Azolla–cyanobacteria, ectomycorrhiza, endomycorrhiza, and rhizobia–legumes. This review focuses on transporters for nitrogen and carbon and other solutes exchanged in the interactions. Their predicted functions are evaluated on the basis of their transport mechanism and prevailing transmembrane gradients of H+ and transported substrates. The symbiotic interactions are presented in the assumed order from oldest to most recently evolved.Intimate interactions between photosynthetic and non-photosynthetic organisms require the orchestrated transfer of ions and metabolites between species. We review recent progress in identifying and characterizing the transport proteins involved in five mutualistic symbiotic interactions: lichens, The vast majority of plant species participate in symbiotic relationships with fungi and bacteria. We know that the formation of symbiotic relationships between species occurred before the first eukaryotic cells which themselves are the product of endosymbiosis that resulted in the formation of mitochondria and chloroplasts. Understanding transmembrane transport processes between species is the key to understanding nutritional symbiotic interactions. This is because direct transfer from cell to cell between species is rare, although there are examples such as secretion between Agrobacterium and plant cells. In nutritional symbioses, cells of both species are bounded by a cell membrane and transfer of ions and metabolites occurs through membrane-bound transport proteins. Identifying the transporters involved and characterizing their activity can reveal which ions and metabolites are transported between species.There has always been great interest in understanding symbiotic systems such as mycorrhiza and lichens, but research at the molecular level has often been too difficult. However, this is an appropriate time to revisit such complex systems and identify transport proteins that function in symbiotic interactions. Technical advances, especially the availability of genome sequences, have had an exceptionally large impact on the ability to study symbiotic interactions. Now, transcriptomic and proteomic experiments involving multiple interacting species can be performed and transporters can be assigned to each interacting partner. Once transporters are identified, heterologous expression experiments can be used to study transport activity, fluorescent protein fusions can be used to localize membrane proteins, and mutational analysis can be used to test whether transporter function is important for the interaction.In the symbiotic associations discussed in this review, the transport of fixed nitrogen (N) and fixed carbon (C) compounds takes center stage. The reason is that all organisms need large amounts of N and C; photosynthetic plants can fix C, but only bacteria (and Archaea) can fix N. Cyanobacteria can fix both N and C but no eukaryotic organism can do the same. In the symbioses discussed here, large amounts of fixed N and C are transported between species. We will discuss transporters for N and C that have been identified and their activity and point out possibilities for transporters that have not yet been identified. We will also discuss selected transporters for other nutrients, ions, metals, and metabolites that are essential to symbiotic interactions.+-coupled antiporters or pumps. Anion uptake transporters are likely to be H+-coupled symporters, and cation uptake transporters are likely to be H+-coupled symporters or channels. For uncharged molecules, efflux transporters could be uniporters, H+-coupled antiporters, or pumps, whereas uptake transporters are likely to be H+-coupled symporters. It is also important to understand the orientation of membranes at the symbiotic interface. For all of the interactions discussed here, in order for ions and metabolites to be transferred from one organism to another, a transmembrane export step followed by an uptake step is required.To identify novel transporters functioning in a symbiosis, it is important to understand that the prevailing negative membrane potential, the transmembrane pH gradient that is more acidic outside, and the gradient of substrate may narrow the types of transporters likely to serve a particular function. For example, owing to the negative membrane potential, anion exporters are likely to be uniporters, such as anion channels. Exporters for cations are likely to be H2.Lichens are a morphologically and taxonomically diverse assemblage of obligate symbioses involving fungi and photosynthesizers. A typical lichen consists of a tough upper and lower fungal cortex protecting a symbiotic interaction zone consisting of a layer of algal or cyanobacterial cells supported by a network of fungal hyphae . The ent4.Seminal radiolabeling experiments in the 1960s and 1970s established the nature of the carbohydrate transfer from the photosynthesizer to the fungus  orsemiSWEETs. Likewise, analysis of ammonium transporters (AMTs) and amino acid transporters as the conduits of symbiotically exchanged N is also necessary.A current priority is testing of hypotheses flowing from genome and transcriptome experiments, such as functional characterization of the putative ribitol transporters identified by YoshinoAzolla filiculoides (and related species) has a mutualistic relationship with the cyanobacteriumNostoc azollae (Anabaena azollae) and traditionally has been employed as a biofertilizer in rice paddies. More recently, there has been interest in usingAzolla for bioremediation as a way to remove ammonium from wastewater or as a protein source17. Azolla has also been implicated in the Arctic Azolla Event. Around 50 million years ago, exponential growth of the plant led to a rapid reduction of carbon dioxide (CO2) levels in the atmosphere, which is thought to have resulted in a cooling of the Earth18. The genomes of bothA. filiculoides andN. azollae have been sequenced20. The leaves of the fern contain cavities that are formed during development by invagination of the epidermis. Cyanobacteria are contained within these gas-filled cavities in close association with trichomes and embedded in a mucilaginous matrix. The structure of the trichomes is similar to that of transfer cells21.The small aquatic fernAzolla the bacterial symbiont is transmitted from one generation to the next. Whereas the fern can grow without its symbiont,N. azollae is unable to exist outside of the plant. This is reflected in the genome ofN. azollae, which has adapted to the symbiont lifestyle and, compared with related free-living cyanobacteria, appears reduced, and some core genes  have been lost19.In contrast to the legume–rhizobia symbiosis, inN. azollae is able to perform photosynthesis, it does so only at a low rate and depends largely upon sugar derived from the plant22. Much of the energy thatN. azollae derives from the sugar it receives fromAzolla is invested into N fixation. At the stage when N fixation is at its highest level, the bacteria are no longer dividing. The major product of photosynthesis inAzolla is sucrose22, but it is not clear in what form C is exported from the plant and taken up into the cyanosymbiont.AlthoughNostoc sp.23. Fixed N is supplied to Azolla, and about 40% of the N is exported from the bacteria and released in the form of ammonium into the leaf cavity23 . This type of transporter is common in bacteria and catalyzes the uptake and phosphorylation of a range of carbohydrates 24.Even though it has been shown that Nostoc receives carbohydrates (at least some of it in the form of sucrose) from its plant partnerSWEET genes are present in theA. filiculoides genome, but there is no evidence that any of them is differentially expressed in the presence of the cyanosymbiont25. If SWEET proteins are involved in C effux in theAzolla symbiosis, the presence of the symbiont may trigger other post-transcriptional regulation.On the plant side, 15N. azollae supplies its plant partner with ammonium, but no specific transporter responsible for this step has been identified. The genome ofN. azollae contains anAmtB gene, encoding a putative ammonium transporter that could export ammonia into the leaf cavity ofAzolla. Interestingly,N. azollae is lacking other N transporters 19. This may be an adaptation to the symbiont lifestyle, preventingN. azollae from obtaining N from the plant and making it dependent upon N fixation.A. filiculoides contains genes for both electrogenic (AMT1) and electroneutral (AMT2) ammonium transporters17. Expression of one of theAMT2 genes,AfAMT2-4 (Azfi_s0034.g025227.AMT2), is upregulated in the fern when no N is supplied in the growth medium but only in the presence of the cyanobiont25. AMT2-4 is considered to function in the uptake of ammonium from the leaf cavity into the plant , and an iron transporter homolog (Azfi_s0018.g014823) are induced in the fern under the same N-limiting conditions asAMT2-425. Both iron and molybdate are required co-factors for nitrogenase, the key enzyme for N fixation in the cyanobacteria. This suggests that, under N-limiting conditions, the plant upregulates Mo and Fe uptake transporters to supply more of these elements to the cyanobiont. AfMOT1 may function as a molybdate uptake transporter into the plant cells rather than as an exporter to the cyanobiont. The iron transporter Azfi_s0018.g014823 is related to vacuolar Fe/H+ antiporter VIT1, so it could function in Fe export from plant cells if it is localized to the plasma membrane.The cyanobiont appears to be dependent onAzolla/Nostoc symbiotic interaction, the key transporters responsible for C efflux from the plant and N uptake into the plant need to be identified. With new technologies such as gene editing, it may be possible to test whether specific transporters such as AMT2-4 fromAzolla are required for the interaction.To fully understand the26.The ectomycorrhizal symbiosis consists of a plant partner, usually a tree species and a fungal partner, either an ascomycete or a basidiomycete. The fungus initially forms a dense layer of hyphae around the root tips of fine roots, called the mantle. Then hyphae penetrate between the cells of the epidermis and outer cortex of the tree root but without entering the cells. This structure is called the Hartig net. The fungal hyphae and the root cells share an apoplastic space, the symbiotic interface, a structure that is important for symbiosis . The hyp27. In the fungus, glucose is rapidly converted into trehalose and sugar alcohols such as mannitol or arabitol, allowing the fungus to continue to act as a sink for the long-distance transport of sugars27.The fungus receives fixed C from its plant partner in the form of hexoses. The tree exports sucrose into the wall space, where the sucrose is hydrolyzed by plant-derived acid invertase into glucose and fructose. Glucose is taken up preferentially28. The form of N transported to the plant is not clear. Larsenet al.29 concluded that amino acids are the main metabolites that the fungus synthesizes and shares with the plant. In their study, they found that expression of amino acid transporters is enriched in both plant and fungus, providing candidate genes to study in the interaction. Ammonium transporters have been identified in both plant and fungus. In poplar, a nitrate transporter in the NRT2 family is induced by the presence of the fungal partner30. TbNrt2, a nitrate uptake transporter from the fungusTuber borchii, is strongly expressed in the Hartig net and mantle and only weakly in free hyphae31. There is no evidence for an enrichment of ammonium or inorganic phosphate (Pi) transporters in the ectomycorrhizal association29. Three fungal H+-coupled phosphate uptake transporters have been isolated fromHebeloma: HcPT1.1, HcPT1.2, and HcPT234. All are likely to function in Pi acquisition by the fungus. HcPT2 is localized at sites of both Pi uptake and Pi release, and RNA interference (RNAi) lines ofHebeloma with decreased expression ofHcPT2 form fewer ectomycorrhizae than the control strain33. However, owing to its predicted transport mechanism and the existing proton gradient with higher proton concentration in the apoplast, it is unlikely that HcPT2 activity is responsible for Pi export to the plant. An additional transporter required for P efflux to the plant has not been identified yet.In the ectomycorrhizal interaction, the plant benefits from metabolic capabilities of the fungus as well as the increased surface area for absorption from the soil. Interaction with the fungal partner enhances the supply of nutrients, in particular N and P35. They function