Characteristic properties of type III CRISPR-Cas systems include recognition of target RNA and the subsequent induction of a multifaceted immune response. This involves sequence-specific cleavage of the target RNA and production of cyclic oligoadenylate (cOA) molecules. Here we report that an exposed seed region at the 3′ end of the crRNA is essential for target RNA binding and cleavage, whereas cOA production requires base pairing at the 5′ end of the crRNA. Moreover, we uncover that the variation in the size and composition of type III complexes within a single host results in variable seed regions. This may prevent escape by invading genetic elements, while controlling cOA production tightly to prevent unnecessary damage to the host. Lastly, we use these findings to develop a new diagnostic tool, SCOPE, for the specific detection of SARS-CoV-2 from human nasal swab samples, revealing sensitivities in the atto-molar range. Type III CRISPR-Cas systems recognize and cleave target RNAs and produce signalling molecules. Here the authors discover that both processes are governed by a flexible seed region, ultimately resulting in SCOPE, a SARSCoV-2 diagnostic assay with atto-molar sensitivity. A CRISPR array is composed of alternating repeat and spacer sequences, typically with the repeats consisting of identical sequences and the spacers consisting of variable sequence fragments acquired from invading MGEs7. The CRISPR array is generally located adjacent to a set of CRISPR-associated (cas) genes encoding the Cas proteins.As a widespread prokaryotic adaptive immune system, CRISPR-Cas  systems target and cleave genetic material of viruses and other mobile genetic elements (MGEs)8. A second maturation event occurs where the crRNA is trimmed at the 3′ end10. The mature crRNAs form a ribonucleoprotein complex together with a set of Cas proteins: the type III effector complex  by the Cas6 ribonucleaselex Fig. . In the 17. Structural and biochemical analyses of the multi-subunit type III complexes have revealed the subunits responsible for these activities and showed that they are induced in a step-wise manner, starting with the binding of a complementary target RNA23. After binding, the target RNA is cleaved by the Cas7 ribonuclease, which is present in multiple copies and constitutes the backbone of type III complexes. As such, type III interference complexes have multiple (2–4) active sites, cleaving the target RNA at 6 nt intervals  second messenger molecules that allosterically activate CARF (CRISPR-associated Rossmann fold) proteins28. Most of the CARF proteins that have been characterized so far appear to be promiscuous RNases (fusion of CARF and HEPN domains), cleaving both viral and host RNAs, thereby potentially inducing cell dormancy or cell death31.Unlike other CRISPR-Cas systems that exclusively target either DNA  or RNA (type VI), many type III systems have the capacity to target both RNA and DNAals Fig. 12,15,24–T. thermophilus HB8 (TtCmr)32. We showed that TtCmr adopts a structure similar to type I (Cascade) complexes: a backbone consisting of several Cas7 (Cmr4) subunits, associated with multiple copies of the small subunit Cas11 (Cmr5). The complex is capped at one end by a heterodimer of the large subunit Cas10 (Cmr2) and Cas5 (Cmr3), and at the other end by a heterodimer of Cas7-like subunits (Cmr1 and Cmr6)23. It is important to note that the Cas10 subunit of the TtCmr complex lacks the HD domain, and hence does not have DNase activity18. The mature crRNA runs along the Cas7 backbone of the complex, with its 5′ repeat-derived end (the 5′ handle) anchored by Cas10/Cas5, and its 3′ end located at the Cmr1/Cmr6 end23.Previously, we characterized the structural and enzymatic features of the endogenous type III-B Cmr complex from 35. Although the details of this 3′ processing event are not known, it is hypothesized that the heterogenous nature of the TtCmr complex might be responsible for this. Indeed, analysis of the crRNA-content of the endogenous TtCmr complex showed that it indeed co-purifies with mature crRNAs of different sizes (with variable 3′ ends), with a distinct 6-nt pattern: 34, 40 & 46 nt18. In addition, our previously obtained cryo-EM structures revealed that the native population of TtCmr complexes consisted of larger (with a stoichiometry of Cmr112131445361) and smaller complexes , with the smaller complexes lacking one or two Cas7–Cas11 (Cmr4-Cmr5) backbone segment(s)  Fig. . Taken tIn this work, we set out to understand the biological significance of these differently-sized Cmr complexes. We reveal yet another unique feature of type III: a flexible seed region at the 3′ end of the crRNA guides, that appears to be important for these systems to prevent phage escapees. Additionally, we identify another key feature at the 5′ end of the type III crRNA that, upon binding a perfectly match target sequence, triggers the catalytic activities of Cas10, thereby ensuring tight control over CARF protein activation. These characteristics form the basis for the development of a highly sensitive type III diagnostics platform called SCOPE (Screening using CRISPR Oligoadenylate-Perceptive Effectors).T. thermophilus HB8 (TtCmr) are loaded with mature crRNA guides of different lengths (34-40-46 nt), and that the crRNA-4.5  is most abundant  at 6 nt intervals, corresponding to the Cas7 subunits in the backbone of the complex. Consequently, this results in 5′ labeled degradation products of 39 (α), 33 (β), 27 (γ) and 21 (δ) nucleotides  of a defined length. Based on their abundance in their native host18, we chose to include crRNA lengths of either 34 (TtCmr-34), 40 (TtCmr-40) or 46 nt (TtCmr-46). Opposed to all four (α-δ) 5′-labeled degradation products observed with the endogenous complex, each of the reconstituted complexes produced defined degradation products decreasing in size with a longer crRNA 14. This motif checks for complementarity between the 5′ handle of the crRNA  and the corresponding 3′ region flanking the protospacer40  target RNA  second messengers. In the structurally-related type I effector complexes , DNA targeting is governed by two factors: the PAM (protospacer adjacent motif) and the seedr40 Fig. . Since TRNA Fig. . The cleRNA Fig. . To probRNA Fig. . SimilarRNA Fig. . We concNext, we tested whether TtCmr utilizes a seed similar as described for the Cascade complexes of type I systems. Activity assays were performed by incubating the TtCmr complex with target RNAs containing single mismatch mutations in the first 7 nt of the spacer region of the crRNA, which is the region on the crRNA base pairing with the protospacer Fig. . The resSince the seed is defined as the region on the crRNA that initiates base pairing with its target, we performed EMSA binding assays with the endogenous TtCmr complex and Fig. . In contand Fig. . The 3′ T. thermophilus HB830. We selected this enzyme to establish a synthetic signal transduction route consisting of an RNA-targeting TtCmr/crRNA complex that generates cOA molecules, which in turn trigger the cleavage of a reporter RNA by TTHB144 thereby generating a detectable fluorescence signal.Based on these stringent target RNA requirements , we concluded that type III CRISPR-Cas systems have a high potential for being repurposed as a novel, highly sensitive, robust nucleic acid detection tool. To investigate this possibility, we opted to couple the production of the second messenger to an easy read-out. In nature, these cOAs specifically bind to proteins with a CARF domain, causing an allosteric activation of fused enzyme domains. A well-characterized example of such an CARF-associated enzyme is a cOA-dependent nonspecific RNase (TTHB144) of We first performed in vitro activity assays, using the TtCmr-46 complex, to which we added purified TTHB144 and a 5′ Cy5-labeled reporter RNA. We observed defined degradation products of the reporter RNA only when both the 4.5 target RNA (T) and TTHB144 are present Fig. , whereas42 LAMP pre-amplification step that specifically amplifies the SARS-CoV-2 E-gene, simultaneously adding a T7 promotor to the amplicon that allowed for a subsequent in vitro transcription step44 (Supplementary Table −18 M) range within a timespan of ~35 min (30 min pre-amplification (1) + 5 min CRISPR detection (2)) 2)) Fig. .To validate our 2-step setup in a more complex reaction environment, we continued by testing human nasal swab samples, which were collected at an on-site SARS-CoV-2 testing facility. Out of the 80 samples tested, our tool scored 62 of them positively. We validated these results by comparing them to a PCR-based test (current standard for SARS-CoV-2 testing) that was performed on the same samples in parallel, which were in excellent agreement up to a relevant Ct-value of ~37. In addition, 20 samples that were considered negative by PCR , were scored negative by SCOPE as well Fig. .Lastly, the thermophilic nature of the type III proteins (Thermus-derived Cmr complex and CARF-RNase) of our tool offers an attractive opportunity for a one-pot reaction by combining the LAMP pre-amplification step with CRISPR detection, as the optimum temperature of the reactions is in the same range. Due to the maximum temperature tolerance of an appropriate, commercially available RNA polymerase , we performed a one-pot LAMP-CRISPR assay at a temperature of 55 °C. The limit of detection was determined at 800 aM, using a synthetic version of the SARS-CoV-2 E-gene, demonstrating the feasibility of this approach Fig. .47 and the potentially large signaling network mediated by cOA molecules in the interference phase50. Furthermore, type III systems are exceptional in the sense that they are the only CRISPR-Cas system characterized to date capable of targeting both RNA (guide dependent) and DNA . However, the latest classification in type III CRISPR-Cas systems suggested that not all type III systems are endowed with DNase activity, due to an inactivated or missing HD domain in Cas1051. This suggests that RNA is the bona fide target of these systems, as is the case for the type III-B system (Cmr-β) of S. islandicus11, and of T. thermophilus presented here.Recent advancements in our understanding of type III CRISPR-Cas systems have highlighted that they have unique mechanistic features compared to other CRISPR-Cas systems. Examples of this include the requirement for reverse-transcriptase activity for some type III systems during the adaptation phase53. Consequently, the cellular population of type III complexes are a heterogenous mixture of complexes with at least three different sizes34. The biological significance of these observations has long remained elusive (see below). Lastly, studies addressing the seed in type III systems are somewhat conflicting, with one report proposing a complete absence of a seed54, whereas other studies report a seed region in either the 5′55 or 3′ end57 of the crRNA guide. These discrepancies can be explained by the different methods used to pinpoint certain regions of importance on the crRNA. For instance, read-outs that either directly or indirectly look at cOA production, such as phage challenge experiments or conformational changes in Cas10, will point towards a bigger importance of the 5′ region. However, studies on the relationship of seed requirements and cOA production have paved the way for a more thorough and complete investigation49. Here, we dissected the importance of different size-variants of the TtCmr complex and the different regions on the crRNA by looking at each step from target RNA binding to CARF protein activation individually. Together, our data resulted in a model presented in Fig. Yet another unique feature of type III systems is the variable crRNA length with a typical 6 nt periodicity, which, in turn, corresponds to the variable number of Cas7 subunits that constitute the backbone of type III-A and type III-B complexes53. We therefore propose that Cmr1 and Cmr6 are involved in the proper positioning of the seed region to initiate base pairing with its cognate target RNA. The position of Cmr1 and Cmr6 on the crRNA is determined by the variable 3′ end of the crRNA. Indeed, we observed that shorter complexes (with the 40 nt crRNA) had a seed region, that was shifted one segment towards the 5′ end , a region that we designated as the CAR (Cas10-Activating Region). In agreement with previous work on type I and type III complexes, the nucleotide on the crRNA after each segment  is excluded from base pairing with the target RNA, due to the thumb-like extension of Cas737.Secondly, base pairing at the seed region promotes a conformational change within the TtCmr complex, opening a channel along the Cas7/Cas11 backbone wide enough to accommodate further base pairing interactions of the crRNA with its target RNA Figs.  and 623.58. Although self-RNAs are bound and cleaved by TtCmr, the complementarity between the 5′ handle and the corresponding region on the self-RNA does completely prevent cOA production.Lastly, even after fulfilling RNA-targeting requirements  we showed that a final checkpoint ensures that no cOA is produced when targeting self-RNAs 60, which ensure within-host spacer diversity. Our findings suggest that type III systems can create this diversity with just a single spacer. On one hand, the ability to recognize heavily mutated MGEs might be beneficial for the host to provide a robust interference response towards