA binding, with minimum of 18‐nucleotide strict complementarity required for partial conformational rearrangement of Cas13d, 18–20‐nucleotide complementarity for half‐maximal cleavage activity, and >21‐nucleotide complementarity for optimal cleavage activity . The Cas13d crRNA spacer was initially thought to lack a clear seed region. However, studies on UrCas13d suggest that two distinct regions of UrCas13d crRNA spacer, namely the internal region (spacer nucleotides 5–8) and 3′‐end region (spacer nucleotides 13–22), are intolerant to mismatches with activator ssRNA and abolish ssRNA cleavage  was systematically tested for mismatch intolerance, and the spacer region between nucleotides 15–21 with center at nucleotide 18 was found to be most susceptible to mismatches, whereas nucleotides of the internal region were more tolerant to mismatches. Thus, currently available data indicates the presence of a highly mismatch‐intolerant region within central–3′ spacer nucleotides and an internal region whose mismatch tolerance presumably varies in ortholog‐dependent manner.During transition from binary to ternary complex, Cas13d undergoes numerous conformational changes to accommodate the target RNA in the positively charged channel and reconfigure the bipartite HEPN nuclease active for cleavage of ssRNA.67 Acte Figure .[66]5 This article will give an overview of the reported applications, their principles and drawbacks before discussing possible strategies for optimizing efficiency and safety of the Cas13‐based tools.In the years following their discovery, biochemical and structural characterization, type VI CRISPR‐Cas systems have attracted much attention because of efficient, highly specific, and programmable RNA‐targeting properties and autonomous pre‐crRNA processing. Transcriptome editing by Cas13 effectors also has important advantages over CRISPR‐based genome editing: it is safer because of its transient and reversible nature, and the extent of editing is dose‐dependent and can be modulated to suit various purposes. In addition, type VI CRISPR‐Cas systems exhibit collateral ssRNA cleavage activity in bacteria and in vitro, which can be utilized for diagnostic applications. Thus, an increasing number of studies have aimed to develop type VI CRISPR‐Cas systems into tools for basic research, biotechnology, and therapeutics. Most of these studies have recently been extensively reviewed and compared to other RNA‐targeting tools elsewhere.79 Thi5.1 Recent studies, however, show that type VI CRISPR‐Cas systems can overcome these barriers and provide new strategies for RNA manipulation  to the hyperactive mutant of deaminase domain of ADAR2 (adenosine deaminase acting on RNA 2) to develop a tool termed REPAIRv2 (RNA editing for programmable A to I replacement version 2) that can be packaged into adeno‐associated viral (AAV) vector for cell delivery. Accompanied with crRNA sequence targeting the gene of interest, REPAIRv2 conducts reversible and directed adenosine‐to‐inosine (A‐to‐I) edits on RNA transcripts; since inosine mimics guanosine in translation and splicing, REPAIRv2 can be used to study or treat disease‐relevant G to A mutations. Further engineering of REPAIRv2 aimed at relaxing substrate preferences of ADAR2 deaminase domain yielded a new tool termed RESCUE (RNA editing for specific C to U exchange), which is capable of carrying out cytidine‐to‐uridine (C‐to‐U) conversions while retaining the original adenosine deaminase activity. Although both REPAIRv2 and RESCUE exhibit high specificity , their current efficiency (up to 30% of on‐target A‐to‐I edits by REPAIRv2 and ≈76% of on‐target C‐to‐U edits by RESCUE) still has room for improvement.In one of the earliest reports on Cas13 application, Cox et al. linked C‐terminally truncated catalytically inactive delivery.42 AccLeptotrichia wadei Cas13a (LwaCas13a), which solves the problems observed with methods based on RNAi or antisense nucleotides, such as poor specificity, off‐target effects, and ambiguity in assigning phenotypes to a single lncRNA. In the assay, a library of K562 chronic myeloid leukemia cells stably expressing LwaCas13a and a unique crRNA targeting one of lncRNA transcripts was exposed to cancer drug‐induced cellular stress, after which the roles of the studied lncRNAs in K562 cell viability were inferred from depletion or enrichment of each crRNA in the assayed cell population.Xu et al. established the first high‐throughput phenotypic assay for functional studies of long noncoding (lnc) RNAs using e lncRNA.81 In  Although efficient and robust methods such as cross‐linking immunoprecipitation sequencing and RNA immunoprecipitation sequencing are broadly applied to identify RNAs bound to proteins of interest, currently available methods for detection of proteins bound to a specific RNA have severe limitations, including nonspecific binding and inability to detect weaker or transient interactions. To overcome these limitations, two Cas13‐based methods have recently been developed for the RNA‐centered study of RNA–protein interactions under natural conditions. The first method, termed CRUIS (CRISPR‐based RNA‐united interacting system), employs catalytically inactivated LwaCas13a (dLwaCas13a)‐crRNA module to bind the RNA of interest, after which the bacterial ligase proteasomal accessory factor A (PafA) fused to dLwaCas13a ligates the small protein prokaryotic ubiquitin‐like protein PupE to RNA‐bound neighboring proteins. The second method uses dRfxCas13d fused with (1) the double‐stranded RNA‐binding domain from human protein kinase R that would enhance and stabilize binding to targeted RNA after initial recognition by the dRfxCas13d‐gRNA and (2) the modified plant peroxidase APEX2 which catalyzes 1 min promiscuous biotinylation of transiently interacting proteins for proximity labeling. The two methods were successfully used to identify new endogenous interacting partners of the noncoding RNA activated by DNA damage (NORAD) and human telomerase RNA, respectively. It should be noted that careful design and screening of gRNAs is required for these two methods to find appropriate targeting sites within RNA of interest, as secondary RNA structure and possible steric hindrance caused by the size of Cas13 effectors may negatively affect target RNA binding and/or detection of some interacting proteins.Mapping RNA–protein interactions is essential for better understanding of various cellular processes.82 Alt Among investigated Cas13 effectors, RfxCas13d was found to efficiently and precisely disrupt maternal and zygotic gene function in zebrafish embryos without inducing toxicity, developmental abnormalities, direct off‐target or collateral cleavage effects. The study also demonstrated that coinjection of RfxCas13d protein and gRNAs can further accelerate knockdown of targeted maternal mRNA in dose‐dependent manner and provide more penetrant phenotypes. The established technique can be effectively used in other vertebrate embryos, including those of medaka, killifish, and mouse. In another study related to model organisms, Jing et al. showed that type VI CRISPR‐Cas systems can be used for RNA knockdown and single‐base RNA editing in the fission yeast Schizosaccharomyces pombe, an important model organism used for studying cellular mechanisms conserved from yeast to humans.Type VI CRISPR‐Cas systems also have considerable potential for implementation in research on various model organisms. Aiming to establish a cost‐efficient and robust technique that would circumvent cytotoxic and off‐target effects of the commonly used morpholinos, Kushawah et al. recently assessed the utility of type VI CRISPR‐Cas systems in studying gene function in early development of teleost embryos.85 Amo Later, Zhao et al. showed that Cas13 effectors can also be considered for therapeutic knockdown of oncogenes for which the use of small molecule inhibitors has thus far proven unsuccessful. Programmed by crRNA to specifically target oncogenic kirsten rat sarcoma virus (KRAS) mutant and not wild‐type KRAS mRNA transcripts, LwaCas13a efficiently decreased levels of mutant KRAS mRNA, inducing cell apoptosis in pancreatic cancer cells and tumor shrinkage in mice with pancreatic cell xenografts. Furthermore, He et al. delivered active RfxCas13d to mouse liver for simultaneous and reversible knockdown of RNA transcripts associated with metabolic regulation, thus laying the groundwork for the use of type VI CRISPR‐Cas systems in treatment of metabolic diseases.To investigate one potential therapeutic application, Konermann et al. delivered dRfxCas13d to cells via AAV vector to manipulate pathological alternative splicing of tau pre‐mRNA in a neuronal model of frontotemporal dementia.39 Lat6‐methyladenosine (m6A), a form of reversible and selective posttranscriptional methylation of adenosine residues that influences alternative splicing, conformation, expression, translation, and degradation of mRNA transcripts. The effects of m6A modifications on mRNA are mediated by m6A reader, writer, and eraser proteins. Previous transcriptome‐wide m6A mappings suggest that distribution and pattern of m6A modifications are dynamic and associated with cell differentiation and various diseases such as cancers; however, the lack of appropriate tools and methods has hitherto hindered deeper understanding of involvement of m6A‐mediated epitranscriptome regulation in cellular processes and diseases. To study m6A regulation on individual RNA transcripts, Rauch and Dickinson recently designed a protocol in which dCas13b effectors fused to the functional output domains of the m6A reader proteins YTH domain‐containing family protein 1 and 2 (YTHDF1 and YTHDF2) were transfected to cells along with crRNA targeting methylated sites in RNA transcript of interest, followed by assessment of protein levels with dual luciferase assay or RT‐qPCR for evaluation of RNA levels. In another study, the m6A eraser protein RNA demethylase alpha‐ketoglutarate‐dependent dioxygenase homolog 5 (ALKBH5) was linked to the C‐terminus of dPspCas13b. When combined with gRNA, the dPspCas13b‐ALKBH5 fusion protein (named dm6ACRISPR) successfully demethylated targeted mRNA transcripts containing single or multiple m6A sites in human cell culture with low off‐target effects. dm6ACRISPR was also used to target m6A‐modified transcripts of the oncogenes EGFR and MYC, which suppressed proliferation of HeLa cells and demonstrated that dm6ACRISPR can be applied in gene repression and regulation of cellular functions. In the third study, Zhao et al. developed a photoactivable RNA m6A editing system using CRISPR‐dCas13 (PAMEC) that includes two main