Numb, APC, and WAF-1P21, key regulators of Notch/Wnt signaling and cell cycle progression, respectively. In this study, we aim to identify small molecule inhibitors of MSI1–mRNA interactions, which could block the growth of cancer cells with high levels of MSI1. Using a fluorescence polarization (FP) assay, we screened small molecules from several chemical libraries for those that disrupt the binding of MSI1 to its consensus RNA. One cluster of hit compounds is the derivatives of secondary metabolites from Aspergillus nidulans. One of the top hits, Aza-9, from this cluster was further validated by surface plasmon resonance and nuclear magnetic resonance spectroscopy, which demonstrated that Aza-9 binds directly to MSI1, and the binding is at the RNA binding pocket. We also show that Aza-9 binds to Musashi-2 (MSI2) as well. To test whether Aza-9 has anti-cancer potential, we used liposomes to facilitate Aza-9 cellular uptake. Aza-9-liposome inhibits proliferation, induces apoptosis and autophagy, and down-regulates Notch and Wnt signaling in colon cancer cell lines. In conclusion, we identified a series of potential lead compounds for inhibiting MSI1/2 function, while establishing a framework for identifying small molecule inhibitors of RNA binding proteins using FP-based screening methodology.RNA-binding protein Musashi-1 (MSI1) is a key regulator of several stem cell populations. MSI1 is involved in tumor proliferation and maintenance, and it regulates target mRNAs at the translational level. The known mRNA targets of MSI1 include  Post-transcriptional gene regulation occurs at the levels of pre-mRNA splicing and maturation, as well as mRNA transport, editing, storage, stability, and translation. This level of gene regulation is essential for normal development, but when dysregulated, contributes to diseases such as cancer. Post-transcriptional gene regulation is mediated by RNA-binding proteins, which are emerging new targets for cancer therapy.Drosophila and studied extensively for its role in sensory organ progenitor (SOP) cell lineage establishment [Drosophila msi1 loss-of-function mutants, a SOP cell divides to produce two daughter cells with low Notch signaling rather than one daughter cell with relatively high Notch signaling and one with low Notch signaling [One such RNA-binding protein is Musashi-1 (Msi1/MSI1), which was first identified in ignaling ,3,4,5,6.ignaling ,13,14,15ignaling ,12 and oignaling . These fNUMB, APC, and WAF-1P21 [MSI1 appears to function by binding to the 3′UTR of target mRNAs and thereby regulating protein translation ,18,19,20P21WAF-1 ,20,21,22Aspergillus nidulans [Previous efforts to identify small molecule inhibitors of protein-protein interactions have focused on proteins with well-defined binding pockets, while inhibitors of RNA-binding proteins were limited to proteins that bind to viral RNAs ,24,25. Inidulans  that inhMusashi-2 (MSI2) shares a high degree of sequence identity to MSI1 , functioNumb. In our initial binding assays, we used 2 nM of RNA as specified in previous publications [Numb RNA (FITCNumb) or control RNA (FITCCTL). As shown in FITCNumb but not FITCCTL bound to GB1-RBD1 as indicated by the increased polarization value. We further tested binding by competing the RBD1-FITCNumb complex with non-labeled Numb or control RNA. Numb RNA displaced the FITCNumb from the protein–RNA complex at a much lower Ki than the control RNA . RNA concentrations less than 1 nM produced such low fluorescent signals that FP values were not stable. FITC complex after 2 h incubation  and cubation D. Upon cFITCNumb complex or were completely negative. These six compounds were included in the later validation assays together with the five hit compounds to examine the structure–activity relationship (SAR).The screening was carried out in a 96-well format. We screened a total of 1920 small molecules from four different libraries A. Z’ facFITCNumb complex; Aza-9 showed the highest affinity towards GB1-RBD1. We thus focused our further validation studies on Aza-9.To further examine the initial hits, we tested compounds with similar scaffolds shown in An SPR assay with the protein GB1-RBD1 and not the RNA allowed us to evaluate the binding of the compound to the protein directly. As shown in Numb RNA in cells, we carried out an RNA pull-down assay using HCT-116 β/W cell lysate. Before we tested our compound in the assay, we tested whether biotinylated Numb RNA (biotinNumb) can pull down MSI1 protein from the cell lysate. We showed that biotinNumb pulled down MSI1 but biotincontrol could not  attenuated its binding to MSI1 . As described in our previous publication , using NSI1-RBD1 C. When mSI1-RBD1 C. ComputSI1-RBD1 D. BindinSI1-RBD1 C. In parFITCNumb RNA in FP  methyl labeled MSI2-RBD1. MSI2-RBD1 residues M23, F64, and K94 showed the most significant reduction in peak intensities  binding in FP and NMR assays as previously described . We showNA in FP A, and itensities B. These ensities  to the sensities C. The ILβ sheets . Our NMRβ sheets C and MSIβ sheets B and disCarrying out the same docking calculation using MSI2-RBD1, we find again that Aza-9 adopts a very similar binding mode as for MSI1-RBD1. Aza-9 is bound near residues K94, M23, and V95 shown in D, consisIn an 3--2,5-diphenyl tetrazolium bromide (MTT)-based cytotoxicity assay, free Aza-9 had no effect on the cell viability A, potentAXIN2, a direct downstream component of Wnt signaling. The levels of SURVIVIN mRNA, downstream of the Notch pathway, also decreased in DLD-1 but not HCT-116 cells, whereas SURVIVIN protein was decreased in both cell lines (MSI1 was observed [CYCLIN D1 (CCND1), mRNA and protein expression were increased. Direct targets APC and NUMB protein levels increased in both HCT-116 , thus we tested the binding of Aza-9 towards MSI2 and showed that Aza-9 disrupted the binding of MSI2 to ct roles ,46,47,48ct roles . HuR is ct roles . Aza-9 fAlthough Aza-9 and the other azaphilones we have tested were produced semi-synthetically from asperbenzaldehyde, our semi-synthesis mimics a natural process. Aza-7 is identical to sclerotiorin, which is produced by a number of fungi ,51,52, aWith respect to our findings, an obvious question is why would fungi produce natural products that inhibit RNA–protein interactions? Fungi compete with other fungi, protozoans, and bacteria in their natural environments. Many organisms, including bacteria, produce extracellular RNAs that are thought to provide a variety of selective advantages . It is qAn exciting aspect of the genomics era in natural products research is that we can now over-express genes to produce azaphilones and other valuable natural products. This allows us to produce natural products abundantly and cheaply. Furthermore, by interrupting biosynthetic pathways in organisms such as fungi, we can accumulate large amounts of intermediates such as asperbenzaldehyde and modify them semi-synthetically to increase their potency, efficacy, and medical value.NUMB, APC, and P21 mRNA, which leads to the up-regulation of both Notch and Wnt signaling pathways and promotes cell cycle progression. With Aza-9-liposome treatment, Aza-9 binds to MSI1/2, presumably releasing NUMB, APC, and P21 mRNA from their translational repression. Increased level of NUMB, APC, and P21 proteins will block Notch/Wnt signaling and cell cycle progression, respectively. In colon cancers, Wnt signaling played a major role in the tumor initiation and progression. Two colon cancer cell lines HCT-116 and DLD-1 used in our study have different genetic profile of APC and CTNNB1 genes that could lead to a different Wnt signaling response. For example, DLD-1 has a truncated APC thus cannot regulate β-catenin encoded by CTNNB1 gene [SMAD3 and TGFβR1 [Investigation of Aza-9-liposome functions showed that Aza-9-liposome inhibited colon cancer cell growth, induced apoptosis/autophagy and led to G1 accumulation of cells, with a modest down-regulation of Notch/Wnt signaling. Our hypothesis is MSI1 and/or MSI2 block the translation of NB1 gene . HoweverNB1 gene . We thind TGFβR1 ,57.In this study, we prepared PEGylated liposomal Aza-9, which facilities cellular uptake of Aza-9. One of our future directions is structure-based optimization of Aza-9 by introducing hydrophilic substituents or shortening the hydrophobic tail, with the aim of improving cell penetration and cytotoxicity to cancer cells with high levels of Musashi family proteins.Human colon cancer cell lines HCT-116, DLD-1, and RKO were obtained from American Type Culture Collection (ATCC) and are as described by Lan et al. ,40. CellFITCNumb complex was added to each well.The chemical libraries used in the initial screening contained three chemical libraries from the National Cancer Institute (NCI)  and our Homo sapiens RNA binding domain 1  of MSI1 were constructed with Mus musculus cDNAs under T7 promoter. MSI1-RBD1 proteins were expressed in Escherichia coli and purified, as previously described [pET21a-GB1-RBD1 (MSI1-RBD1) plasmids encoding the escribed . Proteinescribed ,36,40.FP, SPR and NMR assays were carried out according to the previous publication ,36,40. FNumb  was added and incubated in 4 °C. After 0.5 h, heat-shocked biotinylated-Numb  was added to each sample and incubated at 4 °C for 2 h, after which 50 μL of streptavidin beads were added and incubated for 2–16 h. Beads were washed three times (Roche), and protein sample buffer was added to the beads and boiled for 5 min. Supernatants were taken and loaded in SDS gels for western blot.RNA pull-downs were carried out according to manufacturer’s protocol with modifications . Briefly, HCT-116 β/W cells were plated on 100 mm dish on day 1. The next day, cells were treated with Aza-9 (20 μM) or DMSO for 6 h, and cell lysates were collected using buffer 1 from IP kit (Roche). Protein concentrations were measured for each sample, and streptavidin beads were added for preclearance and incubated at 4 °C for 3 h. After preclearance, for each sample, 500 μg of total protein was transferred to a new tube. For positive control, unlabeled 4 cells per well in a 48-well dish the day prior to transfection. Cells were transfected with 0.125 μg of either TOPflash or FOPflash reporter constructs and a pRL-TK Renilla luciferase plasmid to control for transfection efficiency and cell number. Transfections were performed with Lipofectamine 3000 , according to the manufacturer’s instructions. The next day, cells were stimulated with or without 20 mM LiCl and treated with Aza-9-lip or liposomes control. Cells were harvested and assayed using the Dual-Glo Luciferase Assay  24 h after treatment. All firefly luciferase values were normalized to Renilla control.HCT-116 cells were plated at a density of 4 × 10Aspergillus nidulans. One of the top hits, Aza-9, was further validated by SPR, NMR, and RNA-IP, which demonstrated that Aza-9 binds directly to MSI1–RNA binding pocket. We also showed that Aza-9 binds to Musashi-2 (MSI2) as well. To test whether Aza-9 has anti-cancer potential, we used liposomes to facilitate Aza-9 cellular uptake. Aza-9-liposome inhibits proliferation, induces apoptosis and autophagy, and down-regulates Notch and Wnt signaling in colon cancer cell lines. In conclusion, we identified a series of potential lead compounds for inhibiting MSI1/2 function, while establishing a framework for identifying small molecule inhibitors of RNA-binding proteins using FP-based screening methodology.In our effort to screening for Musashi-1 inhibitors, we identified a cluster of hit compounds that are the derivatives of secondary metabolites from