MGEs61. In Marinomonas mediterranea for example, a horizontally acquired type III-B system was recently shown to effectively bolster the immune response of its native type I-F systems to cope with phage escapees62. On the other hand, this same flexibility might come at the cost of a higher risk of self-targeting. While incidental binding and degradation of self-RNAs by itself might not represent a large fitness cost to the host, the subsequent activation of the Cas10 Palm domain  might have more detrimental consequences16. This scenario is in good agreement with our results, showing that activation of the Cas10 Palm domain is indeed only induced when very specific conditions are met .Although the biological significance of our findings still awaits further investigation in vivo, we anticipate that the flexibility of the seed region in type III systems will lower the chances that MGEs escape CRISPR-Cas targeting by introducing mutations in the protospacer. In type I CRISPR-Cas systems, MGE escapees promote the rapid acquisition of additional spacers, in a process called primed adaptionT. thermophilus63. While TTHB152 is also characterized as a CARF-RNase, it is encoded in the type III-A operon, so for consistency we opted to use TTHB144. We observed highly similar trends in target RNA sequence requirements (CAR and segments mutants) for activation of the RNase activity of TTHB144 compared to those governing cOA production , we selected TTHB144 - one of the three native cOA-activatable (CARF) proteins present in the genome of nds Fig. . For moscol Fig.  on a SARIdeally, a true one-pot reaction is preferred to minimize steps and to reduce the risk of cross-contamination. We therefore investigated the performance of our system in a one-pot setup, at a temperature of 55 °C (to comply with the upper temperature limit of Hi-T7 polymerase). Despite using sub-optimal temperature for the CRISPR detection step, we were able to achieve a limit of detection of 800 aM using a synthetic gene template Fig. . We show65. However, SCOPE is the first Class 1-based CRISPR-Cas nucleic acid detection tool, with some very useful characteristics: highly sensitive  and specific , quick (detection within seconds), flexible (PAM-independent guide design), highly robust (long shelf-life). Furthermore, the potential for a 1-pot system in combination with RT-LAMP offers opportunities to increase the throughput of our tool. The thermophilic nature of the system potentially means that the system is less affected by, enzyme mediated, inhibitory factors in crudely extracted samples. While the 2-step approach currently limits efficient high-throughput testing due to the extra  step that is required, an efficient 1-pot system would mitigate this. The use of a standard fluorophore and no proprietary plastics further facilitates integration in current high throughput testing facilities. All these favorable features make the SCOPE approach a highly attractive alternative over the currently available detection tools.A couple of CRISPR-based nucleic acids detection platforms have been developed over the last years, such as the Class2-based DETECTR and SHERLOCK platformsT. thermophilus HB8 cells, producing the (His)6-tagged Cmr complex, were resuspended in 100 ml of 50 mM NaCL, 20 mM Tris-HCl (pH 8.0). Subsequently, these cells were lysed by sonication in ice water, and spun down at 200,000 × g for 1 h at 4 °C. The supernatant was used for purification using a HisTrap HP column , pre-equilibrated with 150 mM NaCl, 20 mM Tris-HCl, 20 mM imidazole (pH 8.0), after which elution was done using a linear gradient of 20–500 mM imidazole. Collected fractions were desalted using a HiPrep 26/10 desalting column . The sample was then applied to a RESOURCE Q column , pre-equilibrated with 20 mM Tris-HCl (pH 8.0), and the bound proteins were eluted with a linear gradient of 0–0.5 M NaCl. Finally, gel filtration was performed using a HiLoad 16/60 Superdex 200 pg  column, pre-equilibrated with 150 mM NaCl, 20 mM Tris-HCl (pH 8.0). The collected fractions were concentrated with a Vivaspin 20 concentrator 18. For reconstituted complex, each subunit was individually expressed and purified. All subunits were cloned in a bicistronic design elements containing expression plasmid under an Isopropyl β-D-1-thiogalactopyranoside (IPTG) inducible T7 promoter and N-terminal Streptavidin tag. Expression plasmid containing E. coli BL21(DE3) were grown at 37 °C until ~OD600 = 0.6, after which the culture was cold-shocked on ice for 1 h. IPTG was added to a final concentration of 0.5–1 mM and the culture was incubated at 20 °C for 16 h. Cells were harvested and resuspended in Wash Buffer  and a Complete protease inhibitor tablet was added (Roche). Cells were lysed by sonication  and spun down at 30.000 × g for 45 min, subsequent lysate was filter (0.45 µm) clarified. A StrepTrap HP (GE) column was equilibrated using Wash Buffer and the lysate was run over it. Wash Buffer with d-Desthiobiotin added to a final concentration of 2.5 mM was used to elute. The elution fractions were pooled, concentrated and run over a HiLoad® 16/600 Superdex® 75 pg size exclusion chromatography column for further purification. Purification of TTHB144 was performed in similar fashion.Harvested For TtCmr46, 3.5 μL crRNA (700 ng) was added to 3.5 μL 1X Cmr buffer . Subsequently, the subunits were added to the reaction mixture in a specific order  to a final concentration of 2.5 μM, 2.5 μM, 10 μM, 7.5 μM, 2.5 μM and 2.5 μM respectively, to make up a total reaction volume of 20 μL. For TtCmr40 final concentration of subunits was adjusted to 2.5 μM, 2.5 μM, 7.5 μM, 5 μM, 2.5 μM and 2.5 μM respectively. The reaction mixture was incubated at 65°C for 30 min.32P-γ -ATP, after which they were purified from a denaturing PAGE using RNA gel elution buffer  or ordered with a 5′ Cy5 fluorescent label. In vitro cleavage activity assays were conducted in TtCmr activity assay buffer  using the RNA substrate and 62.5 nM TtCmr. Unless stated otherwise, the reaction was incubated at 65 °C for 1 h. RNA loading dye  was added to the samples after incubation and boiled at 95° for 5 min. The samples were run on a 20% denaturing polyacrylamide gel (containing 7 M urea) for about 1–4 h at 15 mA or overnight at a constant of 4 mA. The image was visualized using phosphorimaging or fluorescent gel scanning (GE Amersham Typhoon).RNA substrates (listed in Supplementary Table 2) to which Cmr-complex  as well as the RNA substrates  as a ratio of the OD650 signal obtained from the fully complementary target RNA.The unitless relative PPi levels (cOA-production) presented in Figs. EMSAs were performed by incubating 62.5 nM TtCmr complex with 13.3 nM 5′ Cy5-labeled target RNAs (Supplementary Table S. islandicus Cmr complex (PD 6S6B) was fitted as a single rigid body into the TtCmr46 map, and supervised flexible fitting was performed using Isolde66. Maps were visualized using ChimeraX67.In order to model crRNA within our previously determined TtCmr46 and TtCmr40 maps , the model of 68.Combined human throat/nasopharyngeal swab samples were obtained at a community testing center  from adults with either SARS-CoV2- related symptoms or with contacts of infected persons. Recruitment occurred at a testing site that was set up as a research site to evaluate new diagnostic tests for SARS-CoV-2. Adults who visited the testing center were asked to participate in validation studies of novel diagnostic tests. Participants gave consent to use of residual material of the obtained combined human throat/nasopharyngeal swab samples. As samples were collected within the framework of the national COVID measures and testing efforts, samples were routinely collected at interval timepoints. The medical research ethics committee (MREC) of Utrecht decided that validation studies of new diagnostic tests for SARS-CoV-2 is not subject to the Medical Research Involving Human Subjects Act (WMO) and did not require full review by an accredited MREC. All participants were informed and consented with participation. PCR was conducted in a certified clinical laboratory and all procedures were validated according to the ISO 15189 standard. Nasopharyngeal swabs were transferred into 3 ml Universal transport medium. RNA was isolated and purified using the MagC extraction kit (Seegene) on an automatic nucleic acid extractor Hamilton MicroLAB StartLET (Bonaduz). SARS-CoV-2 qPCR was performed using the HKU protocol for ORF1ab gene detection. Primers and probe (Supplementary Table Orf1ab SARS-CoV-2 gene.Results were interpreted with the 7500 Fast SDS (Applied Biosystems) data analysis software. A positive result was defined as amplification of the The target RNA induced activation of TTHB144 assays were performed similarly to the earlier described in vitro cleavage assays using reconstituted TtCmr-46 complex. However, non-labeled (non)target RNA was used and either a 5′ Cy5 reporter RNA Fig.  or comme44. Final primer concentrations of 0.2 μM, 1.6 μM and 0.8 μM for the F3/B3, FIP/BIP and LoopF/LoopB primers were used respectively. A T7 promotor sequence was added to the loop primer to allow for the subsequent in vitro transcription reaction. After pre-amplification by LAMP, subsequent T7 polymerase transcription will enrich the target RNA, partly consisting of a template derived region which lies between the Loop primer and the B2 primer . Total incubation-time for the one-pot reaction was 180 min.In all cases, the limit of detection (LOD) was determined by the lowest concentration of target RNA in the reaction mixture in step 1, which led to an significant increase in fluorescence compared to the non-target RNA control. The delta-signal SCOPE value was calculated by taking the, blank subtracted, increase of fluorescent signal over time during the 15 min of the CRISPR detection step in the 2-step protocol. Similarly, the same calculation was used for the one-pot assay, by using the signal increase over 180 min of incubation. For the human swap samples presented in Fig. Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


High stakes can be stressful whether one is telling the truth or lying. However, liars can feel extra fear from worrying to be discovered than truth-tellers, and according to the “leakage theory,” the fear is almost impossible to be repressed. Therefore, we assumed that analyzing the facial expression of fear could reveal deceits. Detecting and analyzing the subtle leaked fear facial expressions is a challenging task for laypeople. It is, however, a relatively easy job for computer vision and machine learning. To test the hypothesis, we analyzed video clips from a game show “The moment of truth” by using OpenFace (for outputting the Action Units (AUs) of fear and face landmarks) and WEKA (for classifying the video clips in which the players were lying or telling the truth). The results showed that some algorithms achieved an accuracy of >80% merely using AUs of fear. Besides, the total duration of AU20 of fear was found to be shorter under the lying condition than that from the truth-telling condition. Further analysis found that the reason for a shorter duration in the lying condition was that the time window from peak to offset of AU20 under the lying condition was less than that under the truth-telling condition. The results also showed that facial movements around the eyes were more asymmetrical when people are telling lies. All the results suggested that facial clues can be used to detect deception, and fear could be a cue for distinguishing liars from truth-tellers. Are there any observable behaviors or cues that can differentiate lying from truth-telling? Almost all researchers in the field of deception detection agree that there is no “Pinocchio's nose” that can serve as an easy indicator of deception  emotional facial expressions of fear (fear of being caught) can differentiate lying from truth-telling in high-stake situations; (2) the duration of AUs of fear in lying would be shorter than that in truth-telling; (3) the symmetry of facial movements will be different, as facial movements in lying situations will be more asymmetrical (due to the nature of repressing and leaking).The database we used were 32 video clips of 16 individuals telling lies in half of them and truth in the other half. All of the video clips were recorded in a high-stake game show. The reason we used the current design was that cues to detect deception could differ from person to person, and what spotted one liar was usually different from the signals that revealed the next liar Levine, . Consequhttps://en.wikipedia.org/wiki/The_Moment_of_Truth_(American_game_show) for details). During the game show, most of the people talked emotionally and showed natural emotional facial expressions because of the high-stake situations they were in. The ground truth was obtained by a pre-show polygraph test that determined whether an individual was lying or not in the game show. Meanwhile, the stakes in the game show can be high . If the contestant gave the same answer to a question as they did in the polygraph exam (which means they were telling the truth), they moved on to the next question; lying (as determined by the polygraph) or refusing to answer a question ends the game . In total, there were 50,097 frames for truth-telling video clips and 3,689 frames for lying video clips. The median of frames is 199 for lying