Ribosomal intergenic spacer (rIGS), located between the 45S rRNA coding arrays in humans, is a deep, unexplored source of small and long non-coding RNA molecules transcribed in certain conditions to help a cell generate a stress response, pass through a differentiation state or fine tune the functioning of the nucleolus as a ribosome biogenesis center of the cell. Many of the non-coding transcripts originating from the rIGS are not characterized to date. Here, we confirm the transcriptional activity of the region laying a 2 kb upstream of the rRNA promoter, and demonstrate its altered expression under transcriptional stress, induced by a wide range of known transcription inhibitors. We managed to show an increased variability of anti-sense transcripts in alpha-amanitin treated cells by applying the low-molecular RNA fraction extracted from agarose gel to PAGE-northern. Also, the fractioning of RNA by size using agarose gel slices occurred, being applicable for determining the sizes of target transcripts via RT-PCR. Recently, much attention has been drawn to the investigation of small non-coding RNA molecules, originating from different parts of the genome, which possess a myriad of diverse functions in living creatures ,2. Many In the current work we investigate the phenomenon of the transcription in the pre-promoter region of human ribosomal intergenic spacer (rIGS), which lies between rRNA-coding genes located in the nucleolar-organizing regions (NORs) in human acrocentric chromosomes ,13 Figu. AlthougLittle is known about the mechanisms of transcription regulation of the various non-coding RNAs originating from different parts of the rIGS, and the data to date does not clarify this question. RNA polymerase I (pol I), widely known to be associated with the nucleolus and rRNA-coding regions, was shown to be absent in the intergenic spacers of ribosomal genes . On the Here we confirm the presence of small transcripts originating from the pre-promoter region of rRNA genes in human cells with the modified northern blot technique. We also attempt to estimate the transcriptional activity of the region under the influence of the RNA polymerase II inhibitor, alpha-amanitin, and evaluate the difference between the transcripts revealed in treated and non-treated cells. In addition, we try to assess the length of a possible precursor transcript by extracting the fractions of RNA molecules of different lengths from agarose gel.We were eager to know whether the anti-sense transcripts, which we have recently demonstrated to originate from the zone ~2000 bp upstream of the rDNA promoter  Figure , are traWe tested other toxic substances known to halt DNA-dependent synthesis in the nuclei in an attempt to determine the enzyme providing the transcription of the region of interest and to analyze its expression in different transcriptional stress conditions. Even though the quantitative PCR analysis showed a heterogenous effect of the toxins on the transcription of the target sequences, none of the tested substances demonstrated the pattern observed in alpha-amanitin treated cells neither in RT-PCR, nor in PAGE-northern A. ML6021Next, we applied 3′RACE to verify the results obtained by the northern blot. Southern blotting of the first-round RACE, obtained from the total RNA of the non-treated HEK293 cells, demonstrated bands lower than those of the first-round PCR with the cDNA, obtained from the total RNA of alpha-amanitin treated cells A. CloninThe lengths of the transcripts obtained with RACEs, as well as the data of real-time PCR showing that the ABC region is transcribed as a whole, seem to be inconsistent with the results of northern blot analyses. The length of the major transcript, the presence of which was demonstrated with the latter method, is ~350 nucleotides, while the ABC zone being transcribed is ~600 bp, and, according to the results of step-out PCR, performed in order to determine the 3′-ends of the transcripts, it exceeds the bounds of the A region. In an attempt to determine the length of the transcript, which serves as template for reverse transcription and PCR, we separated total RNA from both alpha-amanitin treated (30 µg/mL) and non-treated HEK293 cells using non-denaturing and denaturing agarose gel electrophoresis and sliced the gel into 9 pieces each corresponding to a fraction of total RNA of different molecular weight and length D.The subsequent RT-PCR analysis of RNA fractions with the primer pairs for the transcripts of known lengths such as 18S rRNA (1869 nt), GAPDH (1231–1525 nt), and 5S rRNA (121 nt) confirmed that we succeeded in separating the molecules according to their size. Even in non-denaturing conditions A the sliAs for the ABC region, we hoped to find the enrichment of its amplification among the low-size RNA molecules (fractions 8 and 9). However, in non-denaturing conditions no peak cycles were observed for A, B, and C primer pairs, except for a slight tendency to the fractions 1–5 of high molecular weight RNAs ≥5 kb, A. The rep < 0. 05), while for primer pairs A and B the difference was not significant (p = 0.1 and p = 0.5 correspondingly). For all the primer pairs the analysis showed a significant difference in the expression between the slices (p < 0.05), so multiple comparison Tukey tests were applied to further analyze the difference between the slices. The comparison of the means of the slices for 5S demonstrated that slice 9 significantly differs from all the rest, what coincides with the observations obtained from the graph demonstrating the highest level of 5S expression in slice 9. Similar results were obtained for 18S and GAPDH with the expression of each tending to slices 7 and 8 correspondingly. The analysis of the means of the slices for the regions A, B, and C revealed the same pattern of significant difference for slices 5, 7, and 9 as the rest of the slices. On the graph the corresponding slices comply with the lowest expression of the regions of interest, which partially confirms the hypothesis that the original transcripts come from the RNA fractions of different molecular weight—primarily, the higher molecular weight. The calculations are attached as To verify the result of the experiment, a two-factor ANOVA test was performed for each primer pair for denatured samples with one factor being the slice number, and the second factor being treatment. The analysis revealed the significant difference in the expression of GAPDH, 18S, 5S, and the region C between the treated and non-treated samples  of total RNA which overload the gel. The procedure of RNA extraction from agarose gel, reported in the study, was quite simple and handy, reminiscent of already existing protocols ,10,11, bAttempting to learn more about the phenomenon of rIGS transcription we applied a wide range of specific and non-specific transcription inhibitors; namely, ML60218, belinostat, D actinomycin, doxorubicin, BMH-21, and alpha-amanitin. The data obtained suggest that the inducement of transcriptional stress in cells has a differential effect on the expression of the pre-promoter region of human ribosomal intergenic spacer depending on the particular inducer. At the same time, the effect of alpha-amanitin observed in this study stands alone, indicating that the region of interest may possess unique functions during the transcriptional stress induced by specific RNA pol II inhibition.The increased amount of target transcripts varying in length under the exposure to alpha-amanitin was demonstrated using qPCR and a modified technic of northern blot carried out after the extraction of low-molecular weight RNA from agarose gel and confirmed by 3′RACE experiments. Apparently, the anti-sense RNA molecules revealed are transcribed by either RNA pol I or RNA pol III, but not RNA pol II. Despite the fact that RNA pol II presence was demonstrated throughout the IGS, its specific enrichment tended to the regions IGS28 and IGS38 , while tAdditionally, according to the published data, the inhibition of RNA pol II can enhance the activity of pol III if the promoter of a gene is shared by the two enzymes ,40. AlsoThe data of our previous investigations and current experiments results suggest at least two possible hypotheses able to explain the origin of the various antisense ABC transcripts (1) the molecules of different length are de novo transcribed in the conditions of transcriptional stress by an RNA polymerase insensitive to alpha-amanitin treatment, and changes in the regulation of transcription cause the different lengths of the transcripts (2) the transcripts originate from an unknown long non-coding RNA molecule, the processing of which is altered under alpha-amanitin stimulation. The qPCR and 3′RACE data partially belie the former idea, as the primers designed to cover 600 bp zone of interest apparently amplify a cDNA obtained on the template of a longer transcript. Therefore, the major ~350 nt transcript demonstrated with northern blot, as well as the minor shorter and longer molecules clearly revealed in PAGE-northern, that appeared after alpha-amanitin treatment of cells, are likely splice variants or processing variants originating from a long non-coding RNA molecule transcribed from the rIGS. This hypothesis is partially verified by the experiments with the fractioning of total RNA and subsequent RT–PCR analysis of the fractions of different molecular weight, in which we demonstrated a differential expression profile in alpha-amanitin treated and non-treated cells at least for the region C. However, northern blot analysis did not manage to demonstrate the precursor molecule, which thus remains concealed and claims further investigations with, possibly, some other methods capable of detecting such transcripts.One more question to be elucidated is the type of non-coding RNAs which the transcripts revealed belong to. Despite the fact that further experiments aimed at characterization of the properties of the molecules are required, we propose that they are likely to belong to the class of long non-coding RNAs (lncRNAs). The transcripts under investigation are ~300 nt long and originate from intergenic regions transcribed in antisense orientation, what coincides with the features of lncRNAs, one of the largest and most heterogenous groups of ncRNAs. LncRNAs differ not only by size, but also by diverse posttranscriptional