Substance-related and addictive disorders, in particular gambling disorder, are known to be associated with risky decision-making behavior. Several neuroimaging studies have identified the involvement of the insular cortex in decision-making under risk. However, the extent of this involvement remains unclear and the specific contributions of two distinct insular subregions, the rostral agranular (RAIC) and the caudal granular (CGIC), have yet to be examined. Animals were trained to perform a rat gambling task (rGT), in which subjects chose between four options that differed in the magnitude and probability of rewards and penalties. In order to address the roles of the RAIC and CGIC in established choice behavior, pharmacological inactivations of these two subregions via local infusions of GABA receptor agonists were performed following 30 rGT training sessions. The contribution made by the RAIC or CGIC to the acquisition of choice behavior was also determined by lesioning these areas before behavioral training. Inactivation of the RAIC, but not of the CGIC, shifted rats' preference toward options with greater reward frequency and lower punishment. Before rGT acquisition, lesions of the RAIC, but not the CGIC, likewise resulted in a higher preference for options with greater reward frequency and lower punishment, and this persisted throughout the 30 training sessions. Our results provide confirmation of the involvement of the RAIC in rGT choice behavior and suggest that the RAIC may mediate detrimental risky decision-making behavior, such as that associated with addiction and gambling disorder. Gambling disorder is classified as an addictive disorder in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders-5, due to findings establishing its similarity to substance-use disorders in terms of clinical expression, brain origin, comorbidity, physiology, and treatment . The insFollowing the work of Models of decision-making under risk are particularly useful for studying gambling disorder. Models of decision-making under expected uncertainty, or risk, involve overt presentation of specific probabilities and quantities for reward/loss, whereas models of unexpected uncertainty, or ambiguity, involve a clear understanding of the existence of risk, but not the specific probabilities/quantities. To our knowledge, only two studies have examined the insular cortex in a rodent model of decision-making under risk , althougThe current study examines the involvement of two insular subregions, the RAIC and CGIC, in a rodent model of decision-making under risk, the rat gambling task (rGT), which is similar to the Iowa gambling task (IGT), a human model of decision-making under risk , previouad libitum water while in their home cages. Animals were single-housed in a temperature-controlled room on a 12-h reverse light cycle, with all behavioral testing occurring during the dark phase.Male Long–Evans rats  weighing 300–325 g at the start of experiments were maintained on ~20 g of rat chow daily and vs RAIC) at different rGT performance periods (acquisition of rGT choice behavior vs prior established rGT choice behavior). Acquisition experiments involved bilateral lesions of the RAIC or CGIC given before any behavioral training. Experiments examining established rGT performance involved bilateral cannulation of the RAIC or CGIC following acquisition of choice behavior .Experiments were conducted to examine the role of insular subregions  induction chamber before being positioned in a stereotaxic apparatus  after which anesthesia was maintained using isoflurane (1%–2%) delivered via nose cone. The animals' heads were shaved and local anesthetic  was injected at the incision site before Betadine was applied to clean the area. An incision was made along the midline and the skull exposed. Location of the bregma and lambda were determined and the skull was leveled. Sites of interest were determined relative to the bregma as follows, CGIC: anteroposterior −0.4 mm, lateral±4.8 mm; RAIC: anteroposterior +2.8 mm, lateral±4.0 mm. Small holes were drilled at the respective sites for each animal. For animals receiving bilateral cannulation, 22G stainless-steel guide cannulae  were lowered relative to the dorsoventral coordinate taken from the cranial surface at the site of interest, which was as follows: CGIC: +5 mm, RAIC: +6.5 mm, with CGIC cannulae being implanted at a 10° divergent from the vertical. Guide cannulae were then fixed to the skull with screws and dental cement, and sealed with a stainless-steel occluder. For animals receiving bilateral lesions, a 28G stainless-steel injector, coupled by polyethylene tubing to a 10-μl Hamilton syringe in a microinfusion pump , was slowly lowered relative to the dorsoventral coordinate taken from the cranial surface at the site of interest, which was as follows: CGIC: +6 mm, RAIC:+7.5 mm, with the CGIC injector again at a 10° divergent from the vertical. Over the course of 2 min, ibotenic acid  or vehicle was delivered to the site of interest and the injector was left in place for 5 min to allow for diffusion, and finally the incision was closed with wound clips. All animals were given prophylactic antibiotics  and analgesic , and given a minimum of 1 week recovery in their home cages.Behavioral testing occurred in traditional five-choice serial reaction time task (5CSRTT) chambers  controlled by software written in MED-PC running on an IBM-compatible computer  being unused. Animals were trained to make a nose-poke response into the illuminated hole within 10 s, which resulted in a sucrose pellet being delivered to the food receptacle. The illuminated hole changed at each trial with equal number of presentations of each possible hole over the course of the session. Once all animals demonstrated two consecutive sessions where 100 