components: (1) an RNA anchor probe consisting of the catalytically inactive Porhyromonas gulae Cas13b (dPguCas13b) fused to CIBN, a truncated variant of the light‐sensitive protein calcium‐ and integrin‐binding 1 (CIB1) that mediates light‐dependent interaction with the photylase homology region of the cryptochrome circadian regulator (CRY2PHR), and (2) an m6A effector probe consisting of CRY2PHR fused to either m6A demethylase fat‐mass and obesity‐associated protein (FTO) for m6A erasure or the METTL3‐METTL14 m6A methyltransferase complex for m6A writing. The system enables efficient and robust m6A editing in cells illuminated by blue light, and it has been further optimized by adding an MS2 aptamer at 3′ end of crRNA for increased efficiency and by coupling it with an upconversion nanoparticle film for deep tissue m6A editing. Considering significant attention that has lately been given to research on m6A‐mediated epitranscriptome regulation and promising prospects of Cas13 effectors, it is likely that even more Cas13‐based tools fused to various m6A reader/writer/eraser proteins will be developed in the near future.In addition to transcriptome manipulation, Cas13‐based tools can also be used for studying and therapeutic regulation of epitranscriptome. One of the most prominent and abundant mRNA modifications is the Nnscripts.89 The5.2 SHERLOCK uses a Cas13‐crRNA module that, once activated by a strictly complementary activator RNA from tested sample, promiscuously cleaves quenched fluorescent reporter RNA molecules at high turnover rate, thus generating a detectable and quantitative fluorescent signal  and adapted the platform for convenient visual readout of results on a lateral flow strip. SHERLOCK has been applied in diagnostics of viral infections, including COVID‐19, cancer mutations, health‐related single nucleotide polymorphisms (SNPs), and genetic traits in plants. The utility of SHERLOCK as a cheap and reliable tool for diagnosing COVID‐19 was recently evaluated on a larger scale in a clinical study conducted in Thailand. Validated on 154 clinical COVID‐19 samples, SHERLOCK exhibited 100% specificity and high sensitivity with both in‐tube fluorescence and lateral flow readouts , successfully detected asymptomatic cases and its results were in full concordance with those from the commonly used RT‐PCR tests. SHERLOCK has also been adapted for simple, fast, and cheap monitoring of graft rejection and opportunistic infections by cytomegalovirus and BK polyomavirus in kidney transplant patients. Available in form of qualitative lateral‐flow readout that can be evaluated by a smartphone‐based software, the test enables frequent and personalized point‐of‐care testing for early prevention of post‐transplantation complications.By harnessing the collateral cleavage activity and stringent crRNA‐activator RNA complementarity requirements of type VI CRISPR‐Cas systems, Gootenberg et al. designed a rapid, cheap, and ultrasensitive portable nucleic acid diagnostic platform named SHERLOCK (specific high‐sensitivity enzymatic reporter unlocking).43 SHE SHINE uses optimized protocol for HUDSON to speed up viral inactivation in nasopharyngeal swabs and saliva samples and combines the recombinase polymerase amplification, T7 transcription, and Cas13‐mediated detection steps of SHERLOCK into a single‐step reaction, thereby reducing time for obtaining COVID‐19 test results to ≈50 min while maintaining 100% specificity and 90% sensitivity compared to RT‐PCR tests. In addition to lateral flow readout, SHINE test results can be visualized via in‐tube fluorescent readout and interpreted by a smartphone application to avoid sample contamination and user bias.As the COVID‐19 pandemic highlighted the need for faster and less labor‐intensive diagnostic tools with minimal equipment usage, SHERLOCK was recently further simplified into the diagnostic platform termed SHINE (SHERLOCK and HUDSON integration to navigate epidemics).95 SHI Among these tools, CARMEN  should be noted for its capability to perform large‐scale simultaneous testing of multiple samples for diverse pathogens at species, strain and SNP level—a feature particularly valuable for surveillance of spreading and evolution of infectious diseases.Apart from SHERLOCK, other Cas13‐based diagnostic tools have been developed for various purposes, such as quantitative detection of microRNA or quantitative virus detection using automated microfluidic device.104 Am5.3 Although fluorescent tools such as molecular beacons, the MS2‐MCP system and fluorogenic RNA aptamers are available, their limitations make tracking individual RNA species in live cells difficult .Subcellular localization of RNA transcripts is spatiotemporally dynamic and directly associated with their function and fate.78 Altg Figure .[1065.4 Considering the importance of viral genome replication for completion of viral life cycle in host cells, viral inhibition through CRISPR‐Cas‐mediated degradation of highly conserved and essential genetic elements could potentially be used as cheaper and more efficient antiviral strategy. The efficacy and feasibility of this strategy was initially explored with CRISPR‐Cas9 systems, which hold considerable promise in curing chronic viral infections caused by viruses with characteristic latency state such as human immunodeficiency virus, hepatitis B virus, herpes viruses and human papillomavirus. However, ≈51%, 44%, and 70% of genera infecting humans, vertebrate animals, and plants, respectively, are ssRNA viruses that do not use DNA intermediates during their life cycles. Even though the RNA‐targeting CRISPR‐Cas9 systems can be used, the exclusively ssRNA‐targeting type VI CRISPR‐Cas systems are more suitable for targeting ssRNA viruses  are often hindered by costliness, long development time, and viral resistance that arises from high mutation rates.109 Co RfxCas13d also exhibits robust and specific antiviral activity against RNA viruses in plants, at which it outperformed LwaCas13a and PspCas13b in both transient and stable overexpression assays; in the study, RfxCas13d did not exert collateral cleavage effect in plants and was able to efficiently target two RNA viruses in parallel when crRNAs targeting both viruses were expressed in tested plants. Recently published protocol describing transient expression of LbuCas13a and cognate CRISPR array in Nicotiana benthamiana will allow more extensive research on potential application of type VI CRISPR‐Cas systems for antiviral defense in plants.The potential use of Cas13 systems in protecting plants against viruses was first demonstrated with LshCas13a, which was transgenically expressed in monocot and dicot plants to interfere with replication of economically important RNA viruses; LshCas13a maintained its pre‐crRNA processing activity in plants and did not cause cytotoxic effects.114 Rf The authors of the study coupled Cas13‐mediated virus targeting with SHERLOCK to create a comprehensive platform for diagnosis and treatment of viral diseases termed CARVER . In the wake of COVID‐19 pandemic and demands for alternative therapeutic approaches created by the lack of effective treatments and time required for vaccine development, Abbott et al. demonstrated the potential of Cas13‐based therapy in combating emerging viral diseases. Selecting RfxCas13d due to absence of PFS‐imposed cleavage restrictions, robust and highly specific RNA interference and its compact size that would facilitate packaging and delivery, the authors developed PAC‐MAN  strategy for inhibiting SARS‐CoV‐2 and influenza A virus, as well as the majority of other coronavirus and influenza virus strains, by simultaneously targeting multiple highly conserved viral genomic regions. The RfxCas13d‐based PAC‐MAN was shown to efficiently cleave SARS‐CoV‐2 RNA fragments and inhibit influenza A virus replication in human lung epithelial cell cultures, with greater inhibition at higher crRNA concentrations and lower viral titers. The results of the study indicated that PAC‐MAN could be effectively used for preventing new viral infections or as a complementary strategy along with traditional pharmaceuticals and vaccines.Antiviral properties of Cas13 have also been tested against high doses of three distinct ssRNA viruses in mammalian cell lines lacking functional innate immune system, displaying potent viral inhibitory activity without affecting cell viability.97 The Taking into account that delivery of Cas effector and gRNAs/CRISPR array via separate plasmids negatively affects targeting efficiency due to inconsistent expression levels of each component, the authors of the study also developed a single‐vector delivery system that facilitates multiplexed targeting and further increases interference levels.A variety of RNA viruses also infect domestic animals, thereby causing substantial economic losses. To investigate feasibility of repressing RNA virus infections in animals and humans with CRISPR‐Cas13b systems, Cui et al. used PspCas13b to target two essential genes of the porcine reproductive and respiratory syndrome virus in infected mammalian cells and almost completely inhibited viral gene transcription and expression.117 Ta Guided by two gRNAs targeting nsP2 or CRISPR array targeting multiple sites in viral genome, PspCas13b performed efficiently against both the chimeric luciferase reporter and the CHIKV split replication system and significantly reduced viral RNA expression. Interestingly, the two gRNAs targeting nsP2 were also capable of knocking down viral RNA in the absence of PspCas13b; further investigation indicated that addition of PspCas13b enhanced viral RNA knockdown when U6 promoter‐driven guides were used but did not increase suppression in cases when in vitro transcribed gRNAs were directly delivered to cells. Since this phenomenon has not been observed in mammalian and plant cells, it is likely specific for mosquito cells, possibly because insect cells are generally more reliant on endogenous RNA interference systems that could utilize gRNAs to target viral sequences independently of PspCas13b.In addition to potential application in targeting viruses in plants and mammals, type VI CRISPR‐Cas systems could also be used in mosquitoes for suppressing mosquito‐borne viral diseases such as dengue fever, chikungunya, and Zika. Tng et al. tested PspCas13b against a chimeric firefly luciferase reporter carrying the chikungunya virus (CHIKV) genomic sequence corresponding to the region encoding the nonstructural protein 2 (nsP2) and a CHIKV split replication system mimicking replication of viral RNA.118 Gu6Although previous structural and functional studies provided