as H+-coupled uptake transporters37. None of them has been shown to be essential for symbiosis, but several are specifically expressed in the root tips or in Hartig net/mantle versus free-living hyphae. In an ectomycorrhizal transcriptome study, sugar transporters were found to be specifically enriched in the transcripts of the fungal partner. No such enrichment occurred in the plant transcriptome29. This may indicate that the fungal partner drives the movement of sugars, at least as far as the transport step is concerned. The plant partner may control the supply of photosynthates through controlling the activity of acid invertase in the apoplast, thereby limiting the amount of hexoses available for the fungal partner to take up.It is generally accepted that the form of C taken up by the fungus is hexoses. Several hexose transporters, HXTs or MSTs in the major facilitator superfamily, have been isolated from a range of ectomycorrhizal fungiAlthough no specific transporters have been shown to be required for ectomycorrhizal symbioses, a lot of progress has been made in genome sequencing and transcriptomic experiments to identify a range of transporters that may be important. Export of sucrose is likely via SWEET proteins and uptake of hexoses by MSTs in the fungus. It would be very useful to know the forms of N and P that are taken up by the plant, and identifying transporters that are necessary for the interaction will help narrow the list of possibilities.38. This intimate association enables nutrient exchange, and plants provide up to 20% of the photosynthetically fixed C to the fungi and derive mineral nutrients from the fungal partner40. Fungal hyphae grow between cells in the root cortex and through the cell wall surrounding plant cells. The fungi do not break through the plasma membrane; they form highly branched structures known as arbuscules in the apoplastic space (41. The arbuscule is surrounded by a plant-derived periarbuscular membrane (PAM), thus being physically separated from the host cytoplasm. Recent studies suggest that the PAM encloses a periarbuscular space (PAS) which contains many hyphal branches, challenging an earlier notion that the PAM trails along each hyphal branch42. The arbuscule provides an increased surface area for exchange of nutrients between the two organisms. Membrane transport in AM symbiosis has been studied mainly on the plant side because of the difficulty of working with AM fungi and the complexity of fungal genomes. The AM fungi establish a new C sink in the roots of plants, thus driving the transport of photoassimilates or C reserves from the host plant, preferentially in the form of hexoses, primarily glucose. Studies reveal significant transcriptional upregulation of the members of MST, sucrose transporter (SUT) and SWEET families of transporters in the arbuscule-containing cells of many plant species, although most of the results await genetic and functional validation40. Recently, SWEET1b fromMedicago truncatula was localized to the PAM and demonstrated to transport glucose43. However, loss-of-functionmtsweet1b mutants show no defect in the plant–fungal symbiotic interaction, indicating the presence of redundant transporters. Interestingly,sut2 mutants in tomato reveal higher AM fungi colonization rates, suggesting a role for SUT2 in reverse transport of sucrose from the PAS space back to the plant44  symbioses are ancient and widespread interactions between obligate biotrophic fungi belonging to the Glomeromycotina and the roots of land plantsc space . The forlant44 . Sugar t49. This dependency was revealed by legume mutants defective in lipid biosynthetic genes that have stunted arbuscules and reduced colonization. Other studies using transgenicMedicago expressing fatty acid synthesis genes and radioisotopes also demonstrate the transfer of fatty acids from plants to fungi. The ABC-type transporters STR1 and STR2 are required for arbuscule formation in rice andMedicago51 and are predicted to transport beta-monoacylglycerol from plants to fungi53. The mechanism of transport or trafficking of lipids at the AM–plant interface is not clear and will require additional research such as using imaging with lipophilic dyes or transport assays using reconstitution of transporter proteins in liposomes.Lipids may serve as another source of C transferred from plants to AM fungi. AM fungi depend on the plant host for lipids since they lack genes encoding the cytosolic fatty acid synthase subunits for fatty acid biosynthesis54 and exogenous Pi treatment in rice inhibits fungal colonization and mycorrhizal uptake of Pi55. Krajinskiet al.56 revealed that Pi uptake by AM fungi is driven by the transmembrane H+ gradient. Fungal Pi/H+ symporters are responsible for Pi uptake from the soil by the extraradical mycelium, although they are also expressed in the intraradical mycelium, suggesting their role in reabsorption from the PAS. Pi is then trafficked as polyphosphate chains to the intraradical mycelium, where breakdown produces Pi which then gets transported into the PAS via a still-unknown mechanism. AM fungi colonization induces the expression of Pi transporters in rice (OsPT11), tomato (LePT1), potato (StPT3), maize (ZmPT9) andMedicago truncatula (MtPT4)40. Both low- and high-affinity H+/Pi symporters of the plant PHT1 family have been implicated in AM fungi symbioses and these cluster in a separate clade from PHT1 transporters in non-AM symbiotic plants. Plant and fungal Pi transporters might also function as transceptors sensing Pi, and further investigation is warranted58. Interestingly, high Pi repressesSTR1/2 expression, suggesting that plants withhold C under high Pi conditions59. For a detailed review of Pi transport in mycorrhiza, see60.Owing to the low mobility of phosphate ions in soil, plants use the extensive network of AM fungi to acquire most of their P. Availability of Pi is also a signal for arbuscule maintenance since plant Pi transporter mutants display premature degeneration of arbuscules61. Fungi encode ammonium transporters in the MEP family that could serve as ammonium exporters62, and high- and low-affinity MEPs have been reported inR. irregularis. AM-inducibleAMTs are found in all host plants (both dicots and monocots) and have been localized to the PAM63. Since the PAS is acidic, NH4+ concentration predominates over NH3. Plant AMTs are thought to bind NH4+, deprotonate it, and co-transport NH3 and H+ , also called the peribacteroid membrane (PBM), surrounds the bacteroids . The pla65. Despite their central importance for the symbiosis, most of the N and C transporters predicted to be required for the interaction have not been identified.Transporters involved in the interaction of legumes and rhizobia have been recently reviewed in detail+ATPases that acidify the peribacteroid space and generate a negative membrane potential64. To understand transport processes at the PBM, the peribacteroid space should be considered equivalent to the apoplast or cell wall space of a plant cell. Accordingly, solutes are transported from the plant to bacteroids via plant exporter proteins.The PBM contains plasma membrane-type H4-dicarboxylates66. Bacterial mutants defective in dicarboxylate transporter DctA are unable to fix N. Malate, succinate, and fumarate are transported by DctA67. Malate appears to be the most important and only required C4-dicarboxylate supplied to the bacteroids by the plant68. It is not surprising that the uptake of dicarboxylates by DctA is coupled to the uptake of at least three H+ so that the transport reaction is driven by the negative bacterial membrane potential and by the transmembrane pH gradient67. The exporter responsible for malate export from the plant across the SM has not yet been identified. There are excellent candidates for dicarboxylate export into the peribacteroid space. Malate is transported by S-type anion channels69 in the SLAC family and by aluminum-activated malate transporters (ALMTs)70. ALMTs were first identified in wheat and were shown to export malate in response to exposure to aluminum. InLotus japonicus, LjALMT4 transports malate and is expressed in nodules but is localized to the vasculature in nodules71. Perhaps another member of the ALMT family localizes to the PBM in infected cells as indicated inIt is clear that the form of fixed C taken up by bacteroids is C4+ or NH3). Although both plants and bacteria encode ammonium transporters in the AMT/MEP/Rh family62, the current view is that transporters in the AMT/MEP/Rh family are not involved in either NH3 release from bacteroids or uptake into infected plant cells. The bacterial AMTAmtB is not expressed in bacteroids and therefore N is thought to be exported from bacteroids by diffusion of NH3 through the bacteroid membrane64. The aquaporin homolog NOD26 has been suggested to serve as the ammonium uptake transporter from the peribacteroid space into rhizobia-infected cells. NOD26 is highly expressed, localized to the PBM, and known to transport NH372. Transporters in the AMT1 family were not identified in proteomic studies of nodules74. GmSAT1 from soybean was originally considered a candidate for the plant PBM ammonium uptake transporter; however, GmSAT1 was subsequently found to be a transcription factor that affects expression of the yeastMEP3 ammonium transporter when expressed in yeast75.The form of N transported from the bacteroid to the plant is thought to be ammonium  for both S-containing amino acids and Fe-S complexes. Bacteroids have been shown to take up 20-fold times more S than the nodule host cells78. The plant SO42− transporter SST1 is required for symbiotic N fixation79, andsst1 mutant nodules show less S accumulated in host cells, in the symbiosome space, and in bacteroids78. SST1 protein was identified by mass spectroscopy in PBM fractions74; however, its localization has not been confirmed by a second method. SST1 belongs to the SULTR family of plant electrogenic H+-coupled SO42− uptake transporters, so the function of SST1 is most likely S uptake into plant cells in the nodule rather than SO42− export to the bacteroids. If SST1 functions in SO42− uptake, then its localization is more likely to be on the plasma membrane rather than the PBM. Other plant nutrient uptake transporters localized to the plasma membrane, such as the phosphate transporter GmPT7 from soybean80, have been shown to be necessary for optimal N fixation and they also function in uptake into nodule cells rather than nutrient export to the bacteroid  and electroneutral (AMT2) ammonium transporters. One common hypothesis is that AMT1s serve as uptake transporters and AMT2s serve as exporters62, but the situation seems to be more complicated and interesting; for example,AMT2-4 fromAzolla has been suggested to be involved in ammonium uptake into the fern. This is an exciting time to study symbiotic interactions because of advances in genome sequencing, transcriptomics, and gene editing. Identification and analysis of the transporters involved will allow us to better understand how symbiotic organisms share nutrients.In this review, we discussed five nutritional symbioses and some common features were found; for example, all of the interactions involve the transfer of fixed C and fixed N. When the form of C exported from a photosynthetic partner is sucrose or its hydrolysis products, glucose and fructose, the type of transporter is likely to be a SWEET. The legume–rhizobia interaction is an exception in that C is transferred in the form of the C


