Naturally occurring antisense RNAs are small, diffusible, untranslated transcripts that pair to target RNAs at specific regions of complementarity to control their biological function by regulating gene expression at the post-transcriptional level. This review focuses on known cases of antisense RNA control in prokaryotes and provides an overview of some natural RNA-based mechanisms that bacteria use to modulate gene expression, such as mRNA sensors, riboswitches and antisense RNAs. We also highlight recent advances in RNA-based technology. The review shows that studies on both natural and synthetic systems are reciprocally beneficial. Antisense RNAs (asRNAs), also referred to as natural regulatory RNAs, are small molecules that perform their regulatory function by recognizing sequence and structural elements that are present in themselves and their target mRNAs. AsRNA-mediated regulation generally inhibits mRNA transcription and/or translation or induces their rapid degradation. In fewer cases, asRNAs activate expression of mRNAs , 2.We are using the terms regulatory asRNAs and natural regulatory RNAs to mean a diverse group of bacterial RNAs that modulate a broad range of physiological responses through complicated and delicate controlling mechanisms . AlthougIn recent years, the prevalence of long non-coding RNAs (lncRNA) and natural antisense transcripts (NATs) has been reported in a variety of organisms. In general, antisense transcript regulatory mechanisms affect different levels of gene expression including: transcription interference, transcription attenuation, translation stimulation or inhibition, and RNA stability . AnotherAntisense RNA can be inherited during conjugation .High-throughput transcriptomics has shown that every organism can potentially possess one or several asRNA regulators for every single gene.New asRNAs evolve easily and automatically during mutations of the original DNA template.cis on their templates, a high local concentration of both types of molecule takes place. These so-called steric effects and the limited diffusion of transcripts lead to an efficient interaction between antisense and target RNAs, which is suggested to be controlled and biologically effective.Because both antisense and target RNAs are transcribed in close proximity due to the position of the The spatial closeness of the promoter sites to antisense and target RNAs also causes transcriptional interference, and thus has a regulatory role.Here are some of the characteristics of this type of RNA.On the other hand, asRNAs can also be defined as endogenous RNA molecules containing complementary sequences to the original transcripts (mRNAs). These endogenous asRNAs have been observed widely in both prokaryotes and eukaryotes .cis-acting 5’ element non-coding asRNAs; (ii) trans-acting small non-coding asRNAs; and (iii) cis-encoded asRNAs.Studies have shown that some asRNAs regulate protein function, mimicking the nucleic acids that are the regulatory targets of the protein, so they involve the protein in an inactive complex, whereas the majority of asRNAs pair with target mRNAs and shift their stability and/or translation . In bactcis-acting 5’ non-coding asRNA is usually attached to the 5’ side of an mRNA, the expression of which is regulated by the non-coding RNA. A structural change in the non-coding RNA occurs through binding to small metabolites (riboswitches) or through change of temperature (thermoregulators) or pH (pH sensors). The structural change influences the transcription or translation of the downstream gene or genes in an operon.A Trans-acting small non-coding asRNAs are usually encoded in intergenic regions on the chromosome and control translation or degradation of their target mRNAs. Generally, each trans-acting non-coding asRNA has multiple target mRNAs and binds near the ribosomal binding site of the target mRNAs.Cis-acting asRNA is expressed as a complementary sequence of mRNA that becomes the sole target RNA. Therefore, cis- and trans-acting non-coding asRNAs are a major part of the asRNAs in bacteria , tail-to-tail (3’ to 3’) and fully overlapping. Tail-to-tail orientation seems to be the most common type. Overlapping transcripts might comprise two protein-encoding genes, one protein-encoding and one non-encoding gene, or two non-encoding transcripts .–16.13–16Trans-asRNAs are generally much longer than the cis-asRNAs. It follows that the promoter and first transcribed nt of asRNAs may play the part of an intergenic spacer and then extend to a complementary region. However, cis-asRNAs form more stable complementary duplexes because of their binding kinetics. In addition, cis-asRNAs seem to exert their target interaction independently of proteins such as Hfq  was identified during the characterization of the E. coli outer membrane porin ompC. During that study, it was noticed that several ompC promoter clones repressed the synthesis of the other major outer membrane porin OmpP. The responsible region for this activity turned out to be a 300-bp fragment located upstream of the ompC promoter, 70 % homologous to the DNA encoding the 5’ end of the ompF mRNA (including the ribosome binding site and the ompF initiation codon). Further studies showed that this homologous 300-bp fragment is transcribed in the opposite direction from ompC to a 174-nucleotide RNA that complements and encompasses a region of the ompF mRNA containing its translation initiation site. Based on this study, it was proposed that micRNA forms a hybrid with ompF mRNA and inhibits its expression by preparing a model that seeded the idea of using artificial micRNAs to regulate selected genes [The first natural ed genes , 20.micF gene produced this asRNA. micF is a stress response gene found in E. coli and related bacteria. It post-transcriptionally controls the expression of the outer membrane porin gene ompF by encoding a trans-asRNA (93 nt) that binds its target ompF mRNA and regulates ompF expression by inhibiting translation and inducing degradation of the message [Studies have shown that the  message .Several mapping, cloning, sequencing and bioinformatics techniques and tools have helped to identify and characterize asRNAs, but various aspects of their functions, structures and mechanisms of action remain to be explored. Accordingly, fundamental and mechanistic studies aiming to characterize novel regulatory RNA are needed if biotechnological and medical aims are to be met .Although regulatory RNAs and their mechanisms were discovered in prokaryotes in 1967, it is only now that the central role of RNA in prokaryote gene regulation in all three domains of life can be demonstrated. The research that led to this discovery occurred in three major phases: 1967 to early 2001; 2001 to recent times; and current research , 23.trans-acting regulatory RNAs were discovered around this time [In 1967, Hindley identified a distinct and abundant RNA species, later named 6S RNAI. Its function in RNA polymerase activity regulation had been determined previously. The first his time .cis-asRNAs controlled the life cycle or copy number of extra-chromosomal genetic elements, bacteriophages, transposons and plasmids. One of the first identified antisense transcripts belonged to the gene cro in bacteriophage λ. It was revealed to be transcribed by bacteriophage λ when overexpression of the 77 nt OOP antisense transcript resulted in its co-degradation with the cII mRNA [cis-asRNA I involved in the regulation of maturation of the ColE1 primer and the control of plasmid incompatibility of ColE1-type plasmids.Initially, it was thought that cII mRNA . AnotherE. coli by early 2001.Over the next two decades, although a small number of chromosomally encoded small RNA regulators such as MicF, DicF and OxyS were discovered, their fundamental importance and privileges were not adequately considered. Only 12 small RNAs containing entities like 6S RNA, tmRNA, RNase P RNA and 4.5 S RNA had been identified in trans-acting asRNAs supplied abundant data for later functional characterization studies [In 2001, considerable progress took place thanks to the application computational techniques and predictive approaches to complex systematic experimental screens. For example, comparative genome analysis of closely related species was used for searching transcriptional signals within intergenic regions and scoring the conservation of predicted RNA secondary structure with the aim of small RNA prediction in Enterobacteria. During this second phase, newly identified  studies .The advent of RNA-seq technology and its use in prokaryotic RNA studies triggered a new wave of discovery. This has led to new standards in the accelerated identification of transcripts and transcriptional start sites , 26.Salmonella enterica, is regulated at the transcriptional level by PhoPQ, and at the level of protein stability by the MgtR peptide. Additionally, it might be regulated at the post-transcriptional level by the AmgR asRNA [Ongoing studies present two reasons for the advantage of asRNA regulation over other methods of regulation. First, asRNAs could provide an advantageous control system when a particular protein such as transposase needs to be expressed