Modulation of m6A modifications relies on methyltransferases and demethylases. The discovery of binding proteins confirms that the m6A modification has a wide range of biological effects and significance at the molecular, cellular, and physiological levels. In recent years, techniques for investigating m6A modifications of RNA have developed rapidly. This article reviews the biological significance of RNA m6A modifications in the innate immune response, adaptive immune response, and viral infection.N However, studies of chemical modifications of RNA, which make up the “epitranscriptome,” are still in their infancy , 2. Currkaryotes . Here, w6A, which refers to a modification occurring at the sixth position of adenine (A) bases in RNA, is widely found in yeast, plants, Drosophila, mammals, and viruses [6A modifications are highly conserved and are mainly confined to the following consensus sequence: RRACH . m6A modifications are preferentially enriched in the long internal exons and 3′UTR regions of linear RNAs [6A mRNA modifications. METTL3 was the first writer identified as a component of a methyltransferase complex [6A modifications [6A on RNA [6A methyltransferase that targets pre-mRNAs and various noncoding RNAs [6A demethylation on mRNA. The fat-mass and obesity-associated protein (FTO) was the first nuclear RNA m6A demethylase to be identified, and it preferentially demethylates the m2 isoform  rather than m6A. Moreover, FTO reduces the stability of m6Am mRNAs [6A levels and impaired fertility arising from effects on spermatocyte apoptosis during meiotic metaphase [6A and participate in the degradation of downstream RNA as well as translation. Different readers produce different biological effects through different pathways. YTHDF1 and YTHDF3 recognize and bind to the modifications on RNA to directly modulate mRNA translation efficiency [6A that directly binds to m6A-modified RNAs [6A-modified RNA, m6A promotes the accessibility of hnRNP A2/B1 to certain binding sites [6A modification is dynamic and reversible, and the discovery of binding proteins confirmed that the m6A modification has a wide range of biological effects and significance [6A modifications in newly formed pre-mRNAs is the same as those on nuclear and steady-state cytoplasmic mRNAs [m viruses . m6A modear RNAs  and are ications . METTL14ications . The METications . Hakai aA on RNA . METTL16ing RNAs . Second,Am mRNAs . FTO is Am mRNAs . ALKBH5 Am mRNAs ; its knoetaphase . Third, ficiency . YTHDF2 ficiency . YTHDC2 ied RNAs . Howeverng sites . The disificance . Nonetheic mRNAs , which sic mRNAs .6A modifications occur at three different levels: molecular, cellular, and physiological [6A modification is inhibited, indicating that the level of m6A in a target mRNA is critical for nuclear export and intracellular distribution [6A-modified target genes [6A modifications determine the fate of mammalian embryonic stem cells (mESCs) [6A level, promotes self-renewal, and inhibits cardiomyocyte and neuronal differentiation [6A abundance stimulates mouse embryonic fibroblast (MEF) reprogramming into pluripotent stem cells, whereas decreasing the m6A levels inhibits this reprogramming [6A modification plays a powerful and precise regulatory role in cell developmental programmes. At the physiological level, reversible m6A modification has various consequences. For example, overexpression of the demethylase FTO results in increased food intake and obesity [6A modification is related to neural stem cells, brain development, Parkinson's disease, and mental illness [6A modification has been found to have an impact on tumour initiation and progression through various mechanisms, which have been covered in other reviews [The biological functions of RNA mological . At the ological . YTHDC1 ological . mRNAs oribution . YTHDF1 et genes , and YTHet genes . At the  (mESCs) . Indeed, (mESCs) , 23, andntiation , 23. Morgramming . These f obesity . In addi illness . Further reviews .6A modifications of noncoding RNAs (ncRNAs), and the role of m6A modifications in ncRNA remains to be further investigated. However, it is known that lncRNA and miRNA function can be regulated by m6A. For example, He et al. proposed that ALKBH5 can inhibit the motility of pancreatic cancer by demethylating the lncRNA KCNK15-AS1 [6A-induced lncRNA RP11 can trigger the dissemination of colorectal cancer cells by posttranslationally upregulating Zeb1 [6A modifications are associated with miRNA synthesis and function [6A modifications to the pre-miRNA transcript of the antioncogene miR-126a [6A modifications of AGO2 mRNA contribute to cellular ageing by regulating global miRNA synthesis [6A marks in mESCs and is essential for X-inactive specific transcript (XIST) activity [6A modified [In contrast, there are few reports on mNK15-AS1 ; m6A-inding Zeb1 . In addifunction , 30. FormiR-126a . SpecifimiR-126a . FurthermiR-126a , and m6Aynthesis . It has activity . Recentlmodified .6A modifications do not change the nature of base pairing, and thus, m6A cannot be directly detected by sequencing. In fact, the lack of sensitive methods for detecting RNA m6A modifications has constrained scientific interest in this field. First, within the context of the rapid development of next-generation sequencing technologies, methylated RNA immunoprecipitation (Me-RIP) for identifying m6A sites on mammalian RNA emerged in 2012 [6A polyclonal antibody; the mixture is immunoprecipitated by incubation with protein A beads, and the enriched m6A-containing pooled RNA and input RNA control are deep-sequenced [6A sites cannot be identified at the single-nucleotide level. Second, single-molecule real-time RNA sequencing and site-specific cleavage and radioactive labelling followed by ligation-assisted extraction and thin-layer chromatography (SCARLET) can accurately determine the precise location of m6A at any site in mRNA/lncRNA with single-nucleotide resolution [6A-containing candidate sites are specifically cleaved, and radiolabelling and site-specific ligation are then performed; the candidate residues containing m6A are separated from total RNA or polyadenylated mRNA (polyA+RNA) by nuclease digestion, and this mixture is subsequently analysed by thin-layer chromatography (TLC) [6A sites on a global, transcriptome-wide level. Third, a newer single-nucleotide resolution method termed m6A individual nucleotide resolution crosslinking and immunoprecipitation (miCLIP) can accurately locate m6A loci in the whole transcriptome at a single-nucleotide resolution level without any pretreatment of cells containing modified nucleotides, such as 4-SU [6A antibodies to RNA by ultraviolet (UV) radiation to form antibody-RNA crosslinks; reverse transcription of the crosslinked RNA results in highly specific mutations in the cDNA, which can be detected by sequencing and used to identify single m6A residues. However, the disadvantage of miCLIP is that it is not quantitative. Fourth, high-resolution melting (HRM), a high-resolution m6A mapping technique, directly detects base changes based on the melting characteristics of nucleic acids, allowing chemical or enzymatic information to be retained and avoiding sequence distortion [6A methylation sites, though the method captures only 16% of the m6A (ACA-containing) sites in the mammalian system [In 1958, RNA was first shown to contain modifications, which play important roles in biological functions . However in 2012 . Specifiequenced . Althougsolution . With thhy (TLC) . The dis as 4-SU . This testortion . Fifth, n system .6A modifications have biological significance for the innate immune response. First, m6A modifications have been demonstrated to promote dendritic cell (DC) activation and function [6A-modified RNA cannot activate TLR3, TLR7, or TLR8 [6A modifications can suppress the antiviral innate immune system by reducing type I interferon production following pattern recognition receptor (PRR) binding to nonself nucleic acids, such as viral RNAs [6A modifications have been demonstrated to further affect the expression of interferon-stimulated genes (ISGs) by repelling RNA-binding proteins such as G3BP1, G3BP2, and CAPRIN1 [6A has been identified in the mRNA of genes encoding several essential molecules of the innate immune system, including TRAF3, TRAF6, and MAVS [6A from the 3′UTRs of TRAF3, TRAF6, and MAVS mRNAs, resulting in decreased export of these transcripts from the nucleus [The immune system is the most effective weapon against pathogen invasion. The immune system detects and removes foreign matter and microorganisms and maintains homeostasis. Immune dysfunction is involved in almost all known human diseases, including infection, inflammation, cancer, and metabolic syndromes. When a person's finger is injured by a large splinter containing many bacteria, within a few hours, the area near the entry point of the splinter becomes red and inflamed. These symptoms are indications that the innate immune system has been activated. In many instances, activation of the innate immune system is so effective and quick that the adaptive immune system is never activated. Mobilization of the adaptive system requires time because B and T cells must be specifically produced through the process of clonal selection and proliferation. Posttranscriptional RNA modifications regulate RNA splicing, transport, translation, stability, and localization, indicating that RNA modifications are likely to play an important role in the immune response. Indeed, studies have reported that RNA mfunction , and depfunction . Second, or TLR8 , 44, and or TLR8 . Third, ral RNAs , 47. Depral RNAs , 47. In  CAPRIN1 . Fourth,and MAVS . ALKBH5  nucleus .6A modifications are also strongly associated with T cells and the adaptive immune response. First, RNA m6A modifications determine cell fate transition in mESCs and help CD4+ T cells differentiate into various T helper (Th) subtypes under stimulation with cytokines and antigens [6A regulates Th cell differentiation; in adaptive immune progenitor cells (naïve T cells), m6A targets the mRNA of the “gatekeeper” IL-7 signalling protein to control the homeostasis and differentiation of naïve T cells in response to various dynamic signals and external stimulation, ensuring homeostasis and expanding the biological effects of RNA m6A modifications [6A specifically controls the degradation rate of genes that respond immediately to various environmental stimuli to regulate T cell homeostasis and differentiation [6A modifications play a role in the generation and function of T regulatory cells (Tregs), which are an essential CD4+ subset of T effector cells that are responsible for immunosuppression in inflammation and in tumour microenvironments. A study by Tong et al. reported that conditional METTL3-knockout mice develop severe systemic autoimmune diseases, suggesting that the absence of m6A modifications induced loss of the suppressive function of Tregs [6A modifications are involved in the crosspresentation of tumour antigens [6A [+ T cells and antigen-presenting cells (APCs), and this process relies mainly on DCs [+ cell infiltration was observed in biopsies of patients with reduced YTHDF1 expression [6A modifications and T cells [6A modifications on T cells have broad implications for the adaptive immune response and may be involved in the development and progression of various immune-related diseases. The m6A eraser ALKBH5 is highly expressed in immune-rich organs such as the spleen and lungs [6A modifications in immune responses.RNA mantigens . Li et aications . Specifiications . These rntiation . Second,of Tregs . Third, antigens . YTHDF1 gens [6A . Therefogens [6A ; YTHDF1 y on DCs . In addipression . Fourth,pression . Dopaminpression , 56, sug T cells . Becausend lungs . Moreovend lungs . These f6A modifications are involved not only in the life cycle of the virus but also in the host response to viral infection, playing either a proviral or an antiviral role. First, m6A modifications in the Rev response element (RRE) of HIV promote binding between Rev and viral RNA, leading to enhanced viral RNA export [6A modifications depends on different stages of the viral life cycle [6A modifications play a positive role in enterovirus 71 (EV71) replication [6A modifications impair viral replication by blocking the packaging of viral RNA into new virions during flavivirus infections [6A modifications in KSHV remains controversial. One study reported that the binding protein YTHDF2 impairs KSHV lytic replication by promoting the degradation of viral gene transcripts [6A modifications, reporting that YTHDC1 is able to facilitate KSHV lytic replication by inducing the splicing of the replication transcription activator (RTA) [Recent works have demonstrated that mA export . ConsistA export . YTHDF ife cycle . Second,fe cycle . Third, lication . Fourth,fections . Flavivinscripts , and anoor (RTA) . Further6A modifications relies on methyltransferases and demethylases, and the discovery of binding proteins has confirmed that m6A modifications have a wide range of biological effects and significance. By summarizing the existing literature, we found that m6A modifications are widely involved in the immune response, including innate immune responses, adaptive immune responses, and viral infection. Compared to studies in tumour research, studies on RNA m6A modifications in immunity are lacking. With the rapid development of technologies to detect RNA m6A modifications, future studies will help to reveal the correlation between RNA m6A modifications and immune diseases.Currently, 172 different modifications of RNA molecules have been identified. However, the lack of a sensitive technique for the detection of RNA modifications has resulted in limited scientific research in this area. The modulation of m