video clips and is 2,872.5 for truth-telling video clips, with a frame rate of 30 f/s.Participants were eight males and eight females who ended the game with lying. That way, there was at least one lying video clip for each participant. The video clips consist of the moments when the individuals were answering the questions, that is, from the end of the questioning to the end of the answering. To simplify calculation, we merged all the truth-telling video clips for each participant into a single one, and we ended up having one video for each type, truth-telling and lying, for each person. The duration of the video clips ranges from 3 s to 280 s, with an average duration of 56.6 s. Because of the game show setting that lying ends the game, the truth-telling video clips were much longer than the lying ones . Because the frame rates of all the videos were the same, the number of frames could represent the duration of AU. Then the precise duration was obtained by dividing the total number of frames by frame rate, i.e., 30.Beh and Goh  proposedAll of the aforementioned steps of classifying the truth or deception in the video clips are demonstrated in https://imotions.com/blog/facial-action-coding-system/). All the three classifiers, Random Forest, K-nearest neighbors (IBK), and Bagging, were trained in WEKA via a 10-fold cross-validation procedure. In building the model, the 10-fold cross-validation procedure split all the data from the 12 participants into 10 subsets, and the algorithms were trained on 9 subsets and tested on the remaining 10th each time, repeating 10 times. When a classifier was deployed from 10-fold cross-validation, it was applied to the other four participants' data to calculate the accuracy of prediction. To highlight the relative importance of AUs of fear in classification accuracy, we eliminated all other indicators used by Beh and Goh  were used for training the model; and the data collected from the remaining four participants  were used to test how accurate were the model to make new predictions. Three classifiers were trained on a dataset of 12 participants to discriminate liars from truth-tellers using feature vectors of AUs of fear .In addition, considering the size of the dataset is relatively small, we did leave-one-person-out cross-validation (LOOCV). LOOCV utilizes each individual person as a “test” set and the remaining dataset as the training set. It is recommended for smaller datasets. The Random Forest algorithm was applied. The results showed that the average accuracy is still above 90% . This analysis revealed that liars and truth-teller had differences in the facial expressions of fear.This analysis was carried out by examining the statistical differences of AUs of fear between truth-telling and lying video clips through paired t-test, using bootstrapping with 1,000 iterations. The results showed that there were significant differences in the total duration and duration from peak to offset between truth-telling video clips and lying video clips . The durations of AU20 in lying video clips were nearly four frames (133 ms) shorter than those in truth-telling video clips on average because the facial movements (herein the AU20) disappeared more quickly in the lying condition. Ekman  reportedWe calculated ld1 and rd1, the distance between facial landmarks predicted at the left eyebrow and left eye and the distance between those predicted at the right eyebrow and right eye  to compare the asymmetry differences between the lying and truth-telling situation. Permutation tests provide elegant ways to control for the overall Type I error and are distribution-free. The results showed that lying and truth-telling situations caused different coherence in facial expressions .The coherence outputs for each player  were then imported into the permutation test . The results also substantiated the other two hypotheses. The duration of AUs of fear in lying was shorter than that in truth-telling, with a shorter total duration and the duration from peak to offset of AU20 of fear when lying compared to telling truth. The third hypothesis predicted that the symmetry of facial movements would be different, and the findings indicated that the facial movements were more asymmetrical in lying situations than in truth-telling situations.In the current study, the use of machine learning classified deception and honesty. It made up the shortcomings of human coding and successfully detected the subtle differences between lying and truth-telling. Meanwhile, an objective measure of asymmetry was proposed. To our best knowledge, this is the first objective method to measure the asymmetry of facial movements. By using these methods, we were able to find differences between lying and truth-telling, which is the prerequisite for looking for clues of deception.The machine learning approach could have some disadvantages. For example, the LOOCV is recommended for small datasets, like what we have in the current study. However, it yielded a higher variance than 10-fold cross-validation. The reason for this high variance might be that the training datasets in LOOCV have more overlap , which made the outputs from different folds highly positively correlated with each other, and hence increases the overall variance  while telling truth and were from 10.32 to 20.11 frames (344 ms ~ 670 ms) while lying. In the current study, the mean was affected by extreme values or outliers see . Thus, wTaken together, our findings suggested that deception is detectable by using emotional facial expressions of fear in high-stake situations. Lying in high-stake situations will leak facial expressions of fear. The durations of fear were significantly different between lying and truth-telling conditions. Besides, the facial movements are more asymmetrical when one is lying than they are when one is telling the truth.Our findings prompted that attending to the dynamic features of fear (such as symmetry and duration) can improve the ability of the people to differentiate liars from truth-teller. Besides, the machine learning approach can be employed to detect real-world deceptive behaviors, especially those high-stake ones in the situations where strong emotions are generated, associated with attempts to neutralize, mask, and fake such emotions .The original contributions presented in the study are included in the article, the dataset used in the current study can be obtained on request from the first author  of Jiangxi University of Traditional Chinese Medicine. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.XS conceived the study, conducted the experiments, analyzed the data, wrote the paper, and acquired the funding. GF analyzed the data and revised the manuscript. ZC analyzed the data. CN contributed the materials used in the current study. All authors contributed to the article and approved the submitted version.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.


Long non-coding RNAs (lncRNAs) are a novel class of regulatory RNA molecules and they are involved in many biological processes and disease developments. Several unique features of lncRNAs have been identified, such as tissue-and/or cell-specific expression pattern, which suggest that they could be potential candidates for therapeutic and diagnostic applications. More recently, the scope of lncRNA studies has been extended to endothelial biology research. Many of lncRNAs were found to be critically involved in the regulation of endothelial function and its associated disease progression. An improved understanding of endothelial biology can thus facilitate the discovery of novel biomarkers and therapeutic targets for endothelial dysfunction-associated diseases, such as abnormal angiogenesis, hypertension, diabetes, and atherosclerosis. Nevertheless, the underlying mechanism of lncRNA remains undefined in previous published studies. Therefore, in this review, we aimed to discuss the current methodologies for discovering and investigating the functions of lncRNAs and, in particular, to address the functions of selected lncRNAs in endothelial dysfunction-associated diseases. Finally, an advanced subtype of RAP-RNA has been developed by using multiple cross-linkers FA and disuccinimidyl glutarate (FA-DSC) which known as RAP-RNA[FA-DSG]. It provides a stronger cross-link and it can detect RNA-RNA interactions, even though multiplex protein complexes bound the RNAs [RAP-RNA is an improved version of RAP technique that can be used to identify RNA-RNA interactions by utilizing different cross-linking methods. There are three versions of the RAP-RNA method available: RAP-RNAractions . For exass-links . Insteadthe RNAs .CLASH is an alternative method for mapping RNA-RNA interaction by using UV cross-linking ,160. ThiRIP is the most widely used method to investigate lncRNA-protein interaction in both in vitro and in vivo ,164. In In HITS-CLIP method, UV-mediated crosslinking forms a covalent bond between RNA and amino acids (AAs) ,169,170.PAR-CLIP is a modified technique from HITS-CLIP with improved crosslinking efficiency and single nucleotide resolution capacity ,172. PARlncRNAs have been identified as the key regulators in many biological and pathological processes over the past decades, including impaired endothelial function. A general perspective of the diverse regulatory mechanisms of lncRNAs has been described previously. In this chapter, we closely focus on the functional involvements of lncRNAs in ED-associated diseases, such as abnormal angiogenesis, diabetes, hypertension, and atherosclerosis . It shouAngiogenesis is defined as the process of new blood vessel formation from a pre-existing vascular network. The complex process of angiogenesis is predominantly controlled by the precise balance of different stimulating and inhibitory factors, such as VEGFs and their receptors . The dysOver the past couple of decades, extensive researches had utilized the regulatory process of angiogenesis to establish promising therapeutic strategies in complex disease management. For example, strategies for inhibiting angiogenesis were beneficial for cancer, haemangioma, and corneal neovascularization treatment . On the One of the most common intergenic lncRNAs, named as TUG1, is present on chromosome 22q12.2 and is 7.1 kb in length. It regulates angiogenesis and it can be found in different types of cancers, including glioblastoma and hepatoblastoma progression ,71,194. Among the angiogenesis promoting lncRNAs, there is one lncRNA, named MEG3, 1.6 kb in length and is present in chromosome 14q32.3 , which wDiabetes mellitus (DM) is a chronic disorder and it is ranked as the ninth leading cause of the death globally . There iOne of the most common intergenic lncRNAs, named MALAT1, which is located on chromosome 11q13.1 and 7 kb in size, has been functionally identified and characterized in ED-associated diabetes . In thatL. barbarum, carries anti-hypertensive effect in both in vitro and in vivo by reducing the blood pressure through up-regulating the expression level of eNOS via suppressing lncRNA sONE, [Hypertension is one of the most important risk factors for CVDs. Studies revealed that vascular endothelium nicotinamide adenine dinucleotide phosphate (NADPH) oxidase, excessive production of mitochondrial ROS, and decreased NO bioavailability were intercorrelated with the impairment of EC function ,211,212.NA sONE, . SimilarNA sONE, .Atherosclerosis is a large arteries disorder that is considered to be one of the major causes of CVD . It is gAn intergenic lncRNA, RNCR3, was found to be significantly up-regulated in both human and mouse aorta atherosclerotic lesion and it accelerates atheroprotective function to the endothelium . In miceIt is recommended to target the aim of lncRNA study at disease specific or cell specific, rather than performing a gross study to discover the biomarkers for CVD due to the complexity of CVS pathophysiology, the interference of IncRNA in gene expression and signal pathways at various stages. Examples of disease specific lncRNAs include MIAT for acute myocardial infarction (AMI)  and myosWe also observed that some identified lncRNAs might be playing critical roles in regulating the development and progression of various ED-associated diseases, and therefore possibly to translate into novel biomarkers and therapeutic targets in ED-associated disease treatments. There is a growing body evidence that suggests that ED is functionally associated with various pathophysiological conditions, including abnormal angiogenesis, hypertension, diabetes, and atherosclerosis, which in turns leads to the increased cardiovascular disease-related deaths. Several lncRNAs were correlated in the regulation of endothelial function and its associated diseases progression. However, the underlying functional mechanisms in the majority of these identified lncRNAs are still not clear. Nevertheless, with the discovery of new advanced technologies mentioned earlier, a massive development was underway in lncRNA biology studies and emerging topics, such as largescale discovery of lncRNAs using genome-wide sequencing methods, the identification of lncRNAs subcellular localization, and the potential interactions of lncRNAs with DNA, RNA, and protein. These will help us to better understand about lncRNAs functions in different biological processes, including endothelial dysfunction and its associated disorders.