modifications (5′-cap or poly-A tail), complex secondary and tertiary structures, and various functions ,46,47. W2. Cells were treated for 24 h with the indicated concentrations of alpha-amanitin or doxorubicin water solutions, or D actinomycin, ML60218, BMH-21, or Belinostat dissolved in DMSO. Untreated cells were grown in the medium containing the corresponding volume of water or DMSO as a vehicle.Prior to total RNA isolation HEK293 cell line originating from human embryonic kidney was grown in monolayer in a complete DMEM medium with 10% FCS at 37 °C, 98% humidity, 5% COw/v) ethanol. Precipitates were dissolved in nuclease-free water and used in downstream analysis or stored at −70 °C. The purity of isolated RNA samples was tested using PCR analysis with 18S primers  according to the manufacturer’s instructions for isolating total RNA with the subsequent treatment of samples with DNase I  with the addition of RiboLock RNase Inhibitor  for 40 min at 37 °C in an appropriate buffer solution. Following the DNase treatment, RNA samples underwent phenol-chloroform extraction, then were precipitated in isopropanol in the presence of 300 mM AcNa and washed with 75%  was applied to denaturing gel electrophoresis in formaldehyde running buffer . Capillary transfer to positively charged nylon membrane  was performed in transfer buffer  for 2 h with the subsequent covalent linkage to the membrane by 254 nm UV light during 50 s. Biotinylated RNA probe was synthesized from a plasmid containing a corresponding sequence  using T7w/v) and incubated in blocking solution  containing 1% Blocking reagent (w/v)  for one hour at room temperature, with the subsequent addition of the appropriate amount of Pierce Streptavidin Poly-HRP to the blocking solution and incubation at room temperature for an hour. After washing in TBS-T, detection was performed using the Amersham ECL Prime Western Blotting Detection Reagent  and developing proceeded by Amersham Hyperfilm ECL .Hybridization was performed in UltraHyb Ultrasensitive Hybridization Buffer  at 68 °C overnight, after that the membrane was washed in buffers A  and B , 2 µg of total RNA was reverse transcribed using random hexamer primer and 100 units of MMLV RT at 42 °C for 60 min.T experiment was performed on AB StepOnePlus Real-Time PCR system  using SYBR Green reagent qPCRmix-HS SYBR + HighROX  with the reaction set up according to the manufacturer’s instructions. The reactions were performed in triplicates and included negative controls in which RNA was added instead of the template. The run protocol consisted of 40 cycles of 95 °C for 15 s, 60 °C for 15 s, and 72 °C for 30 s, with fluorescence intensity measurement performed after the elongation stage. The specificity of PCR products was confirmed using a melting curve analysis. The expression of target sequences in alpha-amanitin treated and non-treated cells was normalized to that of the 18S rRNA. Analysis of the fold difference in the expression of the regions of interest were performed with StepOne Software v2.3 . The primers for the regions of interest, 18S rRNA, GAPDH, and TBP are given in the The comparative Cg at 4 °C. Filtrate was transferred to a sterile tube and proceeded by phenol-chloroform extraction and subsequent precipitation in isopropanol and washing with ethanol. Precipitants were dissolved in nuclease-free water and used in downstream analysis (PAGE northern blot or RT-PCR) or stored at −70 °C.For the fractioning of transcriptome according to the size of the molecules 20–100 μg of total RNA with the addition of 6× Loading dye were loaded to 0.6% agarose gel electrophoresis in 1× TAE. Low-molecular fraction of RNA for further polyacrylamide northern-blot analysis was prepared by the extraction of the region under 1000 bp from the gel see D. For slq values were obtained from the studentized range q tables, MS were obtained from the ANOVA test, n was the number of observations. If the absolute difference exceeded the critical range, the difference between the slices was estimated as significant. The calculations are attached as a Two-factor ANOVA test was performed using the Analysis ToolPak in Excel from Microsoft Office Professional Plus 2016 (version 2101). The subsequent multiple comparison Tukey HSD test was performed manually for each of the primer pairs, using the means for each of the slices. Critical ranges were obtained using the Equation (1):500 ng of the extracted RNA fraction was applied to 5% acrylamide gel containing 8 M Urea and 1× TBE, and electrophoresis was performed at 10 mA for 1.5 h. Next, we performed electroblotting to positively charged nylon membrane  at 400 mA in ice-cold 0.5× TBE for 30 min. Hybridization, membrane wash and development were the same as described in The first strand DNA synthesis was performed in 20 µL using ~2.5 μg of total RNA, a random hexamer primer and a 3′RACE adapter  and 200 The reaction of the second strand synthesis was performed using Phusion High-Fidelity DNA Polymerase  in a volume of 20 μL according to the manufacturer’s instructions for reaction set up and 3-step run protocol. Cr primer  was takeIn this study we report the phenomena of rIGS transcriptional activity in humans and an altered pattern of its transcription under alpha-amanitin treatment. The current investigation does not detail neither the processing of the transcripts revealed, nor their functions. Moreover, we are still unaware of the presence of any long anti-sense RNA molecule that could serve as a precursor of the 200–800 transcripts originating from the pre-promoter region of the rIGS. However, the data reported highlights the importance of further elucidation of the rDNA, and, especially, the functioning of ribosomal intergenic spacers in humans, in particular under stress conditions. The study also contains modified techniques and approaches that may be useful in the investigations of other non-coding still-transcribed regions, giving rise to small RNA transcripts.


It is becoming increasingly evident that the non-coding genome and transcriptome exert great influence over their coding counterparts through complex molecular interactions. Among non-coding RNAs (ncRNA), long non-coding RNAs (lncRNAs) in particular present increased potential to participate in dysregulation of post-transcriptional processes through both RNA and protein interactions. Since such processes can play key roles in contributing to cancer progression, it is desirable to continue expanding the search for lncRNAs impacting cancer through post-transcriptional mechanisms. The sheer diversity of mechanisms requires diverse resources and methods that have been developed and refined over the past decade. We provide an overview of computational resources as well as proven low-to-high throughput techniques to enable identification and characterisation of lncRNAs in their complex interactive contexts. As more cancer research strategies evolve to explore the non-coding genome and transcriptome, we anticipate this will provide a valuable primer and perspective of how these technologies have matured and will continue to evolve to assist researchers in elucidating post-transcriptional roles of lncRNAs in cancer. Transcription is at the forefront of the conversion of stable genomic information into reactive biochemical agents that form and modulate dynamic biological systems. This fundamental process relentlessly transcribes at least 62% of the human genome, resulting in a variety of non-coding RNA (ncRNAs) species that outnumbers the selection of more stable RNAs concerned with translation that accumulate in the cell such as ribosomal RNA (rRNA), transfer RNA (tRNA) and messenger RNA (mRNA) ,2. Far fDiseased states such as cancer arise from cumulative corruption of the genomic source code, resulting in the opportunistic dysregulation of the conserved transcriptional , post-trThe large non-coding transcriptional contributions such as small non-coding RNA (sncRNA), enhancer RNA (eRNA) and long non-coding RNAs (lncRNA) have come under increased interest for cancer research. They feature prominently among the rapidly increasing list of non-coding regulatory elements vulnerable to mutations  and contributing to dysregulating the critical processes aforementioned ,13. AlthH19 [XIST [HOTAIR [Long non-coding RNAs  encompass the largest and perhaps most intriguing category of ncRNAs in cancer currently known, as they exhibit highly dynamic and tissue specific expression patterns , a traitH19 , XIST [219 [XIST ,29, and  [HOTAIR ,31 have  [HOTAIR ,33,34. T [HOTAIR  and chem [HOTAIR . With ap [HOTAIR .A major challenge remains in uncovering these lncRNAs and revealing their functional roles in cancer-exploited regulatory processes. This is principally due to the novelty of the field, which is further complicated by their multifunctional interactive potential. At least four major mechanisms have been suggested to mediate their effects: (1) Act as signals to regulate transcription, (2) as decoys recruiting binding partners away from their other targets, (3) as guides directing the targeting of a ribonucleoprotein complex, for example; (4) as scaffolds bringing together multiple biomolecules together ,39. SuchIn this review, we will provide a survey of the most useful tools and techniques developed to help place lncRNAs on the post-transcriptional interactome map and reveal their roots to cancer. In the first part, we will provide an overview of such resources valued for primary identification and characterisation of lncRNAs, especially those capable of highlighting cancer relevant contextualisation. In the second part, we will cover how more advanced resources have been developed to help characterise how lncRNAs may interact with RNAs and proteins . UltimatMost cancer research strategies begin by identifying potential candidate genes/loci involved in the dysregulatory state under study. Screening for such candidates usually involves the intersection of high-throughput screening experiments, especially next-generation (NGS) or third-generation sequencing . A numbeRegardless of which experimental strategies have been implemented, orthogonal lines of evidence will always fall back on a specific locus or multiple loci of the non-coding genome. From this point, it is possible to infer the identity of potential linear lncRNAs by cross-referencing the loci coordinates