under very selective circumstances or repressed at a very tight level. Second, asRNAs provide one more level of control in the extensive regulation of their targets. For example, translation and expression of MgtC, a virulence factor of gR asRNA .The response to the regulator happens in a shorter time because in this way mRNA is a direct target.In the case of small RNAs, a low number of base pairs provide specific and fast mRNA recognition and binding.Rapid specificity can be attained because a single nucleotide change suffices for a specificity shift.The capacity of RNA regulators to modulate their conformation upon binding increases the number of contacts with a given ligand or makes the recognition of multiple targets easier .In this way, the advantages of RNA-based regulation over classical protein-mediated transcriptional control can be referred as:These features show the potential of artificial mRNA regulators that can be beneficial for various biotechnological applications, supporting the need for more studies .As mentioned, asRNAs affect cellular functions through transcription attenuation, translation inhibition, and regulation of plasmid copy number through the inhibition of primer maturation, prevention of formation of an activator RNA, and promotion or inhibition of mRNA degradation , 28. TheMucD gene expression and consequent alginate (biofilm) biosynthesis in Pseudomonas aeruginosa is regulated by cis-asRNA (named mucD_AS). Functionally, mucD_AS turned out to be able to induce biofilm formation in P. aeruginosa. Considering the biotechnological and medical significance of alginate as a key virulence factor of P. aeruginosa, this finding is particularly important [mportant .micF inhibits the expression of the membrane porin gene, ompF. This occurs under the regulation of environmental and internal stress factors, including elevated temperature, exposure to salicylate and redox stress. ompF is at its maximal expression level at low temperature and osmolarity and this is regulated at the transcription and post-transcription levels by micF asRNA [ompF mRNA and inhibits its translation. It is likely that specific binding proteins are also associated to micF asRNA, while both seem conserved in other Gram-negative species. Other controlling systems are involved at different levels [An asRNA named cF asRNA . Howevert levels , 32.E. coli. ftsZ mRNA, which is apparently involved in initiating division, is inhibited by several factors, including the 53-nt dicF-RNA, which is transcribed from dicB operon (another inhibition factor) and partially complementary to the ftsZ mRNA [dicF is an asRNA that inhibits cell division in tsZ mRNA .gInA) is likely regulated by asRNA in Clostridium. This is an important enzyme for nitrogen assimilation in Gram-positive Clostridium acetobutylicum and is nitrogen regulated. The regulatory 43 nt asRNA is complementary to the ginA RBS and its transcription induced in nitrogen level of environment is high leading to repressed ginA transcripts [The expression of glutamine synthetase gene  or primer inhibition (in the case of the ColE1-type plasmids) can take place too , 31, 34.tra genes are involved in the conjugation of F-like plasmids (such as Incf and R1). One of these is a transcriptional activator, traJ. It is regulated by an asRNA system, FinP, which complements to traJ RBS and blocks its translation. FinP metabolic stability increases with the help of a ribonucleolytic degradation inhibitor protein, FinO. Structurally, FinP has two stem-loops, so loops are responsible for specificity and stems and play a pivotal role in its activity [More than 30 activity , 14.Host-killing systems are employed by many bacterial plasmids to kill cells that fail to keep at least one plasmid copy at cell division to guarantee their maintenance in bacterial cells , 31. AllOOP RNA facilitates cell mRNA decay.PaQ RNA inhibits late gene expression.P22 sar RNA inhibits anti-repression.Sas RNA in phage P22 regulates alternative translation.In the bacteriophages P22 and A, antisense control exists as a secondary control strategy and contributes at various levels to their developmental pathways. Some of these RNA transcripts and their functions are listed below .OOP RNA cis to the SymE gene [SymE protein shows homology to MazE, an antitoxin, encoded from an SOS-induced gene. It is suggested to be involved in cell growth inhibition, decreased protein synthesis and increased RNA degradation, and therefore functionally resembles RNA endonuclease toxins. SymR is one of several mechanisms that repress SymE gene expression. It contains an asRNA that is encoded in ymE gene , 37.Recent studies have revealed that RNAs are key regulators in pathogens. Small RNAs regulate the translation and/or stability of mRNAs that encode virulence factors, or proteins with roles in adaptive responses, which are triggered by environmental cues and stresses. Generally, the transcription of many pathogenesis-related RNAs is dependent on the growth phase but in several pathogens, the secretion of virulence factors is regulated by cell-density sensing (quorum sensing), a process that involves communication through secreted signaling molecules. Several regulatory RNAs are the main effectors of quorum-sensing systems , 39.Vibrio cholerae, the sensory signals converge on a response regulatory protein, LuxO. At low cell density, when the quorum-sensing autoinducer is absent, phosphorylated LuxO activates the transcription of four redundant Qrr RNAs as quorum regulatory RNAs (Qrr1–Qrr4) that regulate the mRNA of the downstream target gene hapR through the inhibition of translation and mRNA degradation. In Staphylococcus aureus, the effector of quorum sensing is encoded by the agr system, which is composed of two divergent transcription units. The first operon combines a density-sensing cassette including agrD and agrB, and a two-component sensory transduction system (agrA and agrC), which is required for its autocatalytic activation as well as for the activation of transcription of RNAIII, the intracellular effector of the agr regulon.For example, in trans-acting regulatory RNAs shown to encode a 26-amino acid peptide that may be involved in biofilm integrity in addition to its regulatory effect in quorum-sensing in S. aureus [Although it had previously been thought that small RNAs are noncoding, based on this research several such entities were recognized to be both regulatory and protein coding (regulatory RNA and mRNA). For example, RNAIII is one of the first identified . aureus .E. coli, when phosphor–sugar intermediates can increase to toxic levels, SgrS, a 227-nt small RNA, represses ptsG, the glucose transporter component of the PTS, at the translational level. SgrS encodes for a 43-amino acid oligo-peptide, SgrT, which inhibits glucose transportation of PtsG. Transcriptional profiling has revealed five potential sRNAs in Listeria monocytogenes. They are suggested to encode 28-to 64-amino acid small peptides [In peptides .cis-acting RNA regulators [Many other kinds of mRNA regulatory elements exist that are actually located on the same strand and near the locus of target mRNA, just upstream of the target coding sequence. These types of regulatory elements are also classified as gulators .Some regulatory mRNAs modulate gene expression through allosteric mechanisms due to stimulant metabolites that modify the mRNA structure and activity by binding to 5’ UTR regulatory elements. The modified structure of the mRNA influences the expression of the following coding sequence. These metabolite-sensing mRNAs, which are called riboswitches, are widespread in bacteria. They give feedback regulation that supplies the cell with a reciprocal regulation system that is responsive to the concentration of stimulant metabolites. In addition, the synergism of different riboswitches in functional units develops even more complex regulatory arrangements. Such metabolite-specific tandem riboswitches may act independently or associate together , 12.RNA molecules have a particular potential to sense temperature due to their versatility and dynamism. Several mRNAs of heat- and cold-shock proteins also act as thermosensors. It is shown that some proteins associated with bacterial pathogenesis or bacteriophage development and lysogeny have mRNAs that are regulated by the thermosensor system. As with the riboswitches, the thermosensor regulatory elements, are settled at the 5’ UTR of mRNAs. Another mutual mechanism controls all heat- and cold-shock responsive elements and translation initiation, so that low temperature causes target mRNA RBS to fold into a helical structure preventing the formation of the ribosomal initiation complex and protein synthesis initiation. However, in higher temperature, the inhibitory structure unfolds and then protein synthesis begins after ribosomal initiation complex formation.Listeria monocytogenes, which contains a similar hairpin that melts at host temperature (37 °C), permitting the protein to start its virulence function. Some other thermosensitive elements may adopt more stable structures. Thus, thermosensitive regulatory activity is influenced by the rate of the transcription, the thermosensitive