In analogy to split-protein systems, which rely on the appropriate fragmentation of protein domains, split aptamers made of two or more short nucleic acid strands have emerged as novel tools in biosensor set-ups. The concept relies on dissecting an aptamer into a series of two or more independent fragments, able to assemble in the presence of a specific target. The stability of the assembled structure can further be enhanced by functionalities that upon folding would lead to covalent end-joining of the fragments. To date, only a few aptamers have been split successfully, and application of split aptamers in biosensing approaches remains as promising as it is challenging. Further improving the stability of split aptamer target complexes and with that the sensitivity as well as efficient working modes are important tasks. Here we review functional nucleic acid assemblies that are derived from aptamers and ribozymes/DNAzymes. We focus on the thrombin, the adenosine/ATP and the cocaine split aptamers as the three most studied DNA split systems and on split DNAzyme assemblies. Furthermore, we extend the subject into split light up RNA aptamers used as mimics of the green fluorescent protein (GFP), and split ribozymes. It eet al. in 1992 by in vitro selection , responsible of binding and inhibiting thrombin. The sequence 5′-GGTTGGTGTGGTTGG-3′, called 60-18[15]   . Then, if 0.5 nM . This apf 0.5 nM  but is pf 0.5 nM , determif 0.5 nM .et al. designed a new fluorescence-based strategy by using a water-soluble polycationic polymer, hexyl)-2,7-fluorenylene ethynylene]-alt-co-} tetraiodide, PFEP), having a high fluorescence emission, and two fragments of the 15-mer thrombin binding DNA aptamer, one of them being labelled with fluorescein  phenomenon. However, the presence of thrombin triggers the formation of the G-quadruplex structure that decreases the interaction between the polymer and the fluorophore and results in a significant reduction of the FRET signal. Compared with the full-length aptamer, this split aptamer-based sensing strategy is isothermal and increases the possibility of forming the G-quadruplex upon thrombin addition, and thus the sensitivity (LOD = 2 nM). A similar approach using identical split aptamer fragments adsorbed on graphene oxide (GO)  that could not be achieved with the intact aptamer.Highly sensitive aptamer-based fluorescent sensors for thrombin have been widely described . In orden Figure  50). In. Inet alide (GO)  took advide (GO) ,53. In tMore recently, a highly selective and sensitive method that combines fluorimetry and colorimetry has been developed . The str32+ is the most used ECL reagent and has been employed in conjunction with silica nanoparticles to develop an aptamer-based ECL sensor for thrombin detection (Ru-SNPs)  is a process that can emit light when species generated at the surface of electrodes undergo high-energy electron-transfer. ECL has received increasing attention in biomolecule analysis due to its efficiency, high sensitivity and wide linear range. Ru(bpy)Ru-SNPs) . An illuide link . In the ide link . Apart fvia polyA-Au interactions , discovered in parallel by Lohmann, Fiske and Subbarow in 1929 ,63, is is Figure  64). A . A in viM Figure  33). Al. Alin viM Figure . To the The adenosine DNA aptamer was cut into two halves to develop a label-free method for selective detection of adenosine. A 21 nucleotides homo dA sequence was added to the first fragment to serve as a template for Klenow fragment polymerase  that is used as an energy donor . In. Inet alvia FRET from AuNPs and gold nanoclusters-linked aptamer fragments  that served as a space modulator . The sysaptamers . Accordiaptamers  the two aptamers .A method widely used for studying biomolecular interactions is SPR spectroscopy that allows to detect refractive index (RI) changes on the surface of metal nanoparticles when the ligand binds to the receptor . This phet al., in which one fragment is immobilized at its 5′-terminus on a gold film, whereas the second fragment is conjugated to AuNPs . In. Inet alet al. in the late 1990s  ,86–88. ODNA can be used as a template to guide and promote chemical reactions owing to the Watson–Crick interaction of two strands that allows to bring the two reagents closer, increasing the effective molarity of the reactants and facilitate the reaction. Because of its biocompatible reaction conditions   azide–alIn most cases, the DNA-templated reaction is directed by the association between the two strands according to Watson-Crick affinity  but, in N-hydroxysuccinimide covered microplate to form an amide link , applicable to small-molecule detection . First, k Figure . Then, tk Figure . This obThe split aptamer concept is advantageous in terms of easier synthesis and delivery of the nucleic acid strands constituting the aptamer, but on the other side harbors the risk of a decrease of target affinity and low sensitivity. This problem was addressed with a recently developed cooperative-binding split aptamer (CBSA) having two binding sites . The firThe aptachain concept relies on splitting an aptamer into two overlapping strands able to assemble upon ligand binding. The nature of the cocaine aptamer makes it an ideal candidate for such an assembly. Interestingly, it has been shown that the cocaine aptamer binds quinine with an affinity that is 30- to 50-fold higher than cocaine ,108. ThiA similar approach was used recently for target induced construction of a hand-in-hand RNA nanowire. In the absence of theophylline as the specific ligand, RNA split aptamer fragments were designed to be stable hairpins. When theophylline was present, hairpin opening of the RNA probe and subsequent assembly of an RNA nanowire was triggered. The nanowire was captured on an electrode interface and sensed with silver nanoparticles as electrochemical species (LOD = 50 nM) .in vitro selection methods, many deoxyribozymes have been evolved to catalyze RNA cleavage, RNA and DNA ligation, and a variety of covalent modification reactions of nucleic acid substrates . T. Tin vits Figure . The fir DNAzyme ,113. Mos DNAzyme . Anotherter bond . The useter bond ,116–120.Multicomponent Nucleic Acid enzymes, and proved their high efficiency for nucleic acid detection and mismatch discrimination , Lu et al. developed a ligation-triggered DNAzyme cascade by combining a split DNAzyme with a catalytic and molecular beacon (CAMB) strategy . The amount of newly formed DNAzyme was found being directly related to the concentration of the cofactor ATP or NAD+. The addition of an invasive DNA frees the 8–17-DNAzyme, which subsequently is hybridized with a hairpin-structured molecular beacon substrate. Addition of the metal co-factor activates the DNAzyme and cleaves the molecular beacon substrate, thereby producing a significant increase of fluorescence. The LOD was found to be 100 pM for ATP and 50 pM for NAD+.With the purpose of detecting ATP or nicotinamide adenine dinucleotide  and lipopolysaccharide (LPS)  . The desde (LPS) . In the e Figure D1. In the Figure D2. The pe Figure D3. In the Figure D4. The l2+ detection (2+-dependent split DNAzyme (two fragments), a binding DNA, a hairpin DNA and a caged substrate, and is also based on colorimetry  supported by the formation of T–Hg2+–T base pairs, thus resulting in the formation of an active DNAzyme able to cleave the caged substrate and release segments E and C–D. The C–D segment will then bind to AuNPs forming an aggregate network that becomes blue, allowing detection of Hg2+ by the naked eye. Segment E can initiate another signal amplification process by opening the hairpin containing one part of the split DNAzyme leading to signal amplification with a LOD value of 10 pM. Furthermore, split DNAzymes have been used to sense miRNA in living cells. The system relies on AuNPs functionalized with a 3′-FAM-labeled substrate strand hybridized to the two fragments derived from the Mg2+-dependent 10–23 DNAzyme, one of them carrying a quencher at its 5′-end . I. I2+ detet al. in 1998  (ABTS2−). The first split DNAzyme was divided into two fragments in a 3:1 split mode , 4-dimethylamino-benzylidene imidazolinone (DMABI), 2-hydroxybenzylidene imidazolinone (2-HBI) and 3,5-difluoro-4-hydroxybenzylidene imidazolinone (DFHBI) Figure  were synelection . The brielection . In the  . CSpinach systems have been used for the detection of small molecules  and specThe use of light up aptamers in split scenarios has potential in particular for the visualization of RNA assembly. To this end, Spinach was cut in two fragments that, upon appropriate interaction, would form the full length aptamer . In ordeSplit systems can also be utilized for RNA self-cleavage detection and quantification. Thus, the hammerhead ribozyme (HHR) has been combined with one of the Spinach aptamer fragments Figure . The Spiet al. developed a Universal Split Spinach Aptamer (USSA) probe able to bind DNA or RNA targets independent of their sequences . A. A191). Catalytic Hairpin Assembly RNA circuit sensor that is Genetically Encoded (named CHARGE) was designed to detect specific RNA molecules inside living cells with high sensitivity  . The thein vivo detection methods. Ribozymes are RNA molecules that can catalyze a wide range of reactions, although ribozymes occurring in nature are limited to catalysis of trans-esterification, hydrolytic or peptidyl transfer reactions -strand of the lite RNA , the terlite RNA .Tetrahymena thermophila is an RNA catalyst that supports mRNA self-splicing  choice of the split site, (ii) stability of the split aptamer/nucleic acid enzyme target complex and (iii) sensitivity of the split system.et al. has addressed this problem by studying split aptamers with broken initial small molecule binding pockets, and demonstrating, in wet lab experiments as well as in silico, that biorecognition and binding capabilities are preserved  and experimental analysis is a very important task. This requires the understanding of the aptamer/nucleic acid enzyme target complex including the role of individual functional groups of nucleobases and of the sugar-phosphate backbone. In order to maintain the functionality of the system, splitting is usually restricted to functionally dispensable sites. Such sites are usually available in DNAzymes and ribozymes, in aptamers however, they are often missing. Recent work by Wang reserved . Thus, ti.e. extension of the individual fragments by additional nucleotides that by complementary base pairing would assist assembly and increase stability of the split aptamer/nucleic acid enzyme target complex. Instead of additional nucleotides also other functionalities that support target-induced fusion of the fragments can be used. A prominent example is the work by Jin et al. (Compared to the parent full-length nucleic acid strand, the individual fragments of a split system often have lower affinity to the target, which results in reduced stability of the aptamer/nucleic acid enzyme target complex. Furthermore, there is a higher entropic cost of complex formation, due to the fact that two or more fragments need to assemble instead of only one nucleic acid strand that binds to the target. Stabilization of the split system can be achieved by structural manipulation, n et al.  describen et al. ,102,103.The problem of limited affinity and stability of split aptamer/nucleic acid enzyme target complexes is also mirrored in reduced sensitivity. Although impressive sensitivity has been demonstrated in some cases Table , there iSplit aptamers and ribozymes/DNAzymes are at the initial stage of design and application. The concept of split aptamers/nucleic acid enzymes involves dissecting the parent full length strand in a series of two or more independent and non-functional fragments, which in the presence of the specific target would assemble to form the functional entity. Thus, in comparison to full length functional nucleic acids, split systems are easier to synthesize, and due to their smaller size are less prone to form unwanted secondary structures, which might deliver false-positive or non-specific signals in the absence of the target. The ideal design would include that the fragments of the split system are brought in close contact and deliver a signal only when the target is present. Aptamers are the key elements for detecting small molecules or proteins, whereas nucleic acid enzymes have been applied mainly for detection of specific nucleic acid sequences or metal ions. The combination of both, aptamers and nucleic acid enzymes, into aptazymes is an appealing concept of signal enhancement by the multiple turnover of the enzyme that amplifies the binding event of the target to the aptamer region into multiple reaction products used for readout.Overall, the design and application of split aptamers and nucleic acid enzymes in biosensing applications is still in its infancy and remains challenging. Further improving the stability of split nucleic acid target complexes and with that the sensitivity is an important task. In addition, fast and practical approaches based on fluorescence, chemiluminescence, colorimetric or electrochemical detection need to be further implemented in split aptamer/nucleic acid enzyme assays to achieve efficient working modes. Nevertheless, the so far reported functional assemblies derived from aptamers and ribozymes/DNAzymes, impressively demonstrate the proof of principle, and pave the way for deeper implementations and exciting new developments in this compelling and emerging field.