with several large databases dedicated to cataloguing lncRNAs or predicting the coding potential of the region. If the coding potential has not already been evaluated, numerous machine-learning tools are available to perform this computation de novo. CPAT, FEELnc and PLEK may be particularly suitable for working with human cancer datasets as extensively evaluated alongside numerous other solutions in . FurtherIn the case of circular RNAs, most achieve their circular conformation via “backsplicing”. This refers to the covalent linkages between a downstream 3’ and an upstream 5’splice sites, which results in a reversal of exon sequences relative to the annotated transcript . This unIn the vast majority of cases—especially for cancer studies based on the human genome—a wealth of sequencing data, pre-generated predictions and annotations relevant for targeted loci are available from a number of public and restricted access databases. Aside from familiar initiatives such as RefSeq, Ensembl and FANTOM , many moWhile these databases offer an increasingly large and reliable set of annotations, they remain putative until validated in the specific cancer model system under study using the experimental approaches covered below.Before any advanced experiments take place, it is usually preferable to validate basic characteristics of the target lncRNAs of interest. We will therefore briefly highlight some key primary techniques valued for lncRNA characterisation as well as potential limitations in their application.Northern blotting has long been applied for analysing expression of specific RNAs, enabling relative quantification, determination of sizes and providing an assessment of the RNA quality [ quality ,125. Mod quality . In addi quality .RT-qPCR (reverse transcriptase polymerase chain reaction) may offer a more convenient high sensitivity assay. The exponential nature of qPCR, however, requires careful consideration of confounding factors such as genomic DNA contamination and appropriate selection of reference genes [Providing the target RNA may be reverse transcribed, ce genes . The latce genes .Another valuable technique, especially for characterising unknown isoforms of lncRNAs suspected of undergoing splicing is rapid amplification of cDNA ends (RACE), which produces full length sequences of RNA transcripts. RACE utilises reverse transcription with a 5′ or 3′ primer of a known sequence of the RNA of interest to produce a cDNA copy, this is then followed up with PCR amplification. The product can then be coupled with high-throughput screening in a technique called RACE-Seq to characterize the RACE fragments ,131.RNA fluorescence in situ hybridization (RNA-FISH) is the reference technique for visually detecting and determining the distribution of any type of RNA in cellular compartments as well as cells that express the RNA of interest. This technique uses fluorescently labelled probes specific for the target RNA [rget RNA ,133. Whirget RNA ,135, therget RNA .SHAPE  involves the use of reagents, such as N-methylisatoic anhydride (NMIA) and 1-methyl-7-nitroisatoic anhydride (1M7) that react with the 2′-hydroxyl group of the RNA backbone, forming ribose 2′-O-adducts [-adducts . Adduct -adducts . This ca-adducts ,140. WitAs mentioned in the introduction, there are four types of molecular mechanisms suggested to mediate lncRNA effects through versatile interactions with DNA, RNA and protein molecules . All thrIn-silico prediction of RNA-RNA and RNA-protein interactions are active areas of research recently boosted by machine learning techniques that have grown in strength and numbers over the past decade, feeding on the wealth of accumulating experimental data ,146. A sRNA:RNA interaction prediction stands to be the most well investigated in large part due to the strong overlap with the small RNA/miRNA field. For instance, lncRNAs acting as ceRNAs can be predicted through their interactions with miRNAs for which a multitude of databases and tools already exist to predict their general propensity to bind certain RNA sequences ; also seRNA:Protein prediction requires a different approach. Notably, network and correlation based predictions  have gaiThese tools and databases should help prioritise the types of hypotheses and experiments planned for experimental validation in the cancer model system of choice utilising several of the numerous techniques covered in the rest of this article.With the advent of next-generation sequencing, multiple high-throughput techniques have been developed which allow for increased screening capabilities to discover novel lncRNA interactions in cancer. One of the primary mechanisms through which lncRNAs have been documented to dysregulate cancer post-transcription is through their participation in ribonucleoprotein (RNP) complexes ,172. ConHOTAIR and EZH2 [MACC1-AS1 to PTBP1 interaction, such effects have significant consequences on breast cancer tumorigenesis [RIP) is one of the first techniques employed to identify such RNAs bound to specific RBPs. RIP involves cell or tissue lysis, followed by immunoprecipitation of native RNA-protein complexes with a specific antibody against the target protein. As these complexes are not stabilized by covalent crosslinking, extra precaution must be taken during washing to remove nonspecific RNA while maintaining the RNA–protein interactions. This limitation makes detection of RNAs with low binding affinity to the protein of interest difficult. In addition, unstably bound RBPs may dissociate from their RNA targets and re-associate with other RNAs under harsh conditions [LncRNAs often interact with RNA-binding proteins (RBPs), such as the interaction between and EZH2 . Severaligenesis . RNA immnditions ,176.MALAT1) and the serine/arginine (SR) splicing factors [MALAT1 is known to be overexpressed in breast, pancreas, lung, colon and prostate carcinomas [MALAT1 was found to interact with SRSF1 and regulate cellular levels of its phosphorylated forms, which modulated AS events downstream. Further exploration of MALAT1 interactions via RIP-Seq by Wang et al. was similarly fruitful. Their study revealed that MALAT1 also binds to EZH2 [EZH2 is overexpressed in endometrium, prostate and breast cancers [EZH2 is associated with increased cell proliferation, invasiveness and metastasis [EZH2 had been shown to interact with several lncRNAs, such as HOTAIR [PCAT-1 [EZH2-driven prostate cancer progression. Ultimately, knockdown experiments demonstrated that EZH2-MALAT1 association played a significant role in cancer progression [Nevertheless, the RIP techniques have been successfully used over the years revealing relevant interactions in the context of cancer. For example, RIP was used by Tripathi et al. to investigate the interaction between lncRNA metastasis-associated lung adenocarcinoma transcript 1  was developed by Ule et al. [CLIP-Seq, after crosslinking, RNA is fragmented, purified and prepared for sequencing [To overcome the low specificity of RIP, crosslinking and immunoprecipitation , which enables identification of RNA duplexes bound to RBPs. This is achieved by ligating the two RNA strands with an additional RNA adaptor, following that, the RNA duplexes are immunoprecipitated and sequenced. This method was used to identify mRNA–mRNA and mRNA–lncRNA duplexes bound by Staufen 1 [iCLIP), which maps RBP binding sites at nucleotide resolution. A limitation of CLIP is that cDNAs prematurely truncate before the crosslinked nucleotide [Since the development of CLIP-Seq, there have been major advancements in CLIP methods that further increase specificity. The first is the development of hybrid CLIP . Circ-lncRNAs may be particularly ideal as ceRNAs due totheir increased stability ,107. ColAgo2-RIP-Seq and Ago-HITS-CLIP  in particular focus on applying RIP-Seq and CLIP-Seq respectively to AGO2, pulling down all miRNAs and possible targets in a single experiment [PAR-CLIP) is another popular variant of CLIP-Seq that uses photoactivatable nucleoside analogues, such as 4-thiouridine (4SU) to crosslink RISC proteins, such as AGO2 or TNRC6 to the labelled RNAs [As a first approach, it is possible to identify RNA–RNA interactions on the basis of co-occupation of the RISC complexes isolated via RIP or CLIP based techniques introduced earlier. periment ,195. Pholed RNAs ,196. A pled RNAs .LAMP) assay system [An alternative approach involves utilising a modified ribonucleotide probe to bait and capture any complementary RNAs when they are loaded in the RISC complex. This can be helpful to identify which miRNA/siRNAs are being sponged by a lncRNA acting as ceRNA (competitive endogenous RNA). Additionally, if a lncRNA is suspected of being processed into a miRNA/siRNA, a probe mimicking the lncRNA-derived miRNA/siRNA can be prepared to enable target identification. The first method to apply this concept employed biotinylated miRNA mimic probes to capture their targets in vivo . An in vy system . Many elmiR-TRAP incorporates a psoralen analogue allowing photoactivatable crosslinking to targets, and more stringent purification [PCP-Seq [A major type of enhancement to the original biotinylated approach has been the inclusion of photoactivatable tags or analogues into the probes (similar to PAR-CLIP). For example, fication . The ori[PCP-Seq . PCP-SeqPhotoclicking” a process borrowed from bioorthogonal protein chemistry uses tetrazole-ene or dibenzocyclooctyne (DBCO) [DBCO-tagged mimic probes in particular have been reported to confer increased miRNA-RISC loading affinity and can be isolated via azide-immobilised magnetic beads [PA-miRNA method, the biotin tag normally used for isolation is attached via a photo-cleavable linker. It is unclear whether this provides a particular advantage in identifying complementary targets, but the modification is claimed to allow the probe to be used as a photoactivatable source of miRNA [TargetLink is a tagless method that utilises a Locked Nucleic Acid (LNA)-based probe for capturing crosslinked miRNA-mRNA complexes and was tested on a human colorectal cancer cell line yielding 12 target genes for miR-21 [Other crosslinking technologies incorporated into probes also alter the tag used for isolation procedures. “e (DBCO) . DBCO-taic beads . In the of miRNA . TargetLr miR-21 .miR-CATCH which targets a single mRNA (or lncRNA) using a biotinylated DNA probe and crosslinked