folding performance and the ribosome recognition efficiency of these structures [In many Gram-negative bacteria, this 5’ UTR regulatory element of heat-shock protein mRNAs contains 4 hairpins. It has the name ROSE (repression of heat-shock gene expression). Another example is the 5’ UTR of prfA mRNA in ructures .cis-acting regulatory sRNAs. Trans-acting regulatory RNAs are the best-characterized class of RNA regulators [Trans-encoded asRNAs are extensively observed in bacterial genomes and show partial complementarity to their target. The pleiotropic regulator protein Hfq is a highly conserved hexameric protein that tends to bind to an AU-rich region of a single-strand RNA preferentially close to a stem-loop structure. It was recently found in association with many trans-encoded regulatory RNAs, regulating the mRNA translation [As implied before, thermosensors and riboswitches were from well-characterized groups of gulators , 44. Translation , 46. Mosnslation .An antisense RNA regulatory system is potentially very useful for metabolic engineering and/or as a therapeutic agent in prokaryotic organisms . The undIn some studies, the targeting region of recognized Hfq-associated regulatory asRNAs was merged to other asRNA backbones to construct custom regulatory asRNAs with a desired regulatory function. As the library of various regulatory small RNA modules becomes more complete, the design of a completely recombinant asRNA becomes more approachable. Mutational techniques and in silico modeling software are helpful to predict the designed asRNAs structurally and functionally , 47. WhaparB partition in the plasmid R1, which stabilizes the plasmid in the carrier cell through toxin/antitoxin counteraction, is also regulated under an RNA-based regulation system. Therefore, this regulatory system might be helpful when R1 is used to produce a special product [Clostridium acetobutylicum and E. coli are noteworthy examples [Natural prokaryotic antisense systems were the first RNA-based regulatory systems applied in bacteria. The locus of  product . In addiexamples .E. coli. One approach is to silence the RNaseE using asRNAs and decrease the cellular level of RNaseE. This is supposed to decrease mRNA degradation in the cell, resulting in augmentation of the target mRNA and the related product [Furthermore, asRNA strategies are suggested to enhance recombinant protein production in  product .Clostridium acetobutylicum. The idea was to redirect the primary metabolism of bacteria trying to reduce the levels of the butyrate-forming enzymes, because butyrate is assumed to induce solvent genesis in C. acetobutylicum. The larger goal was downregulation of the primary metabolism of C. acetobutylicum, which is a promising organism for biorefinery [Regulatory asRNA was also studied in refinery , 51.Lactobacillus rhamnosus, a milk-fermenting bacterium. The purpose was to change the polysaccharide size without any alteration to the total amount. This offers a conditional control of gene expression in metabolic engineering samples without gene inactivation [Regulatory asRNA was also used in tivation .Bacteriophages can be highly disruptive in microbial industries that use starter cultures or produce live mucosal vaccines or enzymes and metabolites. It has been shown that asRNA anneals to sense RNA and makes it subject to dsRNase enzymes. The idea of designing asRNAs against essential genes for phage development is of great interest .E. coli. The goal of the study in question was to survey the silencing efficiency and repression mechanism [Despite all of the controversial reports on the ability of asRNAs to silence genes, one study did show that they can silence a gene by decreasing target mRNA concentration . Since lechanism , 55.cis-encoded antisense sequences provide this. These asRNA coding sequences are situated within a short open reading frame just upstream of the start codon region of both the chloramphenicol and erythromycin resistance genes [A variety of RNA-level regulatory systems have been developed in bacteria. The most important factor in their development is that mRNA can rapidly switch from repression to expression and vice versa in response to environmental stimulation , 57. Thece genes , 59. RNAce genes .S. aureus has been targeted by two research groups applying shotgun technology to make a library of S. aureus genome fragments cloned under inducible promoters aimed to essential gene identification. Although the suboptimal regulatory efficacy of RNA may contravene the desired lethal activity, the RNA regulators have been successful enough to recognize many essential genes of S. aureus, leading to infection resolution in the animal model [Antisense RNA regulation has been employed for determining essential genes of bacteria. al model , 61.trans-acting ncRNAs generally cannot sense cellular signals directly, allosteric RNA fusion molecules have been engineered combining ncRNAs (as the target recognition motif) and RNA aptamers (as the ligand-sensing motif). The fused aptamer part enables the ncRNA modulatory activity in E. coli. This is applicable to both translation ncRNA regulators  and transcription ncRNA regulators . This reconfiguration develops an orthogonally acting fusion molecule capable of recognition of different ligands and affecting different subjects in a biological system [Non-coding RNAs (ncRNAs) have a variety of regulatory functions in cell. Since most l system –64.Finally, the technique of aptamer–ncRNA fusion molecules provides researches with a very extended and efficient tool for ligand-sensing regulatory circuits. A single ncRNA can be fused to various aptamers as sensing domains and can bring up ligand sensor control systems that respond to multiple input signals applicable for structurally related families of ncRNAs .For experimental investigations of small RNAs and their interactions with proteins, they must be purified in a native form. Aptamer-tagged variants of target small RNAs can be produced and used in RNA-based affinity chromatography. Thus, appropriate plasmids have been developed to express target small RNAs tagged with one of three global aptamer sequences: MS2, boxB or eIF4A .gfp mRNA. It could confer temperature dependence to gene expression in E. coli [By exploiting biomimicry, in vivo selection and computational design, synthetic thermosensors have been created. These trials made a simple on/off switch to express any desired gene in response to temperature. A similar principle was implemented to fuse the PrfA leader sequence to  E. coli .Other physical stimuli can also potentially be detected by this sensor-mediated regulatory system, making it possible to apply more criteria to biological systems and offering more metabolic engineering tools to researchers .RNA thermometers (RNATs) mostly regulate translation using a zipper like function and blocking the SD sequence at low temperature, resulting in suspension of translation initiation. As temperature increases, melting of the secondary structure causes the release of an SD sequence resulting in the resumption of translation .Salmonella fused to a hammer-head ribozyme (HHR) that fractions itself to a liberated RBS and a thermo-sensitive hairpin connected to the HHR. It brought a temperature-controlled ribozyme forward – a so-called thermozyme. Therefore, at higher temperature, the self-cleavage activity of the thermometer structure is impaired and the gene expression is silenced. This is the opposite of the natural behavior of thermosensors [A novel functionality was created based on a temperature-controlled element of osensors .Another simple theoretical thermometric mechanism was implemented for de novo design of a synthetic thermosensor based on an RBS embedded in a single stem loop that unmasks when the temperature reaches a predicted range. This hypothesis was assessed by constructing a particular modular structure including a promoter, a start codon, an SD sequence and a complementary anti-SD sequence (separated by four unique restriction sites), and standard reporter genes.cIII gene of coli-phageλ, which switches between two secondary conformations (on/off structures) in response to temperature rather than fully melting. In the off conformation at low temperature, the RBS is veiled, but in the on conformation at higher temperatures, the RBS is revealed. Designed RNA thermometers subjected to extra mutations in practice lead to functional thermosensors that were actually temperature inducible using the reporter gene of lacZ  [Another example is that the synthetic thermometer is designed based on the 5’ UTR of the osidase) , 69, 70.Although RNA regulatory systems have many applications, some obstacles remain.Currently, classical procedures of small RNA identification rely on bioinformatical approaches, which are somehow limited to a predefined data pool. This may direct research to an incomplete library that displays bias to sequence conservation, specific promoters and Rho-independent terminators, while missing several other aspects, including ORFs, Rho-dependent terminators and Hfq-independent small RNAs. To ensure a global unbiased approach to small RNA identification, other experimental