trials were completed with 80% of trials being correct and <20% were omitted , the group experienced 12 daily sessions (30 min each) of a forced-choice version of the rGT where only one of the holes was illuminated at each time. This ensured that all animals had equal experience with the specific number of rewards  and specific duration of punishment , and respective probabilities of each, for the four different holes. Animals were counterbalanced on the forced-choice rGT with version A or version B, corresponding to which they would undergo in the subsequent rGT acquisition. Version A and B differed only based on the assignment of each contingency . On testing days, injection cannulae were coupled to a 10-μl Hamilton syringe by a polyethylene tubing  filled with a GABA agonist mixture  or the vehicle  and inserted into the guide cannula after removing the occluder. Rats were first habituated to the procedure of inserting the injection cannulae 1 day before testing. Over the course of 1 min, 0.5 μl of the GABA agonist mix  was injected into each side , 5–10 min before the session. After the infusion, 1 min was allowed for diffusion, the injectors were removed, and occluders were replaced. Inactivation vs vehicle testing was counterbalanced and animals were given five rGT sessions between testing with stability being statistically confirmed for each respective group .For experiments examining insular subregion involvement in established rGT choice behavior, animals were implanted with guide cannulae, as described above, after completing a total of 30 rGT sessions. Following surgical recovery, animals were given an additional 10 rGT sessions for reacquisition before testing began. Stability of choice, trials, and premature responding were statistically confirmed across the last three sessions (vs sham) as the between-subjects factor. Sham groups for the lesions were pooled after no statistically significant difference was found from an ANOVA conducted with choice, session, and sham region as factors. Data from the experiments involving cortical inactivation were analyzed using a two-way repeated-measures ANOVA with choice , and condition (inactivation vs vehicle) as within-subject factors and with group  as a between-subject factor. Animals were defined as optimal if their responding for P1+P2 was >50% for the two sessions before each inactivation/vehicle session . If the outcome of the main ANOVA yielded significant effects (P<0.05), further post-hoc tests were performed.All statistical analyses were conducted using SPSS for Windows. The main variables analyzed were percentage choice for each option (P1–P4) and percentage of optimal (P1+P2) choice. All choice data were arcsine transformed to control for the effect of a ceiling. Data from the experiments involving lesions were analyzed using repeated-measures ANOVAs with choice , and session as within-subject factors and group . Brains were stored at −80 °C before being sliced into coronal serial 30-μm sections throughout the respective subregion of interest and stained with cresyl violet. The extents of the lesions or the injector tips were mapped onto standardized sections of the rat brain .Illustrations of lesion location and extent along with those of cannulae placement are presented in vs sham: F11, 506=2.083, P<0.05; CGIC vs sham: F11, 484=2.196, P<0.05) and correct responses  and a significantly greater number of incorrect responses . In addition, CGIC-, but not RAIC-, lesioned animals showed a significantly greater number of omissions compared with sham controls . However, by the last 3 days of this pre-rGT training phase, lesioned animals no longer differed significantly in responding from sham controls .Animals were trained on a modified version of the 5CRTT, which only used four holes in order to correspond to the rGT. Lesioned animals, as compared with sham controls, appeared slower to acquire the behavior with a significantly lower number of trials initiated .The acquisition of choice behavior by RAIC, but not CGIC, lesioned animals significantly differed from that of sham controls . Interestingly, there was no significant effect of session , suggesting overall optimal choice remained constant for the duration of training. This finding of consistent optimal choice (P1+P2) appears to contradict the observed change in choice pattern; however, this can be understood if a decrease in P1 choice over time is fully compensated for by a corresponding increase in P2 choice, while non-optimal choice remains fairly constant. Indeed this is the case here with significant effects of session observed for P1  and P2 choice , although not for P3  or P4  choice. The average percentage of optimal animals for each session  in each group was compared for the entire acquisition period  with the RAIC-lesioned group having significantly greater optimal responders (87%) compared with CGIC-lesioned (71%) and sham groups (69% P<0.001).RAIC, but not CGIC, lesioned rats showed a significantly greater preference for the optimal choices compared with sham controls . However, only RAIC-lesioned rats showed a significantly greater preference for P2 choice compared with sham controls . RAIC-, but not CGIC-, lesioned rats showed a significantly lower preference for P3  and P4 choice compared with sham controls .Both RAIC- and CGIC-lesioned rats showed a significantly greater preference for P1 choice compared with sham controls  and collect reward  compared with sham controls along with a decreased number of trials initiated .Animals with lesions did not differ from sham controls in the level of premature responding, omissions, or perseverative responding observed during acquisition of the rGT  3,39=3.683, P<0.05; CGIC: F3, 36=2.167, P<0.05). Specifically, RAIC inactivation resulted in a significant increase in P1 choice  