RISC ribonucleoprotein complexes to detect all miRNAs targetors [miR-CLIP instead focuses on a single miRNA-like probe containing psoralen and biotin groups to capture the “targetome” after subsequent Ago2 immunoprecipitation and streptavidin purification followed by RNA sequencing [MSLN mRNA, which is overexpressed in Malignant Pleural Mesothelioma and miR-CLIP was validated in Hela cells revealing the lncRNA H19 as a target of miR-106a [Similar approaches can be further enhanced by combining with the technologies used for RNA baiting. Such is the case for argetors ,207. miRquencing . Both temiR-106a .Nucleoside analogues, such as diazirine and aryldiazirine, have shown promising results as a means of crosslinking RNA-RNA molecules and post-crosslink tagging has been developed ,211,212.Although RISC independent lncRNA–RNA interactions may be less well known, they have been shown to regulate important biological processes, such as somatic tissue differentiation via post-transcriptional mechanisms  and cancCLASH (cross-linking ligation and sequencing of hybrids), a modified version of iCLIP, is another technique that allows for identification of RNA–RNA interactions by using a tagged “bait” protein [MARIO (Mapping RNA interactome in vivo) allows EZ-link biotinylation of the protein [Many RISC independent RNA–RNA interactions may involve the participation of an RBP other than AGO2. Therefore, a similar RIP or CLIP-based approach targeting other known ribonucleoproteins may allow identification of other proximal RNAs interacting with the lncRNA of interest. Additionally,  protein . After U protein . A biotiin vitro transcribed biotin tagged mimics of the lncRNA prior to pull down. Not only does this ensure sufficient lncRNA for the pull down but can also improve specificity rather than relying on antisense DNA probe binding. This technique was used in characterising the function of antisense lncRNA of MACC1 in gastric cancer [Given that lncRNA expression tends to be lower than mRNAs, the levels of endogenous lncRNA must be considered otherwise there might be insufficient material being pulled down. One way to overcome this technical limitation is to perform c cancer . In thatRIA-seq  allows for mapping of transcriptome-wide RNA-RNA interactions before selectively probing for your lncRNAs of interest [interest . In brieinterest . HoweverPARIS , for example, combines psoralen crosslinking with proximity ligation to identify interactions and structural information of all RNAs [Finally, ribonucleoprotein agnostic methods exist to perform transcriptome wide identification of all RNA complexes without specific baits or probes. all RNAs . In brieall RNAs . Apart fLIGR-seq (LIGation of interacting RNA followed by high-throughput sequencing) which uses a psoralen derivative aminomethyltrioxalen (AMT) that intercalates into the RNA for UV crosslinking [SPLASH  might be seen as a more robust variation of PARIS and LIGR-seq as it utilises biotin-labelled psoralen for enrichment of crosslinked RNA using streptavidin beads [Another similar technique is slinking ,226. cirin beads .RIC-Seq (RNA in situ conformation sequencing) has also recently entered this arena of whole RNA-interactome and secondary structure mapping [ mapping . Similar mapping  instead  mapping . This st mapping .MALAT1 was found to interact with NEAT1 through analysis of RIC-Seq data [Fundamentally, all these RNA–RNA interactome methods apply proximity ligation with key differences at the RNA-complex isolation steps. Interpreting the results from these largescale experiments is challenging especially considering the current bioinformatic tools are still somewhat underdeveloped. Effectively, analyses borrow tools traditionally used for HiC. However, they have all shown promise in being able to identify lncRNA interactions. For example, Seq data . NeverthWhether potential candidate lncRNA and interacting partners have been predicted using bioinformatic tools or via high-throughput sequencing techniques, it is also possible to apply other low- or medium-throughput technologies to characterise or further validate possible interactions.Microarrays provide an alternative method to Next-Generation Sequencing (NGS) for lncRNA-protein interaction studies. This relatively inexpensive method is able to provide information in a couple of hours. However, it has limitations in identifying novel RNA targets. It could be used to quantify and identify either annotated RNA targets or RBPs in ribonucleoprotein (RNP) complexes. RNP immunoprecipitation–microarray (RIP-Chip) has been applied successfully in detecting several QKI-5-binding lncRNAs, especially lnc10 that regulates the apoptosis of germ cells during their development [TINCR RNA and STAU1 protein [TINCR RNA is implicated in the progression of many cancers. TINCR RNA overexpression in epithelial ovarian cancer has been reported to correlate with tumour size, metastasis and survival rates in the patients. By silencing TINCR, FGF2 expression is downregulated and leads to the inhibition of epithelial ovarian cancer progression [elopment . In thiselopment . Besideselopment . Protein protein . Aberrangression .Dot-blot assay is widely used to study lncRNA–protein interaction and is especially useful in mapping the protein binding region in lncRNA. In this assay, lncRNAs of interest are biotinylated and transcribed in vitro, followed by in vitro RNA-protein binding via incubation of the biotinylated lncRNA with recombinant protein. The bound lncRNA is partially digested by RNase to allow only a small fragment attached to the protein. The lncRNA–protein complexes are subjected to proteinase K treatment to dissociate the complexes. Subsequently, the lncRNA is purified and hybridized to nylon or PVDF membranes spotted with 54–60 mer antisense DNA oligonucleotides tiled along the lncRNA of interest [BCAR4 bound by SNIP1 and PNUTS, which is located at positions 235–288 and 991–1044 in BCAR4 [CamK-A are bound and protected by PNCK and IκBα, which is important in tumour progression [interest ,236. Thegression .Mass spectrometry (MS) is commonly used to characterize various proteins that are associated with lncRNAs, following pull-down of the lncRNA of interest. It can identify and quantify molecules in complex mixtures based on their mass and charge. However, the quantification accuracy may not be correct due to the difference in mass spectrometric responses. To overcome this issue, stable-isotope labelling has been applied before proceeding with MS. The stable-isotope labelling by amino acids in cell culture (SILAC) has been shown to simplify the quantification and remove false-positive results [Xist to mediate transcriptional silencing [Xist is associated with tumour progression and metastasis in multiple cancers. Knockdown of Xist in colorectal cancer has been proven to inhibit cell proliferation, invasion, and epithelial-mesenchymal transition (EMT) [Xist. Hence, Xist expression is used to predict the prognosis and survival of colorectal cancer patients [ results . This lailencing . Moreoveon (EMT) . Larger patients .Co-sedimentation assays can be used whereby RNA is extracted from cells and fractionated using sucrose or glycerol gradients. The RNAs found in the different fractions are examined by Northern blot. RNAs found in the same gradient fractions are thought to interact with each other [ch other ,243 thouch other . If the Ribonuclease protection assays (RPA) can also be used to detect these sense-antisense RNA duplexes. RPA involves isolation of total RNA followed by RNase and DNase digestion [igestion ,246,247.igestion .Microarrays as mentioned earlier have been used to identify the alternative splicing (AS) events regulated by MALAT1 for example. PolyA+ RNA isolated from MALAT1-antisense oligo treated and control HeLa cells were isolated and prepared into labelled cDNA. This was hybridized to a custom AS microarray. The GenASAP algorithm was then used to estimate the percent exon inclusion. Semiquantitative RT-PCR using primers specific for exons flanking the AS events was performed to validate the microarray predictions. This assay revealed that MALAT1 depleted cells have changes in AS of B-MYB and MGEA6 pre-mRNAs [re-mRNAs .Throughout this review, we have introduced both computational resources and experimental methods to perform primary and secondary characterisations of lncRNAs to ascertain their potential roles in post-transcriptional regulation and cancer. Primary characterisation establishes basic ground truths relating expression, localisation and relative importance in a model system of choice under normal or perturbed conditions. Secondary characterisation particularly focuses on identifying the interacting RNAs and RBPs that the lncRNAs may influence and importantly deregulate in cancer states due to aberrant expression or non-coding mutations affecting their binding. The RIP and CLIP technologies in particular have been well adapted to next-generation sequencing allowing these newer methods to become reference options for performing high-throughput screening of RNA/Protein or RNA/RNA interactions. Furthermore, a host of improvements to the cross-linking biochemistry have been incorporated and enabled progressive advances in specificity and reliability. It will be important to continue generating these types of experiments and complementing the growing databases dedicated to cataloguing and integrating this information with other valuable sources as presented in MALAT1 in vivo, resulting in reduced metastasis [Some of the findings concerning lncRNA functions in cancer may have direct applications for therapies involving Antisense oligonucleotides (ASOs) for example. ASOs are DNA:RNA chimeras that direct RNase H to degrade target RNAs  such as tastasis . Additiotastasis . Unfortutastasis . This maAs non-coding RNA continues to take on importance in influencing fundamental processes such as post-transcriptional regulation it will be interesting to integrate this knowledge with findings relating to other novel post-transcriptional regulatory mechanisms such as RNA modifications. This field has also benefited from the adoption of CLIP technologies to perform epitranscriptomic studies on some of the hundreds of modifications that are likely to affect RNA stability, structure, localisation and interactions—lncRNAs included ,254,255.