and predictive procedures such as transcriptional profiling with the whole genome, massively parallel sequencing, and targeted identification of small RNAs are suggested .Another difficulty of the practical application of RNA silencers, either naturally existing in the cell or delivered into the cell, is the sufficiency of the silencer agent for efficient silencing activity. Considering the abundance of mRNAs in the cell, an acceptable level of expression or delivery and stabilizing structures should be provided in order to achieve practical silencing .Most delivery methods are culture dependent. Most prokaryotes from natural environments are not readily culturable. Moreover, even in culturable in vitro genetic manipulation methods, the nucleobase polymer transferring process is not 100 % efficient. On the other hand, DNA and RNA transferred to natural microbial communities can change their functionality. However, in addition to their beneficial applications, the inevitable subsequences should also be considered .In the world of molecular biology, the success of every technique such as gene therapy and RNA regulation is highly dependent on the efficiency of the delivery approach of the multi-nucleotide molecule to the cell. A simple and efficient delivery system is necessary to exploit a prosperous RNA regulatory technology. Different biological physical and/or chemical methods are exerted for nucleotide polymers, as summarized in Table E. coli). Other physical techniques are usually only employed for small-scale prokaryotic cells [The most commonly used methods include conjugation, electroporation and heat shock transfer (especially for ic cells . Ultrasoic cells . Howeveric cells .The antisense RNA regulatory system is a mechanism for sequence-specific recognition of a particular transcript. It is usually involved in the degradation of said transcript. However, by definition, it could also be involved other forms of reduction or alteration of expression. New asRNA gene-controlling cases are being identified in nature, accompanied by the discovery of more mechanisms with a variety of potential applications. These utilities derive from variable mechanisms through which RNA regulatory systems influence target mRNA. AsRNAs can cause target mRNA degradation, change mRNA processing and/or affect mRNA transcription. The same applies to artificial asRNAs.It remains to be seen whether transcriptional interference or antisense regulation can regulate sense–antisense pairs, but synthetic biology studies indicate that antisense transcription can improve existing networks by adding some constructive complexities. It is also possible to create new networks with desirable properties.Regulatory RNA systems have considerable potential and are already used in silencing bacterial genes, altering bacterial behavior and inhibiting bacterial biofilm formation. They are also used as novel antibiotics, especially against multidrug-resistant bacteria. These applications have made them a popular subject for research.asRNA, antisense RNA; dsRNA, double-strand RNA; HHR, hammerhead ribozyme; lncRNA, long non-coding RNA; miRNAs, microRNA; NAT, natural antisense transcript; ncRNA, non-coding RNA; RBS, ribosome-binding site; RNAi, RNA interference; ROSE, repression of heat shock gene expression-like thermometers; UDD, ultrasound DNA delivery; UTR, untranslated region


Enteroviruses, specifically of the Coxsackie B virus family, have been implicated in triggering islet autoimmunity and type 1 diabetes, but their presence in pancreata of patients with diabetes has not been fully confirmed.To detect the presence of very low copies of the virus genome in tissue samples from T1D patients, we designed a panel of fluorescently labeled oligonucleotide probes, each of 17-22 nucleotides in length with a unique sequence to specifically bind to the enteroviral genome of the picornaviridae family.With these probes enteroviral RNA was detected with high sensitivity and specificity in infected cells and tissues, including in FFPE pancreas sections from patients with T1D. Detection was not impeded by variations in sample processing and storage thereby overcoming the potential limitations of fragmented RNA. Co-staining of small RNA probes in parallel with classical immunstaining enabled virus detection in a cell-specific manner and more sensitively than by viral protein. Type 1 diabetes (T1D) is a chronic multifaceted disorder that results from selective autoimmune-mediated destruction of the insulin producing β-cells. Environmental factors , interacViruses have been proposed as possible initiators of islet autoimmunity and were first implicated as long ago as the nineteenth century although it was not until much later that a clear association was established between mumps and diabetes –6. ImproPicornaviridiae, and are small positive-sense single stranded RNA viruses, which have been shown recently to induce a persistent, slowly-replicating infection in both myocardium and pancreas. This may result from alteration to the viral genome during the progress of infection including the generation of naturally occurring 5′-deletions [Coxsackieviruses belong to the eletions –14. Seveeletions –20. Enteeletions , 21, whieletions . Also, neletions , 24.A well-characterized cohort of human pancreatic donor tissue has been established by nPOD (Network for Pancreatic Organ Donors with Diabetes) and is available, similar to other cohorts, mainly as formalin fixed, paraffin embedded samples (FFPE) . This mein situ hybridization, where labeled oligonucleotide probes specifically pair with target nucleic acids via Watson-Crick base pairing and some success has been gained using long probes (~50-100nts) labeled with either radioisotopes or enzymes catalyzing chromogenic reactions. However, this approach also has limitations in the face of samples with poor RNA integrity or very low target RNA copy numbers. Thus, improved RNA FISH methods have been developed to overcome these hurdles. Enteroviral RNA was detected by a new generation of RNA probes (QuantiGene® ViewRNA Assay), which depend on signal amplification [This has created pressure to develop alternative  methods to allow the detection of RNA in single cells within FFPE tissue samples. An obvious candidate is fication . This apin situ. These oligonucleotides anneal to common regions of the RNA genome of members of the coxsackievirus family. Such short singly labeled oligo RNA probes are resistant to RNAse and RNA detection is less affected by target RNA degradation, making these probes more versatile while retaining sensitivity and specificity. Because their binding to the target sequences occurs independently for each probe, this gives probe combinations the advantage that there is a degree of freedom in their positioning without risk of the loss of stringency, efficiency or specificity.Because of such limitations to the detection of enteroviruses with high accuracy and sensitivity, we present here an adapted method to target single RNA molecules with short (~20nts) fluorescently labeled oligonucleotides To generate a distinct fluorescent signal above background noise, a sufficient amount of labeled probes must bind in close proximity –29, therIn order to develop a robust protocol for RNA-oligoprobe labeling of FFPE pancreatic tissue sections, we initially tested a commercially available probe set targeting the housekeeping gene (GAPDH) in cultured HEK293 cells and in isolated FFPE human islets Figure . NaturalProbe set CVB_1 included a wide range of group B coxsackieviruses; it consisted of a mixture of 40 short oligonucleotides, each comprising 17-22 nucleotides covering the whole viral genome , a DNA virus of the y Figure , CMV or y Figure , HAV. Foy Figure . CMV appThe likelihood that the signals detected in samples were non-specific was further excluded by staining CVB3 infected islets in the absence of the probe set and by staining uninfected cells with the probe set. In each case, the negative controls delivered no staining, whereas virally infected cells yielded positive signals . RNAse A® ViewRNA virus probes [® ViewRNA by Laiho et al. [We further tested the CVB_1 probe set on an array of cell lines previously generated for use with Quantigenes probes . Green ms probes   . RT-PCR is the most powerful and specific tool for RNA detection; but RNA accessibility and degradation are two important limiting factors. To compare the sensitivity of the RNA probes with analysis by PCR, the pancreatic line CM9  and HEK2H Figure  and RT-PH Figure  were abl) Figure . Using RR Figure . The spe-8. The cells were then fixed and paraffin embedded. When employed at a dilution of 1:2000  antibody, using a cell array of the human alveolar basal epithelial cell line A549 infected with CVB1 for 2, 4 and 6 h to generate a population representing different stages of infection . After iositives , 24), th8 Figure .The design of the RNA-FISH system should circumvent the problem of RNA degradation since it employs multiple probes to detect the target RNA. RNA fragmentation frequently occurs in, for example, autopsy samples, where processing and storage under RNAse free conditions is unlikely. We therefore tested