and a significant decrease in P3 choice  with a decrease in P2 choice that did not reach significance . Animals were defined as optimal if their responding for P1+P2 was >50% for the two sessions before each inactivation/vehicle session . When animals were split into optimal vs suboptimal groups, only RAIC-inactivated animals showed a significant interaction effect . For suboptimal animals  and a significant increase in P1 choice  and P2 choice . Interestingly, for optimal animals  and a significant increase in P1 choice . Overall, RAIC inactivation resulted in the percentage of animals in the optimal group increasing from 64% to 79%. There were no suboptimal responders who became optimal responders following CGIC inactivation .Inactivation of the RAIC, but not the CGIC, significantly altered choice behavior  t12=1.914, P<0.05) and a trend toward an increase in omissions , whereas all other measures were not significantly affected .RAIC inactivation did not result in any significant changes in trials initiated, omissions, choice latency, collection latency, premature, or perseverative responses . In rodents with established choice behavior, RAIC inactivation increased P1 choice and decreased P3 choice. Examining animals by subgroup of optimal (>50% choice of P1+P2) vs suboptimal RAIC inactivation increased P1 choice in both groups and decreased P3 choice in the suboptimal and optimal group. Interestingly, P2 choice decreased in the optimal group but increased in the suboptimal group following inactivation of the RAIC.These results demonstrate insular involvement in decision-making under risk, as assessed by a rodent task with a contingency structure similar to the IGT. Subregion-specific involvement was demonstrated with RAIC disruption affecting both acquisition and performance of choice behavior, whereas CGIC disruption minimally affected acquisition. However, both RAIC and, to a greater extent, CGIC lesions affected the acquisition of appropriate responding on the pre-rGT serial reaction time task. Thus, it should be clearly noted that this suggests the insula is involved in the learning of a serial reaction time task, apart from its involvement in decision-making in the rGT. RAIC lesions resulted in acquisition of a consistently greater preference for ‘optimal' choices (options P1 and P2) which, when consistently chosen, produce the greater overall reward potential  collect latency, our previous findings have demonstrated no effect of CGIC inactivations on pellets obtained or lever presses made for food self-administration under a progressive ratio schedule , loss chvs sure) choice and concluded that RAIC activity promotes risk-taking behavior. Owing to the nature of the rGT, our study cannot confirm this straightforward conclusion. Importantly, those prior two studies used models with only two options (risky vs sure). The optimal choice in the rGT is P2, which yields an average of 411 pellets per session when chosen exclusively. The other choices, in order of descending expected pellet yield if chosen exclusively, are P1 (295 pellets), P3 (135), and P4 (99). Importantly, this distribution of expected values results in overall choice percentage being high for P2, although individual animals may not prefer this option. Our results suggest that RAIC inactivation does not simply increase choice for the optimal risk-reward option. Both optimal and suboptimal animals appear to have an RAIC inactivation ‘shift' in choice behavior toward an increase in preference for options with higher probabilities of reward over punishment and lower number of pellets rewarded, but also lower durations of punishment. Unfortunately, due to the design of contingencies in our model , we cannot distinguish whether this shift following RAIC inactivation is due to an increased preference for reward frequency and/or an increased avoidance of larger durations of punishment.To our knowledge, there are only two studies examining RAIC inactivation in rodent models of decision-making under risk with both examining performance not acquisition. Although historically the insula was considered merely a primary gustatory cortex, more recent evidence has established it as an integrator and processor of somatosensory , autonomvia interoceptive signals  and punishment (time out duration) should be encompassed within an interoceptive representation held within the RAIC. Thus, assuming a reduction in RAIC function resulted in this interoceptive representation no longer affecting decision-making, one would assume that the relative valuation of reward/punishment amounts for each option no longer guided decision-making. This leaves the possibility that RAIC-manipulated animals instead increased their reliance on outcome probability  in their decision-making behavior. This may be a result of an increased reliance on the striatum in decision-making, as the ventral striatum is suggested to underlie learning associations between stimuli and responses In conclusion, our results demonstrate that the RAIC, but not CGIC, is involved in decision-making behavior under risk in the rGT model. Taken along with other findings of insular involvement in the decision-making literature, we suggest that insular activity likely represents an overall interoceptive representation of the available options and thus increased insular activity can precede decisions of both risk avoidance and risk preference. In the case of gambling disorder, where such interoceptive representations likely contribute to detrimental risky decision-making behavior, manipulations of the RAIC may be of potential therapeutic benefit. Future work should examine the effects of manipulating insular activity, such as repetitive transcranial magnetic stimulation, on decision-making tasks and gambling behavior in human laboratory models.