A reference-free computational workflow for the discovery of unannotated RNA biomarkers retrieves novel noncoding RNAs with high potential for prostate cancer diagnosis. The use of RNA-sequencing technologies held a promise of improved diagnostic tools based on comprehensive transcript sets. However, mining human transcriptome data for disease biomarkers in clinical specimens are restricted by the limited power of conventional reference-based protocols relying on unique and annotated transcripts. Here, we implemented a blind reference-free computational protocol, DE-kupl, to infer yet unreferenced RNA variations from total stranded RNA-sequencing datasets of tissue origin. As a bench test, this protocol was powered for detection of RNA subsequences embedded into putative long noncoding (lnc)RNAs expressed in prostate cancer. Through filtering of 1,179 candidates, we defined 21 lncRNAs that were further validated by NanoString for robust tumor-specific expression in 144 tissue specimens. Predictive modeling yielded a restricted probe panel enabling more than 90% of true-positive detections of cancer in an independent The Cancer Genome Atlas cohort. Remarkably, this clinical signature made of only nine unannotated lncRNAs largely outperformed PCA3, the only used prostate cancer lncRNA biomarker, in detection of high-risk tumors. This modular workflow is highly sensitive and can be applied to any pathology or clinical application. A recent approach to RNA-seq data analysis, DE-kupl, combines k-mer decomposition and differential expression analysis to discover transcript variations yet unreferenced in the human transcriptome (PRUNE2 gene and promotes its pre-mRNA editing and degradation (RNA sequencing (RNA-seq) has revolutionized our knowledge of human transcriptome and has been implemented as a pivot technique in clinical applications for discovery of RNA-based biomarkers allowing disease diagnosis, prognosis and therapy follow-up. However, most biomarker discovery pipelines are blind to uncharacterized RNA molecules because they rely on the alignment of uniquely mapped reads to annotated references of the human transcriptome, which are far from complete . Indeed,criptome . Appliedcriptome . They shcriptome . Importacriptome . The onlcriptome . PCA3 isradation . Being oradation . Howeverradation .Since PCA3 discovery and the development of RNA-seq technologies, the PCa transcriptome has been extensively explored by The Cancer Genome Atlas (TCGA) consortium and others to identify numerous PCa-associated lncRNAs (PCAT family) such as PCAT1, PCAT7, or PCAT114/SChLAP1 . HoweverHere, we propose a conceptually novel exploratory framework combining the total stranded RNA-seq of clinical samples and the reference-free DE-kupl algorithm for discovery of novel tumor-specific transcript variations. As a proof-of-concept, we focused on the least explored, noncoding portion of the genome devoid of annotated protein-coding sequences to build an exhaustive catalog of PCa associated subsequences (contigs) embedded into lncRNA genes. The catalog was further refined through minimal filtering to isolate the subset of contigs with best differential expression features and validate 21 of them by a custom NanoString assay in the extended cohort of 144 prostate specimens. From this, a predictive modeling derived a panel of nine yet unannotated lncRNAs validated for robust expression in an independent TCGA cohort. Importantly, its clinical performance surpassed the PCA3 lncRNA specifically in discrimination of high-risk tumors. The proposed probe-set can be further used for development of a PCa diagnostic test. Moving beyond this point, the proposed computational and experimental platform may serve as a tool for biomarkers discovery of any disease and any clinical task aiming at improved medical care and development of precision medicine approaches.Discovery Set, PAIR cohort, Table S1). This Discovery Set was processed by DE-kupl to identify tumor-specific transcripts. DE-kupl directly queries FASTQ files for subsequences (k-mers) with differential counts/expression (DE) between two conditions .Clinicopathological characteristics and recurrence status of the prostate specimens used for the total stranded RNA-seq  contigs (N = 935), splice variants (N = 54), repeats (N = 167), and unmapped contigs (N = 23) . Intersevery Set .P-value below 0.01 were retained for this study.PCa contigs catalog generated by DE-kupl. Only contigs with the length above 200 nucleotides and adjusted Table S2 In conclusion, DE-kupl identified a thousand of PCa-associated RNA variants for the majority embedded into yet unreferenced transcripts which may represent putative novel lncRNAs. This depository was further explored for clinical relevance.Discovery Set. Total RNA-seq produces much more intronic and exon–exon junction reads than poly(A)–selected RNA-seq. This complexity renders laborious in time and machine memory the data analysis by splice graph–based assemblers such as Cufflinks , including multiple intergenic transcripts and transcripts antisense to protein-coding genes, such as HDAC9, TPO, and FBXL7  and the recent GENCODE lncRNA annotation (N = 206) showed that 687 DE-kupl contigs of 1,179 make part of the stand-alone transcripts. Moreover, up to 85.5% and 96.8% DE-kupl contigs embedded into GENCODE and HoLdUp Class 1 lncRNA genes, respectively, were also detected by DESeq as significantly up-regulated transcripts in the same dataset, when the RNA-seq reads were counted within the entire TU  and S2C.XL7 gene .In conclusion, the reference-based assembly protocol HoLdUp is complementary to DE-kupl and allows attributing short RNA subsequences to whole TUs. Nevertheless, DE-kupl was more powerful illuminating much more transcriptomic variations not only within the annotated genes but also within putative new noncoding regions in highly complex and heterogeneous total RNA-seq datasets of clinical origin.signature to describe the set of contigs or genes selected for their ability to predict a sample status. First, contigs were sorted according to their adjusted P-value and, second, were visually selected using the Integrative Genomic Viewer applying the following criteria: (i) when several contigs were present within the same genomic region (5 kb window) the contig with the lowest adjusted P-value was retained, (ii) contigs antisense to expressed exons, bidirectional or positioned in close vicinity to other transcribed protein-coding genes were filtered out. We retained several contigs embedded into already annotated PCa associated lncRNA genes, such as CTBP1-AS , PCAT7 , and PCAT1 , or lncRNAs referenced elsewhere as ctg_104447 (P11) mapped into LOC283177, ctg_123090 (P5) into AC004066.3, and ctg_73782 (P8) into LINC01006. It should be noted that the GENCODE referenced genes enclosing these new subsequences also showed differential expression when counting on the whole gene annotation  downstream of the PCAT7 annotation and antisense to FBP2. The continuous coverage and absence of splice junctions in reads profiling suggest that P2 is enclosed into an extension of the last PCAT7 exon  assigned to the PCAT7 gene itself. Still, additional experiments are required to validate this lncRNA variant, yet absent from the existing PCAT7 annotation.We further leveraged the DE-kupl contig catalog to define a robust PCa signature among putative new lncRNAs using several filters . Hereaftnotation . HoweverAT7 exon . This coP-value below 0.05 are presented.Differential expression analysis of the GENCODE-annotated genes from the total stranded RNA-seq datasets. Only hits with adjacent Table S4 P-values of DE of the Discovery Set (Table S5).In total, 23 candidates belonging to contiguous (N = 21), spliced (N = 1), or repeat (N = 1) subgroups of contigs were selected for further validation, all being expressed at least six times more in tumor tissues than in normal prostate  for RNA expression measurements by the NanoString nCounter assay.Table S5 Selection Set) (Table S6). This cohort contained one additional specimen for normal tissue and 119 additional tumor specimens. To measure contigs expression, an alternative RNA quantification procedure based on the NanoString nCounter platform for direct enzyme-free multiplex digital RNA measurements was carried out .Clinicopathological characteristics, risk classification, and recurrence status of the prostate specimens used in NanoString . Normalized expression of each probe was calculated as a ratio of the raw value to the mean expression of three housekeeping genes .PCA3 and DE-kupl contigs expression measurements by NanoString nCounter assay in 144 specimens of the PAIR cohort  in tumor specimens , CTBP1-AS , and PCAT7  genes, whereas the rest were assigned to novel lncRNAs. Notably, apart from P17 (ctg_36195) and P22 (ctg_119680), expression measurements were consistent between the two technologies, total stranded RNA-seq and NanoString, although the P-value ordering was different .PCA3 and DE-kupl contigs expression quantification assessed by the total stranded RNA-seq in 24 prostate specimens from the PAIR cohort  + RNA-seq datasets, including 52 normal and 505 tumor tissues from radical prostatectomy .Clinicopathological characteristics and recurrence status of the prostate specimens from the TCGA-PRAD cohort  (DLX1 and intergenic P1 (ctg_17297), surpassed PCA3 that ranked third. However, important discrepancies were observed between expression counts in poly(A)+ RNA-seq TCGA datasets and NanoString or total RNA-seq PAIR datasets. First, P22 (ctg_119680) was detected as DE in TCGA-PRAD but failed the DE test when measured by NanoString  antisense to TPO or the intergenic P9 (ctg_9446). Detection of these contigs in TCGA-PRAD was compromised independently of their genomic location (intergenic or antisense) or of the expression level of a sense-paired gene. We hypothesized that it is most likely due to a relatively low RNA-seq coverage and/or to a loss of poorly or non-polyadenylated transcripts during cDNA library preparation in the TCGA experimental setup. Finally, ranking of contigs according to increasing P-values was very different between Selection and Validation Sets highlighting discrepancies between technologies, clinical origins, and cohort sizes.The occurrence of sequences representing 23 DE-kupl contigs was measured and compared with PCA3. In total, 16 of 23 DE-kupl contigs had significant support for overexpression in tumor specimens in the TCGA-PRAD cohort .PCA3 and k-mer contigs expression quantification assessed by the poly(A)+ unstranded RNA-seq in 557 prostate specimens from the TCGA-PRAD cohort . While considering only 21 significantly overexpressed contigs, 17 of them outperformed PCA3 in both contrasts (Table S12). Notably, among the best performe were contigs P6 (ctg_111158) and P2 (ctg_28650) both antisense to FBP2, P10 (ctg_25348) embedded into CTBP1-AS, as well as the novel P16 (ctg_111348) antisense to DLX1 and the intergenic P1 (ctg_17297).To evaluate the robustness of contig expression, we ranked probes by decreasing FC for high-risk against low-risk tumors and positive against negative recurrence status . Most coSelection Set).Mean and FC expression of PCA3, DE-kupl contigs, and housekeeping genes in low-risk (LR) and high-risk (HR) tumors and recurrence negative (NO) and positive (YES) specimens of the PAIR cohort  of the receiver-operating characteristic (ROC), was calculated for each signature and PCA3 alone in the PAIR (Selection Set) and TCGA-PRAD  datasets  logistic regression on the pecimens . First, pecimens . Then, Lpecimens  and S7B.datasets  and S7B.datasets . In addidatasets . RemarkaDiscovery Set retrieved 520 up-regulated genes, protein-coding and noncoding, with adjusted P-values lower than 0.05 and a logFC higher than 2 (Table S4). These genes were then selected on the Discovery Set using LASSO penalized logistic regression to extract a GENCODE whole gene counting based (WGC) signature for further validation  and computational (DE-kupl) tools. De-kupl–derived novel signature demonstrated a sensitivity and robustness towards tumor risk prediction surpassing the state of the art for discrimination of prostate cancer. Furthermore, established nine-probe RNA signature was performed not only independently of tumor origin and its clinicopathological characteristics but also of the technology used for RNA measurements.Molecular biomarker assays are invaluable tools in cancer diagnosis, prognosis and treatment follow-up. Within this scope, sequencing technologies unveiled the pervasiveness and diversity of the human transcriptome, promoting lncRNAs as important cancer signatures . These mDiscovery Set based on comparison of 8 normal with 16 tumor specimens from total RNA-seq datasets was processed by DE-kupl to extract the most significant differentially expressed subsequences in the form of k-mer contigs. Further filtering based on contig length, genomic position, and expression levels powered the pipeline towards the discovery of putative lncRNAs, for the majority, yet unreferenced in the human transcriptome. Then, the catalog of contigs was manually refined and tested for expression using the NanoString single-molecule RNA counting technology in the extended cohort of 144 specimens. Contig expression was next assessed in the independent, publicly available TCGA-PRAD dataset generated by the poly(A)+ unstranded RNA-seq technology. The expression of contigs was systematically compared with that of the benchmark biomarker lncRNA, PCA3. In total, 16 of 23 contigs were validated in both setups but with important differences. Primarily, RNA