a firm basis for leveraging type VI CRISPR‐Cas systems into RNA‐targeting tools, certain mechanisms underlying the functions of Cas13 effectors are still not fully understood, which hinders more sophisticated and standardized application. As the conclusion of this review, we discuss open questions that need to be addressed in order to improve performance and safety of Cas13‐based tools.6.1 This information carries implications for different approaches to crRNA guide design depending on purposed application: while avoiding mismatches in the seed and “nuclease switch” regions would be necessary when designing crRNA guides for RNA interference, introducing mismatches within the “nuclease switch” region of crRNA guides would be plausible to promote tighter binding in applications that use inactive Cas13 variants, such as RNA imaging, labeling of RNA‐interacting proteins, epitranscriptome regulation, etc. However, it is unclear to what extent the findings for LbuCas13a are applicable to other Cas13 effectors.Although fundamental insights into conformational changes through which Cas13 effectors undergo during transition from binary to ternary complex have already been provided, mechanisms underlying the binding of activator RNA, conformational activation of the HEPN nuclease site and ssRNA cleavage are still largely unknown. Understanding which subregions of crRNA spacer play crucial roles in activator RNA binding and HEPN nuclease site activation is particularly important for designing efficient crRNAs. Tambe et al. have shown that activator RNA binding and HEPN nuclease site activation in LbuCas13a are governed by two separate spacer subregions, i.e., the central seed region and the “nuclease switch” region.56 Thiβ‐hairpin located proximally to the HEPN nuclease active site  abolished ssRNA cleavage activity, whereas substituting the hairpin with those from other Cas13b orthologs altered nucleotide cleavage preferences and cleavage efficiency. Thus, it is possible that analogous active site‐proximal structural elements in other Cas13 effectors are of similar importance. It would be worth investigating whether substitutions or modifications within such β‐hairpins and other active site‐proximal regions could improve RNA cleavage efficiency of Cas13 effectors for RNA knockdown and nucleic acid detection platforms such as SHERLOCK. Using Cas13 effectors with modified nucleotide cleavage preferences could further expand capacities of the nucleic acid detection platforms. In addition, verifying whether the active site‐proximal RNA‐binding regions contribute to off‐target RNA binding would be valuable for applications that make use of inactive Cas13 variants, such as REPAIRv2, RESCUE, CRUISE, and RNA imaging.Elucidating the mechanisms by which ssRNAs are guided to HEPN nuclease active sites and cleaved by the catalytic residues would provide rationale for engineering Cas13‐based tools with improved cleavage efficiencies. Although more studies are necessary to validate key residues and structural elements involved in interaction with and cleavage of ssRNA, currently available data suggests that some Cas13a and Cas13b effectors possess a protruded e Figure .[53, a Figure , and its6.2 Distribution of single‐stranded and double‐stranded regions within targeted RNA sequences also has to be considered because type VI CRISPR‐Cas systems preferably bind to and cleave single‐stranded regions, with cleavage rates significantly higher than when using crRNAs targeting double‐stranded regions. For instance, Bandaru et al. have shown that LshCas13a‐mediated targeting of single‐stranded regions of SS18‐SSX2 transcript encoding protein promoting survival of synovial sarcoma cells led to significant decrease in cell viability compared to targeting double‐stranded regions. Moreover, rational design of effective and specific crRNAs based on machine‐learning techniques has already been tested on RfxCas13d—the computational Random Forest model developed by Wessels et al. was capable of distinguishing poorly performing and highly efficient RfxCas13d crRNAs, and its generalizability was confirmed by testing 3979 crRNAs on mRNA transcripts of 48 endogenous genes. In addition, the online tool CHOPCHOP v3 has recently incorporated options for Cas13 crRNA design based on computational predictions for secondary structures within a targeted RNA sequence and transcriptome‐level off‐target effects. However, crRNA design principles and machine‐learning approaches for other Cas13 effectors have not been explored yet, and transcriptome‐wide studies are required to further investigate the local secondary structure within RNA sequences and rules for design of optimal crRNA sequences.Aside from accurate determination of “nuclease switch” and seed regions, optimal crRNA design needs to take into account other factors, including crRNA folding , position, and accessibility of targeted RNA sequence within the transcript as well as its nucleotide composition.119 Di In another case, disrupting the first base pair of the guide‐proximal stem was found to notably improve RNA knockdown, possibly by stabilizing crRNA folding. Thus, although most alterations within crRNA repeat regions have negative impact on activities of cognate Cas proteins, structural studies and systematic screens may allow identification of certain modifications within crRNA repeat regions that could optimize crRNA design.Rational engineering of crRNA repeat region is another potential yet largely unexplored means of optimizing crRNA design and increasing RNA targeting efficiency. For example, we have shown that the crRNA stem‐loop nucleotides not bound by UrCas13d can be truncated without affecting UrCas13d cleavage activity.66 In 6.3 The current lack of large‐scale systematic comparisons of Cas13 effectors with the aim of determining their RNA interference efficiencies in different host cell contexts  impedes more effective use of Cas13‐based tools in RNA knockdown. Once identified, the most potent Cas13 effectors could be further enhanced by a combination of optimal crRNA design, rational crRNA, and protein engineering and use of the positively regulating accessory proteins such as Csx28 or the WYL‐domain‐containing protein to achieve near‐complete RNA knockdown levels while maintaining negligible off‐target rates. Alternatively, Cas13 effectors with lower cleavage efficiencies, suboptimal crRNA design, the negatively regulating accessory protein Csx27 or a combination of these strategies could be used for broad‐range tuning of RNA knockdown levels. In regard to accessory proteins, further studies are needed to understand how they carry out their regulatory functions and whether they could be coupled with orthogonal Cas13 effectors.RNA knockdown efficiency levels are known to vary among studied Cas13 orthologs, targeted RNA sequences and host cell types.70 The6.4In applications such as therapeutics, RNA knockdown and binding activities of type VI CRISPR‐Cas systems need to be tightly regulated in spatiotemporal manner for targeting specific cell types, administering proper dosage and switching off the Cas13 effectors to avoid potential harmful effects. While delivery of Cas13‐based tools to target cells can be achieved using AAV vectors with specific cell tropism, Cas13 activity can be temporally regulated via chemical, radiative or enzymatic induction or via suppression with inhibitory molecules such as the accessory protein Csx27 in case of type VI‐B systems.70 Several anti‐type VI‐A CRISPR proteins (AcrVIAs) were recently discovered and demonstrated to potently inhibit RNA knockdown and nucleobase editing activities of Cas13a effectors in bacteria and human cell lines without producing detrimental effects in host human cells. The identified AcrVIAs were able to act on multiple Cas13a orthologs, albeit more research is necessary to determine the full extent of their utility against diverse type VI‐A CRISPR‐Cas systems. Moreover, AcrVIA1 from the Listeria seeligeri‐targeting phage ΦLS46 has recently been functionally and structurally characterized. AcrVIA1 was found to bind the guide‐exposed face of the Listeria seeligeri Cas13a‐crRNA binary complex, interacting both with Cas13a and crRNA  to prevent activator RNA binding and conformational activation of Cas13a. Despite these promising discoveries, biochemical properties of other identified AcrVIAs and diverse mechanisms by which they exert inhibitory effects need to be investigated, and potential cytotoxic and immunogenic effects should be thoroughly examined before AcrVIAs could be effectively and safely used for regulation of Cas13a activity. Moreover, since AcrVIAs inhibit exclusively Cas13a effectors, anti‐type VI‐B and VI‐D CRISPR proteins remain to be identified and characterized.Another viable strategy for regulation/inhibition of CRISPR‐Cas systems is the use of anti‐CRISPR proteins originating from bacteriophages or prophage regions of bacterial genomes.121 Se6.5 However, potential cytotoxic effects have not been systematically assessed, especially for the long‐term use of Cas13 effectors. Moreover, off‐targeting activity can be further reduced by careful gRNA design and rational engineering of Cas13 effectors. Particular attention should be given to improving the specificity of site‐directed RNA editing , as fusing Cas13 effectors to editases that promiscuously bind RNA substantially increases off‐targeting events. Several strategies can be employed to solve this issue, such as minimizing expression levels of the RNA editors, restricting the RNA editing to nucleus, and reducing RNA–editase interaction by introducing point mutations to the editases or through steric hindrance generated by inserting the editing enzyme into the middle of a Cas13 effector instead of linking it to one of its termini.Thus far, studies using type VI CRISPR‐Cas systems for RNA knockdown in eukaryotic cells have reported high targeting specificity, negligible off‐target activity and absence of collateral cleavage; similarly, no effects on cell viability have been observed.116 HoThe observed absence of collateral cleavage in eukaryotic cells should also be closely inspected to determine the intracellular factors that give rise to this phenomenon. There is a possibility that collateral cleavage occurs upon initial activation of the Cas13 effectors, but is silenced shortly after by certain endogenous pathways in response to increased RNA degradation. In such case, prolonged Cas13 activity may also cause cytotoxic effects through hyperactivation of the pathways that counteract collateral cleavage. Immunogenicity is likely to be one of the main challenges for application