L, 0.5L, 0.618L, and L, where L is the sequence length. These points are just the important golden sections of sequence. With this characteristic, an algorithm is designed to predict RNA hierarchical structures and simulate RNA folding by dynamically folding RNA structures according to the above golden section points. The sensitivity and number of predicted pseudoknots of our algorithm are better than those of the Mfold, HotKnots, McQfold, ProbKnot, and Lhw-Zhu algorithms. Experimental results reflect the folding rules of RNA from a new angle that is close to natural folding.RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is NP-hard. Most RNAs fold during transcription from DNA into RNA through a hierarchical pathway wherein secondary structures form prior to tertiary structures. Real RNA secondary structures often have local instead of global optimization because of kinetic reasons. The performance of RNA structure prediction may be improved by considering dynamic and hierarchical folding mechanisms. This study is a novel report on RNA folding that accords with the golden mean characteristic based on the statistical analysis of the real RNA secondary structures of all 480 sequences from RNA STRAND, which are validated by NMR or X-ray. The length ratios of domains in these sequences are approximately 0.382 RNAs are versatile molecules. Messenger RNAs carry genetic information and act as the intermediary agent between DNAs and proteins; ribosomal RNAs, transfer RNAs, and other noncoding RNAs also have important structural, regulatory, and catalytic functions in cells. To completely understand the various functions of RNAs, we need to first understand their structures. The primary structure of RNA is the sequence of nucleotides  in the single-stranded polymer of RNA. However, these sequences are not simply long strands of nucleotides. In RNA, complementary bases of guanine and cytosine pair can form three hydrogen bonds, those of adenine and uracil pair can form two hydrogen bonds, and those of guanine and uracil pair can form two hydrogen bonds. RNA folds into a 3D structure through hydrogen bonding and base stacking, which are nonconsecutive in the sequence. Noncanonical pairing and base-to-backbone hydrogen bonding also stabilize folding. The 3D arrangement of atoms in a folded RNA molecule is the tertiary structure; the collection of base pairs in the tertiary structure is the secondary structure. Experimental determination of RNA tertiary structures is too expensive and time consuming to meet practical needs; thus, predicting RNA structure by computer becomes a basic method and issue in computational biology .χ2 statistics and mutual information. Akmaev et al. .The results of statistical analysis on these real secondary structures are shown in Figures For 16S rRNA, 26 sequences belong to RNA STRAND. The statistical result is shown in  D , D , D , and D . In addition, the subdomains of D  are D  and D . We can divide the sequence into three groups, namely, 1–442, 1–730, and 731–1174, which represent the length of the entire sequence. The ratio of Group 1 to Group 2 is 0.61, and the ratio of Group 2 to Group 3 is 0.62 to 0.38.For example, four domains belong to sequence PDB_00409, namely, D , D , and D . The subdomains of D  are D , D , D , and D . D  is a pseudoknot, Ratio 1 is the ratio of 1261 to 2040, and Ratio 2 is 2040 to the sequence length.For long 5S rRNA, 23S rRNA, GI Intron, rRNA, and tRNA in RNA STRAND, the statistical results are shown in L to 0.38L, the second in the region of 0.6L to 0.618L, and the third in the region of 0.9L to 1.0L. Among 33 sequences, 25, 28, and 49 have helix 3′-ends located in points 0.382L, 0.618L, and L, respectively.For short RNAs, sequences with lengths less than 50 have generally only one domain and one or two simple helices. For sequences with lengths between 50 and 90, except for synthetic RNA, the folding 3′-end of domains and subdomains is centered on three regions . The seqL, 0.5L, 0.618L, and L, respectively.For tRNAs with lengths more than 50, the folding 3′-end of domains and subdomains is centered on four regions . The seqThe data corresponding to The data corresponding to L and the second in the region of L. For the sequences that fold thrice, the first folds in the region of 0.35L to 0.38L, the second in the region of 0.6L to 0.618L, and the third in the region of L.The sequences tend to fold twice or thrice. For the sequences that fold twice, the first folds in the region of 0.5a and b with a > b, a/b = (a + b)/a = phi = 1.618, and the quantities are 0.382 (a + b) and 0.618 (a + b). These quantities increase several unique ratios, including 0.618, 0.382, and 1.618, that is, the golden ratio. These ratios exist throughout nature, from population growth to the physical structure within the human brain, the DNA helix, many plants, and even the cosmos itself. The golden ratio is also called the golden section or golden mean.In mathematics and the arts, two quantities belong to the golden ratio if their ratio is the same as the ratio of their sum to their maximum. Expressed algebraically, for quantities  L, and approximately half of the sequences are folded at points 0.382L, 0.5L, and 0.618L. For long sequences, the other two key fold points 0.236L and 0.809L may be found, which are 0.382L × 0.618 and 0.5L × 1.618.The golden mean and the numbers of the Fibonacci series  have been used with significant success in analyzing and predicting stock market motion. Elliott presented wave theory, in which the frequent wave relationships are golden ratios . It has a striking similarity to RNA folding. We can determine that 0.382, 0.5, and 0.618 are the only important RNA folding points Tables . The aboTherefore, these points would be closer to natural folding and obtain higher accuracy than before if RNA is dynamically folded according to the above golden points.RNAs fold through a hierarchical pathway, in which the helices and loops are rapidly formed as secondary structures and the subsequent slow folding of the 3D tertiary structures would consolidate the secondary structures , 21. RNAs1,52 of TMVup with a length of 52, that is, 0.618L, and form the helix    . Then, w 49, 54) . Finally 49, 54) . Figure s16,20 and s26,36 form the helix    , and the 69, 74) . The helThe sketch of the GM algorithm is as in Z for all i and j in the start subsequence. The subsequence is then iteratively lengthened to the next golden point to compute the secondary structure values of Z for all i and j in the new subsequence. Finally, the pseudoknots are computed by the crossing of two subsequences, and the values of Z are provided for all i and j in