Most RNA footprinting approaches that require ribonuclease cleavage generate RNA fragments bearing a phosphate or cyclic phosphate group at their 3′ end. Unfortunately, current library preparation protocols rely only on a 3′ hydroxyl group for adaptor ligation or poly-A tailing. Here, we developed circAID-p-seq, a PCR-free library preparation for selective 3′ phospho-RNA sequencing. As a proof of concept, we applied circAID-p-seq to ribosome profiling, which is based on sequencing of RNA fragments protected by ribosomes after endonuclease digestion. CircAID-p-seq, combined with the dedicated computational pipeline circAidMe, facilitates accurate, fast and highly efficient sequencing of phospho-RNA fragments from eukaryotic cells and tissues. We used circAID-p-seq to portray ribosome occupancy in transcripts, providing a versatile and PCR-free strategy to possibly unravel any endogenous 3′-phospho RNA molecules. RNA molecules bearing a phosphate or cyclic phosphate group at the 3' end 3′P/2′-3′cP) are generated by either heat fragmentation , ribonuc′-3′cP arHere, we present circAID-p-seq (CIRCular Amplification and IDentification of short 3′ Phosphate RNA SEQuences) a library preparation method uniquely characterized by the selection of 3′P/2′-3′cP terminated RNA fragments and cDNA synthesis by rolling circular amplification (RT-RCA) ,28. The Ribo-seq can be considered an effective case study to test circAID-p-seq, because it requires the sequencing of 25–35 nt long ribosome-protected fragments (RPFs) produced by 3′-P/cP generating nucleases . To evaluate the performance of our new library construction method, we compared our results to well-known library preparation and sequencing approaches ,30. To o2 in a final volume of 10 μl. The reaction was incubated 2 h at 37°C and then loaded on a 15% acrylamide/8M urea precast gel . The ligated RNA was purified through gel extraction, as described in the ‘RNA extraction from TBE urea gel’ section below. To evaluate and optimize the circAID-p-seq method, different combinations of adaptors and synthetic RNA fragments were employed. For testing the effect of adaptor lengths on RT-RCA and number of repetition, different adaptors  were used for ligation with a 30 nt long synthetic RNA molecule bearing a 3′P group (30RNA-3′P). Subsequently, to identify the best sequence for the 24 nt long adaptor, an equimolar pool of 12 oligos was produced and used in the first ligation step with 30RNA3′P fragment. For quantitative analysis, three different RNA fragments  were combined at the ratio of 1:10:100. In this case, for the circAID-p-seq library preparation, the adaptor ADR-12 was used.Synthetic RNA fragments bearing a 3′P were subjected to 5′ phosphorylation with T4 PNK 3′ minus , according to manufacturer's instructions. RNA fragments were purified using a RNA Clean & Concentrator™-5 column . The resulting RNA fragments were ligated to various adaptors  via 3′P ligase , according to the following conditions: 30 pmol of RNA fragment, 10 pmol of adaptor, 15 pmol 3′P ligase, 1 × 3′P ligase buffer, 100 μM GTP, 1 mM MnClThe circularization of the adaptor-ligated RNA (RNA:adaptor) was carried out at 25°C for 2 h, in a total volume of 20 μl containing 10 U of T4 RNA Ligase 1 , 1× T4 RNA ligase buffer, 20% PEG8000, 50 μM ATP. The reaction was then incubated at 37°C for 1 h with 20 U of RNase R , to remove undesired products (i.e. linear RNA or concatemer product). Circular RNA was purified by using RNA Clean & Concentrator™-5 column  and quantified using Qubit™ RNA HS Assay Kit .2, 2 U Taq Polymerase, 50 pmol primer ADRX_F  in a total volume of 50 μl. The mix was then subjected to the following conditions for second strand cDNA synthesis: initial denaturation at 94°C, one cycle of 94°C for 30 s, 60°C for 30 s and 68°C for 2 min. Double strand cDNA was purified using AMPure XP beads  according to manufacturer's instructions. Validation of second strand synthesis was performed by Nuclease S1 digestion  according to manufacturer's instructions.RT-RCA reaction was performed in 20 μl final volume, with Maxima H Minus Reverse Transcriptase  under the following conditions: 50 ng of circular RNA, 200 U of Reverse Transcriptase, 1× RT buffer, 0.5 mM dNTPs, 50 pmol Primer ADRX_R , 10% glycerol. The reaction was carried out at 42°C for 4 h, then stopped by incubation at 70°C for 10 min. After cDNA synthesis, circular RNA template was hydrolyzed by adding 0.1 N NaOH for 10 minutes at 70°C. The second strand cDNA was produced by performing one PCR cycle using Platinum II Hot start Taq Polymerase . The reaction included 20 μl of single-strand cDNA, 1× buffer, 0.2 mM dNTPs, 2 mM MgClPurified double-strand cDNA was prepared for nanopore sequencing according with ONT protocol for cDNA sequencing (SQK-DCS109). Briefly, cDNA was subjected to end repair and dA-tailing reaction using NEBNext End repair/dA-tailing module  following the manufacturer's instruction and incubated for 5 min at 20°C and then 5 min at 65°C. The reaction mix was purified with AMPure XP beads (Agencourt). ONT Adaptor mix was added according to the direct cDNA sequencing kit protocol , then loaded on a R9.4 flow cell and sequenced in the MinION sequencing device. The cDNA sequencing kit recommends an input of 100 ng poly-A+ RNA that should generate an output of about 5–10 million reads per flow cell. In all our experiments we started with 50–120 ng of RPF extracted from TBE-urea gel. Not all fragments purified from the gel are 3′phosphorylated (data not shown) and therefore cannot be selected by circAID in the first ligation, suggesting that only 25–40 ng of phosphorylated RNA can be used for the library. After final library check by Qubit™ small RNA Assay Kits (Thermo Fisher) the recovery is around ∼10–25 ng, about half of expected. This explain the lower (2–5 million reads/sample) than expected (5–10 million reads/sample) in our experiments compared to manufacturer's guidelines.RNA samples were mixed 1:1 with gel loading II , denatured at 70°C for 90 s before being loaded into the TBE–urea gel and run at 200 V. Gels were then stained with Sybr™ Gold  and scanned using Chemidoc . Gel images were analyzed using ImageLab (Biorad). When required, bands were isolated from the gel, crushed and soaked overnight in Buffer I  at room temperature with constant rotation. The aqueous gel debris was filtered with Millipore ultrafree MC tubes and then precipitated with isopropanol  at −80°C for 2 h or overnight. After precipitation, samples were centrifuged for 30 min at 12 000 g, 4°C. The pellet was washed once with 70% ethanol, centrifuged at 12 000 g for 5 min at 4°C and air-dried before further processing.Custom RNA adaptors, synthetic RNA fragments and DNA primers were purchased from Integrated DNA Technologies . Synthetic RNA fragments consisted of 30-mer oligonucleotides with 5′OH and 3′P termini. Custom adaptors consisted of RNA molecules with different lengths and no modification at 5′ and 3′ ends. Adaptors were carefully designed to minimize their secondary structure, using a combination of RNAFold and OligoEvaluator folding tools. All sequences are listed in Additional file 1.H. sapiens, RRID: CVCL_0045) cells were transfected with a plasmid encoding GFP . GFP expression was monitored by fluorescence microscopy (Olimpus IX-50). After 24 h after transfection, cells were treated with harringtonine (2 μg/ml) for 3 min, followed by cycloheximide addition  and incubation for 5 min at 37°C. Controls were not treated with harringtonine. Cell lysates were obtained using a hypotonic lysis buffer . Lysate absorbance at 260 nm was measured by Nanodrop ND-1000 UV-VIS Spectrophotometer and then diluted to a final value of 1.7 a.u. (absorbance measured at 260 nm) in 250 μl of W-buffer . Ribosome protected Fragments (RPFs) were generated by treating the diluted lysate with 12.7 U of RNase I  at room temperature for 45 min in an orbital mixer  supplemented with 20 μg/ml of CHX. Samples were ultracentrifuged at 95 000 rpm at 4°C for 2 h using a TLA100.2 rotor (Beckman). The pellets were resuspended in 200 μl of W-Buffer and treated with 1% SDS (Sigma cat. no. 05030) and 0.1 mg Proteinase K  at 37°C for 75 min. RNA was extracted by acid-phenol:chloroform, pH 4.5 , precipitated with isopropanol, air-dried, resuspended in nuclease-free water and analyzed on 15% acrylamide/8M urea precast gel. RPFs were size-selected (corresponding to 25–35 nt bands) and extracted from gel. Before starting with library preparation, isolated and purified RPFs were quantified using the Qubit™ miRNA Assay Kit .After RNAse I digestion, HEK293T cell lysates were loaded on top of 900 μl of a 30% sucrose cushion . Tissues were pulverized under liquid nitrogen using a pestle and a mortar and the lysates were obtained according to previous protocols . Lysates® smRNA-Seq Kit for Illumina  and sequenced with 50 cycles single-read on an Illumina NovaSeq 6000. HEK293T RPFs were extracted from independent biological replicates for circAID-p-seq/ONT and SMARTer® smRNA-Seq /Illumina sequencing. Lists of the counts per gene are reported in Additional file 2. Mouse liver RPFs were extracted from three biological replicates. For each replicate, the same pool of PAGE purified RPFs of each triplicate were used for parallel circAID-p-seq/ONT and Illumina sequencing. Illumina libraries for mouse liver were prepared according to Ingolia et al., 2012  was subjected to circularization, followed by RNase R treatment according to the reaction condition described in the paragraph above (Circularization and RNAse R treatment). Circular RNA was purified through RNA Clean & Concentrator™-5 column , then subjected to RT-RCA and second strand synthesis according to the reaction condition described in the paragraph above (reverse transcription-rolling circle amplification (RT-RCA) and second strand synthesis). In particular, 50 pmol of ADR12_R and 50 pmol of ADR12_F primers  were used for RT-RCA reaction and second strand synthesis, respectively. Double strand cDNA was purified using AMPure XP beads  according to manufacturer's instructions