measurements were consistent between two different technologies: NanoString and total stranded RNA-seq. In contrast, the TCGA poly(A)+ unstranded datasets revealed weakness and high heterogeneity of contig counts over the selected regions, resulting in unexpectedly low signals even for PCA3, considered as a highly expressed lncRNA. Hence, our results promote the total stranded RNA-seq as a first-choice strategy for discovery of RNA biomarkers from clinical samples and when searching for transcripts others than highly abundant mRNAs. It reflects far more precisely the transcriptomic landscape of clinical samples and, hence, is more advantageous as a Discovery Set for development of clinical tests. At the same time, full-length transcript assembly from short-read sequencing is inaccurate, time and computer memory consuming, and this is aggravated by the added complexity of total (ribo-depleted) RNA-seq libraries . The ibraries . DE-kuplibraries . Still, KLK15 and the PSA encoding KLK3 genes, this region makes part of a super-enhancer annotated in several PCa cell lines  or long-read RNA-seq approaches can be useful. Among others, detailed examination of newly discovered contigs revealed a genomic locus on chromosome 19 transcribed in PCa specimens in both directions into the GENCODE-annotated AC011523.2 lncRNA and a novel, antisense transcript embedding the P23 contig (ctg_29077). Located between ll lines . Moreovell lines . Presencll lines . In mostIn this work, we propose DE-kupl as a tool for discovery of novel disease-associated transcriptomic variations, which can be further explored for biological and clinical relevance. As a pilot project, we oriented the pipeline towards the discovery of novel lncRNAs, but using proper masking and filtering criteria defined by the investigator, other variant transcripts, including single nucleotide variations, novel splice events, gene fusions, circular RNAs, or exogenous viral RNAs, could be probed. The workflow can be applied to any RNA-seq datasets of any clinical origin  to generate a probe panel that may be implemented as a multiplex platform for simultaneous detection of RNAs in clinical samples. Moreover, different experimental contrasts  will define the biomarker usage in diagnosis, prognosis, or other clinical applications, hence providing clinicians and researchers with a simple and highly sensitive tool for genomic and personalized medicine.Tumor and normal biopsy specimens were retrospectively collected from prostate cancer patients who provided informed consent and were approved for distribution by the Henri Mondor institutional board (PAIR cohort). Tumor classification in low-, intermediate-, and high-risk prognosis was performed according to Gleason and TNM scores and regardless PSA values , according to the manufacturer’s procedure, quantified, and quality-controlled using a 2100 Bioanalyzer (Agilent). RNA samples with RNA Integrity Number (RIN) above six were depleted for ribosomal RNA and converted into cDNA library using a TruSeq Stranded Total Library Preparation kit (Illumina). cDNA libraries were normalized using an Illumina duplex-specific Nuclease protocol before a paired-end sequencing on HiSeq 2500 (Illumina). At least 20× coverage per sample was considered as minimum of unique sequences for further data analysis.GSE115414. TCGA prostate cancer poly(A)–selected RNA-seq and corresponding clinical data were obtained from publicly available TCGA dataset (http://cancergenome.nih.gov), 557 inputs in total . Among them, 369 patients showed no tumor recurrence, 108 presented a new tumor event (Table S10).Raw paired-end strand-specific RNA-seq data were generated by our laboratory from ribo-depleted total RNA samples of prostate tissues  and can be retrieved from the gene omnibus portal, accession number annotate procedure. We further selected contigs of size above 200 nucleotides and classified them into four categories  based on their location and mapping features (Table S2).DE-kupl run was performed from (June 2017) with parameters ctg_length 31, min_recurrence 6, min_recurrence_abundance 5, pvalue_threshold 0.05, lib_type stranded, diff_method DESeq2. K-mer masking was performed against the GENCODE v24 annotation. DE-kupl analysis of the 8 against 16 PAIR RNA-seq prostate libraries yielded 124,809 DE contigs, in total. Contigs were annotated by alignment on the hg19 human genome assembly using the DE-kupl https://github.com/MorillonLab/HoLDuP_pipeline.The human genome version hg19 and the GENCODE v14 annotation were used in this study. First, we performed a quality control of all sequencing data by FastQC Babraham Bioinformatics software. Reads were mapped using TopHat 2.0.4, allowing three mismatches and requesting uniquely mapped reads, which were further assembled using the BedTools suite. Overlapping contigs from all libraries were merged, and only contigs supported by at least 10 reads in either library were further assembled in segments if mapped in the same strand and separated by less than 100 nucleotides. We compared the segments with the GENCODE v14 annotation to extract antisense and intergenic TUs longer than 200 nucleotides. To classify lncRNAs, we applied the following criteria: (i) an expression level above 0.2 quartile of mRNA expression in at least one condition per tissue (Class 2); (ii) within this class, all TUs containing at least one TopHat-identified exon–exon junction and at least one spliced EST from UCSC mapped contigs were assigned to Class 1. The whole catalog, the R code, and Data Tables can be downloaded from Intersection between transcripts was counted only in the case of 50% overlap of nucleotide sequence between genomic coordinates of each fragment.featureCounts 1.6.0 with the following parameters: -F “SAF” -p -s 2 -O and the DESeq R package . Gene expression counts were normalized using the DESeq2 median of ratio  for each sample, using  package . Only RNof ratio . ScriptsRPL11, GAPDH, NOL7, GPATCH3, ZNF2, and ZNF346), 23 contigs and the one known PCa-associated lncRNA, PCA3. Each target gene of interest was detected in RNA samples of 144 specimens  of the PAIR cohort (Table S6) on NanoString nCounter V2 using reporter and capture probes of 35- to 50-nucleotide targeting sequences listed in Table S4. Data was normalized through the use of NanoString’s intrinsic negative and positive controls according to the normalization approach of the nSolver analysis software  and then contig expression was calculated relative to the average signal of three housekeeping genes . Raw and normalized data for each specimen, and mean and fold change expression in normal against tumor samples are presented in Tables S7 and S8.100 ng of total RNA was used for direct digital detection of 29 target transcripts: six housekeeping genes (Jellyfish count and counted representative k-mers in each Jellyfish count file using the Jellyfish query command (Jellyfish Dump files produced for each TCGA-PRAD library. Sampling was performed as follows: (i) we extracted all k-mers from the contig that were unique in the Ensembl human v91 transcript reference, and (ii) from this list, we sampled 10 regularly spaced k-mers, starting from the first 10% and ending in the last 10% of the list. This sampling procedure was repeated four times for each contig. For the whole TCGA library and each contig, the 10 k-mer counts obtained by Jellyfish were averaged, yielding one average count per sample per library Table S13. Pearson correlation analysis for two DE-kupl contigs P1 and P16 are shown in https://github.com/MorillonLab/Prostate-kmer-signatures.DE-kupl provides representative k-mers for each differentially expressed contig. We converted the TCGA-PRAD FASTQ files to k-mer counts using  command . Counts Validation Set).PCA3 and DE-kupl contigs expression quantification assessed by the total stranded RNA-seq in 557 prostate specimens from the TCGA-PRAD cohort  levels of contigs assessed by the NanoString nCounter assay using a ComplexHeatmap R-package . ScriptsSelection Set (23 probes in 144 observations) as a variable selection dataset and contigs counts table of the Validation Set (23 probes in 557 observations) as an external validation dataset  –selected and unstranded. To build the ROC curves, we sampled 100 datasets in two, for training (70%) and testing (30%) preserving the relative ratio of labels in each. We used boosted logistic regression with upsampling, setting the number of boosting iterations to 100 and using leave-one-out cross validation scheme on the training set. After training, we evaluated the predictor on the testing set and repeated the procedure for each one of the 100 training and testing sets described above to obtain an average ROC curve, mean and SD for AUC scores. Contig expression counts in the Validation Set (TCGA-PRAD) were obtained as described above using the DE-kupl derived representative k-mer for each contig. Quantifications based on 10 randomly sampled k-mers per contig did not alter predictive performance  . Selectiecimens) . Second,packages . Note thformance . To builGSE115414. TCGA prostate cancer poly(A)–selected RNA-seq and corresponding clinical data can be obtained from TCGA portal (https://www.cancer.gov/tcga).Raw paired-end strand-specific RNA-seq data can be retrieved from the gene omnibus portal, accession number


Escherichia coli and Sinorhizobium meliloti were largely processed into shorter dsRNA fragments with no or few full-length molecules being present. A loss-of-function mutation in the dsRNA-processing enzyme RNase III, in the widely used E. coli HT115 strain, did not prevent the processing of hpRNA. Consistent with previous observations in plants, the loop sequence of long hpRNA expressed in Agrobacterium-infiltrated Nicotiana benthamiana leaves was excised, leaving no detectable levels of full-length hpRNA molecule. In contrast to bacteria and plants, long hpRNAs expressed in the budding yeast Saccharomyces cerevisiae accumulated as intact, full-length molecules. RNA extracted from hpRNA-expressing yeast cells was shown to be capable of inducing RNAi against a β-glucuronidase (GUS) reporter gene in tobacco leaves when applied topically on leaf surfaces. Our results indicate that yeast can potentially be used to express full-length hpRNA molecules for RNAi and perhaps other structured RNAs that are important in biological applications.Hairpin-structured (hp) RNA has been widely used to induce RNA interference (RNAi) in plants and animals, and an in vivo expression system for hpRNA is important for large-scale RNAi applications. Bacterial expression systems have so far been developed for in vivo expression of hpRNA or double-stranded (ds) RNA, but the structure of the resulting RNAi molecules has remained unclear. Here we report that long hpRNAs expressed in the bacteria  Hairpin-structured RNA (hpRNA) is widely used to induce RNA interference (RNAi) in plants and animals, where the long double-stranded RNA (dsRNA) is processed by Dicer or Dicer-like (DCL) proteins into 21–24 nt small interfering RNAs (siRNAs) that bind to and guide Argonaute proteins to degrade cognate single-stranded RNA .Caenorhabditis elegans where ingestion of synthetic dsRNA or bacteria expressing dsRNA triggered systemic gene silencing  UTP by in vitro transcription [Northern blot hybridization was performed essentially as described using the same hybridization solutions and procedures : 50 ng ocription . The hybFor qRT-PCR analysis of the stem and loop expression, 2 µg of total RNA isolated from yeast (expressing hpGUS-1) and HT115 (containing the 35S-driven hpGUS-1) was treated with RNase-free DNase I  at 37 °C for 30 min, then it was purified with phenol/chloroform extraction and ethanol precipitation. The purified RNA was reverse transcribed with Superscript III reverse transcriptase (Invitrogen) following the manufacturer’s instructions using random hexamer primers. Real-time PCR was performed in three technical triplicates on a Corbett 2000 Rotor-Gene machine , using Fast SYBR Green Master Mix , following the manufacturer’s instructions. The same RNA samples (2 µg) without DNase treatment and reverse transcription were amplified using the same primer pairs for use as reference for qPCR normalization. Primer sequences are listed in the Nicotiana tabacum Wisconsin 38) line containing a single copy of constitutively expressed GUS gene  was used for the RNAi assay. Expanded tobacco leaves were excised from plants in a growth room and placed in a Petridish on top of a wet filter paper. Each leaf was cut into three sections