of Cas13‐based tools in therapeutics because sustained expression would usually be required to achieve desired phenotypic changes, which may trigger both innate and adaptive immune responses that could lead to cytotoxicity, inflammation and even fatality. Given that many CRISPR‐Cas systems originate from pathogenic bacteria , immunogenicity could be further exacerbated by potentially pre‐existing antibodies and reactive T cells. Possible solutions to immunogenicity include immunosuppression, silencing of human T cell epitopes present on Cas13 effectors, use of type VI CRISPR‐Cas systems derived from benign bacteria, and circumvention of immune system with orthogonal Cas13 systems and AAV‐mediated delivery.Since no studies using Cas13‐based tools in animal models have been published to date, nothing is known about potential system‐wide toxic effects. Nevertheless, expression of CRISPR‐Cas13 tools in undesired cell types could be largely mitigated via targeted delivery to specific cells or tissues, and unintended leakages would be less concerning than those of DNA‐targeting CRISPR‐Cas systems due to transient nature of RNA manipulation.70 Imm6.6 Nevertheless, later studies suggested that PFS constraints may vary among orthologs and/or under different conditions, such as in cases of LwaCas13a and PspCas13b that exhibited unrestricted interference under tested conditions. Moreover, due to divergent sequences and geometries of their crRNAs, the A‐cleaving Cas13a orthologs may be subjected to PFS constraints different from the U‐cleaving Cas13a effectors. Thus, the presence and variation of PFS constraints among different Cas13a and Cas13b orthologs needs further investigation, as well as the exact role of PFS constraints. In case of U‐cleaving Cas13a effectors, previous studies indicated that a G at the position of the 3′ PFS does not negatively influence activator RNA binding, but rather appears to inhibit conformational activation of Cas13a, which is further exacerbated by extending base pairing into crRNA repeat region. Further confirmation of this notion would be valuable since PFS constraints would not need to be considered in applications where inactive variants of certain Cas13a orthologs are used.PFSs have been reported for type VI‐A (the U‐cleaving subfamily) and type VI‐B CRISPR‐Cas systems.51 NevThe authors declare no conflict of interest.


The capacitance produced by the former is known as electrochemical double layer capacitance and the latter is known as pseudo-capacitance. Carbon materials are found to be attractive materials for energy storage, due to their various micro-structures and wide source of availability. Polybenzoxazine (Pbz) is used as a source to produce carbon materials, due to the fact that the obtained carbon will be rich in N and O species for enhanced performance. Moreover, the carbon materials were produced via template-free method. In general, activation temperature plays a main role in altering the porosity of the carbon materials. The main purpose of this study is to find the suitable activation temperature necessary to produce porous carbons with enhanced performance. Considering these points, Pbz is used as a precursor to produce nitrogen-doped porous carbons (NRPCs) without using any template. Three different activation temperatures, namely 700, 800 and 900 °C, are chosen to prepare activated porous carbons; NRPC-700, NRPC-800 and NRPC-900. Hierarchical micro-/ meso-/macropores were developed in the porous carbons with respect to different activation temperatures. PBz source is used to produce carbons containing heteroatoms and an activation process is used to produce carbons with desirable pore structures. The surface morphology, pore structure and binding of heteroatoms to the carbon surface were analyzed in detail. NRPCs produced in this way can be used as supercapacitors. Further, electrodes were developed using these NRPCs and their electrochemical performance including capacitance, specific capacitance, galvanic charge/discharge, impedance, rate capability are analyzed. The obtained results showed that the activation temperature of 900 °C, is suitable to produce NRPC with a specific capacitance of 245 F g Supow price ,7,8.Based on the energy storage mechanism, supercapacitors are classified into two categories, i.e., electrical double-layer capacitor (EDLC) and pseudo-capacitor. In EDLC, the capacitance arises from the electrostatic charge accumulated at the electrode/electrolyte, where carbon-based materials act as electrodes, whereas in a pseudo-capacitor, the capacitance arises from the Faradaic charge transfer reactions occurred due to electro-active species ,12,13,14For the past few years, polymer-based porous carbons with nitrogen functionalities have been used as electrode materials for supercapacitor applications. The in-situ method of preparing porous carbon with N atom is the most preferred and costs much less . Polyben2O until a neutral pH was obtained [The benzoxazine monomer (HPh-Bzo) was synthesized from hydroquinone, phenylethylamine and paraformaldehyde through the Mannich reaction according to a previously reported procedure  with somobtained ,35,36,371H-NMR and 13C-NMR spectra of the benzoxazine monomer (HPh-Bzo) were recorded and displayed in −1 corresponding to the ‘D’ band and ‘G’ band, respectively [D/IG was found to be 0.95, 0.93 and 0.89 for NRPC-700, NRPC-800 and NRPC-900, respectively. This result reveals that the structural order and degree of graphitization increased with increasing the activation temperature from 700–900 °C [The precursor of the polybenzoxazine-based nitrogen-doped carbons was synthesized by a Mannich reaction. Novel porous carbons with high surface area were obtained after carbonization and activation processes. Fourier transform infrared (FTIR), ectively . An inte0–900 °C . Figure 0–900 °C .2 isotherms were observed at a relative pressure below 0.1, representing micro-pore adsorption, which increases along with increased activation temperature. When compared with NRPC-700 and NRPC-800, the NRPC-900 sample showed a wider micropore size distribution which might be due to the higher activation temperature. A steady increase of adsorption isotherms were observed with increasing relative pressure up to P/Po = 0.9, which might be due to the gradual adsorption of N2 molecules on the mesopores [0), indicating the existence of macropores. From the BET isotherms, the specific surface areas of NRPC-700, NRPC-800 and NRPC-900 carbons are calculated to be 865.3, 980.6 and 1192.8 m2 g−1, respectively. The average mesopore size was slightly increased with increasing activation temperature from 700 to 900 °C, indicating that the mesopores were enlarged by KOH etching under severe activation conditions. In addition, macropores with pore sizes ranging from 50 to 100 nm for were generated for NRPC-700, NRPC-800 and NRPC-900 by KOH corrosion and nitrogen and oxygen heteroatom functionalities were retained even at this high temperature. As polybenzoxazines possess high chemical and thermal stability, and exhibit high char yield (around 50%), all the samples NRPC-700, NRPC-800 and NRPC-900 prepared using PBz were also obtained at high yield.Nitrogen adsorption-desorption isotherms of the activated carbons are shown in esopores ,39. A shThe surface morphologies of the activated carbons at different activation temperatures are shown in 2-bonded carbon that especially favours the electrical conductivity of carbon materials. Therefore, the existence of hierarchical porous structures that were observed from TEM images is consistent with the SEM observations.Furthermore, at a still higher activation temperature (say 900 °C), NRPC-900 has a collapsed structure with many voids and macropores with pore sizes ranging between 0.5 to 1.0 µm c. Many mThe activated porous carbon materials derived from polybenzoxazines contain relatively higher content of nitrogen species about 3.64–6.26 wt.% and oxygen species about 10.61–13.65 wt.%. The presence of these heteroatoms (N and O atoms) effectively improves the wettability and electrical conductivity of the prepared carbon materials and thus facilitates the accessibility of the electrolyte ions, thereby enhancing their capacitance performance. The XPS analysis data  represen2SO4 aqueous electrolyte and their electrochemical performance were analyzed. 2SO4 aqueous electrolyte with a working voltage range of 0.0–0.6V and −1. The CV curves of all the three electrodes showed a quasi-rectangular profile within 0.0–0.6 V at a scanning rate ranging from 5 to 100 mV s−1, and almost near-rectangular shape is well maintained at a scan rate of 25 mV s−1. Observed results evidenced that the prepared materials have perfect capacitive behaviour. At a low scan rate, all of the NRPC electrodes showed a quasi-rectangular shape, exhibiting a small electrical double-layer contribution (EDLC) due to lower specific surface. On the other hand, a near-rectangular shape was observed for all the electrodes at a scan rate of 25 mV s−1, indicating the existence of pseudo-capacitive reactions, due to higher nitrogen contents. However, at higher scan rate (say 100 mV s−1), all the NRPC electrodes still maintain a less rectangular shape, implying a good capacitive performance for charge/discharge operations. As compared to the sample NRPC-900, CV curves of NRPC-700 and NRPC-800 electrodes become highly distorted at higher scan rates. This could be due to the presence of micropores which restrict fast ionic transportation through them. In contrast, the NRPC-900 electrode containing enormous macropores and few mesopores favours the quick electrolyte diffusion into their interior surface and provides an improved capacitance performance [All the abovementioned results show that electrode materials can be prepared from the NRPC materials. To verify this, the prepared carbon materials were examined by a three-electrode system using 1 M Hformance .−1. The curve indicates that the NRPC-900 electrode shows a high discharge time when compared with NRPC-800 and NRPC-700 samples because of their wider micropore distribution and the presence of meso/macropores. All the obtained results confirmed that the pronounced contribution of pseudo-capacitance for NRPC-700, NRPC-800 and NRPC-900 electrodes.−1, the specific capacitance of the NRPC-700, NRPC-800 and NRPC-900 electrodes were found to be 160–50 F g−1, 175–70 F g−1 and 245–125 F g−1, respectively. Among, the sample NRPC-900 exhibits highest specific capacitance owing to their porous structure [tructure ,54,55,56tructure ,58,59. M−1 in a 1 M H2SO4 aqueous electrolyte using a three-electrode system. The specific capacitance of the NRPC-900 electrode decreased from 194 to 172 F g−1 after 5000 cycles. It also showed a capacitance retention ratio of 89%  and oxygen species (13.65 wt%) as evidenced by EDX and XPS analyses. Such high contents can only be produced through the polybenzoxazine source. Among the three prepared electrodes, NRPC-900 electrode exhibits superior electrochemical performance with a specific capacitance of 245 F g