and then subjected to end repair and dA-tailing reaction using NEBNext End repair/dA-tailing module  following the manufacturer's instruction. The reaction mix was purified with AMPure XP beads (Agencourt). ONT Adaptor mix was added according to the direct cDNA sequencing kit protocol , then loaded on a R9.4 flow cell and sequenced for 20–24 h with MinION device.In particular, upon RPFs isolation, 5′ phosphorylation was performed with T4 PNK 3′ minus , according to manufacturer's instructions. RNA fragments were purified from the reaction using a RNA Clean & Concentrator™-5 column . The resulting RNA fragments were ligated via 3′P ligase , according to the following conditions: 30 pmol of RNA fragment, 10 pmol of ADR12, 15 pmol 3′P ligase, 1 × 3′P ligase buffer, 100 μM GTP, 1 mM MnClhttps://community.nanoporetech.com) base calling are processed to generate the consensus sequence of the RNA inserts within each selected concatemeric read. The selection criteria are defined by the user and include filtering by insert length (for our libraries we selected fragment lengths between 15 and 40 nt), read length and by minimum number of RNA inserts in the concatemeric reads.CirAID-p-seq produces long concatemeric molecules containing tandem repeats; each repeat comprises one adaptor and one fragment of interest . Once the cDNA is produced, it can be sequenced with the ONT platform. In ribosome profiling experiments, each insert is a ribosome protected fragment. To analyse the data obtained with cirAID-p-seq we developed a custom pipeline (written in Python 3): CircAidMe. The FASTQ files obtained by the Guppy 3.6.1  and low quality reads are detected and removed. Finally, a second MSA of the remaining inserts is performed and the consensus sequence generated. Throughout the pipeline, the detection of ONT- and circAID-p-seq adaptors is performed using SeqAn v2.4  searching for remaining ONT adaptors in a read after adaptor removal and (ii) detecting orientation of the circAID-p-seq adaptors, which indicate a fused read. Fused reads are then split at the appropriate position (forward or reverse). Second, for every read the circAID-p-seq adaptors, flanking the inserts, are detected. Thus, the inserts are then identified and extracted. Third, a multiple sequence alignment (MSA) of all inserts extracted from the same read is performed with MUSCLE v3.8.1551 . The MSAqAn v2.4 .https://github.com/ms-gx/CircAidMe.The final consensus sequences are collected in a FASTA file for downstream analyses. Several parameters for each read are collected and stored in a CSV file while executing CircAidMe to evaluate the quality of the circAID-p-seq library, including: number of inserts per read (≥3 for Ribo-seq), number of adaptors detected per read (≥4 for Ribo-seq), read length and consensus length (≥20 nt for Ribo-seq). Moreover, reads discarded by CircAidMe are collected in a separate FASTA file and the reason of their exclusion is provided as a tag in the report file. More details about the function of CircAidMe are available at the following GitHub repository: et al.  of the human and mouse transcriptome in the libraries, the consensus sequences generated by CircAidMe were iteratively mapped with Bowtie2  to diffeet al.  with default parameters, and removed with Samtools. For mouse sample all reads aligning to the very same region were collapsed. The sequencing data have been deposited in NCBI Geo database (accession GSE174754).Read coverages for each protein-coding gene from ONT and Illumina libraries were calculated with HTSeq  and norm10. The p-value is computed using Fisher's exact test. Since the Fisher's exact test produces lower P-values for longer lists even when the input lists are random, EnrichR precomputes a background expected rank for each term in each gene set library  the identification of all insert copies in the concatemeric read, (ii) multiple sequence alignment of the inserts and (iii) generation of a highly accurate consensus sequence of the RNA insert for further analyses  phos Figure . The cirs Figure . Other ws Figure ,49To optimize our strategy, we utilized a 30 nt long synthetic RNA molecule, called RNA30-3′P, bearing a 3′P group. The phosphorylation of the 5′ terminus was carried out by the T4 polynucleotide kinase (PNK 3′-minus), a step required to block self-ligation and obtain 5′P-RNA30-3′P RNA species Figure . The ligTo ensure the robustness of the consensus sequence, a large number of inserts in the concatemer reads is desirable. Thus, we assessed the effect of the ADR length and sequence on the number of generated repeats. We used three adaptors, 20 nt (ADR20), 60 nt (ADR60) or 110 nt (ADR110) long to generate libraries with the same 30 nts synthetic RNA fragment Figure  adaptor and B. TNext, we focused on optimizing the sequence composition of ADRs. We designed twelve 24 nts long ADR oligos , which are predicted to have minimal secondary structure. We pooled them at equimolar concentration for capturing and sequencing the 30 nts synthetic fragment (RNA30-3′P). After sequencing, we evaluated the length and the quality of the consensus sequence of the insert, as well as the relative abundance of each ADR. Almost all adaptors showed a correct consensus length Figure  and a hiR2 > 0.98) between the amount of input and the number of consensus sequences obtained for each insert  at different molar concentrations. For quantitative analysis, we took into consideration only reverse and ‘hairpin’ reads , i.e. thh insert . OverallTo further confirm the selectivity and efficiency of our method for library preparation in complex biological samples, we chose the framework of Ribo-seq, the sequencing of short RNA fragments protected by ribosomes from nuclease digestion. Ribo-seq provides positional information of ribosomes on transcripts as well as an indication of the RNAs engaged in translation. This experimental setup is intrinsically suitable for our purpose because the endonucleases used, e.g. RNase I, produce 25–35 nt long ribosome protected fragments (RPF), with 3′P ends. Therefore, with circAID-p-seq we can selectively and directly capture only fragments digested by the nuclease, without the need for additional de-phosphorylation steps and without the risk of sequencing RNAs fragments not generated by the enzyme.Currently there are no available technologies for selecting and sequencing 3′P RNA fragments, therefore we compared our library preparation method with two established protocols for RPF sequencing: (i) the ligation-free sequencing protocol based on a strand switching approach  and (ii)R = 0.87 in HEK293T and R = 0.91 in mouse liver samples) (R > 0.90) in mouse liver samples  and treated (H+) with Harringtonine, a drug known to stall ribosomes at the start codon . We obtasamples) . A curresamples) , we obsesamples) , confirm samples . As prev samples , the var samples .To finally confirm that circAID-p-seq can detect ribosome footprints, we investigated the number and percentage of reads mapping to protein coding sequences (cDNA). In circAID-p-seq data, 18% of reads from HEK293T and 29% of reads in mouse liver mapped to coding genes. In Illumina data, 20% and 9% of the reads from HEK293T and mouse liver respectively, aligned to coding genes Figure . We idenTo further characterize genes identified by the two methodologies, we performed a Gene Ontology (GO) analysis in both HEK293T and mouse liver datasets. We observed similar enriched terms between ILMN and circAID-p-seq/ONT , confirmOf note, CircAID-p-seq showed less reads mapping on tRNA and rRNA than ILMN in mouse liver samples, although a high percentage of unassigned reads is reported Figure . The lowTo account for ligation biases in the library construction, we analysed the nucleotide composition of the 5′ and 3′ termini of RPFs from the exogenously transfected GFP and the endogenous HSP90AA1, because these transcripts were the two with highest RPF coverage. The nucleotide composition of the first 5′ nucleotide and the last 3′ nucleotide of each RPF was compared to that of the entire CDS. For both ends, we did not observe strong deviations from the CDS Figure . This ren = 4115; >10 TPMs, RPFs are expected to be over-represented within the CDS of the mRNAs, where the P-site positions are expected to exhibit trinucleotide periodicity, in contrast to those positioned in 5′UTR and 3′UTR regions. In line with this, a high percentage of the generated consensus sequences mapped to the coding sequence (CDS) within mRNAs  Figure . The perTaken together, these results confirm that circAID-p-seq allows to select and sequence actual ribosome footprints with 3′P ends. Remarkably, circAID-p-seq requires at least 10 times less raw reads than classical ribosome profiling protocols to have a global view on relatively abundant transcripts (TPM > 1). More specifically, circAID-p-seq, coupled with CircAidMe, generates ribosome profiling data consistent with existing methods. Strikingly, cirAID-p-seq has the unique advantages of a higher efficiency and no PCR amplification steps, confirming that it (i) is suitable for ribosome profiling experiments and (ii) is effective for phospho-RNA-sequencing.To overcome library preparation and sequencing biases due to 3′ modifications of RNA fragments ,58, we iAs a proof of principle, we applied circAID-p-seq to ribosome profiling experiments, which are based on the generation of RNA fragments with a 3′-phosphate generated by endonuclease digestion. We benchmarked our method against commonly used Ribo-seq library preparation protocols that require a dephosphorylation of the 3′ end. In fact, existing approaches are based on PCR steps that can introduce amplification-related issues, although recent methods that include unique molecular identifiers (UMIs) can mitigate this problem ,60. WithCircAID-p-seq is based on two ligation reactions performed by a 3′P ligase and the T4Rnl1. We have strong evidence that in our ribosome profiling data our method is free of any ligation bias because we observed a good balance of the four nucleotides at the 5′-3′ end of the RPFs