to avoid cross contamination among the three hpRNAs, and an approximately 2 cm2 area of each section was treated with hpRNA samples. Sixty micrograms of yeast or bacteria total RNA in 60 µL resuspension buffer  was applied to the leaf areas using a soft paintbrush, usually requiring more than one brushing to apply the whole 60 µL solution. The treated leaf sections were kept in a petri dish at room temperature under natural light. The same assay was performed on four separate GUS-expressing leaves. A homozygous, transgenic tobacco (d-glucuronide (MUG) assay was performed using the kinetic method as described in Chen et al [4, pH = 7; 10 mM EDTA; 0.1% Triton X-100; 0.1% N-laurylsarcosine; and 10 mM β-mercaptoethanol), and centrifuged at 4 °C for 10 min. Supernatant was transferred into a fresh Eppendorf tube, and 5 µL was used for each measurement. MUG assay was carried out in three technical replicates at 37 °C, and the relative GUS activity was calculated using the slope of the reaction curve against protein concentration [hpRNA-treated leaf samples were harvested by cutting out half of the treated areas using a pair of scissors at 5 and 22 h after treatment, and they were immediately frozen in liquid nitrogen. A 4-methylumbelliferyl-β-en et al . Basicalntration . E. coli strain HT115 was developed to facilitate the production of dsRNA for RNAi, which allows for a high level of dsRNA accumulation because of the loss of dsRNA-specific RNase III activity [E. coli and HT115 a plasmid construct designed to express long hpRNA (hpGUS-1) with a ~560 bp dsRNA stem plus ~1.1 kb loop derived from the coding sequence of the β-glucuronidase (GUS) gene. This construct was driven by a cauliflower mosaic virus 35S promoter  was performed using a primer against the stem , they are not suitable for expressing full-length hairpin-loop dsRNA molecules. Our results in this study also confirm the previous observation that hpRNA expressed in plants gives rise to a distinct fragment of the loop sequence, with little full-length hpRNA molecules detectable [In this study we demonstrated that long hairpin-structured RNA expressed in bacteria, including the RNase III-deficient nstructs ,20,21. Ttectable ,34. S. cerevisiae accumulated mainly as full-length molecules. Yeasts are eukaryotic organisms encoding various RNases, including RNase III-like enzymes, in their genomes. How hpRNA loops are protected from RNase processing in S. cerevisiae, and whether this protection also occurs generally in other yeast strains or fungi, requires further investigation. A unique feature of S. cerevisiae among most of the eukaryotic organisms including fungi is that it lacks the key RNAi components such as Dicer [S. cerevisiae can be used to express full-length hpRNA, and the resulting hpRNA was functional at inducing exogenous RNAi. Potentially, the yeast expression system can be modified for large-scale production of hpRNA or other structured RNAi molecules.In contrast to bacteria, long hpRNA expressed in the laboratory yeast strain of as Dicer . It willADH gene promoter construct was relatively low, similar to that from HT115 cells expressing the 35S promoter-driven construct and well below the amount of T7 promoter-expressed dsRNA in HT115. We estimated using northern blot hybridization that each µg of yeast total RNA contained about 2 ng of hpRNA, whereas the bulk of RNA from the HT115-T7 polymerase system was hpRNA-derived product. The advantage of the yeast expression system is the integrity of the resulting structured RNA, and future improvements incorporating high-level expression cassettes similar to the T7 [Currently, the amount of dsRNA from the yeast expression system using the yeast o the T7 ,35 or pho the T7  polymeraS. cerevisiae has been widely used in virus studies, and a number of plant and animal RNA viruses and subviral RNAs have been shown to replicate successfully in the yeast cells [S. cerevisiae. If so, this yeast expression system can be widely used for the production of structured RNAs.In addition to exogenous RNAi, expression of structured RNAs is important in many other applications. For instance, viral and subviral RNAs are characterized by specific secondary structures that are important for their replication in host cells, and maintaining structural integrity is required for the infectivity of viral RNA transcripts in infection experiments . Interesst cells ,25,26,27


The secondary structures of hepatitis C virus (HCV) RNA and the cellular proteins that bind to them are important for modulating both translation and RNA replication. However, the sets of RNA-binding proteins involved in the regulation of HCV translation, replication and encapsidation remain unknown. Here, we identified RNA binding motif protein 24 (RBM24) as a host factor participated in HCV translation and replication. Knockdown of RBM24 reduced HCV propagation in Huh7.5.1 cells. An enhanced translation and delayed RNA synthesis during the early phase of infection was observed in RBM24 silencing cells. However, both overexpression of RBM24 and recombinant human RBM24 protein suppressed HCV IRES-mediated translation. Further analysis revealed that the assembly of the 80S ribosome on the HCV IRES was interrupted by RBM24 protein through binding to the 5′-UTR. RBM24 could also interact with HCV Core and enhance the interaction of Core and 5′-UTR, which suppresses the expression of HCV. Moreover, RBM24 enhanced the interaction between the 5′- and 3′-UTRs in the HCV genome, which probably explained its requirement in HCV genome replication. Therefore, RBM24 is a novel host factor involved in HCV replication and may function at the switch from translation to replication. The genome of hepatitis C virus (HCV) is composed of a single open reading frame (ORF) flanked by 5′- and 3′-untranslated regions (UTRs). The ORF encodes a polyprotein of approximately 3,000 amino acids (aa) that is processed into viral structural and non-structural proteins by host and viral proteinases. Like other positive-strand RNA viruses, the genomic RNA of HCV is believed to serve as the template for translation and negative-strand RNA synthesis  located at the 3′ end of the NS5B coding region -binding protein 2 (PCBP2) and mice minute virus NS1-associated protein 1 (NSAP1) , which bind to double or single-stranded RNA, play key roles in the post-transcriptional control of RNA. Previous reports have shown that RNA binding protein 24 (RBM24), which harbors a single RRM at its N-terminus, is required for cardiovascular development and myogenesis because it regulates the stability and/or alternative splicing of the mRNAs of related genes . The intracellular HCV RNA were monitored by realtime RT-PCR immediately after the electroporation and served as input RNA. When normalized by the abundance of input RNA, the luciferase activity at 4 h post electroporation was decreased by RBM24 overexpression, suggesting that RBM24 inhibit the translation efficiency of HCV  and 3′-UTR (J9440–9678), but not of the regions containing Core  or the NS5B coding region elements (J9116–9463), were strongly crosslinked to Flag-RBM24 . Thus, RBM24 regulate the viral protein expression in a novel way. The binding of RBM24 to RNA could be either sequence-dependent or structure-dependent, and it could interact with different RNAs and possibly be involved in the replication of other viruses, as have been reported for the binding of PTB and La protein to the RNAs of encephalomyocarditis virus (EMCV), Japanese encephalitis virus (JEV) and HBV  and 293T cells were cultured in Dulbecco’s modified Eagle medium (DMEM) with 2 mmol/L of glutamine ,10% fetal bovine serum (FBS)  and 100 U/mL of penicillin-streptomycin  at 37°C in a 5% COin vitro-transcribed and electroporated into Huh7.5.1 cells as previously described , was linearized, To measure the intracellular virus titers, cells were washed and collected in 200 μL PBS and lysed by 3 rounds of freezing and thawing. Jc1 virus was titrated by immunostaining with the NS3 antibody as described by Jones et al. . BrieflyThe HCV protein expression plasmids pXJ40-HA-Core, pXJ40-HA-NS3/4A, pXJ40-HA-NS5A and pXJ40-HA-NS5B have been described previously  cells were transformed with pET33b-EK-RBM24. A positive monocolony was inoculated into 1 L of LB medium containing 50 μg/mL of kanamycin and grown at 37°C in a shaker until the A600 reached 0.6. Cells were induced with 0.5 mmol/L isopropyl β-D-1-thiogalactopyranoside for 4 h at 37°C and were then harvested by centrifugation and resuspended in low imidazole buffer , 0.02% NaN3, 20% glycerol, and 10 mmol/L imidazole) with 0.5% IGEPAL® and 0.07% β-ME. Next, the cells were lysed using an ultrasonic homogenizer, and the lysate was clarified by centrifugation and filtration through a 0.22 μmol/L syringe filter. The supernatant was loaded onto a column containing 10 mL Ni-NTA His∙Bind® resins . After washing sequentially with 10 mmol/L, 50 mmol/L and 100 mmol/L imidazole buffer , the protein was eluted with 1.5 column volumes of 500 mmol/L imidazole buffer and circulated at 37°C for 15 min. After the protein was dialyzed into enterokinase buffer (20 mmol/L Tris (pH 8.0), 50 mmol/L NaCl, 2 mmol/L CaCl2, and 10% glycerol), the tag was removed by enterokinase  digestion followed by Trypsin inhibitor-Agarose  and His∙Bind resin incubation to remove the enterokinase and potentially undigested protein. Tag-free recombinant human RBM24 (rhRBM24) was then dialyzed in RNA binding buffer, concentrated with PEG 20,000, passed through a 0.22 μm syringe filter, aliquoted and stored in liquid nitrogen.Plasmids and siRNAs were transfected into cells using Lipofectamine 2000 , according to the manufacturer’s instructions. The following siRNAs were used: AllStars negative control siRNA , siHCV (target sequence: 5′-GGUCUCGUAGACCGUGCAC-3′) and siRBM24 . Because transfection of siRBM24 once reduces the RBM24 mRNA level but not the protein level, transfection was performed twice as previously described , following the manufacturer’s instructions. The primers for HCV and actin have been described previously . Biotin-11-UTP  or [α-32P]-UTP  was added to the reaction as required to produce labeled RNA. These RNA fragments were then denatured, digested with TURBO™ DNase  at 37°C for 30 min, purified with TRIzol and dissolved in appropriate buffer.First, the DNA templates for in vitro translation was generated according to the sequence of pSGR-Luc-JFH1 -based translation reaction system was established as previously described  and 12.5 pmol of rhRBM24 or BSA were added to a ribosome assembly mixture based on RRL. The mixtures were incubated at 30°C for 15 min. The reaction was halted, and the mixtures were analyzed with 10%–40% sucrose gradients by ultracentrifugation, as previously described , 0.5% IGEPAL®, 1 mmol/L DTT, 100 units/mL RNasin®, 400 μmol/L Ribonucleoside Vanadyl Complex  and complete protease inhibitor cocktail (Roche)) and inverted for 30 min at 4°C, and the cell lysate were then centrifuged at 12,000 ×g for 15 min to remove cell debris. The cell lysate containing 800 μg total protein was incubated with protein G beads pre-coated with mouse anti-FLAG  or a non-specific control antibody at 30°C for 4 h. After washing 5 times with NT-2 buffer (50 mmol/L Tris-HCl (pH 7.5), 150 mmol/L NaCl, 1 mmol/L MgCl2, and 0.05% IGEPAL®), precipitated RNA was extracted with TRIzol for subsequent analysis.RIP was performed as previously described with minor optimizations  were incubated with 100 μg total protein for 20 min and then UV crosslinked with a HL-2000 Hybrilinker on ice for 10 min. 400 μL IP buffer containing 30 μg RNase A and 30 U RNase ONE™ were added to each reaction and incubated at 37°C for 1 h. The mixtures were incubated with protein G beads coated with the indicated antibody at 30°C for 4 h. The beads were then washed 5 times with IP buffer, incubated at 95°C for 10 min with 2× Laemmli buffer and subjected to SDS-PAGE. The gel was dried with a Model 583 gel dryer (Bio-Rad) and autoradiographed on a phosphor screen  for 1–7 days. Signal was collected with a Cyclone® Plus and analyzed with OptiQuant™.Total protein was prepared from 293T cells transfected with Flag-RBM24 using polysome lysis buffer without RNasin. 32P-labeled probes for HCV positive-strand and negative-strand detection were prepared by in vitro transcription and dissolved in 1× RPA Buffer (40 mmol/L PIPES (pH 6.4), 1 mmol/L EDTA (pH 8.0), 400 mmol/L NaCl, and 80% formamide). Standard RPA was performed to detect positive-strand HCV RNA , 5 mmol/L EDTA, 350 U/mL RNase T1, and 4.5 μg/mL RNase A) at 30°C for 1 h. Reactions were stopped by the addition of 50 μg of proteinase K and 20 μL 10% SDS. The samples were precipitated with ethanol and glycogen  and analyzed by 6% urea-PAGE. The gel was dried and autoradiographed as described above.2) were folded by incubation at 70°C for 2 min and cooled at RT. The total protein (400 μg) of interest was incubated with 50 pmol of the indicated folded biotin-RNA fragments, 40 U of RNasin and 50 μg of yeast tRNA  at 30°C for 30 min. Dynabeads M-280 Streptavidin  were resuspended with 400 μL of RNA binding buffer after being sequentially washed with 1 mL each of solution A (0.1 mol/L NaOH and 0.05 mol/L NaCl), solution B (0.1 mol/L NaCl) and RNA binding buffer , 5 mmol/L MgCl2, 10% glycerol, 1 mmol/L DTT, 0.1% IGEPAL®, and 400 μmol/L RVC), with two washes in each solution. The aforementioned motioned protein-RNA mixtures were then added to the beads and incubated at 30°C for 2 h. The beads were washed 5 times with RNA binding buffer by magnetic separation, incubated at 95°C for 10 min with 2× Laemmli buffer, and subjected to Western blotting.The biotin-RNA fragments of interest dissolved in RNA folding buffer , and 5 mmol/L MgCl32P-labeled RNA probes were incubated with BSA or rhRBM24 in the presence of 10 μg tRNA  or **(P < 0.01).The data were analyzed using the two-tailed unpaired