RNA-seq, including single cell RNA-seq (scRNA-seq), is plagued by insufficient sensitivity and lack of precision. As a result, the full potential of (sc)RNA-seq is limited. Major factors in this respect are the presence of global bias in most datasets, which affects detection and quantitation of RNA in a length-dependent fashion. In particular, scRNA-seq is affected by technical noise and a high rate of dropouts, where the vast majority of original transcripts is not converted into sequencing reads. We discuss these biases origins and implications, bioinformatics approaches to correct for them, and how biases can be exploited to infer characteristics of the sample preparation process, which in turn can be used to improve library preparation. RNA-seq has become one of the most important tools in molecular biology. It allows straightforward measurement of RNA expression levels in transcriptome-wide fashion. It is now available in countless variants that allow sequencing of different types of RNAs, from different starting materials, using different experimental approaches, and more . AlthougIn this review, we will discuss current limitations of RNA-seq with respect to its main application of quantifying transcript abundances. Since this is particularly relevant for absolute quantitation, we will explore how technical noise and biases reduce both sensitivity and precision of (sc)RNA-seq specifically, and will discuss novel insights in this regard.The main goal of RNA-seq in most contexts is the accurate quantification of the original RNAs’ abundances in a sample, whether that refers to ‘bulk’ RNA from a homogenized cell population, or single cells. In practice, this amounts to correctly interpreting the number of sequencing reads that are obtained for each transcript. This problem is non-trivial due to several confounding factors preventing precise quantification, most of which are owed to the complexity of RNA-seq sample preparation.Several steps are necessary to convert the RNAs in cell lysates into sequencing reads. Common to the vast majority of protocols are selecting which RNA is to be sequenced, the cDNA production steps of reverse transcription (RT) (often referred to as first-strand synthesis) and second-strand synthesis. The reason for selecting RNA to be sequenced is that the vast majority of RNA in cell lysates is ribosomal RNA, which is normally undesired. Removing it allows for more reads to be used towards the detection of less abundant RNA species of interest, such as mRNA. This is achieved by removing rRNA (‘ribodepletion’) or positive selection of RNAs of interest. RNA is replaced with DNA because RNA is problematic to work with; it is subject to degradation through RNases and metal ion catalyzed hydrolysis at higher temperatures. It has a propensity to form secondary structures and cannot easily be amplified due to a lack of suitable enzymes and its compromised stability during thermal cycling. Synthesis of the second cDNA strand is necessary to enable adapter ligation for next generation sequencing, unless special adaptations are used . Other pThe only RNA-seq strategy that avoids cDNA conversion is direct RNA sequencing, as implemented by the ill-fated Helicos sequencing machine  or nanopin vitro transcription (IVT), as implemented by the CEL-seq protocol [RNA-seq libraries are usually fragmented by various means and size-selected in order to produce more sequencing reads at optimal length. This can occur before or after cDNA production. Direct fragmentation of RNA often uses metal-ion catalyzed hydrolysis at high temperatures (e.g. TruSeq) and cDNA fragmentation often uses physical methods (e.g. sonication) or enzymatic methods. ‘Tagmentation’ is a convenient enzymatic way to combine fragmentation and adapter ligation . It usesprotocol .average of a repeatedly sampled value needs to deviate from the true value to make it an actual bias; random variation per se is not enough. Biases in RNA-seq can have very different effects and it is important to understand, classify and quantify these. Two key properties that help categorize biases are their scale  and their visibility -based approaches have characteristic biases which are likely to affect quantitation of expression levels. These can occur on a well-studied It is generally assumed that expected sequencing read numbers for a particular transcript are proportional to its length, i.e. a linear relationship, giving rise to the RPKM/FPKM  or transcripts per million (TPM) measures . These hlocal bias that is highly visible  genes with peak-valley-peak formations where the 5′ peaks are larger than the 3′ ones  is an inherently unstable molecule, with a reactive 2′ hydroxyl group which (when deprotonated) can attack the neighboring phosphodiester bond , resultiglobal bias can be introduced with RNA degradation when RNA is selected from one end of the transcript (poly-(A) + selection) [A visible lection) . If one To assess this bias, we used a collection of RNA-seq degradation datasets of human dorsolateral prefrontal cortex tissue  that hadAnother major difference between RNA-seq protocols concerns the strategies for producing cDNA. The first step, RT, is initiated from primers that are designed to either bind random positions or that target the 3′ poly-A tail of mRNAs. ‘Random-priming’ was and is common in RT-PCR and is used in strand-specific RNA-seq systems such as the ScriptSeq or Ovation kits , while the latter, ‘oligo-(dT) priming’ is very popular for scRNA-seq. This is because the primers will not target rRNA and therefore eliminate the need for purification of mRNA, thus potentially reducing losses of the limiting starting material.Depending on the protocol, second-strand synthesis may once again start from a random position or from the terminus of the first-strand. The enzymes used in these reactions, reverse transcriptase and DNA polymerase, are both processive. This means that large numbers of nucleotides are incorporated before the enzyme drops off or the reaction stops otherwise (e.g. by reaching the end of the template strand). However, the exact stopping points cannot be predicted and are best described as probabilities for certain positions.These positional dependencies between first- and second-strand priming cause global biases which have been noticed early . AttemptThe protocol-specific global bias is thus hard to experimentally avoid for scRNA-seq. However, it can be understood and thus corrected based on its shape. In fact, the shapes of the global bias are highly characteristic for the library preparation protocol that was used; datasets prepared with ‘SMART’-mechanism-based protocols  , which aet al. found if a FPKM/TPM is used to compare short (200 bp) and long (20 000 bp) transcripts on a dataset prepared with smart-seq2, there would be a ~9-fold error [The effect of these non-linear length-dependent global biases is to miscalculate expression levels when assuming a linear relationship between expression levels and transcript length . For example, using poly-(A) + selection on degraded RNA would result in the underestimation of long transcripts expression levels as these are missing more reads at the 5′ end than shorter transcripts. In a similar fashion, libraries based on Smart-seq also underestimate the expression of long transcripts   address the local bias by redistributing reads within a transcript to make the coverage more uniform. Many tools either implement this strategy directly  or takeufflinks , 42, 43.ufflinks .Some protocols use random hexamers to prime RT, which causes sequence specific bias . This reGC content can also contribute to under-representation of sequences, presumably due to incomplete PCR amplification, which can also be modeled and corrected for , 40.There are few tools which attempt to understand and correct for global biases. Maxcounts  tries toet al. [in silico reproduces aspects of the global bias, but does not provide any bias correction and uses a model with some shortcomings [Wan et al.  model thet al. , can simtcomings .et al. [Our group has developed the tool LiBiNorm  which foet al.  and fundThis is exemplified by Smart-seq and similar SMART-based protocols, where underrepresentation of long transcripts is expected based on the library preparation logics; SMART refers to the ‘Switching Mechanism At the 5’ terminus of the RNA Transcript,’ which introduces the second-strand primer at the end of the first-strand . Due to The protocol also leads to more even coverage, which serves to render the global bias less obvious.However, imperfections in the protocol such as the spurious occurrence of the SMART mechanism inside of some transcripts (and not at 5′ ends only), usually yield non-uniform coverage of the observed shape . This alWhile local bias is too strong to permit precise bias estimation in many cases, we found LiBiNorm to perform well on Smart-seq2 datasets; these are prepared using additional measures to reduce local bias  and alloA summary of bias correction tools is in 2 [Many bias correction methods use RT-PCR as a gold standard to measure the success of the correction and benchmark data to other tools. However, RT-PCR involves cDNA production as well and is therefore subject to the global bias, too. Employing a different gold standard might be advisable, such as datasets prepared with the ‘TruSeq’ protocol that fragments RNA (not cDNA), thus reducing the bias in RT  are eff2 .Ideally, the model and tools employed will be able to correct biases and provide insight into how the latter occur. This will help to develop experiments to test these insights, enabling better understanding of the biology and make improvements into RNA sequencing protocols based on model predictions – a particularly pressing issue to resolve the zero-inflation controversy in scRNA-seq (see section Dropouts). Whilst most tools make little attempt to explain these technical issues, some do – which we will briefly touch upon.global bias is interpreted as RNA degradation in Wan et al. [For example, the n et al. . This maet al. [The approach taken by Archer et al.  showed tet al. ).