sequenced, and no positional discrepancy with ILMN methods were detected. Although we did not find detailed reports about 3′P ligase bias, our results on T4Rnl1 are in agreement with previous works, where long incubation times (≥2 h) ensures negligible ligation biases ,61. We cBased on ribosome profiling data, we showed that, circAID-p-seq coupled to ONT sequencing produces high-quality information in terms of (i) number of genes per million of reads and (ii) positional data of the ribosomes along transcripts. In addition, circAID-p-seq/ONT sequencing requires less absolute number of raw reads than classical ribosome profiling coupled with Illumina sequencing to achieve comparable coverage of the translatome. Furthermore, circAID-p-seq showed lower rRNA contamination than other methods, at least in our experiments. These features make the circAID-p-seq library generation extremely useful for genome-wide 3′ phospho-RNA analysis.If required, an increase in the sequencing depth can be achieved with other ONT sequencing platforms, such as PromethION or GridION. In terms of experimental time, circAID-p-seq combined with CircAidMe allows fast ribosome profiling experiments from sequencing to data analysis (24–48 h). Of note, circAID-p-seq sequencing was performed with the portable and low throughput MinION (ONT) sequencer, affording lower instrumental costs compared to ILMN sequencing. Another advantage of circAID-p-seq/ONT sequencing is that, in the case of samples displaying sequencing problems, the run can be stopped and the flow cell re-used. The main constraints identified for circAID-p-seq are the low sensitivity with low abundance transcripts and the detection of translation events only marginally represented in Ribo-seq data, such as the translation of upstream open reading frames (uORFs), new and rare translation events or ribosome readthrough events ,67. FutuIn addition to ribosome profiling, many other RNA footprinting techniques may take advantage of this method. For example, protocols employing endoribonucleases and generating 3′P termini with the aim of characterizing RNA-protein interactions, large RNA-protein complexes , and/or More importantly, 3′P phosphorylated RNAs are hallmarks of biological processes and can be generated in living cells by toxins , ribozymIn conclusion, the combination of circAID-p-seq with ONT allows single molecule, fast and easy detection of biologically relevant 3′-P/cP RNA species with a portable ONT device. CircAID-p-seq is the first phospho-RNA-sequencing library preparation method successfully tested in ribosome profiling experiments and could be used in the near future to better uncover the biological role of 3′-phospho RNA molecules, a still hidden transcriptomic layer in many genome-wide profiles.https://github.com/ms-gx/CircAidMe. The sequencing data have been deposited in NCBI Geo database (accession GSE174754).Source code of CircAidMe along with a pre-compiled package and a description of the software are available on GitHub: All animal tissue was obtained under full licensed approval from the UK Home Office following internal  and external ethical review.gkab1158_Supplemental_FilesClick here for additional data file.


Penicillium digitatum is the main postharvest pathogen of citrus fruit. Although the inner fruit peel part  is less resistant than the outer part (flavedo) to P. digitatum, the global mechanisms involved in their different susceptibility remain unknown. Here, we examine transcriptome differences between both tissues at fruit harvest and in their early responses to infection. At harvest, not only was secondary metabolism, involving phenylpropanoids, waxes, and terpenoids, generally induced in flavedo vs. albedo, but also energy metabolism, transcription factors (TFs), and biotic stress-related hormones and proteins too. Flavedo-specific induced responses to infection might be regulated in part by ERF1 TF, and are related to structural plant cell wall reinforcement. Other induced responses may be related to H2O2, the synthesis of phenylpropanoids, and the stress-related proteins required to maintain basal defense responses against virulent pathogens, whereas P. digitatum represses some hydrolase-encoding genes that play different functions and auxin-responsive genes in this peel tissue. In infected albedo, the repression of transport and signal transduction prevail, as does the induction of not only the processes related to the synthesis of flavonoids, indole glucosinolates, cutin, and oxylipins, but also the specific genes that elicit plant immunity against pathogens. Plant and fruit epidermis is constantly exposed to environmental factors, including pathogenic and non-pathogenic microorganisms. Thus, apart from its main function as a protective barrier, the cuticle plays an important role in the interaction with such microorganisms . ColonizPenicillium digitatum (Pers.:Fr.) Sacc., the causal agent of green mold disease, is the main postharvest pathogen of citrus fruit worldwide. This ascomycete is present on fruit surfaces and penetrates through wounds caused during postharvest handling and storage, which easily lead to rot. The penetration of spores from contaminations in storing and packing houses markedly increases rot incidence, especially if spores are resistant to widely used fungicides. The control of P. digitatum is based mostly on applying chemical fungicides. The demand for effective and safe alternative control methods to eliminate mold fungi and their toxic metabolites (mycotoxins) is increasing due to consumer health and environmental concerns and the occurrence of fungicide-resistant strains  escribed . FinallyCitrus sinensis (L.) Osbeck) orange cultivar were harvested at the end of January (30 January) from adult trees grown in an experimental orchard at the ‘The Spanish Citrus Germplasm Bank’ of the Instituto Valenciano de Investigaciones Agrarias (IVIA) in Moncada , Spain. The color index was determined in three replicates of 10 freshly harvested fruit as previously described [The mature fruit  of the Navelate  and three replicates of five fruit each (second sublot). The first sublot was used for the transcriptomic analysis and to periodically analyze changes in the expression levels of the genes selected according to the results obtained from this analysis. For these analyses, peel discs (7 mm in diameter) were taken around the inoculation site and three replicates of 10 fruit per sampling period, and 16 discs per fruit were used in each replicate (160 discs per replicate). To compare any changes in both albedo and flavedo in response to P. digitatum inoculation, flavedo and albedo tissues were carefully separated from all the discs with a razor blade, and both tissues were immediately frozen separately and homogenized in liquid nitrogen before being left at −80 °C for the later analyses. The samples inoculated with both the pathogen and sterile water (control) were taken at 1, 2, and 3 d post-inoculation . Flavedo and albedo discs were also taken from three replicates of 10 fruit from the freshly harvested fruit. The second sublot was made up of three replicates of five fruit and was used to evaluate disease evolution. All the fruit were stored at 20 °C and 90–95% relative humidity (RH) to avoid dehydration.The selected oranges were surface-sterilized with 5% commercial bleach for 5 min and rinsed with tap water as previously described . Then, t4 conidia mL−1) (infected fruit) or with 10 µL of sterile water (mock-wounded control fruit). Sixteen and four inoculations per fruit were performed on each fruit to take the flavedo and albedo samples for the later analyses and to follow disease severity evolution, respectively.Fruit were wounded with a flame-sterilized needle at a depth of 4 mm and inoculated with 10 µL of conidial suspension (10Disease severity was determined as the mean lesion diameter (mm) of the fruit macerated zone by considering all the inoculated wounds. Diameters were measured in two perpendicular directions on each wound with a flexible ruler before calculating the average diameter of each wound. Three replicate samples, containing five fruit each, with four wounds in the equatorial zone per fruit were used. Lesion diameters were measured periodically in the inoculated fruit left in plastic boxes at 20 °C and 90–95% RH in the dark.Total RNA was extracted from 1 g of the flavedo or albedo samples, previously frozen, homogenized, and kept at −80 °C, as previously described . The RNAP. digitatum and their respective mock-wounded control fruit, were employed to construct sequencing libraries, as previously described [® with PolyA selection for ribosomal RNA depletion  following the manufacturer’s recommendations. The Illumina NextSeq 500 platform was used to sequence libraries and 75-bp single-end reads were generated by the Genome Facility at the SCSIE-UV . The quality of the raw sequence reads was checked by FastP  and FastQC v0.11.8 . To obtain clean data, the reads containing only adaptors were removed and sequence reads were filtered by at least a mean Q20. Trimmed sequences were mapped to the Citrus sinensis genome (Phytozome release Csinensis_154_v1.1) https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Phytozome, accessed on 6 March 2020) with the default settings in the TopHat2 v2.1.0 software. Quality control, visualization, and quantification were performed with the Seqmonk v1.41 software . Only the reads mapped over protein-coding genes were counted with the RNA-Seq quantification pipeline by assuming opposing strand specificity to generate raw read counts. The edgeR R/Bioconductor package (v3.20.9) in the R (v3.4.4) environment  was utilized to perform the differential expression analysis between two experimental conditions, which included three biological replicates each. p-values were determined by the Benjamini and Hochberg approach, and the genes satisfying an adjusted p-value ≤ 0.05 in each comparison were considered differentially expressed genes (DEGs). An estimation of the unique gene expression levels was obtained by the Log2 