SOD1, TARDBP, FUS, and C9orf72 are involved in aspects of RNA metabolism processes such as mRNA transcription, alternative splicing, RNA transport, mRNA stabilization, and miRNA biogenesis. In this review, we highlight the current understanding of RNA dysregulation in ALS pathogenesis involving these major ALS genes and discuss the potential of therapeutic strategies targeting disease RNAs for treating ALS.Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease and is characterized by the degeneration of upper and lower motor neurons. It has become increasingly clear that RNA dysregulation is a key contributor to ALS pathogenesis. The major ALS genes  Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neurodegenerative disorder of motor function. It is characterized by the selective degeneration of the lower and upper motor neurons. Among the symptoms of this disease are progressive muscle weakness and paralysis, swallowing difficulties and breathing impairment due to respiratory muscle weakness that ultimately causes death, usually within 2–5 years following clinical diagnosis . Though SOD1 (Cu-Zn superoxide dismutase 1), TARDBP (transactive response DNA Binding protein 43kDa), FUS (fused in sarcoma) and hexanucleotide expansion repeat in Chromosome 9 Open Reading Frame 72 (C9ORF72). These genetic discoveries have led to the development of animal models  (TAF15) (hnRNPA1) (hnRNPA2 B1) (MATR3) (EWSR1) (TIA1) (SETX) and angiogenin (ANG) (Mutations in over more than 20 genes contribute to the etiology of ALS  Table 11. Amongsl models  that perl models . Mutatioproteins . In addi (ATXN2) , TATA-bo (TAF15) , heteroghnRNPA1) , heterogNPA2 B1) , matrin  (MATR3) , Ewing’s (EWSR1) , T-cell-) (TIA1) , senataxin (ANG) , play crSOD1, TARDBP, FUS, and C9orf72) and present how they play critical roles in various RNA pathways. We particularly highlight recent developments on the dysregulation of RNA pathways  (NLGN1-2) (MAP1B)    and reduced quantal transmission. Remarkably, they also demonstrated that all these synaptic dysfunction features in their zebrafish TARDBP mutant were stabilized by chronic treatment the L-type calcium channel agonists , a glycine rich domain in the C-terminus and nuclear localization and export signals (NLS and NES) . TDP-43 NRXN1-3) , neuroliNLGN1-2) , scaffolNLGN1-2) , microtu (MAP1B) , GABA re GABRA3) , AMPA re, GRIA4) , syntaxi, GRIA4) , and cal, GRIA4) . The dev, GRIA4)  and cont, GRIA4) . Armstroagonists . In drosagonists . Overexpagonists . In TDP-POLDIP3) variant-2 mRNA (lacking exon 3) was significantly increased in the CNS of ALS patients with ALS, while that of variant-1 mRNA remained unchanged (POLDIP3 and that depletion of TDP-43 in cell culture models increased variant-2 mRNA (CFTR) gene and controls exon skipping by within the pre-mRNA (APOAII) (SMN) transcripts  to the pathogenesis of ALS.TDP-43 is also known to act as a splicing regulator to reduce its own expression level by binding to the 3′ UTR of its own pre-mRNA . Additionchanged . This wat-2 mRNA . TDP-43 pre-mRNA . Importa(APOAII)  and survnscripts . Specifi neurons . Furthersplicing . TDP-43 splicing . Collectin vivo and in vitro (NFL) mRNA to stabilize it , dendritic development (ACTL6B) and action potential transmission in skeletal muscles (SCN8A and SCN4A) (MAPT) (NTNG1) ((NRCAM) (LIM (ABLIM1)   and may ) (MAPT) , Netrin  (NTNG1) , neurona((NRCAM)  and the (ABLIM1) . For exa(ABLIM1) . Loss of(ABLIM1) . DisruptTAF15, which is mutated in some case of ALS , RNA polymerase III (RNAP3) or cyclin D1 . For inse of ALS , has beee of ALS , FUS knoe of ALS . HoweverIn vivo expression of Pur-alpha in Drosophila significantly exacerbates the neurodegeneration caused by mutated FUS. Conversely, FUS is also incorporated into stress granules under cellular stress conditions . SequestVEGF) and NFL and negatively affects their expression, stabilization and function  subunits and subsequent NF aggregation in motor neurons (NFL mRNA level has been reported to result in NF aggregation and neurite degeneration (In motor neuron-like NSC34 cell lines expressing mutant SOD1 (G37R or G93A), the level of  reduced . ReductiLS cases . It is p neurons . NF incl neurons . In IPSCneration . AltogetNFL mRNA stability  can be generated by repeat-associated non-ATG-dependent (RAN) translation of both the sense and antisense strands that have a variety of toxic effects . Poly-PRPTX3 RNA . DipeptiPTX3 RNA . Poly-GRPTX3 RNA . This suPTX3 RNA . Suzuki PTX3 RNA . RNA seqPTX3 RNA . Other fPTX3 RNA . The accPTX3 RNA .C9orf72 transcripts  . They aronecut1, which in turn helps to drive differentiation of neural progenitor cells into spinal motor neurons  which consequently to depolymerization and degradation of tubulin alpha-4A (TUBA4A), which is encoded by a known ALS gene  expression leaving wild-type SOD1 intact . The desin vitro and in vivo  exhibited delayed diseases onset and significantly increased their survival by 23%  systemically delivered using the viral vector AAVrh10 in G93ASOD1 mice was also found to significantly delayed disease onset, preserved muscle motor functions and extended survival  has been proposed as a therapeutic strategy for SOD1-link ALS and has been clinical tested. In a phase I testing, intrathecal administration of the ASO IONIS-SOD1Rx was showed to be both practical and safe in SOD1 ALS patients n RNA and showed that the bioactive small molecule 1a significantly inhibited RAN translation and foci formation in cultured cells (GGGGCC)66 repeat expansion and in patient-derived neurons . They represent an important way to treat ALS and other neurodegenerative diseases that need to be considered in the near future. However, there are still some concerns and challenges to overcome for ALS therapeutic applications.Off-target effects RNAi and ASO remain an important consideration though thorough toxicological and safety research prior to clinical application can diminish some of this concern. The negative charge of siRNA and ASO as well as their size makes it difficult for them to cross the cell membrane. Viral packing is currently widely used to deliver ASO and siRNA into cells. Although, viral vectors are highly efficient as transfer vehicles, immunogenicity of the viral vectors is a major concern. Various other delivery strategies such as nanoparticles, liposomes and aptamers could be more effective and safe. Efforts are also underway to chemically stabilize siRNA, which will avoid the need for viral vectors . RNA focTDP-43, SOD1, FUS, and C9orf72 mutations are involved at various aspects of RNA processing and many of which are shared. It is becoming clear that impaired RNA regulation and processing is a central feature ALS pathogenesis. Given that defects at multiple steps of RNA processing impair cellular function and survival, RNA metabolism can be considered an essential target for therapeutic intervention for ALS and other neurodegenerative disease such as FTLD. The application of RNA-based therapies to modulation of gene and subsequent protein expression is an attractive therapeutic strategy. The preclinical testing of RNA-based therapies targeting SOD1 and C9orf72 mutations are indeed very promising. Similar studies are yet to be undertaken for FUS and TDP-43 mutations. RNA-based therapies could be considered in the future for the treatment of ALS.SP contributed to the idea conception and overall review design. ZB and SP wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Ribosome biogenesis is a complex process orchestrated by a host of ribosome assembly factors. Although it is known that many of the proteins involved in this process have RNA binding activity, the full repertoire of proteins that interact with the precursor ribosomal RNA is currently unknown. To gain a greater understanding of the extent to which RNA-protein interactions have the potential to control ribosome biogenesis, we used RNA affinity isolation coupled with proteomics to measure the changes in RNA-protein interactions that occur when rRNA transcription is blocked. Our analysis identified 211 out of 457 nuclear RNA binding proteins with a >3-fold decrease in RNA-protein interaction after inhibition of RNA polymerase I (RNAPI). We have designated these 211 RNA binding proteins as the RNAPI RNA interactome. As expected, the RNAPI RNA interactome is highly enriched for nucleolar proteins and proteins associated with ribosome biogenesis. Selected proteins from the interactome were shown to be nucleolar in location and to have RNA binding activity that was dependent on RNAPI activity. Furthermore, our data show that two proteins, which are required for rRNA maturation, AATF and NGDN, and which form part of the RNA interactome, both lack canonical RNA binding domains and yet are novel pre-rRNA binding proteins. The ribosome is a complex macromolecular machine, composed of ribosomal RNA (rRNA) and ribosomal proteins, which translates the genetic code into functional polypeptides. Ribosome biogenesis commences with the synthesis of a large precursor rRNA (pre-rRNA) by RNA polymerase I (RNAPI). Processing of the pre-rRNA through cleavage and trimming events leads to the production of mature 28S, 18S and 5.8S rRNA. Ribosomal proteins are precisely guided on to the folding rRNA to form the pre-40S and pre-60S ribosomal subunits . Many ofWith the advent of RNA interactome capture (RIC) it has emerged that RNA binding proteins are considerably more prevalent than was previously realised . One rec2. U-2 OS were cultured in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% FBS and MCF10A in DMEM/F12 Ham's Mixture supplemented with 5% horse serum, 10 μg/ml insulin (Sigma-Aldrich), 100 ng/ml cholera toxin (Sigma-Aldrich), 20 ng/ml EGF (Peprotech) and 0.5 mg/ml hydrocortisone (Sigma-Aldrich). MCF10A and U-2 OS cells were treated with 10 nM actinomycin D (Sigma-Aldrich) or 2.5 μM CX5461 (Selleckchem).U-2 OS and MCF10A cells were grown at 37°C with 5% COThe U-2 OS Flp-In T-REx cell line was generated using the manufacturer's recommended protocol (Thermo Fisher Scientific). The coding regions of AATF, NGDN and TAP26 were inserted in frame with the N-terminal 3xFLAG tag in pCDNA5/FRT/TO (Thermo Fisher Scientific). Constructs were then transfected into the U-2 OS Flp-In T-REx cell line and stable clones were selected with 100 μg/ml hygromycin B (Invitrogen) and 2.5 μg/ml blasticidin (Corning).For western analysis, proteins were separated on 4–12% SDS PAGE gel (Thermo Fisher Scientific), transferred on to PVDF membrane (Bio-Rad) and detected with the indicated antibodies .2, 0.35 M sucrose, 0.5% NP-40) with protease inhibitors  for 5 min on ice and then centrifuged at 1300g for 5 min at 4°C. The nuclear pellet was washed twice with CLB and incubated for 30 min in SNEB buffer  with protease inhibitors, with or without 0.2 U/ml Benzonase (Novagen), as indicated. The extract was then cleared by centrifugation.To prepare nuclei, U-2 OS cells were incubated in CLB buffer  were incubated for 30 min with 3 μg of specific antibody  or rabbiFor RNA immunoprecipitations (RIP), U-2 OS cells were cross-linked with 0.2% formaldehyde for 8 min, incubated in neutralisation buffer (2.5 M glycine and 25 mM Tris pH 7.4) for 5 min and washed twice in PBS. Nuclear