FFPE CVB1-infected GMK cell sections, which had been infected and processed at the same time, but then cut and processed at different times (covering periods between 2012 and 2015) and stored at room temperature. The probes showed similar signals in all three samples regardless of the processing and storage time. Importantly, uninfected controls were negative .Important advantages of the use of RNA-FISH probes relate not only to their high sensitivity and specificity but also their ability to localize RNA molecules within specific cells of tissues such as the pancreas. We, therefore, investigated the localization and distribution of the signal emanating from the viral probes within the pancreas and compared this with detection by immunohistochemistry with the widely used VP1 antibody.Figure Successful double staining of viral RNA and VP1 was confirmed in FFPE infected mouse spleen. Spleen sections from mice infected with CVB1 were stained with the CV_1 probe set to detect the viral genome and subsequently with anti-VP1 in an additional round of staining of the same section. Both techniques showed positive staining within the same regions of the samples .2 fixed and paraffin embedded cells. To demonstrate efficacy for virus staining in various tissues, we stained a section from a coxsackie-infected neonatal heart and found cells displaying a strong signal corresponding to viral RNA . It should also now be possible, to increase the specificity of the probe sets for particular virus strains in order to specifically characterize the infection of pancreatic islets in patients with T1D. This is a major undertaking, but is possible using the well-preserved and -characterized FFPE tissues available within the nPOD initiative.Although enteroviruses (including members of the Coxsackie B virus/ CVB family), have been suspected as potential triggers of T1D for a long time, firm evidence of viral genome expression in the pancreas has been largely elusive.Most evidence supporting a causative role for enteroviral infections in diabetes onset have come from epidemiological studies –6, 11 orFor a long time the approach to identify the disease's trigger has been based on the four Koch's postulates , which wSeveral hypotheses have been proposed to explain why the viral genome has proven so difficult to detect in the islets of patients with T1D  and in tIn the present work, we have overcome these difficulties by deploying our highly sensitive FISH method to provide evidence that enteroviral genome can be detected more frequently in the pancreas of patients with T1D than in equivalent controls.The technique applied in this study combines the advantages associated with access to FFPE samples  with a highly sensitive detection method. The sensitivity of detection was much greater than that achieved with classical immunohistochemistry to detect the viral capsid protein, VP1, implying that it is ideal for use in circumstances where viral replication may be compromised .in situ hybridization (ISH) and fluorescent in situ hybridization (FISH) have increased both the sensitivity and specificity of RNA detection such that they now represent a valid alternative to PCR, with the advantage that they can spatially localize particular RNA molecules within fixed cells [To verify these conclusions, we compared directly results obtained by RNA-FISH with those employing a widely used anti-VP1 (clone 5-D8/1) antibody in infected FFPE material. We carefully established optimized conditions for specific virus detection to avoid interactions of VP1 antibody with other cellular proteins. As a result, we were able to identify viral RNA with much greater sensitivity such that a single RNA molecule was labelled. The use of other sensitive techniques, which might match the sensitivity achieved here , is limited because of the low accessibility and stability of nucleic acids . By conted cells .The unique advantage of the small contiguous probe sets presented in this study is that RNA duplexes are detected via microscopy, because of direct conjugation of fluorophores to the probe . In ordeA significant problem in fluorescence microscopy can be a high background signal, generated either intrinsically from cellular molecules or induced by the fixatives , 38. ThiOf note, our modified deparaffinization/ hybridization protocol had no effect on either tissue morphology or the signal intensity at different wavelengths as shown, for example, by the strongly retained DAPI staining.Despite the labour-intensive pre-hybridisation protocol employed to ensure background signal reduction, the use of small contiguous RNA-labelled oligonucleotide probes offers several advantages when compared to either classical FISH (using long probes of >100nt) or indirect FISH that relies on intense signal amplification. Firstly, the strength of the bonds between the probe and the target is influenced by various factors such as formamide, salt concentration, temperature and pH. All these factors are easier to control for short than for long sequences. Secondly, systems which use branched probes for signal amplification may be more influenced by RNA degradation, because of the reduced freedom in positioning and flexibility that is allowed for the docking of two consecutive probes.Sensitivity and specificity of our probe set was tested on different virus strains as well as on various embedding procedures and was compared with indirect FISH on a set of previously analysed samples  as well Probe specificity was further tested in cell culture conditions and on a cell array . We wereAs mentioned above, with the use of small contiguous RNA probes we were able to overcome the issue of RNA stability/degradation in samples, which had been stored over long periods of time. In particular, no signal loss occurred in samples processed at various points over a time course of 3 years.To test the utility of our probes in archive pancreatic tissue we undertook a blinded evaluation of T1D pancreata from a UK , 41 cohoAmong the group of 7 RNA positive individuals, 6 had viral RNA in insulin-containing cells whereas only 4 were also immune-positive for VP1 (the parameter used to define “T1D VP1+” in this concordance study). The two pancreata, which were negative for viral RNA within islets using FISH probes were also immunonegative for enteroviral VP1. Typically, 1-2 islets per section showed viral genome staining but, unlike immunoreactive VP1, enteroviral RNA was not restricted solely to insulin positive cells.Viral RNA was detected in two young non-diabetic control pancreata but at a much lower prevalence than among patients with T1D. Thus, enteroviral infection may not be absolutely unique to the islets of patients with T1D and it remains possible that cellular response to viral infection (rather than infection per se) is a critical determinant of autoimmunity.In conclusion, we have developed a stringent and highly specific method for the detection of enteroviral genome in fixed pancreatic tissue with high sensitivity. We have used this method to confirm that viral RNA is detected in the pancreas in 7 of 8 patients with T1D and in only 2 of 8 controls. We propose that this new method may find wide applicability in future studies of the viral aetiology of type 1 diabetes.2, if not stated otherwise.Human islets were isolated and cultured as previously described , HEK 293All viruses were propagated in FHRK-4 cells and purified in a sucrose gradient , aliquots were stored at -80°C as previously described . Cells w® FISH Probes recognizing human GAPDH labeled with Quasar 570  and custom Stellaris® FISH Probes, each recognizing various enteroviral strains, labeled with Quasar 570 were purchased from Biosearch Technologies, Inc. . Briefly, the initial set of custom RNA FISH oligonucleotides (CVB_1) was designed on the CVB3 consensus based sequence (M33854.1). The consensus sequence was generated from a ClustalW alignment of several coxsackieviruses to localize conserved regions, with thermodynamic characteristics fitted to the probe design [® RNA FISH Probe Designer  available online at www.biosearchtech.com/stellarisdesigner As a result, 40 probes (Premade Stellaris0 probes  distribu0 probes  and diviwww.biosearchtech.com/stellarisprotocols (version 11.04.2013).The pre- and post-hybridization protocol for RNA fluorescent in situ hybridization (FISH) was modified based on the manufacturer's instructions available online at 2O for 1 min. All steps were performed with constant stirring.We adapted the pre-hybridization procedure by increasing the temperature of the xylene bath, in order to also access older FFPE tissue libraries . The mel2 where washed with iodine to remove mercury, before the deparaffinization protocol. To facilitate probe annealing, sections were incubated for 20 min in 0.2M HCl (room temperature) and washed with 2x SSC Buffer  and PBS . Pepsin (Sigma) was applied and washed off after 10 min incubation at 37°C with PBS . To quench any remaining autofluorescence of biological molecules 0.5-1% Sudan Black (Sigma-Aldrich) in 70% EtOH was added for 20 min (room temperature) and thoroughly washed off with PBS . Tissues were equilibrated with washing buffer  before