the entire sequence. In this study, we use our previous LZ algorithm to compute pseudoknotted structures , which do not exist in real structure . Only thFor pseudoknotted structure in GM, sequence TMVup is folded to form two pseudoknots and one helix , which exist in real structure, except for one redundant base pair  . The seqIn the PKNOTS algorithm, sequence TMVup is folded to form four helices, three of which are equal to those in GM, but one helix  is redundant . This seFurther statistical analysis shows that the selected helices by the first step of GM basically belong to the real structures and control the folding pathway. This finding is precisely ascribed to the GM processing before PKONTS and LZ improve the accuracy.In this section, we test the TT2NE data set, which includes 47 sequences from PseudoBase and PDB, which is also a subset of those used in the HotKnots.We present the prediction results of our method compared with those of HotKnots , McQfoldThis set includes most of the sequences where HotKnots has been tested and shown to perform better than ILM and PKnots-rg. Thus, we will not compare GM to these latter algorithms.The total number of base pairs to be predicted in this set is 1115. Mfold, HotKnots, McQfold, ProbKnots, TT2NE, LZ, and GM predicted 618, 671, 740, 669, 870, 785, and 798, respectively. The total numbers of predicted base pairs are 1024, 1019, 991, 1041, 1146, 1102, and 1112, respectively.The sensitivity of GM is better than that of the other algorithms, except for TT2NE, either on the average 1 or on the average 2 . The PPVHowever, TT2NE has shown the most feasible value after several times folding with different parameters. Thus, TT2NE is not the autocomputing value. When given new sequences, we do not know which result should be selected.The part of computing pseudoknots in GM is the same as that in the LZ algorithm, and the difference between them lies in the preprocessing of secondary structures. The performance of GM is better than that of the LZ algorithm, either on the average 1 or on the average 2. GM improves the sensitivity of sequences Bs_glmS, EC_S15, and HDV_antigenomic from 36, 59, and 44 to 51, 100, and 84, respectively. GM also improves the PPV of these sequences from 57, 63, and 34 to 67, 74, and 64, respectively. However, for sequences AMV3 and BVDV, the performance of GM is only below LZ.The number of predicted genera by GM is better than that by other algorithms, except for TT2NE . All MfoHowever, TT2NE predicted more redundancy genera than other algorithms. For example, GLV_IRES, R2_retro_PK, and 1y0q sequences have only one native pseudoknot, but two pseudoknots are predicted by TT2NE. Bs_glmS has two native pseudoknots, but three are predicted by TT2NE.The percentages of sensitivity and PPV of each algorithm are shown. The column Gen indicates the predicted number of genera, and GR is the redundancy number in the predicted genus, which is more than the number of native genera. Average 1 is the total number of base pairs that are correctly predicted in the entire database divided by the corresponding total number of native base pairs (average sensitivity) and the total number of predicted base pairs (average PPV). Average 2 is the usual average of sensitivity and PPV values of all sequences. The detailed results are displayed as Supplementary data.L, 0.5L, 0.618L, and L. These points are the important golden sections of sequence. Applying this characteristic, we design a GM algorithm by dynamically folding RNA secondary structures according to the above golden section points and by forming pseudoknots with the crossing of subsequences. We implement the method using thermodynamic data and test its performance on PKNOTS and TT2NE data sets.In this study, we provide a novel report that RNA folding accords with the golden mean characteristic based on the statistical analysis of real RNA secondary structures. The folding 3′-end points of the sequence are almost close to 0.382For PKNOTS data set, we preprocess the sequence with the first step of GM and then obtain the output of the partially folded sequence as the input of the PKNOTS and LZ algorithms. Subsequently, the two algorithms improve by 2% to 3%. The reason is that the partial folded sequence forms its structural frame. In other words, the folding at the golden points controls the folding pathway and subsequently prevents the formation of some redundant structures.Preprocessing of GM may also be applied to other algorithms of RNA structure prediction to improve the prediction accuracy and to reduce the predicted redundant base pairs.For TT2NE data set, the sensitivity and number of predicted pseudoknots of GM are better than those of Mfold, HotKnots, McQfold, ProbKnot, and LZ. The PPV of GM is better than that of Mfold, HotKnot, ProbKnot, and LZ. These findings indicate that the GM method has good performance in predicting secondary and pseudoknotted structures. The sensitivity and PPV of the GM algorithm surpass those of most algorithms of RNA structure prediction. The experimental results reflect the folding rules of RNA from a new angle that is close to natural folding.The performance of long sequence needs to be further explored, and parameters for improvement and testing in large data sets to support web service are topics for future studies.PKNOTS data set includes 116 sequences, that is 25 tRNA sequences randomly selected from Sprinzl tRNA database, HIV-1-RT-ligand RNA pseukonts, and some viral RNAs. Column len and base pair indicate the length and the number of the native base pairs of sequence. For each algorithm, the sensitivity and specificity are shown. Average is is the usual average of sensitivity and specificity values reported in the table.TT2NE data set has 47 sequences from PseudoBase and PDB. In column ex, X indicates whether the native has been found experimentally. For each algorithm, the sensitivity and specificity are shown. Column g indicates the genus of the native structure and gT, gHK, gMQ, gPK, gLZ and gGM, are the respective genii of the predictions of TT2NE, HotKnots, McQfold, ProbKnot, LZ and GM. All Mfolds prediction have genus 0, as Mfold generates only structures without pseudoknots. Average 1 is the total number of base pairs correctly predicted in the whole database divided by respectively the total number of native base pairs (average sensitivity) and the total number of base pairs predicted (average specificity). Average 2 is the usual average of sensitivity and specificity values reported in the table .Notice: TT2NE is shown the best value after several times folding with different parameters, so it is not the auto-computing value.