In vivo characterization of RNA-protein interactions is the key for understanding RNA regulatory mechanisms. Herein, we describe a protocol for detection of proteins interacting with polyadenylated RNAs in the yeast Saccharomyces cerevisiae. Proteins are crosslinked to nucleic acids in vivo by ultraviolet (UV) irradiation of cells, and poly(A)-containing RNAs with bound proteins are isolated from cell lysates using oligo[dT]25 beads. RBPs can be detected by immunoblot analysis or with mass spectrometry to define the mRNA-binding proteome (mRBPome) and its changes under stress.For complete details on the use and execution of this protocol, please refer to   •in vivoDetection of proteins that interact with polyadenylated RNAs •UV irradiation of cells to crosslink RNA-protein interactions•Polyadenylated RNAs are captured with oligo[dT] beads from yeast cell lysate•Suitable for monitoring dynamic changes of the mRNA-binding proteome In vivo characterization of RNA-protein interactions is the key for understanding RNA regulatory mechanisms. Herein, we describe a protocol for detection of proteins interacting with polyadenylated RNAs in the yeast Saccharomyces cerevisiae. Proteins are crosslinked to nucleic acids in vivo by ultraviolet (UV) irradiation of cells, and poly(A)-containing RNAs with bound proteins are isolated from cell lysates using oligo[dT]25 beads. RBPs can be detected by immunoblot analysis or with mass spectrometry to define the mRNA-binding proteome (mRBPome) and its changes under stress. The protocol has also been applied to cells treated with 0.5 mM hydrogen peroxide (He stress .The procedure is based on the capture of poly(A) RNA, a major component of it comprising mRNAs. Hence, the protocol presented here is preferred for investigation of mRNA regulation executed by mRNA binding proteins (mRBPs) that mediate the processing of mRNA precursors (pre-mRNAs) in the nucleus, the export and localization of mRNAs to different subcellular locations in the cytoplasm, and the translation and eventual decay of mRNAs . We wishTM or likewise RNase decontamination solutions.Yeast lysates contain a substantial amount of enzymatic activities . Cell lysates and samples should therefore be kept on ice, which substantially reduces enzymatic activity. It is also necessary to add RNase and protease inhibitors to buffers/samples immediately before use according to the suggestions given in the protocol. Furthermore, we recommend using sterile filter tips and RNase-free tubes with low RNA/protein binding capacities. Gloves must be worn, and the protocol should be performed in an RNase-free workspace, which can be accomplished by cleaning surfaces with RNase ZAPTiming: 2–3 daysSaccharomyces cerevisiae (S. cerevisiae) cells. In our case, we used autoclaved YPD media, a rich media supplemented with glucose as the carbon source  from the glycerol stock and streak cells on a YPD agar plate with a sterile inoculation loop.Remove approximately 10–20 μL Note: Keep the glycerol stock on ice to prevent rapid defrosting. Put the stock vial back to the −80°C freezer immediately after use.Note: We used the BY4741 strain, but the protocol is also applicable to other S. cerevisiae strains.3.Incubate the plate upside-down in a 30°C incubator in the dark until individual colonies have approximately 0.2–0.3 cm diameter .Note: The plate can be stored at 4°C for up to 3 months.Before starting the protocol, sterile media needs to be prepared for the growth of yeast n source . The desNote: Distilled (d) water (H2O) was used to prepare yeast media.Note: Yeast media must be autoclaved before use for 20 minutes at 121°C.Note: Media and dextrose stock solutions can be stored for up to one year at room temperature (22°C–25°C).Note: Pour the plates in a fume hood or in the vicinity of a Bunsen burner flame. The flame can also be used to remove air-bubbles from the surface.Note: Double-distilled (dd) RNase-free water (H2O) was used through the procedure.Note: Buffers are preferentially prepared freshly from sterile stock solutions and filtered (0.22 μm).Note: Wash buffer A can be supplemented with 10 U/mL of RNasin if RNA degradation is of concern  competition used in this protocol are introduced in the next step of the protocol.1.Pick 1 yeast colony from the YPD agar plate with a sterile loop and inoculate 20 mL YPD media placed in a sterile 100 mL Erlenmeyer flask. Place the flask in a shaker and grow cells overnight (12–14 h) at 30°C with constant shaking at 220 rounds per minute (r.p.m.).Note: To ensure good aeration of cells, we recommend using at least 1:5 ratio of culture volume to Erlenmeyer flask volume .2.600 ∼0.1, and grow at 30°C at 220 r.p.m to OD600 ∼0.6. This takes about 3 h 30 min (doubling time of cells ∼90 min).a.Set the spectrophotometer at 600 nm wavelength.b.Set up a blank cuvette by placing 1 mL YPD in a disposable plastic cuvette.c.Place the blank cuvette in the spectrophotometer and take the blank measurement (absorbance (A) = 0.00).d.Make a 1:10 dilution of the 20 mL pre-culture and measure the absorbance.e.600 ∼0.1.Calculate the volume of pre-culture required to inoculate 500 mL YPD with a starting ODf.Remove appropriate volume of pre-culture with a pipette and transfer cells to the 500 mL YPD in a sterile 3 L Erlenmeyer flask.g.600 every 2 h until the OD600 reaches ∼0.4. At this point, cells have passed the lag-phase and reach mid-log phase, so it is advisable to start the measures every 30 min.Place the culture in a shaker and grow cells at 30°C at 220 r.p.m. Measure the ODRefresh culture in 500 mL YPD placed in a sterile 3 L Erlenmeyer flask, setting ODNote: Cells can also be subjected to stress treatments to eventually monitor changes in RNA-protein associations as compared to untreated cells. For instance, we treated yeast cells at mid-log phase (i.e. OD600 ∼0.6) with 0.5 mM hydrogen peroxide (H2O2) for 15 min to induce a mild oxidative stress response .Harvest cells in 500 mL centrifuge tubes at ODb.Wash cells three times at room temperature with 25 mL phosphate-buffered-saline (PBS). Collect cells in between by centrifugation as indicated in the previous step.c.Resuspend cells in 15 mL 1× PBS.d.Spread the cell-suspension in a 15 cm petri dish.e.2 of 254 nm UV-light with two 2-min breaks and gentle mixing between each exposure.Place the dish on ice in the UV-crosslinker. Expose cells to 3 × 400 mJ/cmf.g for 3 min at 4°C.Harvest cells by centrifugation at 3,000 × Irradiate cells with UV light at 254 nm to crosslink RNA-protein interactions.4.Snap freeze pellets in liquid nitrogen.Pause point: Cell pellets can be stored at −80°C for up to two months.CRITICAL: It is important that cells are evenly spread in the dish, making a thin layer of cells for exposure to UV-light.In this step, the cells are UV-irradiated to crosslink RNA-protein interactions Timing: 1 h 30 min5.Resuspend cells in 4 mL lysis buffer by pipetting up and down on ice and split cells in 4 × 2 mL safe-lock microcentrifuge tubes.6.Add 2/3 vol. glass beads to each tube.7.Place the tubes balanced in a TissueLyser adapter and break cells at 30 Hz for 10 min at 4°C.Note: The TissueLyser is preferentially placed in the cold room to maintain samples at 4°C whilst lysis. Tubes must be balanced within the TissueLyser adapter set to avoid motor failures.8.g for 3 min, and 5,000 × g and 10,000 × g for 5 min each at 4°C. Carefully remove the supernatant with a filter tip and transfer to a fresh microcentrifuge tube after each centrifugation, avoiding any pellet contamination.Clear lysate by three sequential centrifugations at 3,000 × Note: Repeated centrifugation at progressively higher-speed removes non-lysed whole cells , cell debris  and nuclei and cytoskeletons .9.After the last centrifugation, combine all supernatants in a 15 mL Corning centrifuge tube.10.manufacturer’s guidelines.Quantify protein concentration of the final extract with a Bradford assay taking bovine serum albumin (BSA) as a reference standard following the Note: Typically, we obtained a concentration of ∼3.5 mg/mL protein.11.manufacturer’s guidelines. Ensure that the final volume does not go below 1.2 mL. Prepare 500 μL aliquots containing ∼5 mg of protein lysate (∼10 mg/mL) in Eppendorf Protein LoBind microcentrifuge tubes.Concentrate protein sample up to 10 mg/mL with an Amicon® Ultra-4 Centrifugal Filter Unit 10 kDa, following the Note: Make sure the membrane of the Centrifugal Unit is not getting damaged with the pipette tip. Quantify protein amount after concentration as explained in step 10 and ensure that proteins have not aberrantly leaked through a damaged membrane.12.Keep 75 μL of the extract as reference. 