hybridization. Stellaris® FISH Probes  were diluted in hybridization buffer  and samples incubated overnight at 37°C in a humidified chamber. Hybridization mix was aspirated and sections were washed extensively. Stringency was increased with each washing step to remove any unspecific probe binding, thus reducing background noise and increasing relative signal intensity. Slides were washed at 37°C with constant agitation; twice with 2xSSC and 10% formamide for 20 min, twice with 2xSSC for 15 min, twice with 1xSSC for 15 min, once with 0.1x SCC for 15 min and 5 min. VECTASHIELD® antifade mounting medium (Vector laboratories) including 4′,6-Diamindino-2-phenylindole (DAPI) was immediately added and images were acquired with a Nikon Ti MEA53200  microscope. A 60x oil-immersion objective . TRITC filter (ex. 520- 560nm) was used to acquire images of the Quasar 570 labeled probes. Control images were always taken with the FITC filter (ex. 465- 495nm) at the same exposure time to ensure no false-positive signals caused by a bleed-through from one channel to another. NIS-Elements BR  and ImageJ  were used for image analysis.Slides fixed with HgClwww.biosearchtech.com/stellarisprotocols (11.04.2013). Briefly, cover glasses were rinsed with PBS and cells were fixed  for 10 min at room temperature, followed by two washes with PBS (room temperature). To permeabilize the cellular membrane 70% EtOH was added for overnight incubation at 4°C. EtOH was removed, cells were equilibrated with washing Buffer  and respective RNA FISH probe mix was added for overnight hybridization at 37°C in a humidified chamber. Hybridization mix was aspirated; cells were washed twice with washing buffer  and rinsed with 2xSSC (room temperature). Cover glasses were placed on glass slides with VECTASHIELD® antifade mounting medium (Vector laboratories) including DAPI and analyzed as described above.Cells were cultivated on 13×13 mm #1 microscope cover glasses  in 24-well plates to a confluency of 80-90% and treated as indicated. Further processing followed manufacturer's instructions available online at FFPE sections were deparaffinized as described above. Antigen retrieval was performed in heated unmasking solution (Vector laboratories) in three consecutive 5 min microwave cycles (full power). Sections were blocked  for 1h at room temperature and primary anti-VP1  was applied for over night incubation at 4°C. FITC anti-mouse (1/100) for 1h at room temperature was used as secondary antibody.® antifade mounting medium (Vector laboratories) including DAPI.Samples were first probed for RNA targets and analyzed as described above. Afterwards, the coverslip was gently removed, slides were immersed in washing buffer and anti-insulin (DAKO) was applied for overnight incubation at 4°C. Sections were washed three times with washing buffer , incubated for 1h at room temperature with fluorescein isothiocyanate (FITC) anti-guinea pig, were washed 3x with 2xSSC  and mounted with VECTASHIELDCells were infected with CVB3 (MOI 1000) for 1h (16°C). Media was changed and temperature shifted to 37°C. Cells were fixed 30 min post-infection using a solution of 3,7% formaldehyde in 1x PBS for 10 min. Cells were permeabilized with 70% EtOH overnight at 4°C and probed with RNA probes as described above. Cells were washed and stained for VP1  and FITC anti-mouse as secondary antibody.® reagent  according to manufacturer's protocol. Extracted RNA was treated with DNAse I  and reverse transcribed with ReverseAid kit (Fermentas) according to manufacturer's instructions. Real time PCRs reactions were prepared according to Applied Biosystems guidelines using SybrGreen assay and performed in a StepOnePlus instrument . PCR efficiencies were monitored for each sample according to a previously described approach [RNA was extracted using Trizolapproach . ResultsCVB fw 5′ GGCCCCTGAATGCGGCTAAT 3′,CVB rev 5′ TGGCTGCTTATGGTGACAATTG 3′;Microglobulin β2 fw 5′ TTTACTCACGTCATCCAGCAG A 3′;Microglobulin β2 rev 5′ CGGCAGGCATACTCATCTTT 3′.RNAse treatmentCVB3 infected FFPE human islets sections were prepared as described above. To digest any viral or endogenous RNA 100µg/ml RNAse A (Macherey-Nagel) in 2xSSC buffer or 2xSSC Buffer alone was applied to the sections for 1h at 37°C. At this salt-concentration (150mM NaCl) single-stranded, as well as double-stranded RNA, is enzymatically cleaved by RNase A .2 (MOI 100) to 10^-8. Infection media was added to respective cells in a 24-well plate either grown on coverslips or without. Cells were directly transferred to a tabletop centrifuge and spun for 1h at 16°C and 105 rcf., followed by 1.5h (HEK 293) or 3h (CM9) post-infection at 37°C. Afterwards one set of cells was used for RNA isolation and the other for microscopical analysis. Ten images were acquired for each condition, choosing the same areas of the slide for every dilution.CVB 3 was diluted in RPMI-1640 media in logarithmic steps, starting from 10


KIF3B that significantly affects kinesin–microtubule interactions. Simul-seq provides a new streamlined approach for generating comprehensive genome and transcriptome profiles from limited quantities of clinically relevant samples.Paired DNA and RNA profiling is increasingly employed in genomics research to uncover molecular mechanisms of disease and to explore personal genotype and phenotype correlations. here, we introduce Simul-seq, a technique for the production of high-quality whole-genome and transcriptome sequencing libraries from small quantities of cells or tissues. We apply the method to laser-capture-microdissected esophageal adenocarcinoma tissue, revealing a highly aneuploid tumor genome with extensive blocks of increased homozygosity and corresponding increases in allele-specific expression. Among this widespread allele-specific expression, we identify germline polymorphisms that are associated with response to cancer therapies. We further leverage this integrative data to uncover expressed mutations in several known cancer genes as well as a recurrent mutation in the motor domain of  Furthermore, combined DNA and RNA profiling is useful for characterizing regulatory variation4, RNA editing5 and allele-specific expression8, important contributors to phenotypic diversity and disease.Integration of both DNA and RNA sequencing data enables a variety of analyses that are useful for exploring the genetics of normal phenotypic variation and disease. In addition to enumerating global patterns of gene expression, RNA sequencing data provides an orthogonal verification of DNA variant calls and can be used to prioritize expressed candidates, which are more likely to exert biologic effects. In cancer, for example, roughly a third of the somatic single-nucleotide variants (SNVs) that fall within coding regions can also be observed in the RNA9 and gDNA and mRNA sequencing (DR-seq)10, have recently produced the first genome-wide glimpses of the correlation between copy number and expression at a cellular level. However, due to the large technical variance and coverage gaps inherent in current single-cell sequencing approaches, these new methods have limited utility in contexts where more comprehensive genomes and transcriptomes are required. Moreover, both methods still require the DNA and RNA libraries to be generated independently.Currently, most integrative experiments are performed in parallel and on distinct cell populations, a strategy that requires lengthy library preparation times and potentially exacerbates variability on account of sample heterogeneity. Single-cell integrative sequencing approaches, genome and transcriptome sequencing (G&T-seq)Our simultaneous DNA and RNA sequencing method, Simul-seq, leverages the enzymatic specificities of the Tn5 transposase and RNA ligase to produce whole-genome and transcriptome libraries without physical separation of the nucleic acid species , reducinTo rigorously assess the specificity of the Simul-seq method, we first produced libraries derived from a mixture of 50 ng of human genomic DNA and 100 ng of yeast mRNA . We quan11. In parallel, we also prepared independent RNA-seq libraries from these cells using an analogous RNA-ligase-based protocol. For the Simul-seq library, we obtained 560,218,621 and 57,091,162 dual-indexed DNA and RNA 101-bp paired-end reads, respectively  isolated from a male subject with metastatic esophageal adenocarcinoma (EAC). Deep sequencing of the Simul-seq EAC library produced 727,341,682 DNA and 191,398,961 RNA 101-bp dual-indexed paired-end reads, with 95.1% and 79.4% of the reads mapping to the genome and transcriptome, respectively  from the multitude of passenger mutationsectively . Similarectively . Howeverectively . The tumectively .16) where a PolyPhen-2  were found to harbor expressed somatic missense mutations. While ESWR1 is typically a constituent of an oncogenic fusion protein, and the R45W mutation in the ATM serine/threonine kinase tumor suppressor is not yet characterized, the Y220C mutation is a known TP53 hotspot that decreases protein stability24. Moreover, we found that the TP53 locus exclusively expressed the damaging allele  as well as the cyclin D1 gene   , polymor29, KIF3B somatic coding mutations have not been previously