Nowadays a variety of biosensors are widely used in different fields, including biomedical diagnostics and self-testing. Nucleic acid-based biosensors are typically applied to detect another nucleic acid, proteins, ions, and several other types of compounds. It is most promising to develop simple and effective biosensors for the use in situations where traditional methods are not available due to their complexity and laboriousness. In this project, a novel smart deoxyribozyme-based fluorescent sensor for the detection of androgen receptor mRNA was developed. It consists of several functional modules including two deoxyribozymes 10–23, an RNA-dependent split malachite green aptamer, and an oligonucleotide platform. Deoxyribozymes specifically release a 27-nucleotide RNA fragment that is readily available for the interaction with the aptamer module. This solves a problem of secondary structure in hybridization with the target sequence of full-length mRNA. It was shown that within 24 hours the proposed sensor specifically recognized both a synthetic 60-nucleotide RNA fragment (LOD is 1.4 nM of RNA fragment at 37 °C) and a full-sized mRNA molecule of the androgen receptor. The constructed sensor is easy to use, has high efficiency and selectivity for the RNA target, and can be reconstructed for the detection of various nucleic acid sequences due to its modular structure. Thus, similar biosensors may be useful for the differential diagnosis. The fast and precise diagnostics of diseases are one of the key factors that allow choosing the most effective method of treatment. Disease markers can be found at a few different levels, including DNA, RNA, proteins, and small molecule metabolites. Today, along with other methods in clinical diagnosis biosensors are ubiquitously used in the biomedical field.The first prototype of a biosensor was invented by Leland Clark and Champ Lyons in 1962 as an amperometric Clark electrode, covered by immobilizing enzyme glucose oxidase, for the detection of glucose [2+, but for many targets it averages in the 1–10 nM range [Unlike proteins or antibodies the nucleic acid-based biosensors (NAs) can be easily commercially synthesized, they are smaller, more stable, and can be repeatedly used without losing their binding capability  with sennM range .Although the diversity of NAs is very large, they can be divided into DNA-based biosensors, for example, molecular beacon or TaqMan probes, deoxyribozyme-based biosensors , and aptA serious problem for the detection of full-sized nucleic acids is the secondary structure, which interrupts the access of sensors to the binding site. For single-stranded RNA this problem may be partially solved by including additional substrate-delivering strands into the biosensor . HoweverThe AR  belongs to the steroid nuclear receptor superfamily, capable of being activated after a direct interaction with nuclear DNA and works as a transcription factor . Among tLaboratory diagnostic methods may easily detect systemic hyperandrogenism, however, the measurement of local androgens changes or AR expression is still a serious problem and requires the development of additional test systems. Therefore, we have chosen AR mRNA as a target for our sensor. The design of SDFS included a number of functional advantages over most known biosensors and has the potential to solve the problems mentioned above.The human AR gene is located on the X chromosome at Xq11_12 and is encoded by eight exons. The first exon contains polymorphic CAG microsatellite repeats and codes a variable length of the N-terminal domain (NTD). In vitro studies demonstrated that the progressive expansion of the length of the CAG repeat in NTD decreased its transactivation function. Exons 2 and 3 code the central DNA-binding domain and exons 4 to 8 code the C-terminal ligand-binding domain –15. Therhttps://blast.ncbi.nlm.nih.gov/Blast.cgi).Based on the results of the bioinformatics analysis, an RNA sequence of 60 nucleotides (nt) was selected as a target . This sequence was located in the conserved exon 1, position 1–2140 nt. The specificity of 60-AR_RNA for the human androgen receptor was further verified using the BLAST algorithm (http://www.nupack.org/).We proposed the model of SDFS  developeFor our sensor, a malachite green aptamer (MGA) modified by Kolpashchikov  was chosIn the SDFS structure split MGA has two RNA-binding sequences, which are complementary to the target 60-AR_RNA, and connected with T2 and T3 strands through polythymidine linkers . The MGAAfter hybridization between SDFS and 60-AR_RNA we expected to see a specific cleavage of target mRNA by Dz1 and Dz2, which are parts of T1 and T4 strands, respectively, that leads to the release of a short 27-nt fragment from 60-AR_RNA  and G ne2 all three catalytically active molecules started to cleave 60-AR_RNA at 37 °C already in 6 hours.Due to the close proximity of “GU” cleavage sites in the selected 60-AR_RNA fragment, we decided to use asymmetric Dz1 design with an extremely short left RNA-binding part (4 nt). In cleavage tests with the synthetic 27-nt and 46-nt RNA fragments it was shown that for Dz 10–23 an optimal length of RNA-binding parts were 7-nt right/7-nt left . Given tTo estimate the functional activity of the SDFS we simultaneously evaluated the biosensor fluorescence intensity and the efficiency of the target RNA cleavage in the presence of SDFS under the same conditions. The complete assembled SDFS (100 nM), mix of Т1–Т5 (100 nM of each strand) without annealing and mix of Т2–Т3 (100 nM for each chain) with integrated MGA, also without annealing, were incubated for 6 h or 24 h at 37 °C, 25 °C, and 4 °C with 60-AR_RNA (fluorescence assay) or for 6 h at 37 °C with FAM-60-AR_RNA (cleavage assay). The concentration of the malachite green dye was 25 μM. After incubation fluorescence measurement was conducted using fluorescence spectrophotometry (610/648 nm) .According to the densitometry analysis of PAGE, after 6 h of incubation at 37 °C around 90% of FAM-60-AR_RNA were cleaved by one or both deoxyribozymes in the composition of complete SDFS, and 70% were cleaved by the mixture of separate T1–T5 strands.In the fluorescence study several temperature conditions were chosen as optimal parameters for deoxyribozyme (37 °C) and MGA (4 °C) activity, calculated by NuPACK. The temperature of 25 °C was chosen as a compromise temperature. The observed results showed that after 24 h of incubation at 37 °C and 1 h of cooling at 4 °C, the effectiveness of SDFS was highest among the tested parameters. Cooling was an essential part of sample preparation still 4 °C was an optimal temperature for MGA to assemble into the complex with the dye molecule. In such conditions the increase of fluorescence signal was 13 times higher than the signal demonstrated by individual MGA strands and 5 times higher than the signal given by unassembled SDFS strains . At 25 °Selectivity of SDFS cleavage activity in relation to 60-AR_RNA was tested with two random RNA sequences  demonstrFurthermore, even after 6 h of incubation at 37 °C the intensity of the fluorescent signal in the sample containing the assembled SDFS with 60-AR_RNA was 10 times higher than the signal demonstrated by individual MGA strands, and 5 times higher than the signal given by unassembled SDFS strands  of SDFS. For this experiment, samples containing 100 nM of annealed SDFS and 25 μM of malachite green dye in the same buffer were incubated with different amounts of 60-AR_RNA  for the above-mentioned times and temperatures. According to the obtained data, the LODs of SDFS were 1.4 nM for 24 h at 37 °C, 3.5 nM for 24 h at 25 °C , and 1.6These data proposed our biosensor as a suitable agent for the rapid detection  or detection at room temperature (but for longer periods of incubation).2) [Despite the fact that MGA has long been known, there is still insufficient experimental data on the sensitivity of it. It was mentioned that single harpin MGA increased the fluorescence of the malachite green dye by more than 2000-fold  upon bin2) .To investigate the ability of the proposed SDFS to selectively detect a full-length AR RNA we performed experiments on total RNA that was extracted from human dermal papilla cells (HDPC) obtained from the cell culture collection of the Koltsov Institute of Developmental Biology of the Russian Academy of Sciences . These cells demonstrated a high level of AR mRNA expression  for the current task optimization. Proposed SDFS design used malachite green dye, which is easily available and cheap, but today it is not too often applied for the detection of nucleic acids. We showed that SDFS can be used to efficiently detect at least 60 nt AR mRNA fragments both at 37 °C and at room temperature (25 °C) with different sensitivity and incubation times. Thus, by varying the test setup time and the sensor/target ratio, it is possible to achieve design optimization for various tasks, and the ability to recognize full-length mRNA makes our sensor promising for further development.The next step in this work will be the optimization of the SDFS for the detection of AR mRNA into a biological material.File 1Detailed experimental description.