50 μL will be used to assess the RNA quality and the remaining can be used for protein analysis (see below).Pause point: Lysates can be kept on ice and immediately used for later steps in the protocol, or snap frozen in liquid nitrogen and stored at −80°C for up to one month.Cell lysates are prepared by mechanical disruption of cells with glass beads in a TissueLyser.Control step: Analysis of RNA integrity before proceeding with poly(A) RIC.13.a.manufacturer’s guidelines.Isolate total RNA from 50 μL of extract (=input) with the ZR RNA MiniPrep kit, following b.Quantify RNA with a Nanodrop ND-2000 device.c.Visualize 1 μg RNA on a 1% agarose gel stained with peqGREEN RNA/DNA dye.RNA quality control.Note: Typically, we obtained 30 μg of total RNA from 50 μL extract.CRITICAL: We highly recommend checking RNA integrity after UV-irradiation by comparing the pattern with a non-crosslinked sample. Ribosomal RNA (rRNA) bands should be clearly visible before proceeding with the poly(A) RNA isolation  RNA will mainly recover mRNA binding proteins, allowing for analysis of the cellular mRBPome. Stringent washing conditions are used to avoid isolation of unspecific binders.Note: As negative control for this protocol, we recommend the addition of an excess of polyadenylic acids (poly(A)) to the sample as a competitor. As an alternative, RNA is digested in the extract with an RNase. Optionally, a non-crosslinked sample has been used in a related protocol .15.Control sample with poly(A) competitor: Add 20 μL of poly(A) (10 mg/mL) to 500 μL extract, briefly vortex sample and place on ice.Note: Optionally, an RNase digested control sample is prepared. Therefore, add 100 U RNase ONE to 500 μL of extract (∼ 5 mg protein lysate), briefly vortex and incubate for 2 h at 37°C.16.25 Dynabeads in lysis buffer. Add 500 μL lysis buffer to the beads and vortex. Place tubes on the Dyna-Mag-2 magnet for at least 30 s and remove supernatant with a tip. Repeat three times and finally resuspend beads in 500 μL lysis buffer until use.Equilibrate one milligram of oligo[dT]17.25 Dynabeads by placing the tubes on the Dyna-Mag-2 magnet. Add 500 μL of the extract and incubate the tubes on a shaker/rotating wheel for 10 min at room temperature.Remove lysis buffer from the pre-equilibrated oligo[dT]Note: We recommend using Eppendorf Protein LoBind microcentrifuge tubes for the poly(A) RIC protocol.18.Retrieve the beads by placing the tubes in a Dyna-Mag-2 Magnet for at least 30 s and carefully remove the supernatant and transfer to a fresh low-bind tube.19.Wash beads once with wash buffer A. Add 500 μL of pre-cooled wash buffer A on ice and gentle vortex for 10 s at room temperature.20.Wash beads twice with wash buffer B. Add 500 μL of pre-cooled wash buffer B on ice and gentle vortex for 10 s at room temperature.Note: Repeated washing is required to remove unspecific binders from RNA, the beads and the tube wall. Wash buffer B also removes traces of Triton X-100, which may interfere with absorbance measurements and compromise elution efficiency (see step 25 below). Ensure complete removal of wash buffer at each step. We also recommend changing the tubes at least once during the procedure .21.Elute poly(A) RNA from beads. Add 60 μL of pre-heated elution buffer to the beads and incubate in a Thermoblock for 2 min at 80°C. Place tubes in a Dyna-Mag-2 Magnet and quickly transfer the eluate to a fresh tube.Note: Incubation at 80°C denatures the hybrid between poly(A) RNA and oligo[dT]25 beads, thereby releasing the poly(A) RNA into the solution (=eluate). Therefore, the eluate must be collected as quickly as possible to prevent re-association of eluted poly(A) RNA on beads. Elution from beads at 80°C follows the manufacturer’s suggestions. Other bead suppliers may use different temperatures.Note: An alternative for the elution is to release proteins via RNase digestion .Combine the three sequential eluates (∼180 μL) and concentrate to ∼70 μL in a 0.5 mL Microcon-10 kD Centrifugal Filter Unit with Ultracel-10 membrane in a microfuge  RNA with a Nanodrop ND-2000 device.Note: We usually obtained ∼55 ng/ μL of poly(A) RNA. The 260/280 nm ratio should be at least 1.8:1. Lower ratios and an absorbance peak at 230 nm may relate to residual contamination from Triton X-100 in the eluate (see uate see .This step describes the recovery of poly(A) RNA and interacting proteins with oligo[dT]Control step: Successful poly(A) RNA/ mRNA isolation can be assessed with RT-PCR.26.a.18 and random hexamer primers for RT with the Transcriptor High Fidelity cDNA Synthesis Kit (Roche) following the manufacturer’s guidelines.500 ng of input total RNA (Step 13.a) or 500 ng of eluted RNA (∼ 9.5 μL) are combined with a mixture of oligo[dT]b.PCR is conducted with 1 μL of complementary DNA (cDNA) with the following conditions:c.PCR products are visualized on a 1.5% agarose gel stained with peqGREEN RNA/DNA dye.Detection of mRNAs in poly(A) eluates by reverse-transcription (RT) PCR A.a.500 nNote: Poly(A) RNAs captured from negative control samples, either through poly(A) competition or RNase digestion should be included in the analysis to ensure that no mRNA is amplified in these samples -binding protein 1 (Pab1), which is known to be involved in regulating mRNAs fate and stability  and at least 10% of the eluates on a 4–15% Mini-PROTEAN® TGX™ Precast SDS-PAA gel.b.Run the PAA-gel at 120 V for 90 min in the appropriated electrophoresis chamber. Regularly check the progress of the sample migration.c.manufacturer’s guidelines.Stain gel with ProteoSilver™ Plus Silver Stain Kit, following the Analyze the protein complexity with a silver-stained PAA gel B.a.ResolNote: One lane of the gel should contain a protein ladder as a molecular weight marker . We recommend loading up to 3 μL of a 1:10 dilution of the protein ladder to avoid an overstaining.28.a.Resolve 0.1% of the input and at least 10% of the eluate on a 4%–15% Mini-PROTEAN® TGX™ Precast SDS-PAA Protein Gels.b.Run the gel for 90 min at 120 V.c.Cut a gel-sized polyvinylidene difluoride (PVDF) membrane and activate it with 100% methanol for 2 min.d.Soak the gel, filter papers, and PVDF membranes in the appropriate transfer buffer for 2 min at room temperature.e.Note: Voltage and length of transfer may vary depending on the molecular weight of the protein of interest. Proteins with high molecular weight (>200 kDa) need longer transfer time.Note: We recommend checking for transfer of proteins by staining the membrane with Ponceau-S solution according to manufacturer’s instructions. We also recommend loading a pre-stained protein marker .Transfer proteins from the PAA gel to PVDF membranes with a Trans-Blot® Turbo™ Transfer System .f.Block membrane in 1× PBS-0.1% Tween-20 (PTST) containing 5% low fat milk for 1 h at room temperature.g.Probe membrane with respective primary antibodies , anti-Pgk1 , anti-actin , PAP reagent ) diluted in PTST containing 2% low fat milk, for 1 h at room temperature with constant shaking.h.Wash the membrane 3 times in PBST for 10 min each at room temperature with constant shaking.i.Add the corresponding horseradish peroxidase (HRP)-coupled secondary antibodies  diluted in PTST containing 2% low fat milk for 1 h at room temperature with constant shaking.j.Wash the membrane 3 times in PBST for 10 min each at room temperature with constant shaking.k.manufacturer’s guidelines.Develop membrane with the Immobilon Western Chemiluminescent HRP Substrate, following the l.Take a picture of the chemiluminescent signals with standard gel imaging system.Identify specific proteins with immunoblots C.a.ResolNote: Immunoblotting has been described in detail  RNAs are electrophoresed on SDS-polyacrylamide (PAA) gels and stained with silver B; and spThe herein described processing of 500 mL yeast cells yields ∼12 mg of protein in the extract and ∼7.5 μg in poly(A) RIC eluates. Thus, about 0.06% of protein from the total protein extracts is usually recovered with this RIC protocol. The amount of captured proteins is sufficient to proceed with label- free mass spectrometry (MS) analysis, allowing for identification of the yeast mRBPome under different stress conditions , 2021. OACT1 mRNA, in the RIC eluates directly by RT-PCR (A successful poly(A) RIC enables the monitoring of particular mRNAs, such as y RT-PCR A, addingy RT-PCR A. In addy RT-PCR B. Of noty RT-PCR . Well kny RT-PCR . Conversy RT-PCR C.Saccharomyces cerevisiae  and shows some preference for uridine-rich single-stranded RNA regions, possibly adding a bias towards single-stranded RNA-binding proteins. In addition, we wish to note that UV-irradiation can also induce protein-protein and protein-DNA crosslinks - albeit at lower efficiency – but may lead to false positives through indirect interactors (This protocol is based on capturing poly(A) RNAs from cells, a major component of it comprising mRNAs. Hence, it is less suitable for identification of RBPs that preferentially interact with other RNA species that lack a poly(A) tail, such as rRNAs and tRNAs. Furthermore, the protocol is based on UV-irradiation of cells to crosslink RNA protein interactions eractors . Other teractors  or the feractors  may consRNA degradationTo avoid RNA degradation during UV-irradiation and lysate preparation, it is very important to keep cells on ice (step 3e). UV-light can directly damage RNA and a careful check of the settings and prior testing of the UV-crosslinker is recommended. Since the suspension absorbs the energy from UV-light and warms-up, we recommend keeping cells on ice for 2 min between three UV exposures (400 mJ each) B. After UV-spectra of eluted RNA with a 260/280 nm ratio of less than 1.8 alongside peak absorbance at 230 nm (step 25).g) and careful removal of residual wash buffer B (step 20) with a pipette.The eluate may still contain some detergents supplied in lysis and wash buffer A (Triton X-100 absorbs in the range of 230 nm and at 280 nm). This can be solved by a quick spin of tubes in a microfuge .Detection of proteins in the eluate of neThe detection of non-specific RNA-protein interaction in poly(A) competitor or in non-crosslinked samples (data not shown) is due to non-specific protein-protein interactions or non-covalent binding of protein to the RNA. This has been solved by increasing the stringency of the washes during the poly(A) RNA pull down through addition of 0.2% lithium dodecyl sulfate (LiDS) to wash buffer A (step 19).Absence of signal for a determined protein in the eluate fraction monitored by immunoblots (step 27).25 beads) and wash fractions to follow the protein under consideration during the entire procedure.The detection of proteins in the poly(A) RNA eluate with immunoblots depends on a variety of instances, ranging from biological factors like protein and mRNA target levels and their affinities to technical variables, such as transfer of protein to membrane and quality of antibodies. Therefore, resolving 10% of the RIC eluate may not be sufficient for reliable detection and requires loading of a higher fraction of the eluate (up to 40%). To monitor the success of the experiment we recommend using a positive control such as Pab1 - a highly expressed protein binding to the poly(A) tail of mRNAs. However, in many cases no suitable antibodies for detection of a specific protein may be available. In that case, strains bearing TAP/GFP-tagged proteins can be used, allowing detection of tagged-proteins with highly sensitive commercially available reagents .Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, André P. Gerber (This study did not generate new unique reagents.