extraction and immunoprecipitation were conducted as described above with the following modifications. The beads were washed twice in 20 mM HEPES pH 7.5, 350 mM NaCl, 1% NP40, 0.5% deoxycholate, 0.25% SDS, 5 mM DTT for 3 min and twice with 20 mM Tris pH 7.4, 150 mM NaCl, 0.1% NP-40 for 5 min. Finally, the beads were treated with proteinase K (Thermo Fisher Scientific) and Turbo DNase (Ambion). Purified RNA was used for RT-qPCR analysis.Reverse transcription was performed with random primers (Invitrogen) and Superscript™ II (Thermo Fisher Scientific) according to the manufacturer's instructions with 5 μl of purified RIP RNA or 300 ng of total RNA. The qPCR was performed using SensiFAST™ Sybr Lo-Rox Mix kit (Bioline) with specific primers to amplify sequences .2) irradiation. Nuclei were isolated as described above and were resuspended in oligo(dT) binding buffer . Nuclear lysate was incubated with magnetic oligo(dT) beads (NEB) for one hour at room temperature. Subsequently, the beads were washed and the RNA was eluted from the beads  and 300U RNase I (Ambion) to digest the RNA.RIC was performed on nuclear extracts of MCF10A and U-2 OS. Briefly, cells were treated with 10 nM actinomycin D, 2.5 μM CX5461 or DMSO. Cells were washed with cold PBS, and cross-linked with UVC (150 mJ/cmin situ with trypsin (LC–MS/MS was used to identify and quantify RNA binding proteins (RBPs) as described previously . Briefly trypsin . Extract trypsin .U-2 OS cells were seeded on to glass coverslips and after the indicated treatments were fixed in 4% paraformaldehyde. Primary antibody incubations were performed at 4°C overnight with the indicated antibodies . Secondahttp://bioconductor.org/packages/release/bioc/html/mygene.html). We assessed our dataset using Gene Ontology, InterPro domain and KEGG pathway annotations all accessed via the ‘mygene’ package  affinity chromatography. This isolation process allows for the use of highly stringent wash conditions to remove any non-covalently bound proteins. Consequently, after nuclease digestion to remove the RNA, the sample is highly enriched for proteins that interact with mRNA  to preferentially inhibit rRNA transcription . Furthermore, a comparison of the MCF10A RNA interactome capture data with those from three other cell lines  terms (95%) are functionally annotated as RNA binding  and intell lines ,20 showell lines . A substll lines . In conjet al.  of which 75% (144) are RNAPI-dependent . In addiet al.  with 79%et al. . To gainet al. ) and nucet al. ). Our daet al. . Taken tTo gain insight into the function of the nuclear RBPs, we performed enrichment analyses using Kyoto Encyclopedia of Gene and Genomes (KEGG) pathways and GO terms Figure . KEGG paWe chose to investigate further RNAPI-dependent RBPs that have no canonical RNA binding domains and have a poorly characterised role in ribosome biogenesis Figure . Thus, Amyc mRNA was unaltered by these treatments  or nucleophosmin (NPM), which are RBPs with well-described roles in ribosome biogenesis, were used as positive controls, and the mRNA binding protein, PTB, was used as a negative control. After inhibition of RNAPI, there was a considerable reduction in the recovery of AATF, NOL10, NGDN, TAP26 and IFI16 in the RIC samples and a more modest reduction in the recovery of the Ku proteins Figure . The preTo provide direct evidence for the interaction of proteins identified in our RNAPI interactome with ribosomal RNA we chose to study AATF and NGDN in further detail. It has been suggested that these proteins in combination with NOL10 form a complex, the ANN complex, that plays a role in 18S rRNA maturation by facilitating endonucleolytic cleavage within the 5′ETS and ITS1 . Our RNAInitially, we attempted to confirm the previously published interaction between these three proteins . When enin vivo using a short exposure to a relatively low concentration of formaldehyde. Subsequently, immuno-affinity isolation was performed with stringent lysis and wash conditions to selectively purify cross-linked RNA-protein complexes. After immunoprecipitation, the association of AATF and NGDN with pre-rRNA was investigated by RT-qPCR amplification of the 5′ETS pre-rRNA sequence. In the absence of cross-linking, pre-rRNA is enriched in the AATF immunoprecipitation by ∼40-fold compared to the IgG control. However, after cross-linking there is a 315-fold enrichment of pre-rRNA in the AATF immunoprecipitation /DNA oligonucleotides covalently coupled to a magnetic resin , suggesting that some of these interactions may not be rRNA specific. The authors suggested that the dearth of ribosomal proteins identified was likely to be due to inefficient crosslinking of proteins bound to double-stranded RNA, which involves much of the ribosomal RNA. Importantly, our data show that the many interaction sites provided by mRNA-rRNA contacts in the RIC technique are sufficient to overcome such issues and the method that we use provides an accurate data set of the RBPs that interact with rRNA.An alternative strategy to identify RBPs associated with a specific transcript is to use oligonucleotides-linked to beads that target a defined RNA. For example, the recently developed method by Rogell ic resin . HoweverRNAPI is known to generate two species of RNA, the 45S pre-rRNA and non-coding RNA derived from the intergenic spacer region of rDNA (IGS rRNA) . IGS rRNImportantly, the RNAPI RNA interactome provides a new tool to understand how RNA-protein interactions control ribosome biogenesis. These data are of considerable interest since there are a number of disorders that are associated with dysregulated ribosome biogenesis. These include leukaemias , solids tumours  and a group of rare syndromes termed ribosomopathies, many of which are associated with an increased cancer risk ,34. Ribo. Ribo34.https://bitbucket.org/emm13/2018_pineiro_nucleolarrbp/src.Code used in this study and supplementary data can be accessed via Bitbucket using this link Supplementary DataClick here for additional data file.


The role of many lncRNAs in cancer remains elusive including that for a Prostate Cancer Associated Transcript 92 (PCAT92). PCAT92 shares the locus on chromosome 13 with ABCC4 gene, known to be implicated in prostate cancer. It has been shown that PCAT92 and ABCC4 are up-regulated in prostate cancer samples from multiple transcriptome datasets. Among the prostate cancer cell-lines LNCaP showed maximum overexpression of PCAT92 compared to control cell-line RWPE-1. We have shown that knockdown of PCAT92 in LNCaP cells reduces cell viability and proliferation and down-regulates ABCC4 transcript/protein expression. The shared region between PCAT92 and ABCC4 has a binding site for an oncogenic transcription factor (ZIC2) which is also upregulated in the majority of datasets studied here. ZIC2 binding to the predicted ABCC4 promoter has been confirmed using pull-down assay. Interestingly, under PCAT92 knockdown condition, there is a reduction in the ZIC2 binding to ABCC4 promoter indicating the potential involvement of PCAT92 in the recruitment of ZIC2. We have identified distinct regions on PCAT92 with potential to bind to ZIC2 non-DNA binding Zinc-finger domain and potential for triplex formation near ABCC4 promoter region, which have been experimentally validated. Together, these observations and localization in the nucleus suggests that PCAT92 may play a role in prostate cancer by increasing the local concentration of ZIC2 by forming RNA-DNA triplex near ABCC4 promoter thus helping in recruitment of ZIC2 for ABCC4 regulation. Long non coding RNAs (lncRNAs) are bringing a new level of understanding of cancer biology. Using high-throughput sequencing, a large number of cancer-associated lncRNAs are being discovered and involvement of many of them in cancer is slowly emerging. The mechanism of MALAT1, one of the earliest lncRNAs associated with cancer, is still emerging. Using mouse knockout models, it was shown that a set of metastasis associated genes were deregulated, strongly indicating its basis as a regulator of gene expression –4. OvereMore recently, using high-throughput transcriptome sequencing, it has been shown that almost a quarter of abundant transcripts in prostate cancer are lncRNAs with many that are still unannotated . This isOne of more established mechanism of action of lncRNAs is by regulation of genes within the same locus. For example, PCA3, located in intron 6 of the PRUNE2 gene, is co-expressed along with PRUNE2 in the nucleus to form a double-stranded RNA . The lncWe have previously shown that PCAT92 is located closely to ABCC4 gene on chromosome 13 . ExpressZinc-finger transcriptional regulators ZIC1 through ZIC5 have been associated with increase in transcriptional activity of many genes . ZIC2 isHere our work demonstrates how PCAT92 transcript is regulating the expression of ABCC4 by recruiting ZIC2 at the ABCC4 promoter region and forming triple helix near the promoter site to stabilize the binding of ZIC2 at ABCC4 promoter region.PCAT92 and ABCC4 are only 4305 bases apart on chromosome 13 in a divergent configuration sharing the 5’ regulatory region Figure . PromoteIt was reported that PCAT92, ABCC4 and ZIC2 are overexpressed in multiple prostate cancer datasets in the public repository (SRP002628 and ERP000550) . The oveFigure Binding affinity of ZIC2 at the ABCC4 promoter region in cell line is studied using ChIP-RTPCR with anti-ZIC2 antibody. Primers flanking the predicted ZIC2 binding site on ABCC4 promoter region was made. As shown in Figure in vitro. The transcribed RNA was then titrated onto the purified zinc finger domains of ZIC2 using Nano Isothermal Titration Calorimetry (NanoITC). This validated the interaction between the predicted PCAT92 RNA strand and the zinc finger domains of ZIC2. Antisense strand to the predicted PCAT92 RNA region was also cloned and transcribed to be used as negative control. As shown in Figure in-vivo validation of interaction between PCAT92 and ZIC2, we performed RNA Immunoprecipitation (RIP). The cells were fixed and RNA and protein were crosslinked. Using anti-ZIC2 antibody RNA-protein complexes were pulled down. RNA-Protein complex were broken by reverse crosslinking and the resulting RNA was subjected to cDNA synthesis. HEIH, one of the well-established non-coding RNA  ATP using T4 Polynucleotide Kinase . Zinc finger domains of ZIC2 protein were PCR amplified and cloned in pET28a expression vector. The clone was sequenced verified and the induced using 0.5mM IPTG, at 16°C overnight. Induced protein was purified using His Tag affinity chromatography and eluted with the buffer containing 200 mM imidazole. 2μg of ZIC2-HIS protein and 100pmol of radiolabeled target dsDNA, was mixed in the binding buffer. The reaction solutions were incubated for 30 minutes at 37°C and subject to electrophoresis on 6% polyacrylamide gels prepared in 1×TBE (Tris-borate-EDTA) buffer for 16 to 18 hours at 100V at 4°C. Imaging was done using phospho imager .To find all putative regions within PCAT92 transcript with triplex forming potential against the 4kb shared 5’UTR region on the chromosome, Triplexator computational pipeline was used  with all*DD) triple helical structure comprising U*AT and C*GC (Sequence 1) base triplets is generated conforming to a 12-fold helix [A parallel RNA.DNA.DNA  experiments were performed at 25°C using Nano ITC . The protein sample was prepared as explained in Electrophoretic Mobility Shift Assay study. The predicted region of PCAT92 was cloned in pBS-SK plasmid followed by synthesis of sense and antisense RNA from the clone using T3 RNA polymerase  and T7 RNA polymerase . 50μl of each sense RNA (60μM) and antisense RNA (60μM) was titrated into 300μl protein solution (5μM) with a fixed stirring speed of 300 rpm at 25 °C. Both RNA and Protein were dialysed in the same buffer . Similarly to under the interaction between the PCAT92 RNA and ABCC4 DNA we performed ITC for the predicted PCAT92 and ABCC4 region. The oligos corresponding to both were obtained. 50μl of each PCAT92 RNA (10μM) and random RNA (10μM) was titrated into 300μl ABCC4 DNA solution (5μM) with a fixed stirring speed of 300 rpm at 25 °C. Both RNA and DNA were dialysed in the same buffer . For both the titration experiment, 5μL of RNA was dropped for 10 injections. To achieve complete equilibration, the spacing time between each injection was set to 300 seconds. All measurements were repeated at least twice. Using Nano ITC NanoAnalyze software, the raw data was integrated, corrected for nonspecific heats and analysed according to independent model.