The RIG-I-like receptors (RLRs) play a major role in sensing RNA virus infection to initiate and modulate antiviral immunity. They interact with particular viral RNAs, most of them being still unknown. To decipher the viral RNA signature on RLRs during viral infection, we tagged RLRs  and applied tagged protein affinity purification followed by next-generation sequencing (NGS) of associated RNA molecules. Two viruses with negative- and positive-sense RNA genome were used: measles (MV) and chikungunya (CHIKV). NGS analysis revealed that distinct regions of MV genome were specifically recognized by distinct RLRs: RIG-I recognized defective interfering genomes, whereas MDA5 and LGP2 specifically bound MV nucleoprotein-coding region. During CHIKV infection, RIG-I associated specifically to the 3’ untranslated region of viral genome. This study provides the first comparative view of the viral RNA ligands for RIG-I, MDA5 and LGP2 in the presence of infection.DOI:http://dx.doi.org/10.7554/eLife.11275.001 An immune system can protect against disease-causing microbes such as viruses. Human cells contain three different receptors that can recognize and respond when a virus enters and begins to replicate inside. These receptors include RIG-I, MDA5 and LGP2, and they are collectively known as the RIG-I-like receptors. RIG-I-like receptors specifically recognize viruses that store their genetic material in the form of molecules of RNA. However, the specific viral parts that trigger RIG-I-like receptors to respond remain almost completely unknown.RNA viruses include well-known and re-emerging viruses such as polio and measles, as well as chikungunya – a virus that is spread by mosquitoes and causes illness worldwide. This means that understanding how RIG-I-like receptors identify RNA viruses and then trigger an immune response to eradicate them has the potential to inform the development of vaccines and antiviral therapies for many diseases.Sanchez David et al. now describe and validate a new experimental approach to determine the distinct viral regions that are recognized by human RIG-I-like receptors. The approach involves purifying the RIG-I-like receptors out of infected cells and then working out the sequence of RNA fragments that bind to the receptors. This approach revealed that each of the three human RIG-I-like receptors detected different viral RNA sequences during a measles infection. On the other hand, only RIG-I could recognize a specific part of the chikungunya virus genome.All together, the experiments illustrate how to identify the RNA sequences recognized by any of the three human RIG-I-like receptors during infection by a RNA virus. With the ability to gain this kind of insight, it may soon be possible to develop ways of using the RIG-I-like receptor pathway to control viral infections and enhance the body’s immune response to vaccination.DOI:http://dx.doi.org/10.7554/eLife.11275.002 Because of increasing global population and worldwide exchanges, infections by RNA viruses are expanding with a huge impact on public health. New infections are emerging almost every year , tropical fevers are expanding  and even previously controlled diseases are re-emerging . Although several efficient vaccines against RNA viruses are used in human medicine, we still lack potent therapeutic treatments for the majority of viral infections as well as rational strategies to create efficient new vaccines. Recent progress in our understanding of cellular pathways controlling viral replication suggests that modulating host cell functions early upon viral infection could inhibit a large panel of RNA viruses . The RIGvia binding to pathogen-associated molecular pattern (PAMP) motifs. To date three RLR members have been identified: RIG-I (Retinoic acid-Inducible Gene-I), MDA5 (Melanoma-Differentiation-Associated gene 5), and LGP2 (Laboratory of Genetics and Physiology 2) (reviewed in 3) Further bioinformatic assays of the current data are helpful to understand the commons and differences of RNAs recognized by individual RLRs. At least, further description of the detected RNA profiles and the comparison to previous studies is necessary.In the revised manuscript, we performed additional bioinformatic analysis of the NGS data. Our studies concluded that not specific RNA sequences but rather structural elements are more likely to be linked to RLRs functionality. The relevant results are presented and discussed.4) For the confirmation of the detected RNA signatures, it can be performed in alternative permissive cells that naturally respond to the viruses using the enriched RNAs. First, we would like to provide a short introduction about MV and CHIKV permissive cells.For CHIKV the main virus-permissive cells are dermal fibroblasts, migrating monocytes/macrophages, and endothelial cells . Using our RLR-tagged approach we have found that RIG-I specifically interacts with CHIKV 3’-UTR. CHIKV 3’-UTR contains multiple 21 nucleotide-long repeated sequence elements forming dsRNA structure. The evolutional pressure exerted by mosquito vectors on this region and the length of CHIKV 3’-UTR are directly linked to the viral pathogenesis . We are currently performing additional studies in various cell types in which 3’-UTR of different CHIKV strains and mutant genomes are used. These studies will be later published elsewhere.via aerosols or droplets. Further, MV enters local lymphatic tissues and during the systemicphase of infection MV spreads by mononuclear cells that carry the virus to various organs . So in the late stage of the infection epithelial cells are the main targets of MV.Monocytes and dendritic cells of respiratory tract are the first targets of MV that is transmitted Taking into account that immune cells  harbour TLR7/8 that recognise viral single- stranded RNA in endosomes of infected cell and lead to activation of the transcription factor NF-κB and