described. KIF3B has been linked to the intracellular trafficking of several tumor suppressor genes30, and biochemical data have shown that substitution of specific arginine and lysine residues within the kinesin motor domain negatively impacts kinesin-microtubule association31. To further explore KIF3B mutation frequency in EAC, we performed targeted resequencing of the KIF3B locus in a cohort of 49 EAC samples, with 25 paired normals. Overall, KIF3B harbored verified nonsynonymous mutations in ∼6% of the tumor samples, and the R293W mutation was observed in a second independent patient , a type II kinesin motor protein. Although several kinesin family members have established roles in cancer patient . To inve patient . When co patient . Togethe32 and G&T-seq33. Simul-seq provides a complementary approach that focuses on producing comprehensive DNA and RNA profiles from limited quantities of tissues or cells rather than single cells. In contrast to previous dual-sequencing approaches, Simul-seq generates a single pooled library, and thus both reduces the library preparation time and keeps paired data sets physically linked. Importantly, whereas DR-seq and G&T-seq depend upon polyadenylation to distinguish RNA transcripts from genomic DNA, the use of RNA ligase in Simul-seq allows for a ribosomal RNA depletion step. Therefore, Simul-seq retains biologically and clinically important nonpolyadenylated RNA transcripts and may reduce 3′ bias for samples with lower RNA quality35. Overall, Simul-seq produces high-quality DNA and RNA sequencing data, enabling genotype and phenotype comparisons in a single workflow.As sequencing technologies advance and more individuals are profiled in both clinical and research settings, straightforward methods for generating comprehensive and accurate whole-genome and transcriptome sequencing data will become increasingly valuable. The combined sequencing of both DNA and RNA from single cells was recently enabled by the development of two methods, DR-seq36, KIF3B has not been classified as a cancer gene in large-scale EAC exome sequencing studies38. These efforts, however, are still largely statistically underpowered14. Intriguingly, overexpression of C-terminal truncations of KIF3B-induced aneuploidy in NIH3T3 cells39. Moreover, KIF3B has been linked to the intracellular trafficking of several tumor suppressors, including the adenomatous polyposis coli (APC)30 and von Hippel–Lindau (VHL)29 proteins. Together, our findings suggest that additional experiments are warranted to delineate specific functional roles for KIF3B mutation in esophageal tumorigenesis.Cancer genome interpretation is one scenario where integration of precise and comprehensive DNA and RNA landscapes has proven useful but can be challenging on account of limited starting material. Moreover, tumor heterogeneity increases the likelihood of discrepancies between genome and transcriptome profiles prepared in parallel on separate cell populations. Applying Simul-seq to laser-capture-microdissected tumor tissue revealed a highly aneuploid somatic landscape, including a recurrent R293W mutation in KIF3B that dramatically reduced kinesin–microtubule interaction. Although the ∼6% mutation frequency that we observed is consistent with recently published data from whole-genome sequencing of 22 esophageal adenocarcinomas24 and is also a target of several small molecules designed to restore TP53 function in tumors40. TP53 inactivation followed by whole-genome duplication and chromosomal catastrophe is a frequent trajectory for EAC development41 and is consistent with our observations for this tumor. Among the widespread LOH induced by this genomic instability, we detected ASE for germline variants with pharmacogenomic links to the efficacy of cancer therapies used in EAC. The EGFR polymorphism (rs2227983) observed in this patient is associated with increased survival of colorectal cancer patients treated with Cetuximab28, perhaps via attenuation of EGFR pathway signaling42. In contrast, the patient harbored a second variant in CCND1 (rs9344) that is inversely correlated with overall survival in colorectal cancer patients treated with Cetuximab43. In both cases, however, the beneficial allele was predominantly expressed in the tumor, suggesting a positive overall response. Taken together, our results in this EAC patient both highlight the utility of Simul-seq as well as the many benefits of acquiring combined DNA and RNA profiles for genome interpretation and personalized medicine.In addition to the novel KIF3B mutation, we also identified a number of clinically relevant variants in this EAC patient sample. We observed a known TP53 hotspot mutation (Y220C) that destabilizes the TP53 protein at body temperaturesThe male-patient-derived fibroblasts used in this study were collected and derived with informed patient consent under a protocol approved by the Institutional Review Board at Stanford University Medical Center (IRB17576). Cells tested negative for mycoplasma and were cultured with DMEM supplemented with 10% fetal bovine serum (FBS). The deidentified male esophageal cancer sample was obtained from Stanford Cancer Institute's Tissue Repository and was exempt from IRB requirements by the Stanford Research Compliance Office. Investigators were not blinded to experimental groups, and no power calculation was performed before experiments to ensure detection of a prespecified effect size.6 cells, whereas the laser-capture-microdissected (LCM) tumor library started with approximately 150 μg of tissue (based on isolating ∼150 × 106 μm3 and assuming an average tissue density of 1.0 g/cm3). The quality of the starting total RNA was measured using Bioanalyzer, with RNA integrity number (RIN) values ranging from 8 for LCM-isolated tissue to 10 for LCM-isolated cells. For Simul-seq library preparations, ERCC spike in mixture A (Life Technologies: 4456740) was added per manufacturer's instructions before the ribosomal RNA depletion step.For the mixing experiments, yeast mRNA was obtained from Clontech (Clontech: 636312) and human genomic DNA was isolated using the DNA Mini kit (Qiagen: 51304). For all other Simul-seq experiments, total nucleic acids were extracted using the RNeasy Mini kit (Qiagen: 74104) per manufacturer's instructions, except the optional DNase I treatment was not performed. DNA and RNA were then quantified using the Qubit DNA HS and RNA HS , respectively. For fibroblast experiments, extraction began with 1 × 10Ribosomal RNA sequences were depleted from the total nucleic acid mixture using Ribo-Zero gold (Illumina: MRZG126) and following the manufacturer's instructions. To reduce potential hybridization to genomic DNA sequences; however, the standard 70 °C hybridization step was changed to 65 °C. Ribosomal RNA depletion began with the recommended amount of total RNA (1 μg for LCM tissue to 5 μg for fibroblasts). For 50,000 fibroblast experiments, ∼400 ng of total RNA was used. Following ribosomal RNA depletion, the total nucleic acid mixture was purified using RNA Clean and Concentrator 5 columns (Zymo Research: R1015) and quantified using high-sensitivity DNA and RNA Qubit reagents as above.2O. To remove secondary RNA structure, 6 μl of the eluate and 1 μl of the 3′ ligation adapter were first heated to 65 °C for 5 min and then immediately placed on ice. For ligation of the 3′ adapter to the RNA molecules, 10 μl of 3′ ligation buffer and 3 μl of 3′ ligation enzyme mix were added and incubated for 1 h at 25 °C in a thermal cycler with the lid heated to 50 °C. To reduce adapter–adapter ligation products, 1 μl of the reverse transcription primer (SR RT primer) and 4.5 μl of H2O were added to the 3′ adapter ligation reaction and incubated in a PCR machine for 5 min at 65 °C, 15 min at 37 °C, 15 min at 25 °C and held at 4 °C until the next step. To ligate the 5′ adapter, 1 μl of 5′ SR adapter, which had been previously heated to 70 °C and then placed on ice, along with 1 μl of 5′ ligation buffer and 2.5 μl of 5′ ligase enzyme mix were added to the 3′ adapter-ligated and SR-RT-primer-hybridized RNA. This reaction was incubated for 1 h at 25 °C with the lid heated to 50 °C and then placed on ice. First-strand cDNA synthesis was performed by adding 8 μl of first-strand reaction buffer, 1 μl of murine RNase inhibitor and 1μl of ProtoScript II reverse transcriptase to the previous mixture and incubating the reaction for 1 h at 42 °C with the lid heated to 50 °C. 48 μl of Ampure XP beads (Beckman Coulter: A63880), or 1.2× of the reaction volume, were then used to clean up the cDNA and transposed genomic DNA. The beads were incubated for 5–10 min with the DNA, washed twice with 80% ethanol and mixed with 26.5 μl of H2O to elute the DNA. PCR conditions varied depending on whether differential PCR was performed. DNA libraries were amplified using standard Nextera indexing primers. RNA libraries were amplified with a custom I5 indexing primer AATGATACGGCGACCACCGAGATCTA CACTATCCTCTGTTCAGAGTTCTACAGTCCG-s-A, where -s- indicates a phosphorothioate bond, and a standard I7 indexing primer. For differential PCR, 25.5 μl of the eluate was combined with 1.25 μl of each RNA indexing primer (10 mM stock) and 12 μl Nextera