RPM method. Only the DEGs that met a cut-off of |Log2 FoldChange| ≥ 1 were considered in the Venn diagrams, which show the number of DEGs induced or repressed by wounding (control) or infection in flavedo and albedo in relation to the same tissue taken at fruit harvest. This cut-off was also established for all the subsequent bioinformatics analyses. For the multivariate analyses, the Seqmonk tool was used to select highly variable genes by a standard deviation cut-off above 0.6. The Log2 RPKM values were employed for the principal component analysis (PCA), which was 3D-plotted by plot.ly . The selected genes were hierarchically clustered following the average linkage method with Pearson Correlation distance metric, and were then represented by a hierarchical cluster analysis (HCA) and HeatMap according to the MultiExperiment Viewer (MeV 4.9.0). The MapMan software package  was used to visualize the gene expression data on a metabolic map. The significantly induced or repressed KEGG metabolic pathways were identified by the KEGG enrichment analysis using the TBtools.KeggBackEnd package (TBtools v 1.046) [p-value (pgoFisher) was lower than 0.05.Three biological replicates of 2 μg of the RNA of the albedo and flavedo samples from the freshly harvested Navelate oranges, and from the flavedo and albedo samples collected at 1 dpi from the fruit inoculated with escribed . They wev 1.046) . The biov 1.046)  with theP. digitatum. The cDNA from each sample was synthesized from 2 μg of total RNA by SuperScript III RT  and ribonuclease inhibitor , as indicated by the manufacturer. Gene-specific primers were designed with the DNAMAN 4.03 software . The forward and reverse primers are summarized in ACT and TUB were used to normalize the expression levels of the target genes. The expression levels of the flavedo and albedo samples of the control and infected fruit were referred to those obtained in the flavedo and albedo of the freshly harvested fruit, respectively, in the Relative Expression Software Tool . Gene-specific primer pairs, and the cDNA obtained from 25 ng of RNA and SYBR Green 1 Master , were used to generate the relative gene expression data in a LightCycler480 System  instrument. cDNA amplification was monitored during 40 cycles at 95 °C for 10 s, 60 °C for 5 s, and 72 °C for 10 s. Values were the means of three biological replicates samples with two technical replicates ± standard deviation.For the gene expression analysis, total RNA was treated with ribonuclease-free DNase  following the manufacturer’s instructions to remove genomic DNA contaminations. A RT-qPCR analysis was carried out following the procedure described in  to validwww.statgraphics.com, accessed on 5 April 2021). A mean comparison by a t-test (p ≤ 0.05) was made to determine whether the mean gene expression values were significantly different between the infected and mock-wounded control fruit of the same tissue and for the same storage time.Statistical analyses were performed by the STATGRAPHICS software (P. digitatum (104 conidia mL−1) by determining the lesion diameter of the wounds inoculated with the pathogen for up to 7 dpi. As shown in Disease severity evolution was evaluated in the Navelate oranges infected by P. digitatum in citrus fruit. Given the relevance of the rapid-signaling transcriptional outputs induced by the host in response to pathogen infection in the host immunity, we examined the very early transcriptional changes that occurred in both peel tissues in response to P. digitatum and compared them to those produced during the same period in the mock-wounded tissues. It should be noted that wounding was the control of infection because P. digitatum is a wound pathogen.The transcriptomic differences between outer and inner peel parts were examined at fruit harvest to know the differences in the mechanisms associated with preformed constitutive defense barriers against p ≤ 0.05 that met a cut-off of at least a two-fold change (−1 ≥ log2 ≥ 1) in the wounded and infected albedo and flavedo tissues by 1 dpi, in relation to the same tissue taken at fruit harvest, are summarized in The number of up- and down-regulated DEGs at 2 = 0.863 p ≤ 0.05) was found between both analyses  than the other pathway subcategories   between both tissues and highlighted the repression of photosynthesis in albedo, which showed the lowest corrected × 10−12) . The vis× 10−12) A agreed × 10−12) . The exa× 10−12) B involvi× 10−12) A.P. digitatum were related to defense stress-related responses in plants. Some DEGs were commonly induced by infection in both tissues, while others were specific to each peel part. The functional categorization of these DEGs identified that different BP, MF, and CC were significantly repressed or induced in an early infection stage   . It is wne 2021) . Of the ne 2021) . They weIn flavedo, the induction of the processes related to the chloroplast/light stimulus prevailed, which included a chloroplast signal recognition particle component (CAO), and cell wall biosynthesis involving a cellulose synthase (CSLB4) and carboxypeptidase activity . The DEGP. digitatum infection had a stronger impact on the induction of the biotic-stress related responses in albedo than in flavedo. Major differences were found in the DEGs involved in signaling, which mostly encoded the RLKs belonging to different families. This analysis also showed a stronger effect of infection on the metabolic changes related to secondary metabolism, cell wall modification, or the involved PRs, and also on the expression of two TFs (WRKY72 and AP2/EREBP) in albedo.Only one BP and two MF processes were commonly regulated in both peel tissues, which involved the repression of the RmlC-like cupin and the CXXS1-encoding genes in both tissues, as well as the induction of the different DEGs that encode OMT proteins, which differed between albedo and flavedo . The ‘biChanges in the expression of the DEGs selected for the RT-qPCR validation of RNA-Seq were analyzed for up to 3 dpi  before dP. digitatum is based mostly on using fungicides. The development of alternative control methods would benefit if our knowledge about the mechanisms involved in citrus fruit’s natural defense ability against this fungus increased. As flavedo is less susceptible than albedo to infection [P. digitatum attack of each peel tissue before disease symptoms develop , and its RNA-Seq analysis was performed later after inoculation. Therefore, the present study bridges the knowledge gap about the specific responses of inner and outer peel parts to the pathogen, and is more restrictive when examining early responses to infection. In fact, under our experimental conditions, the number of up- and down-regulated genes in either the albedo or flavedo of the infected fruit in relation to the control wounded fruit was much smaller (<150 up- + down-regulated in each peel tissue) than those found previously in the pericarp (4353 up-/4724 down-regulated) [P. digitatum [P. digitatum secretes PME and ROS-related responses to colonize citrus fruit [Considerably fewer DEGs were regulated by infection than the DEGs found when comparing albedo and flavedo at fruit harvest . No earlcultivar . Howevergulated) . Some DEigitatum . Likewisigitatum . A pectiigitatum , but no us fruit , the repP. digitatum. In line with this, it is worth noting the results showing major increases in the expression of two genes (CAO and GLOX) encoding H2O2-generating enzymes in the flavedo of the infected fruit compared to wounding . H2O2 may play a role in attacking P. digitatum [By focusing on early specific flavedo-induced responses to infection, the obtained results unveiled the relevance of both the chloroplast, which is necessary for photosynthesis and is one of the main sources of ROS production , and of wounding , which sus fruit . It is aus fruit . Howevernfection . It is nnfection , and ourn plants , and we igitatum ,44 and iigitatum , but couigitatum ,46.P. digitatum infection. The transcriptomic analysis also highlighted the repression of the ‘hydrolase activity’ MF in the P. digitatum–flavedo interaction . In line with this, it is remarkable that a stearoyl-acyl carrier protein desaturase, which favors jasmonic acid-mediated pathways [P. digitatum mycelial growth can be promoted by citrus fruit epicuticular wax and the conidial germination inhibited by cutin [P. digitatum [P. digitatum virulence. These ideas not only agree with a previous study that identified the genes involved in the virulence of this pathogen toward citrus fruit [P. digitatum in citrus fruit [P. digitatum may operate in the inner peel part by negatively affecting signal transduction and transport.The results presented herein also revealed that defense responses in the inner peel part against proteins , and invpathways , was alsby cutin . Thus, iigitatum , the ALDigitatum , and of igitatum  or playiigitatum . As a β–igitatum . Inoculaus fruit , but alsP. digitatum in the flavedo of freshly harvested fruit involve: (1) energy metabolism; (2) secondary metabolism, including phenylpropanoids, lipids, waxes and terpenoids; (3) ERF, WRKY, and MYB TFs; and (4) signaling molecules, and biotic stress-related proteins involving plant hormones, PRs, and ROS homeostasis, which were generally less expressed in the albedo. The early specific induced responses against P. digitatum infection in flavedo might be regulated by ERF1 TF and are mostly associated with the reinforcement of the plant cell wall. Other protective-related responses might be related to either H2O2 or the synthesis of phenylpropanoids, while the repression of both hydrolase-encoding genes and auxin-responsive genes would contribute to P. digitatum virulence and colonization in this outer peel tissue. In contrast, the induction of the secondary metabolism-related processes, involving terpenoids, phenylpropanoids and oxylipins; the synthesis of wax and cutin-related compounds; and the repression of signal transduction and transport, prevailed in albedo.Taken together, the herein presented data suggest that constitutive defenses against