Site-specific fluorescent labeling of RNA is crucial for obtaining the structural and dynamic information of RNAs by fluorescence techniques. Post-synthetic modification of RNA based on N-hydroxysuccinimide (NHS) coupling reaction is an economic, efficient and simple strategy to introduce fluorophore to samples. However, this strategy are not that frequently used in RNA molecules, and the reported reaction conditions and yields varied among different systems. This study results mainly focused on screening the reaction conditions  between NHS-linked fluorophore and aminoallyl-RNA (aa-RNA) to optimize the yield of fluorescent RNA up to 55%, doubled the initial yield. What’s more, as low as one tenth of fluorescent reagent was used in our protocol compared with the reported protocols, greatly reducing the experimental cost. The protocol can be applied as a general guide potentially for RNA labeling by NHS-ester coupling reaction.  Post-3) or phosphate buffer has been optional in fluorescent labeling of aminoallyl-labeled RNAs [Here, 71nt adenine riboswitches aptamer domain (rbA71) was used as a model RNA to optimize the NHS ester coupling reaction for fluorescent labeling of RNAs. rbA71 located at the 5ʹ untranslated region of mRNA, regulates the downstream gene expression by binding with adenine –20. The led RNAs ,7.FigureStudies on protein or peptides labeling indicated that the NHS ester coupling reaction has been influenced by buffer pH greatly, while the buffer pH for RNA conjugation with NHS-reagent narrows in 7.0–9.0 –17,22–262.2.1.3 mL PLOR reaction, containing initiation stage, three elongation cycles, and termination stage was used to incorporate 5-Aminoallyl-UTP  into Site 22 of rbA71. The detailed procedure and reagent usage were performed as the following: In the initiation stage, 5 µM T7 RNA Polymerase (T7 RNAP), 5 µM solid-phase bead-DNA template, 0.48 mM ATP, 0.48 mM GTP and 48 µM UTP were incubated in the initiation buffer  at 37°C for 15 min to initiate synthesis. The transcription in the initiation was paused due to CTP missing with the production of a 13nt (nucleotides) transcript  10 µM CTP  and 10 µM UTP  were added to the reactor and the incubated for 10 min at 25°C, pausing again due to lack of GTP  and lengthening 6 nt  buffer  and 5 µl of DMSO was added. After addition of bicarbonate buffer, the aa-RNA was mixed with NHS-TF3. Repeated pipetting incubated reaction solution for 1.5 h at room temperature in the dark.1 mg of NHS-TF3  was dissolved in 40 µl of DMSO  and divided into aliquots of 2 µl. To 2 µg of aa-modified RNA in 3.33 µl of DEPC-treated water, 1.66 µl of NaHCO2.2.2.Take optimization of reactants concentration for example: dissolved the lyophilized aa-RNA (0.3 nmol) in diethylpyrocarbonate-treated  water (DEPC-treated water), mixed with 5.0 µl of DMSO and 1.0 µl of sodium bicarbonate buffer . The resulting solution was treated with 0.6 µl of 5 mM NHS-TF3, 0.5 µl, 1 µl of 30 mM NHS-TF3, 0.4 µl, 1 µl of 150 mM NHS-TF3 dissolved in DMSO respectively, additional DEPC-treated water was added to take the total reaction volume to 10 µl. Vortex, following incubation at 28°C in the dark for 4 h. Then kept NHS-TF3 at 15 mM (added to 1 µl of 150 mM NHS-TF3 dissolved in DMSO), aa-RNA concentrations were increased to 0.1 and 0.3 mM . As for optimization of DMSO, solution conditions and reaction times, concentration of aa-RNA and NHS-TF3 was kept at 30 µM and 1.5 mM. For 10 µl of reaction volume, 10% (vol/vol) is 1 µl and so on. In each optimization experiment, another reaction conditions and the detail procedure were same as the protocol described in optimization of reactants concentration while change the reaction condition needing optimized.2.2.3.One vial of mono-reactive dyes (1 mg) was dissolved in 10 µl of DMSO and divided into aliquots of 1 µl. To 3 nmol of aa-modified RNA dissolved in DEPC-treated water, 5.5 µl of DMSO and 1.0 µl of 300 mM sodium bicarbonate buffer with pH 7.0 was added. The resulting solution mixed with 1 µl of NHS-TF3 (150 mM) dissolved in DMSO. Additional DEPC-treated water was added to take the total reaction volume to 10 µl. Vortexed well, the following incubation at 28°C in the dark for 30 min.2.3.The yields of reaction conditions optimizations were detected by denaturing (10 M Urea) polyacrylamide gels . Samples were diluted in 3 volume of loading buffer  prior to gel loading. 1.5 mm gels were generally run at 200 V. Fluorescent labels were directly visualized on a scanner . The refined and original reaction efficiency was determined by High-Performance Liquid Chromatography (HPLC)  at absorption spectrum of 260 nm. Run the sample on the following HPLC program: 10 min at 10% buffer B (90% buffer A) and then ramp from 10 to 50% buffer B over 50 min, ramp from 50 to 80% over 70 min (flow rates are 0.5 ml/min).3.3.1.According to the mechanism of PLOR , 6 step 3.2.In my hand, the labeling efficiency of TF3 to U22-aa-rbA71 is about 26.0%  followin3  and 1×, 3× PBS buffer (pH 7.4) were screened for the fluorescent strategy (3 buffer (0.3 M) than PBS buffer. No obvious changes in yields were observed from 10 to 25% NaHCO3, however, about 50% less labeled sample was obtained at 40% NaHCO3 , the labeling efficiency was obviously improved , howeverstrategy . Higher % NaHCO3 . In addiabeling. . To optiabeling. . To avoi4.3 buffer  for 0.5 h at 28°C in the dark, the degree of fluorescent labeling is 55%, which is two times higher than the reported protocols [With stronger research interest in structural and dynamics of RNAs, fluorescent RNAs are in great request. However, preparation of fluorescent-labeled samples was inhibited to some extent by high cost of fluorescent reagents or complicated experimental procedures. Coupling between NHS ester and aminoallyl offers a convenient way to introduce fluorophores to RNAs as multiple fluorophore-NHS and aminoallyl-NTP are commercial. We optimized the labeling efficiency of the labeling strategy by screening various conditions. Based on my results: when 0.3 mM aa-RNA mixed with 15 mM NHS-TF3 (RNA to dye ratio is 1:50), incubated with 55% (vol/vol) DMSO and 10% (vol/vol) NaHCOrotocols , and therotocols –17,22–263 (300 mM) buffer has been indicated that is more suitable for fluorescent labeling of aa-RNA than PBS buffer, the optimal buffer pH in this study is 7.0–7.5. Thus, 10–25% (vol/vol) NaHCO3 buffer  is recommended as reaction buffer for users. Shortening the reaction time to 0.5 h is another advantage of present conditions. Such short experimental time is favorable for RNAs as most RNAs are fragile for degradation. Although the RNAs tested in this research are limited and the actual relationship between yields and reaction conditions may be much more complicated than exposed in this work, present finding can be applied as a general guide potentially for RNA labeling by NHS-ester coupling reaction to facilitate fluorescent studies.Growing degree of aa-RNA fluorescent labeling observed in higher concentration of aa-RNA at the same RNA to dye ratio. This implies that higher concentration of aa-RNA may more efficiently couple to NHS-ester-linked dye thus decrease the ratio of RNA to fluorophores. However, restricting by experimental cost, the concentrations of aa-RNA was just increased to 0.3 mM, higher concentration of aa-RNA are suggested for users in future studies, which may further enhance the reaction efficiency and reduce the cost. Unlike most of protocols for DNA or protein labeling ,27,28, t5.In conclusion, the results indicated the effects of various reaction conditions  on fluorescent labeling of RNAs by using NHS and aminoallyl coupling reaction. The labeling efficiency increased 2 times by using optimized conditions with the use less fluorophore-labeled NHS compared with the reported protocol. Briefly speaking, present protocol reached higher efficiency with less cost and time.