PCR Master Mix (NPM) and then thermocycled as follows: 72 °C for 3 min; 98 °C for 30 s; then two to seven cycles of 98 °C for 10 s, 62 °C for 30 s and 72 °C for 3 min; before a final hold at 4 °C. After this hold, the reaction was removed from the thermocycler and combined with 12.5 μl of a master mix comprising 2.5 μl of each DNA indexing PCR primer (5 mM stock), 5 μl of PPC and 5 μl NPM. This combined reaction was then subjected to five additional cycles using the same program described above. The fibroblast, LCM and 50,000 fibroblast Simul-seq libraries used two, four and seven cycles of RNA-specific PCR, respectively. The final libraries were cleaned using 66 μl Ampure XP beads as described above and eluted in 12 μl of H20. To quality control the dual-indexed libraries, we performed high-sensitivity Qubit DNA and Bioanalyzer assays prior to sequencing of paired-end 101 bp reads on Illumina HiSeq or MiSeq machines. A typical Simul-seq library will be approximately 10 ng/ml, with an average size distribution of ∼350 bp  or Illumina (Illumina: FC-121-1031). Simultaneous RNA fragmentation and DNA tagmentation was achieved by mixing 25 μl of TD buffer, 5 μl of TDE, 1 μl RNase III  and 19 μl of DNA/RNA consisting of 30-50 ng of genomic DNA and 10–100 ng of ribodepleted RNA. This reaction was incubated for 5 min at 55 °C, and the thermocycler was cooled to 10 °C before the reaction was placed on ice. 100 μl Ampure XP RNAclean beads (Beckman Coulter: A63987), or 2× the reaction volume, were then added to the reaction and incubated for 10–15 min to bind the nucleic acids. The beads were placed on a magnet stand until clear, washed twice with 400 μl of 80% ethanol and dried for 10 min at room temperature The total nucleic acids were eluted from the dried beads using 7 μl of H ∼350 bp . A detaiFor both DNA and RNA reads, Cutadapt v1.8.1  was used45 to hg19 and then realigned around indels with GATK IndelRealigner46. Next, base recalibration was performed with GATK BaseRecalibrator taking into account the read group, quality scores, cycle and context covariates. Variants were called with GATK HaplotypeCaller with the parameters–variant_index_ type LINEAR-variant_index_parameter 128000. VQSR was used to recalibrate the variants, first with GATK VariantRecalibrator and then ApplyRecalibration. For the cross-contamination analysis shown in DNA libraries were processed and analyzed using the Bina Technologies whole-genome analysis workflow with default settings. Briefly, libraries were mapped with BWA mem 0.7.5 software49 was then used to perform per-sample gene expression analysis. Finally, Cuffdiff was used to find differential expression between replicates and different library types. For cross-contamination analysis shown in RNA libraries were also processed and analyzed using Bina Technologies RNA analysis using default settings. Briefly, TopHat 2.0.11  was usedhttp://broadinstitute.github.io/picard) for the DNA and RNA sequencing libraries. Strand specificity and gene-body coverage were calculated with RSeQC 2.6.2 (10(FPKM + 1) expression values between Simul-seq RNA libraries and control RNA-seq libraries.Coverage plots were calculated from the Bina output. SNV and indel concordance between sequencing libraries was calculated using VCFtools v0.1.12  on all vQC 2.6.2 . For theDuplicates were removed from hg19-aligned reads using Picard v1.92, and Bedtools v2.18.0  was used53 was used to determine the total read counts for each ERRC transcript. Read counts were then normalized across transcripts and libraries using the RPKM methodology . ERCC RPKM measurements for Simul-seq and RNA-seq replicates were averaged, zero values were set to one and then log10 transformed. ERCC transcript data for Simul-seq and RNA-seq replicates is shown . The ddPCR reactions were then subjected to the following cycling program: 10 min at 95 °C; 40 cycles of 30 s at 95 °C and 1 min at 60 °C, 10 min at 98 °C; and a hold at 4 °C. Triplicate reactions were done for each sample, and quantitation was performed using QuantaSoft version 1.3.2.DNA:RNA ratios of between 5:1 to 10:1 are optimal for whole-genome and whole-transcriptome sequencing of human samples. ddPCR experiments were performed according to manufacturer's guidelines  using a Bio-Rad QX200 system. Briefly, custom qPCR assays were designed to the unique the DNA-seq and RNA-seq library adapter sequences and purchased from IDT as PrimeTime Std qPCR Assays . These a6 μm3 (or ∼150 μg) of esophageal adenocarcinoma tumor tissue. The LCM-isolated tissue was then subjected to the Simul-seq protocol; and 727,341,682 DNA and 191,398,961 RNA 101 bp paired-end reads were obtained using an Illumina HiSeq2000 machine. For all transcriptome analyses using Simul-seq RNA tumor data, 116,217,162 reads were analyzed.For LCM, 7 μm cryosections were placed onto 76 × 26 PEN glass slides (Leica: 11505158) and stored at −80 °C for up to 4 d. To guide the isolation process, serial sections were immunofluorescently stained with Keratin 8  and counterstained with Hoechst 33342 dye (2 mg/ml in PBS), marking the tumor epithelium and nuclei, respectively. On the day of laser capture, the LCM slides were stained with Cresyl violet according to the manufacturer's protocol . Immediately following staining, a Leica AS LMD system was used to isolate ∼150 × 10Somatic variant analysis was performed using Bina tumor-normal whole-genome calling workflow. Briefly, somatic variants with a Bina ONCOSCORE of greater than or equal to 5 were considered high confidence and reported. To identify somatic variants and generate the ONCOSCORE, Bina integrates JointSNVMix 0.7.5 , Mutect 58 was run on the tumor-normal paired genomic data. To refine the variant calls, we only reported SVs with greater than five supporting reads on both the 3′ and 5′ arms of the variant, which resulted in 142 total potential genomic SVs , CRESTomic SVs . Somatic fusions . Circos  fusions  was used61. GATK SelectVariants was then used to interrogate these heterozygous positions in the tumor VCF, classifying them as heterozygous or homozygous alternative. Heterozygous positions in the normal that were not present in the tumor VCF were considered homozygous reference and counted as LOH positions.For the LOH analysis, heterozygous positions in the normal were selected in the VCF file using SNPsift62. Briefly, GENOTYPE mode was run on a bam file derived from the paired normal genome with the following options: mbq = 20 mrq = 1 mdc = 5 htperc = 0.2. Next, ASE mode was run using a bam file from the tumor RNA with the following options: mbq = 20 mrq = 20 mdc = 10 pht = 0.01 pft = 0.01. This analysis was performed using an hg19 Ensembl transcript model and identified 21,797 transcripts—corresponding to 6,698 independent gene symbols—as exhibiting ASE  in the tumor RNA was calculated for heterozygous positions called in the normal using ASEQting ASE . Circos 63 was used to generate a pileup, and SNVs were identified using four criteria: mapped to a targeted region, allele read fraction of ≥10%, mapping quality of ≥10 and coverage of ≥500. Using these criteria, three variants in KIF3B were identified and subsequently validated using pyrophosphate sequencing  were amplified using the following primers: CATATGTCAAAGTTGAAAAGCTCAG and CTCGAGCTAGAGCCGAGCAAT CTCTTCCT. The PCR products were digested with NdeI/XhoI restriction enzymes and cloned into NdeI/XhoI-digested pET28a backbone, tagging the KIF3B motor domains on the N terminus. Recombinant KIF3B was purified using nickel affinity purification ). Lysates were pulse sonicated for three cycles of 18% amplitude (Bronson) for 5 s (0.5 s on and 1 s off), followed by 1 min on ice. Lysates were then cleared by centrifugation for 10 min at 4 °C and maximum speed. Cleared lysates were incubated with His-tag magnetic beads (Life Technologies: 10103D) for 1 h at 4 °C, washed 2× in washing buffer  supplemented with 250 mM ATP followed by an additional two washes in buffer excluding ATP. Beads were subsequently eluted in 25 mM PIPES, pH 8.0, 2 mM MgCl2, 125 mM NaCl2, and 250 mM imidazole. Kinesin ATPase end-point biochemical assays (Cytoskeleton: BK053) were performed in duplicate according to manufacturer's instructions with 0.4 μg of recombinant protein and increasing amounts of polymerized microtubules (see Full-length kinesin proteins exhibit poor solubility in bacteriafication . Brieflyules see .SuppSupplementary Table 1: Simul-seq and control library read counts and mapping rates.Supplementary Table 2: Somatic SVs for Simul-seq EAC tumor genomeSupplementary Table 3: Somatic, expressed gene fusions in Simul-seq EAC tumor genomeSupplementary Table 4: VCF of somatic SNVs for Simul-seq EAC tumor genomeSupplementary Table 5: VCF of somatic indels for Simul-seq EAC tumor genomeSupplementary Table 6: EAC tumor ASE analysis at heterozygous SNV positions in the normal genomeSupplementary Table 7: ASE of annotated tumor supressor genes harboring damaging germline variantsSupplementary Table 8: Simul-seq RNA and RNA-seq ERCC spike-in transcript quantificationSupplementary Table 9: Genomic regions of KIF3B locus targeted for resequencingSupplementary Table 10: Primer sets used in KIF3B targeted resequencing