SRRM4). Overexpressing SRRM4, known for regulating ME inclusion in mRNAs critical for neural differentiation, in human HEK293 cells resulted in the biogenesis of over 2000 novel ME-circRNAs, including ME-circEIF4G3, and changes in the abundance of many canonical circRNAs, including circSETDB2 and circLRBA. This shows SRRM4, in which its expression is correlated with poor prognosis in gliomas, acts as a bona fide circRNA biogenesis factor. Given the known roles of MEs and circRNAs in oncogenesis, the identification of these previously unrecognized ME-circRNAs further increases the complexity and functional purview of this non-coding RNA family.High-throughput RNA sequencing (RNA-seq) and dedicated bioinformatics pipelines have synergized to identify an expansive repertoire of unique circular RNAs (circRNAs), exceeding 100,000 variants. While the vast majority of these circRNAs comprise canonical exonic and intronic sequences, microexons (MEs)—which occur in 30% of functional mRNA transcripts—have been entirely overlooked. CircRNAs which contain these known MEs (ME-circRNAs) could be identified with commonly utilized circRNA prediction pipelines, CIRCexplorer2 and CIRI2, but were not previously recognized as ME-circRNAs. In addition, when employing a bespoke bioinformatics pipeline for identifying RNA chimeras, called Hyb, we could also identify over 2000 ME-circRNAs which contain novel MEs at their backsplice junctions, that are uncalled by either CIRCexplorer2 or CIRI2. Analysis of circRNA-seq datasets from gliomas of varying clinical grades compared with matched control tissue has shown circRNAs have potential as prognostic markers for stratifying tumor from healthy tissue. Furthermore, the abundance of microexon-containing circRNAs (ME-circRNAs) between tumor and normal tissues is correlated with the expression of a splicing associated factor, Serine/arginine repetitive matrix 4 ( In its simplest terms, RNA splicing converts precursor mRNA into mature mRNA through the removal of introns and sequential ligation of canonical exons. The RNA splicing machinery, called the spliceosome, is a large and dynamic ribonucleoprotein complex consisting of small nuclear RNAs and approximately 80 distinct proteins ,2. Like Alternative splicing is a dynamic, well-orchestrated, and cell-type specific process which play critical roles in cell differentiation, maintenance of stem cell pluripotency  and geneThe most common alternative splicing events in humans are exon skipping/inclusion (>40% of variants), use of alternative splice sites, and intron retention. While the size of exons and their flanking introns can impact the profile of alternatively spliced transcripts, in the central nervous system, it has been reported that the inclusion of short exons is more frequent ,9. The mUbx gene. While found sporadically since that time, it was not until 2003 through a combination of bespoke computational analysis on a reference databases of full-length mRNA sequences, that MEs were systematically identified in a range of model species, including humans . C. C25]. CIt has emerged that alternative splicing is a critical factor in the initiation and progression of human pathologies, including cancer ,31. MutaA number of protein factors have been identified that contribute to circRNA biogenesis and a variety of circRNAs have been identified containing permutations of canonical exons ; yet theFor all primary tissue sourced for these experiments, written informed consent was obtained from each subject or from their guardian. Specimens were received from the SA Neurological Tumor Bank (SANTB) which is supported by Flinders University, Flinders Foundation and The Neurosurgical Research Foundation. The ethics for this project is approved by the Central Adelaide Local Health Network Human Research Ethics Committee (CALHN HREC) with approval number HREC/17/RAH/284. The SANTB is approved by the Southern Adelaide Clinical Human Research Ethics Committee (SAC HREC) with approval number 286.10. Resected tumor tissue was processed in theatre, placed into sterile cryovials and immediately snap-frozen in liquid nitrogen to preserve RNA integrity and histology. Any non-pathological  brain tissue that was removed during surgery, in order to access the tumor, was collected and processed in a similar manner. Clinical grading was performed by SA Pathology and classified according to the WHO classification of tumors of the central nervous system .CircRNA sequencing was performed on 20 tissue samples collected from the South Australian Neurological Tumor Bank with informed patient consent. This included 15 primary gliomas, with five grade II, five grade III, and five grade IV (GBM) tumors as determined by histopathological grading  and 5 heRNA was harvested 48 h post-transfection using TRIzol™  & Direct-zol™ RNA miniprep kit  with on-column DNase I treatment. Ten micrograms of RNA were digested with 20 U Ribonuclease R  at 37 °C for 30 min. RNA was subsequently purified by RNA MinElute columns  as per Conn et al. . RNA-seqReads were mapped against the human reference genome (hg19) using the STAR spliced alignment algorithm  version. The resFor identifying ME-circRNAs, we utilized the known MEs present in linear RNAs from Irimia et al. . Firstlyhttps://github.com/gkudla/hyb), and codes can be provided upon reasonable request.To identify novel ME-circRNAs, at the beginning of the Hyb analysis we permitted reads of 3-30 nt in-between all chimeric reads. Once identified, the chimeric reads identified as backspliced circRNAs were extracted and filtered to determine microexon length (if present) and sequence for further mapping and analysis of these ME-circRNAs. Calculations of circRNA counts was performed using the merging program within the Hyb package. Format of Hyb-identified circRNAs was then transformed into the more widely used output format of CIRCexplorer2 to contain information on chromosome location, gene name, count, and included exons. This format was used to compare the results to CircExplorer2 and CIRI2. The Hyb package is available at Github  values rather than counts in order to avoid preference to samples with larger library sizes. Using the edgeR package , we calcp-adjusted < 0.01. Volcano plots were generated with EnhancedVolcano R package [The filtered read counts were normalized using DESeq2 median of ratios  method a package  and heat package .2 in air in DMEM  supplemented with 10% v/v FBS  and 1 mg/mL Antibiotic-Antimycotic . Cells were passaged with TrypLE express .HEK293 cells were cultivated at 37 °C with 5% COEcoRI and EcoRV , ligated, and transformed into TOP10 chemically competent E. coli. Sanger sequencing was performed to validate the overexpression construct. Overexpression of ME-circEIF4G3 was performed by using 800nt, reverse complementary introns flanking the circRNA exons (Exons 6a-10) and cloned into pcDNA3.1::FLAG as per [Full-length SRRM3 (HsCD00813375) and SRRM4 (HsCD00295084) in pENTR223.1 were obtained from DNASU Plasmid Repository. The coding sequence of each gene, lacking the termination codon, was amplified from this vector using Phusion DNA polymerase . The PCR products and pcDNA3.1::FLAG  were digG as per ,54. Sang® reverse transcription kit (Qiagen). After RT, QuantiTect SYBR® Green PCR Kit  was used for qRT-PCR as per [RNA, either total RNA or RNase R-treated RNA, harvested using TRIzol™  & Direct-zol™ RNA miniprep kit  with on-column DNase I treatment was reverse transcribed with QuantiTectR as per . RNA wasTotal soluble protein was harvested from HEK293 cells using RIPA buffer with 1× protease inhibitor cocktails (mini-EDTA free) and phosphatase inhibitor cocktails  with western blotting performed as per Conn et al. . Anti-FLPurified RNA from healthy and glioma tissues underwent digestion with Ribonuclease R (RNase R) to degrade linear RNAs and enrich for circRNAs. Validation of this digestion was achieved by performing RT-PCR on cDNA from RNase R-digested, or mock-treated RNA. In each case, the linear RNA targets were depleted following RNase R digestion, while known circRNA targets could be amplified . The RNACircRNAs were predicted from these libraries using three distinct pipelines, CIRCexplorer2 , CIRI2  and Hyb circGLIS3, was also previously shown to be more highly expressed in GBM compared to normal tissue [Interestingly, despite the distinct population of circRNA identified between the three pipelines, the PCA plots for the unfiltered lists are similar and each showed a clear separation between healthy and grade IV (GBM) samples c. Howevel tissue . While bSUPT5H which is incorporated into reads spanning canonical exons 4-5 —defined herein as an exon comprising 3–30 nt in length—into circRNAs may occur within the body of the circRNA or at the backsplice junction a. Therefxons 4-5 .REST mRNA could not be detected following RNase R digestion in any of the healthy or tumor samples, or by RT-PCR  overlapping our high-confidence circRNAs with, on average, 8.5% of these located at either the 5′ or 3′ exon comprising the circRNA backsplice junction and the remainder within the body of the circRNA . As deply RT-PCR , while ca et al. . The cirThis is the first report, to our knowledge, of ME-cirRNAs, with CIRCexplorer2, CIRI2, and Hyb identifying previously annotated MEs in the reference genome, rather than new ME-circRNAs. As this indicates there is greater complexity within the cellular repertoire of circRNAs than previously appreciated, we expanded our search to identify de novo MEs in this circRNA-seq data.The Hyb pipeline was originally designed to identify de novo RNA chimeras in an unbiased manner from RNA-seq , and hasbona fide ME-circRNAs.As the first report of MEs in circRNAs, we performed two in silico analyses to assess the predictive accuracy of the Hyb pipeline. Taking all reads supporting ME-circRNAs using the Hyb pipeline across the 19 brain tissue samples , we isolated the ME sequence. These were then either (1) randomly shuffled into the backsplice junction of one of the circRNAs (without rearrangement of the ME sequence) or (2) the ME sequences (>6 nt in length) was scrambled and reinserted into the same circRNA. These tests were to mimic an artefactual or random inclusion of a sequence which could arise by chance or library preparation artefact and give rise to false positive ME-circRNAs. We then aligned these shuffled or scrambled ME-circRNAs with the original ME-circRNA reads from the Hyb output. If these shuffled or scrambled ME-circRNA reads were still detected at high levels, then our Hyb pipeline could not be considered