RNA-seq has emerged as an important technology for measuring gene expression in peripheral blood samples collected from humans and other vertebrate species. In particular, transcriptomics analyses of whole blood can be used to study immunobiology and develop novel biomarkers of infectious disease. However, an obstacle to these methods in many mammalian species is the presence of reticulocyte-derived globin mRNAs in large quantities, which can complicate RNA-seq library sequencing and impede detection of other mRNA transcripts. A range of supplementary procedures for targeted depletion of globin transcripts have, therefore, been developed to alleviate this problem. Here, we use comparative analyses of RNA-seq data sets generated from human, porcine, equine, and bovine peripheral blood to systematically assess the impact of globin mRNA on routine transcriptome profiling of whole blood in cattle and horses. The results of these analyses demonstrate that total RNA isolated from equine and bovine peripheral blood contains very low levels of globin mRNA transcripts, thereby negating the need for globin depletion and greatly simplifying blood-based transcriptomic studies in these two domestic species. Mycobacterium bovis  . RNA-seq data was then generated using 24 paired-end (PE) RNA-seq libraries (12 undepleted and 12 globin-depleted) generated from the six biological replicates and six identical technical replicates created from pooled total RNA across all six donor samples. The multiplexing and sequencing was then performed such that data for the 12 samples in each treatment group (undepleted and globin depleted) was generated from two separate lanes of a single flow cell twice, for a total of four sequencing lanes  was collected into PAXgene blood RNA tubes . Total RNA, including small RNAs, was purified from the collected blood samples using the PAXgene Blood miRNA Kit  as described by Shin et al. . Human HHBA and HBB mRNA transcripts were subsequently depleted from a subset of the total RNA samples using a modified RNase H globin depletion method with custom porcine-specific antisense oligonucleotides for HBA and HBB. RNA-seq data was then generated from 24 PE RNA-seq libraries (12 undepleted and 12 globin-depleted).Porcine peripheral blood samples were collected from 12 healthy crossbred pigs [Duroc × (Landrace × Yorkshire)] using Tempus™ blood RNA tubes  and total RNA was purified using the MagMAX™ for Stabilized Blood Tubes RNA Isolation Kit (Invitrogen™/Thermo Fisher Scientific)  at three different time points during flat racing training  was used to perform total RNA extraction and purification, following the manufacturer's instructions. RNA quantity and quality checking were performed using a NanoDrop™ 1,000 spectrophotometer  and an Agilent 2,100 Bioanalyzer using an RNA 6,000 Nano LabChip kit . The majority of samples displayed a 260/280 ratio >1.8 and an RNA integrity number (RIN) >8.0 . Globin + RNA purification were performed for all RNA samples using the Dynabeads® mRNA DIRECT™ Micro Kit (Thermo Fisher Scientific) according to the manufacturer's instructions. The purified poly(A)+ RNA was then used to generate strand-specific RNA-seq libraries using the ScriptSeq™ v2 RNA-Seq Library Preparation Kit, the ScriptSeq™ Index PCR Primers (Sets 1 to 4) and the FailSafe™ PCR enzyme system , according to the manufacturer's instructions.Individually barcoded strand-specific RNA-seq libraries were prepared with 1 μg of total RNA from each sample. Two rounds of poly(A)https://rtsf.natsci.msu.edu/genomics; Michigan State University, MI, USA). Each of the three pooled libraries were sequenced independently on five lanes split across multiple Illumina® flow cells. The pooled libraries were sequenced as PE 2 × 100 nucleotide reads using Illumina® version 5.0 sequencing kits.RNA-seq libraries were purified using the Agencourt® AMPure® XP system  according to the manufacturer's instructions for double size selection (0.75 × followed by 1.0 × ratio). RNA-seq libraries were quantified using a Qubit® fluorometer and Qubit® dsDNA HS Assay Kit (Invitrogen™/Thermo Fisher Scientific), while library quality checks were performed using an Agilent 2,100 Bioanalyzer and High Sensitivity DNA Kit (Agilent Technologies Ltd.). Individually barcoded RNA-seq libraries were pooled in equimolar quantities and the quantity and quality of the final pooled libraries  were assessed as described above. Cluster generation and high-throughput sequencing of three pooled RNA-seq libraries were performed using an Illumina® HiSeq™ 2,000 Sequencing System at the MSU Research Technology Support Facility (RTSF) Genomics Core . Computational analyses were performed on a 32-core Linux Compute Server (4 × AMD Opteron™ 6220 processors at 3.0 GHz with 8 cores each), with 256 GB of RAM, 24 TB of hard disk drive storage, and with Ubuntu Linux OS (version 14.04.4 LTS). Deconvoluted FASTQ files (generated from SE equine RNA-seq libraries and PE RNA-seq libraries for the other species) were quality-checked with FastQC (version 0.11.5)     within the RStudio IDE version 1.1.447)  Wickham, , dplyr , tidyr , reshapeHBA1 and HBA2, respectively) is well-established for the human genome; however, annotations for these genes in the porcine, equine, and bovine genomes are inconsistent across databases. As shown in Table HBA gene annotation is absent from Ensembl and the UCSC Table Browser. For the NCBI RefSeq database, this gene has been assigned to two loci (LOC110259958 and LOC100737768) that have similar descriptions . Therefore, these NCBI LOC symbols were used.Annotation of the haemoglobin subunit alpha 1 and 2 genes (HBA (HBA1) and HBA2 genes are absent from the current Ensembl annotation release. Similarly, bovine HBA1 and HBA (HBA2) have been annotated as GLNC1 in Ensembl, whereas HBA1 is absent from the UCSC Table Browser annotation (Table HBA (HBA1) is described as haemoglobin subunit alpha 1; and bovine HBA (HBA2) is described as haemoglobin subunit alpha 2, thus their descriptions are shown in parenthesis herein. In contrast to these observations, haemoglobin subunit beta (HBB) genes for the four species are well-annotated in Ensembl, NCBI RefSeq and UCSC Genome Browser databases  or PE  RNA-seq FASTQ files were quality-checked, adapter- and quality-filtered prior to transcript quantification. As shown in Table After adapter- and quality-filtering of RNA-seq libraries, an average of 20 and 29% read pairs were removed from the human undepleted and globin-depleted libraries, respectively. Conversely, ~12% of read pairs were removed from each of the porcine undepleted and globin-depleted libraries. For the undepleted equine and bovine RNA-seq libraries, an average of 0.2% reads and 17% read pairs were removed, respectively. Detailed information on filtering/trimming of RNA-seq libraries from all species, including technical replicates from libraries sequenced over multiple lanes, is presented in Transcript-level TPM estimates generated using the Salmon tool were imported into the R environment and summarised at gene level with the package tximport  resulted in 12,951 genes expressed across all human samples, and represented 24% of 54,644 total annotated genes and pseudogenes. Porcine samples showed a total of 9,396 expressed genes ; and equine and bovine samples exhibited 12,724  and 14,044  expressed genes, respectively.10 TPM values for the globin-depleted samples in Figure The density distribution of TPM values for the human and porcine samples improved after globin depletion; this is evident by the shift of gene detection levels toward greater logHBA1, HBA2, and HBB) detected in undepleted human peripheral blood samples for the current study averaged 70%  observed as a proportion of the total expressed genes was 72%  and Ensembl release 71 (S. scrofa) were used by Shin et al.  disease caused by infection with The RNA-seq data generated for this study using peripheral blood from 10 age-matched healthy male Holstein-Friesian calves can be obtained from the ENA database (PRJEB27764).Animal experimental work for the present study (cattle samples) was carried out according to the UK Animal (Scientific Procedures) Act 1986. The study protocol was approved by the Animal Health and Veterinary Laboratories Agency , now the Animal & Plant Health Agency (APHA), Animal Use Ethics Committee (UK Home Office PCD number 70/6905).DEM, SG, CC, and KM conceived and designed the project and organised bovine sample collection. KM, NN, DAM, and JB performed RNA extraction and RNA-seq library generation. CC, KM, NN, KR-A, and DEM performed the analyses. CC and DEM wrote the manuscript. All authors reviewed and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.