Cryopreservation of whole blood is useful for DNA collection, and clinical and basic research. Blood samples in ethylenediaminetetraacetic acid disodium salt (EDTA) tubes stored at − 80 °C are suitable for DNA extraction, but not for high-quality RNA extraction. Herein, a new methodology for high-quality RNA extraction from human blood samples is described. Quickly thawing frozen whole blood on aluminum blocks at room temperature could minimize RNA degradation, and improve RNA yield and quality compared with thawing the samples in a 37 °C water bath. Furthermore, the use of the NucleoSpin RNA kit increased RNA yield by fivefold compared with the PAXgene Blood RNA Kit. Thawing blood samples on aluminum blocks significantly increased the DNA yield by ~ 20% compared with thawing in a 37 °C water bath or on ice. Moreover, by thawing on aluminum blocks and using the NucleoSpin RNA and QIAamp DNA Blood kits, the extraction of RNA and DNA of sufficient quality and quantity was achieved from frozen EDTA whole blood samples that were stored for up to 8.5 years. Thus, extracting RNA from frozen whole blood in EDTA tubes after long-term storage is feasible. These findings may help advance gene expression analysis, as well as biomarker research for various diseases. Blood samples are frequently collected and cryopreserved for clinical and basic research in many facilities, including our laboratory2, because the collection procedure is simple and relatively noninvasive. For example, research on blood biomarkers has been vigorously conducted for various diseases, including psychiatric disorders and cancers. Particularly, in psychiatric disorders, blood analysis is an important assessment tool as the central nervous system is difficult to evaluate3. Furthermore, it has been suggested that gene expression and DNA methylation patterns in the peripheral blood and brain are to some extent correlated4. In addition, it may be necessary to analyze samples from several different facilities to ensure a large sample size, as RNA and DNA isolation and analysis are more clinically efficient and cost effective when performed on a large number of samples. The extraction of RNA and DNA from the same blood sample enables to study the relationship between the methylation of promoter regions of DNA and mRNA expression. Therefore, it is desirable to establish a highly reproducible method for the coextraction of pure RNA and DNA from blood samples.Cryopreserved blood samples are mainly used for DNA extraction and analysis8 and/or that blood be stored with RNA-stabilizing reagents, such as the PAXgene blood RNA tubes to prevent RNA degradation11. Without these precautions, it is difficult to extract intact RNA from cryopreserved whole blood samples in ethylenediaminetetraacetic acid disodium salt (EDTA) collection tubes. This is because freeze/thaw cycles invariably damage the plasma membrane13, and RNA is degraded by RNases that leak from the ruptured cells and into the plasma. However, RNA-stabilizing reagents are expensive and not always available in general clinics. Moreover, removing leukocytes is a cumbersome procedure that requires specialized equipment, such as a centrifuge and clean bench, which are generally not available in clinics. When thawing frozen samples, the most common method is to thaw them quickly in a water bath at 37 °C16. Several research groups have attempted to extract RNA from blood cryopreserved in EDTA tubes18. However, there are only a few studies comparing the differences in RNA degradation depending on the thawing conditions15, and methods for extracting RNA from frozen blood without pretreatment have not been well established.Although several products for isolating RNA are available, most purification kits are designed for fresh blood samples. If blood is to be cryopreserved for RNA purification, it is recommended that peripheral leukocytes be removed before storage to eliminate RNase activity19; thus, DNA extraction yield has also been reported to be reduced upon freezing and thawing20. When frozen blood samples stored for DNA extraction are donated from different institutions, the amount of DNA extracted might decrease when the blood has already been used for RNA extraction. Increasing the amount of DNA to be extracted without compromising its quality would make it easier for institutions to provide samples.Freezing induces DNA strand breaks in cellsThe primary aim of this study was to establish a methodology for extracting high-quality RNA from human blood samples. We compared RNA quality and yield under the following six conditions: P-Con, fresh blood and the PAXgene kit; P-37, frozen blood thawed using a 37 °C water bath and the PAXgene kit; P-Al, thawed using aluminum blocks and the PAXgene kit; N-37, thawed using a 37 °C water bath and the NucleoSpin kit; N-Al, thawed using aluminum blocks and the NucleoSpin kit; and N-Ice, thawed on ice and the NucleoSpin kit Fig. .Figure 1The secondary focus was to increase the yield of high-quality DNA extraction from frozen blood. We compared DNA yield under the following three thawing conditions using the QIAamp DNA blood kit: Q-37, thawed using a 37 °C water bath; Q-Al, thawed using aluminum blocks; and Q-Ice, thawed on ice Fig. .The thawing method using an aluminum block for the isolation of high-quality DNA and RNA from frozen blood samples may help in the molecular characterization of genetic and transcriptional processes and may be applied to more efficiently explore biomarkers in human diseases.n = 7) using six different protocols after short-term (48–72 h) storage  and at 260 and 230 nm (A260/230), and RNA integrity numbers (RINs) are shown in Table RNA was purified from blood samples    and on an aluminum block at room temperature (protocols P-Al and N-Al), as well as among samples purified using the PAXgene kit (P-37 and P-Al) and the NucleoSpin kit (N-37 and N-Al). The RNA yields were significantly higher in the samples from the N-37 and N-Al groups than in those from the P-37 and P-Al groups (−7) Fig. a. The RI44) Fig. b.Figure p = 0.014), and it was comparable to that from N-Ice samples, thawed on ice (6.23 ± 2.29 μg/mL of blood) (p = 0.26)  using the NucleoSpin kit. The average yield of RNA from the N-Al samples, thawed on an aluminum block (6.69 ± 2.04 μg/mL of blood), was significantly higher than that from the N-37 samples, thawed in a water bath (5.83 ± 2.31 μg/mL of blood)  mRNA was quantified using quantitative real-time polymerase chain reaction (qPCR). The mRNA expression was significantly lower in the P-37 group than in the P-Con (p = 0.001) and P-Al (p = 0.036) groups  was significantly lower in the P-37 group than in the P-Con (p = 8.9 × 10−4), N-37 (p = 0.027), and N-Al (p = 0.033) groups  and Q-Ice  (p = 0.021) groups  was observed between the Q-Al (1.91 ± 0.03) and Q-37 (1.90 ± 0.03) groups, it was not meaningful, as both A260/280 ratios were good. The DNA samples were electrophoresed, but no obvious smears were observed, suggesting that DNA degradation had not progressed  after long-term storage . The yield of RNA (9.07 ± 2.83 μg/mL of blood) was significantly higher than that after short-term storage (6.69 ± 2.04 μg/mL of blood) (p = 0.006), but it is difficult to make a simple comparison because the short-term storage samples were in 5 mL tubes and the long-term storage sample were in 7 mL tubes. The A260/280 and A260/230 ratios were 2.05 ± 0.03 and 1.65 ± 0.19, respectively, and the RIN and 28S/18S rRNA ratio were 5.9 ± 0.8 and 1.2 ± 0.3, respectively  was performed using RNA from long-term storage samples (Participants2) and independent control RNA samples from fresh blood , are used when freezing and storing cells. Specifically, cryoprotectants are considered effective in preventing ice crystal formation in cells during freezing25, bacterial DNA26, and circulating DNA in plasma27. It has been reported that a single freeze–thaw step of blood reduced DNA yield by approximately 25%20. However, it was unclear why thawing with aluminum blocks would increase DNA yield, but we propose the following hypothesis. This research was inspired by the idea of how to cook a good steak. A previous study reported that steaks thawed at 20 °C for 20 min had significantly less thaw drip loss than those thawed at 4 °C for 20 h28. Furthermore, steaks thawed at 20 °C for 20 min had significantly less total moisture loss than those thawed at 39 °C for 11 min or at 4 °C for 20 h28. These findings suggest that moderate quick thawing decreases damage to frozen muscle structure. A similar phenomenon might occur in frozen blood. The decrease in cell damage may have affected the yield of DNA.In addition, our thawing method significantly increased the yield of DNA, which can be used to analyze epigenetics research involving methylationOur methodology may offer various benefits in clinical studies. First, cryopreserved whole blood samples can be used for both RNA and DNA analyses. Second, the RNA purification protocol can be inexpensively modified with no special equipment other than an aluminum block for thawing. The cost of a single aluminum block is less than 1 US dollar, and it can be used for blood collection tubes of any shape and size. Third, the number of storage tubes can be reduced because DNA and RNA can be purified from a single EDTA tube of whole blood. Finally, the viability of other stored cells may be increased by further developing an appropriate thawing method.29. Second, we did not examine materials other than aluminum for thawing. For example, copper and silver are known to have higher thermal conductivity than aluminum and may be more efficient than aluminum for thawing. Third, only some RNA purification products were tested. We preliminarily tried to purify RNA from frozen and thawed EDTA blood using a TRIzol kit; however, the RNA was degraded (data not shown). Indeed, a previous study has reported that the NucleoSpin kit is the most suitable for RNA purification from frozen blood17. Finally, a control using fresh blood and Nucleospin was not set up due to limited samples. Although there were no statistically significant differences, RPS18 tends to be higher in NucleoSpin-purified samples than in PAXgene-purified samples. We checked the size of the GAPDH and RPS18 amplicons, and found a single band of the expected size, with no unspecific amplification  between 2019 and 2020. RNA and DNA were extracted from five individuals; from two individuals, only RNA was extracted and from one individual, only DNA was extracted.Thirty participants were recruited at the Hiroshima University Hospital and collaborating local clinics between 2012 and 2018 for the depression biomarker project .Ten participants were recruited at Tokushima University Hospital .The demographic data of all the participants are shown in Supplementary Table 2 tubes  or PAXgene tubes . RNA isolation from samples filled in PAXgene tubes was performed using the PAXgene Blood RNA Kit  according to the manufacturer’s protocol. The filled EDTA tubes were immediately placed in a − 20 °C freezer and transferred to a − 80 °C deep freezer the next day. RNA was purified after 48–72 h of storage. At the Hiroshima University Hospital and collaborating local clinics, venous blood samples (7 mL from each participant) were collected into EDTA-Na2 tubes and stored in a − 80 °C deep freezer for several years. Detailed conditions until cryopreservation were not recorded. At the Tokushima University Hospital, PAXgene Blood RNA tubes (Qiagen) and PAXgene Blood RNA Kits (Qiagen) were used according to the manufacturer’s recommendations to extract the total RNA from whole blood samples.The RNA purification protocol is summarized in Fig. The frozen samples were thawed under the following conditions: in a water bath at 37 °C for approximately 5 min, on an aluminum block at room temperature (23 °C) for approximately 18 min, or on ice for 2 h. Original aluminum blocks were prepared by wrapping an EDTA tube with aluminum foil and beating it with a hammer  according to the manufacturer’s instructions. The DNA quality was determined using a NanoDrop One spectrophotometer.30, with slight modifications. Briefly, cDNA was synthesized using the PrimeScript RT reagent kit (Takara Bio) with oligo(dT) primers and 1 μg of total RNA. The synthesized cDNA was mixed with SYBR Premix Ex Taq II (Takara Bio) and specific primers. Amplification was performed for 50 cycles, each at 95 °C for 15 s and 60 °C for 1 min, using a StepOnePlus real-time PCR system (Thermo Fisher Scientific). The list of primers used is presented in Supplementary Table GAPDH and RPS18, a calibration curve was generated using 10, 5, 2.5, 1.25, 0.625, and 0.3125 fM synthetic DNA, which included the target sequence . The list of synthetic DNA sequences used is provided in Supplementary Table cDNA synthesis and qPCR were performed using a previously reported methodSequencing libraries were constructed from 100 ng (for Participants2) or 300 ng (for Participants3) of RNA using the TruSeq Stranded Total RNA with Ribo-Zero Gold LT sample prep kit  according to the manufacturer’s instructions. The libraries were pooled after quantification by Bioanalyzer analysis and fluorometry using the Qubit dsDNA HS assay kit and a Qubit 2.0 fluorometer (Thermo Fisher Scientific). Sequencing of paired-end fragments (75 bp × 2) was conducted on the NextSeq 500 sequencing platform (Illumina) to a depth of 13 to 35 (average: 21) million fragments.31 and cmpfastq_pe.pl (http://compbio.brc.iop.kcl.ac.uk/software/cmpfastq_pe.php). After a quality control step, the filtered short reads were mapped to the reference genome (hg38) using STAR (version 2.5.1b)32. Strand-specific transcripts per million were obtained from each sample using RSEM (version 1.3.3.)33.Data for each sample were separated to generate FASTQ files. Next-generation sequencing data were cleaned using cutadapt (version 1.8.3)260/280 ratios, and RNA and DNA yields were analyzed using a two-way analysis of variance or repeated-measures analysis of variance with Bonferroni correction with EZR software version 1.54 (http://www.jichi.ac.jp/saitama-sct/SaitamaHP.files/statmedEN.html)34. The housekeeping gene expression in RNA-Seq was analyzed using F-test with Bonferroni correction using EZR software version 1.54. Results with P ≤ 0.05 were considered statistically significant. A statistical summary is shown in Supplementary Table RINs, mRNA expression, ASupplementary Information.