λ, where λ = UMI length), meaning that each RNA is very unlikely to be tagged with the same sequence. When sequenced, reads bearing the same UMI are counted once only, thus removing the potential bias of unequal PCR-amplification [UMIs are random oligonucleotide tags which are designed to label each individual mRNA molecule. When the length of the random oligos increases, there is an exponential increase in the number of possible distinct UMIs  – UMI concatenates, thus restricting detection to poly-(A) + transcripts. There is also a trade-off with sensitivity; UMI usage restricts quantification of a transcript to the single fragment  bearing the UMI, whereas other fragments are lost. Therefore, for studying any processes away from the 3′-end, such as alternative splicing, UMI-based methods are not useful. This problem may be solved in the future with greatly increasing sequencing lengths, ideally resulting in full length UMI labeled transcripts being sequenced. For now, coverage based methods (or combining coverage based methods with UMIs ) still hRestricting this quantification to the single fragment at the 3′ end means that the global length dependent biases of degradation and processivity are irrelevant. However, whilst we have said that local biases might not have a strong effect on quantitation for coverage-based protocols, the opposite may be true for UMI based ones. This is because restricting quantitation to only a single fragment means that local peaks or valleys in that fragment will not be averaged with reads from the rest of the transcript (unlike coverage-based protocols). Worse still, it will be an invisible type of bias.Sequencing at a single cell level has recently gained huge traction in a variety of fields  introduces biases which, if not accounted for, can confound data analysis . The besThis is not possible for all scRNA-seq protocols, however. Specifically in droplet-based sequencing, the standard balanced experimental design cannot be easily achieved as cells need to be encapsulated and sequenced separately for each sample, in order to retain each sample’s identity . Of noteDoublets result when two cells are co-encapsulated in the same droplet or land in the same well of a multi-well plate in the case of plate-based scRNAseq. The result is that reads from these cells cannot be de-multiplexed, leading to artificial transcriptomes in the data. While these can often be identified by their unusually high number of associated transcripts, inherent variation in transcriptome size often found in cell populations means arbitrarily setting a threshold also introduces a bias . Recent Ambient gene expression refers to extracellular RNA which becomes encapsulated into the same droplet as a cell or accompanies a cell in the same well, leading to contamination of a cell’s resulting transcriptome. The presence of extracellular RNA in the sample results from RNA leaking from damaged cells during the sample preparation process, and unless it is accounted for leads to biases in the interpretation of the data. While it is difficult to completely remove non-endogenous RNA from the sample prior to library preparation , novel mMethods such as SoupX  use the Specifically, certain types of cells  will also have fewer counts than the average cell and can thus be mistakenly excluded from the analysis. The opposite problem also exists – empty droplets containing cell-free RNA can be mistaken for a distinct cell type. This has motivated the development of methods which model the profile of empty cells to efficiently exclude them from analysis , 100 witBecause of the finite size of the single cell starting material, often genes with moderate or low expression level will not be detected, which leads to the over representation of zero counts of gene expression in the final scRNA-seq datasets. This ‘dropout’ phenomenon has been an actively discussed topic since the first emergence of the scRNA-seq itself , 102 andIt is thus common to process scRNA-seq data using zero-inflated distribution models for deconvoluting meaningful biological variance from high counts of zeros due to technical noise. Therefore, many ‘imputation’ algorithms have been proposed to ‘rescue’ scRNA-seq data from the inflated zero counts for downstream applications , 101. Foet al. [Recently, it was argued by Svensson  that at et al.  developeHowever, this might hold true only for the latest generation of UMI low-volume emulsion techniques as opposed to earlier methods, owing to improvements in capture efficiencies. All the same, high-dropout rates are still observed in modern methodologies and compatibility with Poissonian models does not prove genuinely biological origins. Moreover, the evidence collected from pure RNA control solutions might not convincingly explain sequencing data derived from cellular RNA samples, which exist in more complex environments.The assumption that at least some of the zero counts reflect biological variance is supported by recent work from Qiu , who preA further issue with scRNA-seq datasets is illustrated well by the differing conclusions obtained from these compared to alternatives, such as single molecule RNA FISH (smFISH)  or live One field of note here is spatial transcriptomics, where researchers combine measuring RNAs with their positional contexts. Here, imaging data such as smFISH appear well suited to the task, e.g. , however(sc)RNA-seq is a rapidly maturing technology, with technical improvements continuing to increase the output in terms of numbers of samples/cells sequenced at an exponential rate ; it is nWhile for many biological questions, high sensitivity, precision or absolute quantification might not be necessary, biases are still present and underappreciated, which can skew the estimation of transcript abundances and influence the conclusions that are made.Furthermore, for more complex aims such as analyses of non-genetic heterogeneity , gene reBy highlighting them here, we hope researchers will consider these issues when designing experiments and continue to develop methods for dealing with them. These methods can be experimental, such as using spike-ins, employing UMIs to combat the PCR amplification bias and fragmenting RNA to combat RT bias, or computational, such as improving expression level estimation by modeling the sample preparation process.RNA-seq is subject to trade-offs between sensitivity and single transcript labelingCoverage bias can be local or global, visible or invisibleGlobal bias can cause systematic and length-dependent over- or underestimation of transcripts, with protocol dependent patternsscRNA-seq in particular is affected by technical noise and dropoutsThese biases can be explained, understood, and partially corrected by novel analysis approaches


Non-coding RNAs, such as miRNAs and piRNAs, play critical roles in gene regulation through base-pairing interactions with their target molecules. The recent development of the crosslinking, ligation, and sequencing of hybrids (CLASH) method has allowed scientists to map transcriptome-wide RNA–RNA interactions by identifying chimeric reads consisting of fragments from regulatory RNAs and their targets. However, analyzing CLASH data requires scientists to use advanced bioinformatics, and currently available tools are limited for users with little bioinformatic experience. In addition, many published CLASH studies do not show the full scope of RNA–RNA interactions that were captured, highlighting the importance of reanalyzing published data. Here, we present CLASH Analyst, a web server that can analyze raw CLASH data within a fully customizable and easy-to-use interface. CLASH Analyst accepts raw CLASH data as input and identifies the RNA chimeras containing the regulatory and target RNAs according to the user’s interest. Detailed annotation of the captured RNA–RNA interactions is then presented for the user to visualize within the server or download for further analysis. We demonstrate that CLASH Analyst can identify miRNA- and piRNA-targeting sites reported from published CLASH data and should be applicable to analyze other RNA–RNA interactions. CLASH Analyst is freely available for academic use. RNA molecules perform some of the most fundamental and important functions in organisms, including coding for proteins (mRNAs), providing structural support , acting as vital enzymes , and guiding proteins to regulate other RNAs . Although discovered only relatively recently, this last category of RNA function has been shown to play a prominent role in posttranscriptional and transcriptional gene regulation. By guiding Argonaute family proteins to RNA targets using base-pairing interactions, miRNAs, piRNAs, and siRNAs can effectively and specifically target diverse mRNAs for regulation. For example, it has been estimated that ~50% of human genes are regulated by miRNA ,2,3. To Recently, a technique has been developed to capture in vivo RNA–RNA interactions, called CLASH  ,6,7. UV To allow scientists with and without knowledge of bioinformatics to perform integrative analysis of CLASH data, we developed CLASH Analyst, which accepts raw CLASH data and outputs fully processed and easy-to-understand representations of the transcriptome-wide RNA–RNA interactions contained within those data. CLASH Analyst allows users to select default or customized parameters of the analysis pipeline, which are comprehensively explained within the application, to parse their data according to their specific needs. Furthermore, CLASH Analyst’s output displays comprehensive information about each identified RNA–RNA interaction, including the sequences of the regulatory RNA and its target, the relative abundance and location of that interaction, and the free energy of pairing for the targeting event. All resultant analyses are available for user-friendly browsing within the CLASH Analyst interface, as well as for download, to facilitate any downstream analyses.During the development of CLASH Analyst, another tool similar to CLASH Analyst named ChiRA was published that provides a similar analysis pipeline to analyze RNA–RNA interactions . While Clin-4 miRNA), they can immediately sort all chimeric reads containing such RNA of interest, based on the abundance of the interaction in chimeric read count (lin-4 miRNA and its target lin-14 (T25C12.1a.1), the user can click to reveal comprehensive information of each chimeric read, including where along each molecule the chimeric reads originated, how many reads were captured, and where mismatches occurred within the base-pairing interaction  and target RNA sequences  are preloaded and can be selected by the user using a drop-down menu to skip uploading/downloading those data.The user must upload a compressed FASTQ file and two