highly accurate due to a high false positive rate. On the contrary, only 172 shuffled ME-circRNA reads (1.44%) and 38 scrambled ME-circRNA reads (0.3%) could be found by chance in our ME-circRNA database. This suggests a predictive accuracy exceeding 98.5%, providing confidence in the Hyb pipeline for identifying EIF4G3 gene (circEIF4G3) and the equivalent ME-circRNA (ME-circEIF4G3) incorporating a 21nt ME  could be detected with 16 and 17 reads, respectively, in the healthy brain tissue of GBM patient #170 and 3 and 0 reads in the matched GBM tumor. This provides evidence that Hyb is the only pipeline currently with the capacity to capture this non-trivial panel of potentially functional ME-circRNA candidates.One example of a novel ME-circRNA is evident from the trimmed reads from the 4G3 gene c. For thME-circEIF4G3  and ME-circRIMS1 which also incorporates a 30nt ME at the backsplice junction between exons27-29. However, for the remaining ~75% of ME-circRNAs, these did not have a cognate circRNA, suggesting a large proportion of mutually-exclusive circRNA splicing events with respect to MEs.For the de novo ME-circRNAs identified by Hyb, we wanted to see how many cognate circRNAs were present which shared the same backsplice junction as a ME-circRNA, but lacking the ME. We found 629 examples (24.9% of ME-circRNAs) where both the circRNA and the ME-circRNA were present d. In addrcEIF4G3 c, anotheWe sought to identify the most likely genomic coordinates for the novel ME sequences predicted by Hyb in the 2558 ME-circRNAs. Due to small ME sequences mapping at multiple loci, we focused only on MEs 6 nt or longer and wanted to establish whether canonical intron splicing motifs flanked these MEs. For these MEs, the strongest hit was identified by prioritizing following three criteria: matching sequence must be on the same strand as the circRNA, within the same gene and in closest proximity to the 5′ or 3′ exon comprising the canonical circRNA backsplice junction. Once this list of putative coordinates was generated, we performed sequence enrichment motif analysis using WebLogo (ver2.8.2) to assess whether the canonical GT-AG rule for spliced introns is abided by for MEs . By lookME-circEIF4G3 comprising exons 6a-9, with the ME at the 5′ end of the backsplice junction—was undertaken by RT-PCR. RNase R-treated RNA from grade II tumors underwent reverse transcription and RT-PCR using an oligonucleotide anchored in the 21 nt ME itself (exon 6) and another divergent oligonucleotide in exon 10. The 218 bp PCR product corresponding to the ME-circRNA was detected in the tumors and at the same relative abundance of that ME from within each RNA-seq dataset , with Sanger sequencing confirming the ME comprises the backsplice junction . This was similar when looking at the high-confidence subset of 13,209 circRNAs with 11,773 found in healthy tissue and 10,621 in grade IV tumors  and the ubiquitously-expressed SRRM1 and SRRM2. Comparing expression by qRT-PCR, SRRM4 was the only family member to be significantly decreased  in expression in GBM compared with the normal brain tissue  and transfected into HEK293 cells. This produced a protein of the anticipated size for each construct by western blotting with anti-FLAG antisera  or pcDNA3.1::SRRM4. CircRNA-seq was performed as for GBM cells on three biological replicates of EV and SRRM4 overexpression and the resultant libraries sequenced on the Illumina NextSeq550. The distribution profile of circRNAs predicted with the three pipelines CIRCexplorer2, CIRI2 and Hyb e were sing cells f. Furtheng cells g. Howeveng cells . This agy vector c,d. Whilpression c.ME-circEIF4G3, but notably absent from the HEK293 data. We constructed a circRNA overexpression vector to express ME-circEIF4G3, which was transiently transfected into HeLa cells, a cell line known for possessing one of the highest expression levels of SRRM4 expression from the Human Proteome Atlas [ME-circEIF4G3 transgenic construct  detected in circular RNAs. We identified thousands of circRNAs containing MEs, which we deem ME-circRNAs, which were previously unidentified, or unappreciated. These should now be recognized as a non-trivial sub-family of non-coding RNAs and be a focus of new research. In the most comprehensive study to date on diverse circular RNA composition, Zhang et al.  identifiEIF4G1 and EIF4G3 transcripts were shown to be misregulated in autism patients and control synaptic translation and cognition contributing to pathogenesis of this condition [p < 0.0001) between low SRRM4 expression and poor survival in GBM and low-grade glioma across the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA) and Repository of Molecular Brain Neoplasia Data (Rembrandt) datasets . This is also the first report showing a dependence of a transgenic circRNA overexpression construct encoding circME-EIF4G3, requiring co-expression of SRRM4  to generate the circRNA product. This may be a consequence of the ME perturbing the secondary structure of the RNA, despite the presence of reverse complementary introns which are normally sufficient to drive circRNA expression. Further research will need to be undertaken on the newly identified ME-circRNAs including their unique regulation, impact on RNA secondary structure and function.The expression of SRRM4 in HEK293 cells, which do not express this neural-specific transcript, was a deliberately controlled experiment and with that we found thousands of circRNAs and ME-circRNAs were altered in expression. Interestingly, many of these were intermediate-lowly expressed circRNAs with the four most abundant circRNAs unchanged (rcSPECC1 , circMAN


Mechanistically, PCAT7 activates TGF‐β/SMAD signaling by upregulating TGFBR1 expression via sponging miR‐324‐5p. In turn, TGF‐β signaling forms a positive feedback loop with PCAT7 via SMAD3/SP1 complex‐induced PCAT7 upregulation. Finally, the clinical positive correlation between PCAT7 and TGFBR1 and TGF‐β signaling activity, and the negative association with miR‐324‐5p are further demonstrated in PCa tissues and clinical primary PCa cells. This study reveals a novel mechanism that is responsible for the constitutive activation of TGF‐β signaling in PCa bone metastasis, implying that PCAT7 can act as a potential therapeutic target against bone metastasis of PCa via disrupting the constitutive active loop between PCAT7 and TGF‐β signaling.Bone metastasis is associated with cancer‐related death in patients with prostate cancer (PCa). Long noncoding RNAs (lncRNAs) play critical roles in tumor progression of PCa. Nevertheless, the biological function of lncRNAs in PCa bone metastasis remains unclear. PCAT7 was identified as a bone metastasis‐related lncRNA via analyzing TCGA dataset. Meanwhile, PCAT7 was found to be elevated in primary PCa tissues with bone metastasis and associated with bone metastasis status and poor prognosis of patients with PCa. Functionally, our results reveal that PCAT7 overexpression promotes PCa bone metastasis  lncRNA PCAT7 is upregulated in primary prostate cancer tissues with bone metastasis. PCAT7 activates TGF‐β/SMAD signaling by upregulating TGFBR1 expression via sponging miR‐324‐5p. In turn, TGF‐β signaling forms a positive feedback loop with PCAT7 via SMAD3/SP1 complex‐induced PCAT7 upregulation. This feedback loop promotes prostate cancer bone metastasis. EMTepithelial–mesenchymal transitionH&Ehematoxylin and eosin stainmiR‐324‐5pmicroRNA‐324‐5pMMP13matrix metallopeptidase 13PCAT7prostate cancer‐associated transcript 7PCRpolymerase chain reactionSMAD2/3/4SMAD family member 2/3/4SP1Sp1 transcription factorTCGAThe Cancer Genome AtlasTGFBR1transforming growth factor beta receptor 11et al., et al., et al., Prostate cancer (PCa) is the second leading cause of cancer‐related death among men in the United States  are a class of RNA transcripts with no protein‐coding capacity that is greater than 200 nt in length. They regulate many biological processes through various mechanisms, including scaffolds or guides to regulate interactions between proteins and genes, decoys to bind proteins, and enhancers to modulate transcription of their target genes , also known as PCAN‐R2, which locates in chromosome (chr) 9q22.32 and has been reported to be involved in tumor progression  and normal prostate epithelial cells (RWPE‐1) were provided by the Shanghai Chinese Academy of Sciences Cell Bank (China). C4‐2B PCa cell line was obtained from the MD Anderson Cancer Center. Abovementioned human cells were cultured as described previously : SP1, PCAT7 expression vector, and short hairpin RNA (shRNA) against PCAT7. Plasmids encoding TGFBR1 and SMAD2/3/4 were obtained from the laboratory of Professor Libing Song . Small interfering RNA (siRNA) for the SMAD3 was purchased from RiboBio . The target sequences were as follows: shPCAT7#1, 5′‐ACAGGAAGCTCTAGCAGTA‐3′; shPCAT7#2, 5′‐CCATCAACAGTGAGAGGAA‐3′; siSMAD3#1, 5′‐GGTGCTCCATCTCCTACTA‐3′; and siSMAD3#2, 5′‐GAGGCTGTCTACCAGTTGA‐3′. Retroviral production and infection were performed as previously described . Primers for U6 and miR‐324‐5p were purchased from RiboBio. The specific process of qRT‐PCR was described in our previous study  between May 2008 and March 2018. The informed consent was obtained from all patients. The detailed information of all patients is shown in Table 2.5et al., Western blotting was performed as described previously (Ren 2.63 cells were cultured in 48‐well plates for 1 day. The control luciferase plasmid or luciferase reporter plasmids (100 ng) were added to 1 ng of pRL‐TK Renilla plasmid  and transfected into cells using the Lipofectamine 3000 reagent (Invitrogen). Twenty‐four hours after transfection, luciferase and Renilla signals were measured using the Dual Luciferase Reporter Assay Kit (Promega), according to the manufacturer’s instructions.A total of 3 × 102.7. ChIP‐re‐ChIP was performed as previously described  following the manufacturer’s instructions. In brief, the cells were lysed in a RIP lysis buffer, and RNA magnetic beads were conjugated with a human anti‐Ago2 antibody or with a negative control normal mouse anti‐IgG. Subsequently, the retrieved RNA was assayed using real‐time PCR2.8in situ hybridization (FISH) was performed using a FISH Kit (RiboBio), following the manufacturer’s instructions. A nucleus and cytoplasm segmentation PARIS™ Kit  was used to segment the nucleus and cytoplasm of cells following the manufacturer’s instructions.Cy3‐labeled PCAT7 was obtained from RiboBio. RNA fluorescence 2.9et al., Transwell assays were performed to determine the migration and invasion capability of PCa