activation of type I IFN production, we used in our validation experiments MV-permissive epithelial cells (A549) naturally lacking TLR 7/8 receptors.In the revised manuscript, a validation of MV RNA signatures for RLR has been added . Thus, due to this gradient of transcription, promoter-proximal genes are expressed more efficiently than promoter-distal genes, a differential level that corresponds to the virus needs. To provide a clear vision of MV transcriptome, we now introduced a figure with NGS analysis of total RNA from MV-infected cells , nor to compute this specificity because we do not know which positions are truly not enriched (no reference population). However, we used statistical methods that are well adapted to analyse count data with a low number of replicates. These methods have been shown to be among the most reliable  and to control the false positive rates to expected levels.It is true that read counts are low in the L region, but this is the situation where the statistical analysis has less power. So the fact that read counts in this region are significant over the whole L region gives even more confidence about the significance of the difference.In We modified MV genome scheme to show that V region was deleted. We thank the reviewer #1 for this remark .In  This global enrichment in sequencing reads corresponding to the C-E2-E1 region has also its biological reason. Indeed, previous studies have shown that alphaviruses subgenomic RNA is more abundant than genomic RNA in cytoplasm of infected cells To provide a better vision on CHIKV NGS results, Reviewer 2: 1) This study is based on a HEK293 cell model after overexpression of tagged RLRs. This cell line is different in expression of the three endogenous RLRs. So could these differences affect the enrichment of RNAs for NGS? Moreover, single cell clones were used to perform the infection and RNA isolation, which may also bias the enriched RNAs. In fact, it is better to use a RLR-deficient cell (cell line) with rescue of respective RLR. I may also encourage the authors to use a typical virus-permissive immune cell model instead of HEK293.http://www.proteinatlas.org/). Indeed, we did not detect any of the three RLRs by western blot in the background HEK293 cells when using RLR specific antibodies  Previously, some studies have revealed the RNA features of several RNA viruses using different approaches. Despite the proposals of advantages of current approach by the authors, I am more interested in the similarities and differences identified by these researches for RNA viruses. Did common sequence or structural similarities exist for recognition by individual RLR? Otherwise, did common sequence or structural similarities exist in RNA viruses that could be recognized by RLRs?RLR specific PAMPs were previously detected for two paramyxoviruses (MV and Sendai virus) by immuno-precipitation of RIG-I and MDA5 and NGS of specific RNA ligands . This was already discussed in the previous version of the manuscript. In the revised manuscript we provide further information on the similarities and differences of our results and previous data (Discussion).Additionally, did the authors find particular self-RNA in the enriched RNAs?6 reads per sample, whereas in order to analyse human transcripts we need at least x108 reads/per sample. In the future, our protocol will be adapted to identify RLR-specific cellular partners that will include less or no multiplexing upon NGS.Unfortunately, in the current experimental setup we used samples multiplexing for NGS that allowed an appropriate analysis of viral -derived RNA but not cellular RNA molecules. Indeed, the mean number of reads aligned to the human genome in our NGS results were 16x10More bioinformatics analysis data should be performed, and these concerns may need further discussions.In the revised manuscript, we performed additional bioinformatic analysis of the NGS data obtained for the three RLRs upon infection with MV. We evaluated AU bias of the RLR sequencing results  as well The Results, Discussion, Materials and methods sections as well as the Figure legends were modified accordingly.3) To evaluate the stimulatory effects of the enriched RNAs, total pooled RNAs were used to activate the IFNβ reporter. Since RNA signatures in MV and CHIKV have been revealed by the study, it may be better for the authors to use these individual "RNA signatures" to examine the effects in IFNβ induction. Considering that IFNβ expression is rather complicated than transactivation, I suggest the authors to use an immune cell to examine the IFNβ levels after transfection of the identified signature RNAs.Immune cells  express TLRs capable of recognizing viral RNA (TLRs 3/7 and 8), and secrete type-I IFN upon ligand binding. In order to assess the immunostimulatory activity of RLR-specific RNA fragments synthesised in vitro and containing the RLR specific signatures, human PBMCs were transfected ex vivo. Indeed, we observed an increased secretion of type-I IFN. However, we were unable to discriminate what percentage of the response was TLR-dependent or RLR- dependent. In the presence of TLR7/8 inhibitor, the cytokine response was strongly reduced (Data not shown). Therefore, using immune cells represented a technical bias that makes it complicated to address this question in the allotted period. However, we believe that studying the RLR response in non-immune cells that do not respond through the TLR pathway is highly pertinent. Indeed, RLRs are ubiquitously expressed, and any cell is susceptible of recognizing viral RNA in their cytoplasm. In addition, non-immune cells are classically used as a model to study the RLR response . Consequently, validation experiments were done using MV-permissive epithelial cells naturally lacking TLR7/8 .The Results, Discussion, Materials and methods sections as well as the Figure legends were modified accordingly.