compressed FASTA files . The FASCLASH Analyst performs all necessary steps to preprocess the raw reads  so that chimeras can be identified. The user can choose default settings or select specific settings according to how the CLASH libraries were prepared . Users sOnce data are preprocessed, CLASH Analyst identifies chimeric reads using default or user-defined settings. The user can choose among three different algorithms to assign chimeric reads: CLAN , Hyb 1212, and pIf the user chooses to use CLAN, they can use default settings or specify criteria for searching chimeric reads, including (1) the minimum size of each fragment within a chimeric read for analyses; (2) how much overlap between the two fragments is allowed ; (3) how many hits will be allowed for each fragment, as each fragment could match multiple user-input FASTA sequences. Similarly, the user can use default or specify criteria for searching chimeric reads using Hyb or piRTarBase. We recommend users first analyze their data with CLAN if they are unsure of which algorithm to choose, as CLAN performs the least stringent analysis and identifies more RNA–RNA interaction candidates , so we provided an option to input an email address for the user to be notified once the analysis is complete. This is an optional, step and the email address is used only to notify and send the user a link to the results page.The user can input the Job ID or use the website link to browse the results within CLASH Analyst. The user can choose one of the three ways to display their results, which include browsing by (1) regulatory RNAs within the chimera, (2) target RNAs within the chimera, or (3) individual RNA–RNA pair ranked by chimera abundance or pairing energy. Regardless of what the user chooses to browse by, a summary of the analysis is first displayed in two tables . The firlin-4 and lin-14 (T25C12.1a.1). Additionally, any of the regulatory RNA–target RNA pairs can be further examined by clicking “show interaction”. A graphic showing the interactions between target RNA and regulatory RNA is available for viewing  [Among the three searching algorithms available in CLASH Analyst, piRTarBase is the most stringent, and CLAN is the least stringent but most sensitive algorithm. Specifically, piRTarBase first searches for the regulatory RNA sequences within each read, and the default settings do not tolerate mismatches or deletions. It then uses the remaining sequence to identify targets with perfect matches. By using its default setting, piRTarBase requires the presence of intact regulatory RNA and does not allow insertions between regulatory RNA and target RNAs. Hyb tolerates short deletions and insertions in regulatory RNAs and target RNAs, and it also tolerates overlapping fragments. Nonetheless, Hyb will then choose one RNA–RNA interaction with the highest score among multiple possible matches, which increases its searching stringency. The least stringent algorithm, CLAN, will identify more interactions using more sensitive searching and will report all possible matches, resulting in multiple interpretations of RNA–RNA interactions for some individual chimeric reads. To compare the performance of each of the three searching algorithms  ,12,15 av6512652)  and comp6512652) . In thesC. elegans miRNAs, and C. elegans piRNAs [C. elegans miRNAs and piRNAs did not provide the full details of their results, we were not able to compare the number of targets found in CLASH Analyst to those from previous studies. Nonetheless, we found that C. elegans miRNA-binding sites are enriched at 3′ untranslated regions (UTRs) of their mRNAs, consistent with the previous report  piRNA and xol-1 mRNA  to translationally repress mRNAs . ResearcWe are confident that CLASH Analyst will allow users from any background to analyze their own data or previously published data to identify potential in vivo RNA–RNA interactions. We believe that with such advanced bioinformatic techniques available to all researchers in the RNA community, CLASH Analyst will allow for significant and novel advancement in our understanding of RNA regulation.https://cosbi7.ee.ncku.edu.tw/CLASHanalyst/ (main site) and https://cosbi.ee.ncku.edu.tw/CLASHanalyst/ (backup site).CLASH Analyst analysis pipeline behind the web interface was implemented using awk, bash, and Python scripts. The web interface of CLASH Analyst was constructed using Django, a Python web framework that encourages rapid web development. All figures in CLASH Analyst were generated using D3.js, a JavaScript library that provides powerful visualization components. All tables in CLASH Analyst were generated using DataTables, a table enhancing plug-in for the jQuery JavaScript library, which adds sorting, paging, and filtering abilities to plain HTML tables with minimal effort. CLASH Analyst is available at


Studies in humans and mice indicate the critical role of the surrogate light chain in the selection of the productive immunoglobulin repertoire during B cell development. However, subsequent studies using mutant mice have also demonstrated that alternative pathways are allowed. Our recent investigation has shown that some species, such as pig, physiologically use preferential rearrangement of authentic light chains, and become independent of surrogate light chains. Here we summarize the findings from swine and compare them with results in other species. In both groups, allelic and isotypic exclusions remain intact, so the different processes do not alter the paradigm of B-cell monospecificity. Both groups also retained some other essential processes, such as segregated and sequential rearrangement of heavy and light chain loci, preferential rearrangement of light chain kappa before lambda, and functional κ-deleting element recombination. On the other hand, the respective order of heavy and light chains rearrangement may vary, and rearrangement of the light chain kappa and lambda on different chromosomes may occur independently. Studies have also confirmed that the surrogate light chain is not required for the selection of the productive repertoire of heavy chains and can be substituted by authentic light chains. These findings are important for understanding evolutional approaches, redundancy and efficiency of B-cell generation, dependencies on other regulatory factors, and strategies for constructing therapeutic antibodies in unrelated species. The results may also be important for explaining interspecies differences in the proportional use of light chains and for the understanding of divergences in rearrangement processes. Therefore, the division into two groups may not be definitive and there may be more groups of intermediate species. H genes belong to the ancestral VH3 family sharing the same leader and framework sequences, and only one JH segment is functional  gene rearrangement has evolved in all jawed vertebrates and involves recombination of variable (V), diversity (D), and joining (J) gene segments at their corresponding loci  repertoire by V(D)J rearrangement is derived from mouse studies (reviewed in L and JL segments. Rearrangement in the IgLκ loci is finished when (1) any IgLκ protein can form an authentic BCR with existing IgH and small preB-II cells become immature B cells or (2) all functional Vκ and/or Jκ segments on both chromosomes have been used and/or IgLκ loci have been inactivated. Inactivation of IgLκ occurs by excision of Cκ segments from the genome by recombination of any remaining Vκ segment or upstream Cκ recombining element (RE) to downstream recombining sequence in mice or κ deleting element in other species (hereafter referred to as KDE recombination)  . The exiination) .+IgLλ—IgH—. There are no IgH rearrangements in these precursors yet, and if some occur rarely, if they are productive, and if they match productive IgL, the precursors become immature B cells expressing BCR. This is only a small fraction of the final IgLκ+ B cell pool as evidenced by cultivation and sorting studies  further Vλ genes until IgH rearrangement occurs. As indicated by sorting and sequencing studies  , 12. For studies . In the  studies , most ofromosome , 9. The VJ joins –33. The VJ joins , 9. In td expand . Since i earlier . The genromosome . During nscripts , 11. Thinscripts –12.Studies in pigs have shown that some steps in the sequential process of V(D)J rearrangement are essential, whereas others are optional. The first essential process is that the IgH and IgL loci rearrange at different developmental stages. Thus, the process is sequential, but the respective order may vary (see below). This may be related to a reduction in the number of IgL isotypes during evolution, resulting in only one or two isotypes in birds and mammals. These can be more comfortably controlled than in skates and sharks, which have multiple IgH and IgL loci rearranged simultaneously , 35. In On the other hand, an optional process includes the independence of IgH and IgL gene rearrangements so that the respective order may vary. While IgH precedes IgL rearrangement in mice, IgL precedes IgH rearrangement in swine. Interestingly, the independence of IgH and IgL rearrangement was predicted based on results with virus-transformed preB cells  and demoH rearrangements on both chromosomes occur in the earliest precursors in all species. In swine, they do as in mice and humans J rearrangement machinery. It is apparent that essential components are also critical enzymes, such as the recombinase-activating genes (RAG), which are required for DNA cleavage, or the terminal deoxynucleotidyl transferase (TdT), which can facilitate N-nucleotide additions. As indicated by genome sequencing, this is also true for recombination signal sequences (RSS) and regulatory factors required for rearrangement processes. The encyclopedic information on these aspects can be found in other reviews.Originally, SLC was expected to ensure the allelic exclusion. This was disproved by the construction of knockout mice in which different components of SLC were deleted but the exclusions remained intact , 48. OnlThere are three VpreB in mice  and two in humans (VpreB1 and VpreB3). While VpreB1 and VpreB2 are co-expressed and serve for IgH selection , 51. Howvia interaction with phospholipids such as sphingomyelin A  IgLκ+ B cells highly predominate over IgLλ+ B cells, (3) IgLκ+ B cells have both IgLλ loci in the germline, while (4) IgLλ+ B cells have rearranged IgLκ loci inactivated by Cκ ablation  appears to be an effective mechanism to achieve isotypic exclusion. Such an exclusion function would be of particular interest given that KDE recombination is highly conserved in many  species . On the  B cells , 10–12.  