cells following the previous description , the substrate of bioluminescence signal to luciferase, was intraperitoneally injected into the anesthetized mice, and bioluminescence imaging (BLI) was captured in the light‐tight box of the IVIS Imaging System . The detailed procedures regarding the luciferase‐expressing PC3 cells and the detection of BLI in vivo have been described as in the previous study . Osteolytic lesions were identified on radiographs as radiolucent lesions in the bone. Each bone metastasis was scored based on the following criteria: 0, no metastasis; 1, bone lesion covering < 1/4 of the bone width; 2, bone lesion involving 1/4 ~ 1/2 of the bone width; 3, bone lesion across 1/2 ~ 3/4 of the bone width; and 4, bone lesion > 3/4 of the bone width. The bone metastasis score for each mouse was the sum of the scores of all bone lesions from the hind limbs. For survival studies, mice were monitored daily for signs of discomfort and were either euthanized all at one time or individually when presenting signs of distress, such as a 10% loss of body weight, paralysis, or head tilting.All mouse experiments were approved by the Institutional Animal Care and Use Committee of Sun Yat‐sen University and performed as previously described (Ren 2.11http://www.broadinstitute.org/gsea), and gene set was obtained from the Molecular Signatures Database v5.2 (http://software.broadinstitute.org/gsea/msigdb). The C2 and C5 gene sets’ collection was used in this study. mRNA expression profiles from 498 PCa patients in TCGA were used as input. False discovery rate (FDR) q values were calculated using 1000 permutations, and a gene set was considered significantly enriched if its normalized enrichment score (NES) has an FDR q below 0.25.Gene set enrichment analysis (GSEA) was used in this study to determine whether a defined set of genes show significant, concordant differences between two sample groups divided by the median of PCAT7 expression in TCGA, PCAT7‐High (PCAT7‐H), and PCAT7‐Low (PCAT7‐L) groups. GSEA was performed using GSEA 2.2.1 (2.12https://gdc.cancer.gov/). lncRNA expression of 498 PCa tissues, 52 adjacent normal tissues, 10 PCa tissues with bone metastasis (PCa/BM), and 12 PCa tissues without bone metastasis (PCa/nBM) was analyzed in this study. Patients with available information about survival status were used for survival analysis. All data analysis was performed using graphpad 7.0 (USA), Microsoft Excel (USA), and SangerBox . All data were normalized as TPM format. Gene expression was presented as the mean value of multiple probes for each gene after log2 transformation. The lncRNA expression levels with more than or equal to twofold in PCa tissues and primary PCa tissues with bone metastasis (PCa/BM) compared with those in adjacent normal tissues and primary PCa tissues without bone metastasis (PCa/nBM), respectively, were selected for further study. P < 0.05 was considered statistically significant.lncRNA expression profiles of all 498 PCa tissues and 52 adjacent normal tissues were downloaded from TCGA . Student’s t‐test was used to determine statistical differences between the two groups. A P value of < 0.05 was considered to indicate statistical significance.All data analyses were performed by 33.1http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21032) datasets that found PCAT7 to be markedly elevated in PCa tissues compared with adjacent normal tissues (ANT) , 26 PCa tissues with bone metastasis (PCa/BM), and 11 metastatic bone tumor tissues . Consistently, the results indicated that PCAT7 was elevated in PCa tissues relative to that in ANT  dataset were first analyzed, and the screening rationale is depicted in Fig. NT) Fig. a. More iANT Fig. b–e, and 3.2in vivo bone metastasis model was employed, in which the PCAT7‐overexpressing, PCAT7‐downregulated, and corresponding control PC‐3 cells labeled with luciferase were directly inoculated into the left cardiac ventricle of nude mice  based on TCGA dataset showed significant enrichment of tumor metastasis and EMT‐related gene modules in sample group with high expression of PCAT7 (PCAT7‐H group), which indicated that PCAT7 may promote EMT and tumor metastasis Fig. c. Subseq3.4phylocsf (https://omictools.com/phylocsf-tool), and the results support the finding that PACT7 is noncoding. To reveal the specific mechanism of PCAT7 in PCa bone metastasis, we performed RNA FISH and nuclear–cytoplasmic fractionation assays to determine the subcellular localization of PCAT7. The results demonstrated that PCAT7 was mainly detected in the cytoplasm of PCa cells (Fig. et al., et al., in vitro experiments showed that miR‐324‐5p mimics partially reversed the promotive effect caused by PCAT7 overexpression, whereas the miR‐324‐5p inhibitor attenuated the inhibitory effect of silencing PCAT7 on the migration and invasion of PCa cells (Fig. The protein‐coding potential of PCAT7 was predicted by the online tool, lls Fig. A–B. The 3.5et al., et al., et al., et al., In order to determine the molecular mechanism that underlies the PCAT7/miR‐324‐5p axis in PCa bone metastasis, luciferase reporter assays were performed to assess the function of PCAT7 and miR‐324‐5p in multiple well‐known pathways that contribute to bone metastasis of PCa, including the Notch (Zayzafoon et al., et al., Then, the functional role of TGF‐β signaling in PCAT7‐induced bone metastasis was further investigated. As shown in Fig. 3.6Through analyzing Starbase and miDIP, the results implied that TGFBR1 may be the target of miR‐324‐5p Fig. a. It is Since PCAT7 acts as a sponge for miR‐324‐5p, it is conceivable that PCAT7 should upregulate TGFBR1 expression. As expected, the overexpression of PCAT7 increased, while silencing PCAT7 reduced the luciferase activity of wild‐type TGFBR1‐3′‐UTR and the protein expression of TGFBR1 (Fig. 3.7As demonstrated above, PCAT7 upregulates TGFBR1 via sponging miR‐324‐5p, which further activates TGF‐β signaling. Intriguingly, our results showed that TGF‐β enhanced PCAT7 expression in PCa cells Figs b and S6a3.8et al., et al., Many studies have reported that TGF‐β‐dependent SMAD proteins and ubiquitous transcriptional factor SP1 can form a transcriptional complex to individually or concomitantly modulate the expression of downstream target genes (Feng 3.9et al., Given the significance of the PCAT7‐miR‐324‐5p‐TGF‐β signaling axis in bone metastasis of PCa cells, we analyzed the clinical relevance of this loop in PCa patients. We found that the expression of PCAT7 was reversely associated with the expression of miR‐324‐5p, while it was positively associated with TGFBR1 expression in PCa patients of our cohort and the TCGA cohort Fig. a,b. The 4The present study reveals the oncogenic role of lncRNA PCAT7 in bone metastasis of PCa. Our findings indicate that PCAT7 is upregulated in bone metastasis‐positive PCa tissues. Meanwhile, the upregulation of PCAT7 is associated with advanced clinicopathologic characteristics, bone metastasis status, and poor prognosis of PCa patients. Mechanistically, PCAT7 upregulates TGFBR1 expression by sponging miR‐324‐5p, which further activates TGF‐β signaling, contributing to the onset of bone metastasis in PCa. Reciprocally, the SMAD3/SP1 transcriptional complex enhances PCAT7 transcription, forming a feedback loop between PCAT7 and TGF‐β signaling. Hence, our study has uncovered a new mechanism of PCAT7‐induced activation of TGF‐β pathway, elucidating the critical role of PCAT7 in PCa bone metastasis.et al., et al., et al., et al., et al., et al., et al., Dysregulation of a variety of lncRNAs, such as PCAT1/14/19, DNACR, TTTY15, and SChLAP1, has been extensively reported in PCa, and these dysregulations contributed significantly to the aggressiveness and progression of PCa via varying mechanisms (Hua et al., et al., et al., et al., et al., et al., et al., Previous studies have revealed that cytoplasmic lncRNAs generally function as ceRNAs to regulate mRNA expression via sponging versatile miRNAs, thereby playing a pivotal role in cancer metastasis (Lian et al., et al., Increasing evidence has shown that lncRNAs are under extensive regulation by transcription factors, which has been documented as a main mechanism that contributes to the dysregulation of lncRNAs in many types of human cancers. For instance, NF‐κB transcriptionally upregulated LINC01410 expression in gastric cancer, which further promoted the angiogenesis and metastasis of gastric cancer (Zhang et al., et al., et al., et al., et al., et al., et al., et al., The constitutive activation of TGF‐β pathway has been widely documented to participate in bone metastasis of multiple types of cancers, such as prostate cancer and breast cancer (Dai 5In summary, this study, for the first time, uncovers the probone metastatic function of PCAT7, which forms a positive feedback loop with TGF‐β signaling in PCa, indicating PCAT7 may serve as a promising therapeutic target in PCa via disrupting the PCAT7‐miR‐324‐5p‐TGF‐β loop.The authors declare no conflict of interest.XP and DR developed ideas and drafted the manuscript. CL, YD, and ZW conducted the experiments and contributed to the analysis of data. XZ, SH, and QY contributed to the analysis of data. YL and HD contributed to the analysis of data and revised the manuscript. WG edited the manuscript. All authors contributed to revise the manuscript and approved the final version for publication.Fig. S1. Identification of PCAT7 as a pro‐bone metastasis‐relevant lncRNA in PCa.Click here for additional data file.Fig. S2. PCAT7 promotes bone metastasis of PCa cells.Click here for additional data file.Fig. S3. PCAT7 acts as a competitive endogenous RNA for miR‐324‐5p in PCa.Click here for additional data file.Fig. S4. PCAT7 promotes bone metastasis by activating TGF‐β signaling via sponging miR‐324‐5p.Click here for additional data file.Fig. S5. PCAT7 disrupts miR‐324‐5p‐mediated suppression on TGFBR1.Click here for additional data file.Fig. S6. SP1 promotes PCAT7 transcription in PCa cells.Click here for additional data file.Fig. S7. Clinical relevance of PCAT7‐miR‐324‐5p‐TGF‐β signaling in PCa.Click here for additional data file.Table S1. List of primers used for real‐time RT‐PCR.Click here for additional data file.Table S2. Clinicopathological features of 57 prostate cancer patients.Click here for additional data file.Table S3. List of primers used for ChIP assay.Click here for additional data file.Table S4. Relationship between PCAT7 and clinicopathological features in 57 patients with prostate cancer.Click here for additional data file. Click here for additional data file.