Circular RNAs (circRNAs) are circular RNA molecules without a 5′ cap and a 3′ poly(A) tail structure, which play an important role in tumor development, invasion and metastasis, etc. However, the mechanism of circRNA dysregulation in cancer remains unclear. Different from the classic splicing of linear RNA, circRNA is formed by back-splicing and is regulated by many cis-acting elements and trans-acting proteins. Exploring how the dysregulation of cis-regulatory elements and trans-acting proteins in tumor cells affects the biogenesis of circRNA, which in turn affects the development and prognosis of cancer, is of great significance for circRNA to become a cancer biomarker and therapeutic target.Circular RNAs (circRNAs), which are a class of endogenous RNA with covalently closed loops, play important roles in epigenetic regulation of gene expression at both the transcriptional and post-transcriptional level. Accumulating evidence demonstrated that numerous circRNAs were abnormally expressed in tumors and their dysregulation was involved in the tumorigenesis and metastasis of cancer. Although the functional mechanisms of many circRNAs have been revealed, how circRNAs are dysregulated in cancer remains elusive. CircRNAs are generated by a “back-splicing” process, which is regulated by different cis-regulatory elements and trans-acting proteins. Therefore, how these cis and trans elements change during tumorigenesis and how they regulate the biogenesis of circRNAs in cancer are two questions that interest us. In this review, we summarized the pathways for the biogenesis of circRNAs; and then illustrated how circRNAs dysregulated in cancer by discussing the changes of cis-regulatory elements and trans-acting proteins that related to circRNA splicing and maturation in cancer. Circular RNAs (circRNAs) are a class of endogenous RNAs, which form a covalently closed continuous loop structure without 5′-3′ polarity nor polyA tail . As an ecis-regulatory elements and trans-acting factors [cis-regulatory elements include the splice sites, enhancers, and silencers, especially the intronic complementary sequences (ICSs) near the junction points, such as the inverted Alu repeats [trans-acting factors include spliceosome factors, cleavage factors RNA helicases, and RNA-binding proteins (RBP) [Different from the classic canonical splicing of linear RNA, the biogenesis of circRNAs via back-splicing reversely connects the downstream (3′) splice donor site to an upstream (5′) splice acceptor site covalently . Two hyp factors . The cis repeats ; and thens (RBP) . Just lins (RBP)  of lineans (RBP) , aberranns (RBP) .In this review, we summarized the pathways for the biogenesis of circRNAs; and then illustrated how circRNAs dysregulated in cancer by discussing the changes of cis-regulatory elements and trans-acting proteins that related to circRNA splicing and maturation in cancer.The biogenesis of circRNAs via back-splicing is generally coupled with but different from the canonical splicing of linear RNAs . MoreoveMost scientists believe back-splicing and canonical splicing are coupled processes that are both required for the formation of circRNA. According to which step comes first, the processes of circRNA biogenesis can be classified into two groups. Once canonical splicing happens first, the RNA precursor will generate a linear RNA with skipped exons and a long lariat containing introns and exons, which is then back-spliced to generate a circRNA A. We calIn summary, the circRNA biogenesis is a complex process that involved spliceosomal machinery, complementary intron pairing, RBP binding, and so on. How these elements regulate circRNA expression as well as how they change during tumorigenesis are of great interest.A variety of trans-acting proteins have been reported to be involved in the biogenesis of circRNAs. By regulating the splicing process of pre-mRNA, they affect the production and expression of circRNA at the post-transcriptional level, and further affect the proliferation and migration of tumor cells and the prognosis of cancer patients. According to the different mechanisms of trans-acting factors, we divide them into four categories: spliceosome factors, cleavage factors, RNA helicases, and RNA-binding proteins; and explain separately to illustrate the biogenesis process of circRNA and its influence on cancer.The spliceosome is a large complex composed of five small nuclear RNAs (snRNAs), which combine with proteins to form particles, called small nuclear ribonucleoproteins (snRNPs). In eukaryotes, it is composed of U1, U2, U4, U5, and U6 snRNPs and a large number of proteins ,30. BothU2 auxiliary factor (U2AF) is a spliceosome factor and a non-snRNP protein, which is necessary for the binding of U2 snRNP to pre-mRNA branch sites . U2AF2 aStudies have found that changes in the expression levels of many core components of the spliceosome have a profound impact on the level of circRNA production. For example, an important part of the spliceosome U2 snRNP (SF3B1 or SF3A1), snRNP-U1-70K, and snRNP-U1-C involve in 5′ splice site recognition, and the largest protein component of the spliceosome cross-links with U5 and U6 snRNAs (prp8), etc. When they are exhausted, the splicing products of pre-mRNA will shift to the direction of circRNA production, and the production of linear RNA will decrease . Among tAccording to the reports, several cleavage factors can directly cut the adjacent intron sequences of exons forming circRNA to promote the formation of circRNA .For example, the cleavage factor ESRP1 can evenly target circRNA GGT-rich sequences to accelerate the circRNA biogenesis, such as circANKS1B and circUHRF1. Clinically, in breast cancer, the expression of ESRP1 is positively correlated with circANKS1B. The high expression of circANKS1B is closely related to the clinical stage and is an independent risk factor for the overall survival rate of breast cancer patients. At the same time, breast cancer patients with high expression of ESRP1 also have a poor overall survival . In oralThe cleavage factor NUDT21 is a part of the cleavage factor Im (CFIm) complex. In the form of a dimer, it combines with two UGUA sequences upstream of poly(A) to form a loop to prevent the splicing of pre-mRNA by the CPSF family, thereby promoting the formation of circRNA . In hepaAs the core component of the 3′-end splicing complex, Cleavage and Polyadenylation Specific Factor 4 (CPSF4) also has a regulatory effect on the formation of circular RNA. It can specifically bind to the PAS regulatory elements on the precursor mRNA, and mediates the cleavage of the CPSF family complex, thereby inhibiting the formation of circular RNA and affecting the expression of the formed circular RNA. The high expression of CPSF4 in HCC also corresponds to the overall down-regulation of circular RNA. Further studies demonstrated that overexpression of CPSF4 could promote the proliferation of HCC cells and was closely related to the clinicopathological characteristics of HCC patients .RNA helicases, a family of proteins that promote the unwinding of RNA during splicing and translation, play important roles in circRNA biogenesis because unwinding of the paired RNA sequence is a critical process for RNA circulation.DExH-box helicase 9 (DHX9) is a nuclear RNA helicase that can interact with inverted complementary sequences and unwind RNA pairs flanking circularized exons to prevent the production of circRNAs . In lungEukaryotic initiation factor 4A3  is a member of the DEAD box family, which is one of the largest helicase families characterized by an Asp-Glu-Ala-Asp (DEAD) motif . EIF4A3 ADAR1 is an RNA editing enzyme that can catalyze adenosine (A) in the reverse complementation region of introns to inosine (I), untie the pairing structure, and prevent the splicing site from approaching for reverse splicing, thereby strongly inhibiting the generation of circRNA ,61. StudExcept for the spliceosome factors, cleavage factors, and RNA helicases, several RNA-Binding Proteins (RBPs) can shorten the distance between the receptor site and the donor site through interaction with the flanking introns of exons, which promotes the production of corresponding circRNAs , such asHNRNPL can bind to the flanking introns of exons to promote the production of circRNA, especially when it exists on both sides . In GastThe Quaking (QKI) belongs to the evolutionarily conserved signal transduction and activator of RNA  family aFUS, a well-known proto-oncogene, is reported to regulate the expression of circRNA in murine embryonic stem cell-derived motor neurons . In primIn addition to trans-acting factors that regulate circRNA biogenesis, many cis-regulatory elements can also influence the cyclization of RNA. In particular, reverse complementary sequences  and direct-action sites of some splicing factors  play important roles in the generation of circRNA.Bioinformatics analysis shows that there are long introns at both ends of the reverse spliced circRNA exons. According to the calculation, the presence of Alu in the flanking introns is highly correlated with the formation of circRNA . The paiThe formation of circRNA depends on the pairing ability of complementary sequences, which can be repetitive sequences such as Alu elements, or non-repetitive but complementary sequences. For example, intron 14 and intron 17 of CircLONP2 have a highly matched sequence. Intron 17 is composed of several repeated “GUUG” or “ACUU” regions, which are located exactly within the binding motif between the proto-oncogene FUS. FUS binds to the flanking introns of CircLONP2 to promote its generation . In addiBut not all intron complementary sequences can promote pre-mRNA reverse splicing and exon circularization, the hairpin structure caused by base pairing may inhibit the biogenesis of circRNA . For exaBoth the RBPs and the mutual pairing sequences regulate circRNA generation by bringing upstream splicing receptors and downstream splicing donors close to each other. While the splicing factor can directly cleave the splice site on the intron to regulate the biogenesis of circRNA.The polyadenylation site (PAS), which plays an important role in the process of pre-mRNA 3’-UTR cleavage and maturation, plays an important role in regulating the expression of circular RNA. Among them, AAUAAA is the classic PAS motif , and othThe two UGUA elements located upstream of the PAS site can also regulate RNA cyclization. In HCC, the UGUA sequence located at the proximal end of the 3’-UTR is considered to be the splicing and polyadenylation site in the alternative splicing and alternative polyadenylation  process,In addition, studies have shown that the GGT-rich sequence on the flanking intron of the pre-mRNA exon is the binding sequence of the splicing factor ESRP1. ESRP1 is closely related to the poor prognosis of cancer patients, because ESRP1 can directly bind to the GGT-rich sequence to cut the circRNA, thereby accelerating the circRNA (such as circUHRF1 and circANKS1B) biogenesis, which in turn promotes tumor growth and metastasis ,45.circRNA has been proven to be an important biomarker of cancer in many studies. In this review, starting from the biogenesis mechanism of circRNA, we further explored the causes of circRNA dysregulation in cancer from two aspects of trans-acting factors and cis-acting elements, as well as the relationship with the occurrence, development, and prognosis of cancer . There a