B cells . Also, ne second . The coee second , where K. On the other hand, experiments in pigs have shown that the initial IgL rearrangements used for selection of subsequent IgH rearrangements are >88% in-frame, have no mutations, and no N-additions . The established order of IgH before IgL gene rearrangement seems to be the most ancestral because this strategy is used in amphibians . However segment  and pigsith them . This mae genome .+ precursors during IgH rearrangement and is overcome by expression of authentic BCR , especially in species that have relatively high numbers of functional Vκ genes such as horse (www.imgt.org). According to the results from swine, the difference in the use of IgLκ compared to IgLλ is more likely explained by the sequence of IgL rearrangements on different chromosomes and/or the permissiveness of the microenvironment to support efficient B cell development. Although IgL rearrangement begins with IgLκ and progresses to IgLλ probably in all mammals J segments to a minimum. This is especially true for IgH, which is critical for BCR formation. For example, pigs have all five JH segments “functional” in terms of the WGxG motif and the absence of stop codons (Another important factor is the limited number of Vnversion –44, but pertoire . These apertoire Table 1.pertoire . Indeed,pertoire  instead pertoire . In any pertoire . In compd cattle . In thisp codons . Howeverp codons , and funp codons . A similp codons .H genes share the same leader and framework sequences and only one JH segment is functional. Furthermore, both porcine IgLκ and IgLλ loci contain only two families and two functional JL genes. This allows the recovery of all VDJH rearrangements using a single non-degenerate primer set or the generation of deficient pigs for B cells by modifying just a single JH segment (In summary, different species appear to have evolved different strategies for the order of rearrangement of Ig genes and for the selection of a productive Ig repertoire. Possibilities for these strategies have even been indicated in mice themselves, which showed that the order of rearrangement is independent , 40, 41  segment . HoweverAll authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.The research was supported by the Czech Science Foundation grants No. 19-01504S and No. 20-03282S.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Significant progress has been made in our understanding of how RNAs are regulated to provide spatial and temporal control over gene expression. However, due to the cell-type diversity and specialized morphology and physiology of neurons, much remains to be uncovered about how local RNA regulation and translation influence neuronal function. In this collection of reviews focused on “RNA Localization and Localized Translation in Neurons,” several aspects of RNA metabolism that are critical for localized RNA regulation are discussed. From transcription to transport and compartment-specific regulation, these reviews highlight the many knowns and unknowns of how local RNA regulation contributes to neuron function, how it is dysregulated in neurological diseases, and how emerging tools and technologies are revolutionizing our understanding of the functional roles local RNA regulation plays in neurons.Agrawal and Welshhans  discuss key findings from multiple studies on how distinct pools of RNAs localize in radial glial cells and axons during neuronal development. The active transport of RNAs bound by RNA binding proteins (RBPs) and their local translation have functional consequences for both, with roles in neurogenesis, differentiation, branching, synaptogenesis, and maintenance. The local transcriptome and the associated local translatome are modified and rendered more complex throughout development to meet the subcellular functional demands. Local translation in axons allows for the precise spatiotemporal regulation of gene expression by coordinating RNAs that are functionally related, especially in response to external stimuli. However, how this co-regulation is mediated mechanistically is still not well-understood. A handful of studies show that local proteomes can be remodeled by receptor interactions with local translational machinery, activation of signaling cascades that modify RBP-RNA interactions and/or the local translational machinery, or localized translation on specific organelles . A better understanding of these molecular processes is becoming crucial as molecular dissection of the clinical phenotypes of neurodevelopmental diseases, such as Fragile X Syndrome, Autism Spectrum Disorders, and Down Syndrome, points to dysfunctional local translation in axons of cell adhesion molecules, transcription factors, translational machinery, and cytoskeletal- and membrane-associated proteins.In their review, Gamarra et al. highlight the importance of these proteins in a review discussing how mutations or depletions of RBPs can lead to a number of neurological and neurodegenerative disorders, including Amyotrophic Lateral Sclerosis and Parkinson's Disease. The molecular consequences of these mutations or depletions are discussed in depth, with a particular focus on how dysregulation of local translation may underlie and contribute to the development and progression of nervous system pathologies. What remains to be directly tested is whether these molecular changes in response to RBP mutations or loss drive neurological diseases through dysregulation of the local transcriptome or if these are secondary to other cellular adaptations. Further technological innovations will be needed to dissect out such mechanisms, for instance methods which would allow us to specifically target and manipulate RNAs in distinct neuronal compartments.RBPs are key players in the regulation of RNA transport and local translation. Rodrigues et al., provide a comprehensive overview of “the few knowns and many unknowns” regarding the molecular principles underlying neuronal RNA trafficking. They describe in detail the direct and indirect evidence that have led to the discovery of many proteins involved in RNA transport. They highlight the specific roles of RBPs, adaptor/motor proteins and organelles in RNA distribution in axons and dendrites and describe the technical advances that are now opening the possibility to better decipher the essential components of the RNA trafficking machinery.It has been reported that thousands of RNAs are enriched in neuronal compartments, and specific transcriptomic signatures have been observed in distinct subdomains . Moreover, restricted pools of RNAs can also be recruited to these subcompartments in response to stimuli. In view of the morphological complexity of neuronal cells, one of the biggest challenges in the field is now to understand how RNA transport is controlled in a precise manner. In their review, Park and Farris highlights the role of alternative isoform expression as one means of diversifying RNA regulation to provide spatial and temporal control over compartmentalized gene expression. They review several specific gene examples to illustrate how alternative isoform expression is used in hippocampal neurons to provide distinct subcellular compartments with the necessary transcripts to support specialized functions, with a focus on development and plasticity. They emphasize how unraveling this RNA regulatory code is vital to fully understanding how RNA is regulated across different contexts and cell types to support neuronal functions.Advancements in RNA sequencing technologies and methods for cell-specific profiling have led to the identification of diverse cell- and compartment-specific transcriptomes. Contributing to this diversity is the extent of alternative isoform expression within and across neuronal subtypes. By changing the cis regulatory sequences of a given transcript, and thereby the associated trans acting RNA binding proteins and other interactors, many aspects of RNA metabolism—from transport to translation and degradation—can be impacted. The review by Minehart and Speer discuss state-of-the-art approaches being employed to understand these processes with subcellular resolution. These include methods from subcellular transcriptomics, translatomics, proteomics, and super-resolution imaging. In particular they highlight three critical areas of exploration: (1) molecular-genetic approaches for quantifying mRNA diversity, abundance, and regulation of the local transcriptome/translatome in targeted subcellular compartments, (2) proteomic techniques for assessing nascent proteins interaction networks in synaptic connections, and (3) super-resolution fluorescence microscopy for quantitative analysis of subsynaptic resolution in circuits. These approaches are currently revolutionizing our understanding of where mRNAs localize and the functional role their compartmentalization plays in neuronal function.Technical hurdles have impeded our understanding of the functional role for localization of mRNA and protein synthesis. Multiple layers of RNA regulation highlighted in these reviews point to complex post-transcriptional and translational mechanisms that orchestrate neuronal function. Given the complexity of local RNA regulation in neurons, there are still numerous unanswered questions. Many lines of work in the field are geared toward understanding how neuronal development and different patterns and forms of neuronal activity can modify subcellular RNA metabolism and, in turn, how local changes in RNA metabolism influence neuronal activity and behavior. Neurons integrate a multitude of signals received over short and long distances and time scales. It remains unclear how different RNA regulatory mechanisms, such as splicing, localization, or local translation, play a role in (re)structuring proteomic states as a consequence of this complex signal integration. Another area of great interest lies in the transport of RNAs to distal sites. What is the subset of RNAs that travel to neurites and how is this transport mediated, particularly in response to changes in neuronal activity? What is the composition of RBPs and RNAs in transport granules across neuronal compartments and under different physiological states? How do the principles of RNA regulation differ across neuronal compartments and under different physiological states? Finally, the dynamics of protein synthesis and degradation is a topic of exciting investigation. How are the transcriptome and proteome remodeled in neurites throughout development and in response to plasticity and does this differ across cell types and conditions?All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.