Understanding the transcriptome is critical for explaining the functional as well as regulatory roles of genomic regions. Current methods for the identification of transcription units (TUs) use RNA-seq that, however, require large quantities of mRNA rendering the identification of inherently unstable TUs, e.g. miRNA precursors, difficult. This problem can be alleviated by chromatin-based approaches due to a correlation between histone modifications and transcription.Here, we introduce EPIGENE, a novel chromatin segmentation method for the identification of active TUs using transcription-associated histone modifications. Unlike the existing chromatin segmentation approaches, EPIGENE uses a constrained, semi-supervised multivariate hidden Markov model (HMM) that models the observed combination of histone modifications using a product of independent Bernoulli random variables, to identify active TUs. Our results show that EPIGENE can identify genome-wide TUs in an unbiased manner. EPIGENE-predicted TUs show an enrichment of RNA Polymerase II at the transcription start site and in gene body indicating that they are indeed transcribed. Comprehensive validation using existing annotations revealed that 93% of EPIGENE TUs can be explained by existing gene annotations and 5% of EPIGENE TUs in HepG2 can be explained by microRNA annotations. EPIGENE outperformed the existing RNA-seq-based approaches in TU prediction precision across human cell lines. Finally, we identified 232 novel TUs in K562 and 43 novel cell-specific TUs all of which were supported by RNA Polymerase II ChIP-seq and Nascent RNA-seq data.https://github.com/imbbLab/EPIGENE.We demonstrate the applicability of EPIGENE to identify genome-wide active TUs and to provide valuable information about unannotated TUs. EPIGENE is an open-source method and is freely available at:  Accurate identification of TUs is important to better understand the transcriptomic landscape of the genome. With the rapid development of low-cost high-throughput sequencing technologies, RNA sequencing (RNA-seq) has become the major tool for genome-wide TU identification. Hence, popular TU prediction tools such as AUGUSTUS , Cufflin7 cells) –20. In a7 cells) , 22, dueEukaryotic DNA is tightly packaged into macromolecular complex called chromatin, which consists of repeating units of 147 DNA base pairs (bp) wrapped around an octamer of four histones H2A, H2B, H3, and H4 called the nucleosome. Post-translational modifications (PTM) to histones in the form of acetylation, methylation, phosphorylation, and ubiquitination, play an important role in the transcriptional process. These PTMs are added, read, and removed by so-called writers, readers, and erasers, respectively. In this way nucleosomes serve as signalling platforms  that enaCurrently many computational approaches such as ChromHMM , EpicSegBased on the training, these HMMs can be classified as: (a) unsupervised methods that do not include prior biological information and require users to interpret and annotate the learned states based on existing knowledge about functional genomics  and (b) supervised methods, that rely on a set of positive samples for training (e.g. chroModule). Although these approaches annotate genome modules such as promoter, enhancer, transcribed regions, etc., they fail to identify active TUs as they do not constrain the chromatin state sequence to begin with a transcription start site (TSS) and end with a transcription termination site (TTS).To address these shortcomings, we developed a semi-supervised HMM, EPIGENE (EPIgenomic GENE), which is trained on the combinatorial pattern of IHEC class 1 epigenomes  to infer hidden “transcription unit states”. The emission probabilities represent the probability of a histone modification occurring in a TU state and the transition probabilities capture the topology of TU states. In addition to the TU states, the HMM also includes background states. The transcription start site (TSS), exons , introns  and transcription termination site (TTS) are referred to as the TU states. The emission probabilities of these states as well as the transition probabilities between them are learned from the structure of TUs given by an existing transcript annotation. The transition and emission probabilities of the background states, the transition probabilities from and to TSS and TTS states, and the transition probabilities between TSS and TTS states are learned in an unsupervised manner from the data.In the forthcoming sections, we describe the EPIGENE approach, validate the predicted EPIGENE TUs with existing annotations, RNA-seq, and ChIP-seq evidence, compare the performance of EPIGENE to existing chromatin segmentation and RNA-seq-based methods within and across cell lines, and show that EPIGENE outperforms state-of-the-art RNA-seq and chromatin segmentation approaches in prediction resolution and precision. In summary, EPIGENE yields predictions with a high resolution and provides a pre-trained robust model that can be applied across cell lines.EPIGENE uses a multivariate HMM, which allows the probabilistic modelling of the combinatorial presence and absence of multiple IHEC class 1 histone modifications. It receives a list of aligned ChIP and control reads for each histone modification, which is subsequently converted into presence or absence calls across the genome using normR see “” sectionWe validated the predicted TUs using existing gene annotations and RNA-seq evidence. For this, we combined the EPIGENE predictions 24,571 TUs) and RNA-seq predictions that were obtained from Cufflinks  and StringTie  and the receiver-operating characteristic (ROC) curves a higher AUC  exist that provide chromatin state annotation using histone modifications. These approaches were inherently designed to provide a whole-genome chromatin state annotation and hence, the model parameters do not represent a specific topology. We examined the results of these approaches to evaluate their accuracy in identifying TUs.We compared EPIGENE predictions with a widely used chromatin segmentation approach, ChromHMM, as both methods use a binning scheme. We did not include Segway in this comparison because it operates at single base pair resolution and, therefore restricts fair comparison of different profiles. Additionally, Segway is quite slower than chromHMM.TU identification with chromHMM was performed in two modes: strand-specific and unstranded. Strand-specific TUs were obtained by linking the promoter and transcription elongation states. We defined TU as a genomic region that begins with promoter state and proceeds through transcription elongation states. A promoter state was defined by an enrichment of H3K4me3 and H3K27ac , evolutionally conserved, non-coding RNAs , 53 deriIn this work, we introduced EPIGENE, a semi-supervised HMM that identifies active TUs using histone modifications. EPIGENE has TU (forward and reverse) and background sub-models. The TU sub-models were trained in a supervised manner on predefined training sets, whereas the background was trained in an unsupervised manner. This semi-supervised approach captures the biological topology of active TUs as well as the probability of occurrence of histone modifications in different parts of a TU.We first showed that majority of the predicted TUs can be explained by existing gene annotations and were supported by RNA Polymerase II evidence. A quantitative comparison with RNA-seq revealed the presence of TUs with RNA Polymerase II enrichment but negligible RNA-seq evidence. Considering RNA Polymerase II ChIP-seq and Nascent RNA-seq as true transcription indicator, we compared the performance of EPIGENE with chromatin segmentation approach chromHMM and two RNA-seq-based approaches Cufflinks and StringTie. Based solely on the AUC of PRC and ROC curve as performance measure, EPIGENE achieves a superior performance than chromatin segmentation and RNA-seq-based approaches. We further showed that EPIGENE can be reliably applied across different cell lines without the need for re-training the TU states and accomplishes a superior performance than RNA-seq-based approaches.We examined other performance scores like precision, sensitivity, and specificity values, and observed that the low AUC of RNA-seq-based approaches is due to RNA-seq mapping artefacts that resulted in higher number of false positives in Cufflinks and StringTie. We further evaluated the presence of differentially identified TUs in K562, HepG2, and IMR90 cell lines that lack RNA-seq evidence. The results suggested the presence of cell line-specific transcripts that lack RNA-seq evidence. We additionally identified potential microRNA precursors that lacked RNA-seq evidence presumably due to their instability. All of the aforementioned TUs showed an enrichment of RNA Polymerase II in TSS and gene body indicating that they had been transcribed.It is important to note that EPIGENE does not differentiate between functional and non-functional units of a TU (exons and introns) as the association between histone modifications and alternative splicing is yet to be elucidated . HoweverEPIGENE uses six core histone modifications that are available for many cell lines and species, which leads to a broad applicability. All the core histone modifications are essential for accurate TU identification, as the accuracy of TU prediction decreases in the absence of any of the core histone modification. In the absence of a core histone modification, imputation techniques such as ChromImpute  and PREDIn summary, the superior performance within and across cell lines, identification of TUs, especially primary microRNAs lacking RNA-seq evidence as well as interpretability makes EPIGENE a powerful tool for epigenome-based gene annotation.With increasing efforts in the direction of epigenetics, many consortia continue to provide high-quality genome-wide maps of histone modifications, but determining the genome-wide transcriptomic landscape using this data has remained unexplored so far. Extensive evaluations in this work demonstrated the superior accuracy of EPIGENE over existing transcript annotation methods based on true transcription indicators. EPIGENE framework is user-friendly and can be executed by solely providing binarized enrichments for ChIP-seq experiments, without the need to re-train the model parameters. The resulting TU annotations agree with RNA Polymerase II ChIP-seq and Nascent RNA-seq evidence and can be used to provide a cell type-specific epigenome-based gene annotation.6 K562 cells were cultured as recommended by ATCC. Chromatin immunoprecipitations were performed using the Diagenode auto histone ChIP-seq kit and libraries were made using microplex kits according to manufacturer’s instructions and 10 PCR cycles.For K562 cell line presented in this study, ChIP against six core histone modifications, H3K27ac, H3K27me3, H3K4me1, H3K4me3, H3K36me3 and H3K9me3, was performed. The sheared chromatin without antibody (input) served as control. 10 × 10K562 cells were cultured in IMDM (#21980Gibco) with 10% FBS and P/S. Cells at a concentration of 1.2 mio/ml were fixed with 1% formalin at 37 °C for 8 min. Nuclei were isolated with a douncer, chromatin concentration was measured and 750 µg chromatin per CHIP was used. Samples were sonicated with Biorupter for 33 cycles (3 × 11 cycles). Chromatin, antibodies (RNA Pol II Ser2P (H5), RNA Pol II Ser5P (4H8), RNA Pol II Ser7P (4E12) and PolII (8WG16)) and protein G beads were combined and rotated at 4 °C. For elution 250 µl elution buffer (1% SDS) was used and after reverse crosslinking DNA was isolated by phenol chloroform extraction and eluted in 1xTE. Final concentration was measured by Qubit. Bioanalyzer was done to check fragment sizes.plotFingerprint which is a part of deepTools [Sequencing for RNA Polymerase II and histone modifications was performed on an Illumina Highseq 2500 using a paired end 50-flow cell and version 3 chemistry. The resulting raw sequencing reads were aligned to the genome assembly “hs37d5” with STAR  and dupleepTools  to accesThe raw reads from RNA-seq experiments were downloaded from European Nucleotide Archive , European Genome Archive (EGAD00001002527 for HepG2) and ENCODE (ENCSR00CTQ for IMR90) and were aligned to the genome assembly “hs37d5” with STAR .The transcript annotation for K562 obtained from TT-seq were downloaded from Gene Expression Omnibus (GEO) (GSE75792). The genomic co-ordinates of transcripts were lifted over to hg19. For HepG2, raw reads from GRO-seq were downloaded from GEO (GSM2428726). The raw reads were aligned to the hg19 and the pre-processing was done based on the instructions specified in Liivard et al. . For IMRObtaining read counts Read counts for all the bins was computed using bamCount method from R package bamsignals [msignals , with thEnrichment calling and binarization After having obtained the read counts, binarization of ChIP-seq signal for the histone modifications and RNA Polymerase II across all bins enrichR (binFilter = zero) and getClasses (fdr = 0.2) method from normR [om normR . This stEPIGENE requires the enrichment values of IHEC class 1 histone modifications in a binarized data form or a “class matrix” to learn a transcription state model. This was done by partitioning the mappable regions of the genome of interest into non-overlapping sub-regions of the same size called bins. In the current setup, the transcription states are analysed at 200-bp resolution, as it roughly corresponds to the size of a nucleosome and spacer region. Given the ChIP and input alignment files for each of the histone modifications, the class matrix for multivariate HMM was generated using the following approach:m × n matrix, where ith bin for the jth histone modification. The model constitutes Initializes the emission, transition, and initial probabilities.Fits the emission, transition, and initial probabilities using the Baum–Welch algorithm .As we are concerned about the most probable sequence of active transcription unit, therefore the sequence of hidden states was inferred using the Viterbi algorithm .EPIGENE uses a multivariate HMM  of individual transcription unit component  for each transcript was computed to generate the coverage list, where each entry of the coverage list contains the coverage information (in bp) for individual transcripts.The transition probability of each “transcription unit state” was computed from the coverage list, and the missing probabilities from and to the “background state” were generated in an unsupervised manner.The gencode transcripts were filtered to obtain transcripts that report an enrichment for RNA Polymerase II. This was done by clustering the binarized enrichment values of RNA Polymerase II in TSS and TTS bins of the transcripts and obtaining TSS and TTS bins that report a high cluster mean for RNA Polymerase II. The emission probability of each “transcription unit state” was computed from class matrix and coverage of these transcripts (coverage computed from Step 2). The missing emission probabilities for the background states were trained in an unsupervised manner.The transition and emission probabilities of the multivariate HMM were trained using GENCODE annotations with the following approach:Nascent RNA transcript annotation for GRO-seq profiles was obtained using groHMM . For HepThe performance of EPIGENE and RNA-seq-based transcript prediction approaches was evaluated using RNA Polymerase as performance indicator. This was done by removing assembly gaps in the genomic regions of interest and partitioning the remaining contigs into non-overlapping bins of 200 bps. The actual transcription status of each 200 bp bin was given by the observed binarized RNA Polymerase II ChIP-seq and Nascent RNA-seq enrichment in the bin. The actual transcription The predicted transcription status of the bin for method m, The predictions of EPIGENE and other RNA-seq-based approaches were evaluated by computing the area under curve for precision–recall (AUC-PRC) and receiver-operating characteristic curve (AUC-ROC) with primary focus on AUC-PRC. Considering a very high class imbalance, i.e. Additional file 1. Data details and additional results. Details of datasets used and additional results.Additional file 2. RNA Polymerase II enrichment. RNA Polymerase II enrichment in consensus TU set.Additional file 3. Cell specific TUs. Additional details about cell specific TUs that lack RNA-seq evidence.