NALCN gene were identified in Infantile Neuroaxonal Dystrophy (INAD) patients, as well as in patients with an Autosomal Recessive Syndrome with severe hypotonia, speech impairment, and cognitive delay. Deletions in NALCN gene were also reported in diseases such as 13q syndrome. In addition, genes encoding NALCN, NLF- 1, UNC-79, and UNC-80 proteins may be susceptibility loci for several diseases including bipolar disorder, schizophrenia, Alzheimer's disease, autism, epilepsy, alcoholism, cardiac diseases and cancer. Although the physiological role of the NALCN channelosome is poorly understood, its involvement in human diseases should foster interest for drug development in the near future. Toward this goal, we review here the current knowledge on the NALCN channelosome in physiology and diseases.Ion channels are crucial components of cellular excitability and are involved in many neurological diseases. This review focuses on the sodium leak, G protein-coupled receptors (GPCRs)-activated NALCN channel that is predominantly expressed in neurons where it regulates the resting membrane potential and neuronal excitability. NALCN is part of a complex that includes not only GPCRs, but also UNC-79, UNC-80, NLF-1 and src family of Tyrosine kinases (SFKs). There is growing evidence that the NALCN channelosome critically regulates its ion conduction. Both in mammals and invertebrates, animal models revealed an involvement in many processes such as locomotor behaviors, sensitivity to volatile anesthetics, and respiratory rhythms. There is also evidence that alteration in this NALCN channelosome can cause a wide variety of diseases. Indeed, mutations in the  More thDrosophila melanogaster and NCA-1/2 in Caenorhabditis elegans) was first cloned from rat brain and described by Perez-Reyes and colleagues who named it Rb21  motif that remain to be explored at the functional level . lncRNAs are thought to function in various cellular contexts, including post-transcriptional regulation, post-translational regulation of protein activity, organization of protein complexes, cell–cell signaling, as well as recombination . Several splice variants were identified during our cloning step and by database scanning -resistant sodium leak current in mouse hippocampal neurons  is located on human chromosome 2q34 and has at least 45 exons. UNC-80 is a large protein of about 3300 amino acids without any predicted transmembrane segments or particular functional domains. UNC-80 contributes to the neuronal localization and/or stabilization of NALCN channel in C. elegans and D. melanogaster  is located on human chromosome 14q32.12 and has at least 48 exons. UNC-79 is also a large protein (~2800 amino acids) without any predicted transmembrane segments or particular functional domains. UNC-79 was found to be involved in regulating the neuronal localization of the NALCN channel complex both in C. elegans and D. melanogaster  is an endoplasmic reticulum (ER) resident protein of around 438-468 amino-acids, depending on the species, that interacts with NALCN and promotes its neuronal localization in C. elegans  with no known function. In C. elegans, the loss of function of nlf-1 results in a reduced leak current and a hyperpolarized resting membrane potential in premotor interneurons. NLF-1 function is conserved across species as the mouse homolog functionally substitutes to the C. elegans one. In addition, knockdown of the D. melanogaster ortholog gene, CG33988 results in similar phenotypes as for na  at the amino-terminus region. nlf-1 is expressed in sensory neurons, interneurons, and excitatory motor neurons in C. elegans. Endogenous UNC-79 level is also significantly decreased in nlf-1 mutants but the NLF-1 level is unaffected by the absence of UNC-79 and UNC-80. In humans, there is another gene homologous to NLF-1, FAM155B that is localized to Xq13.1 and encodes for a putative protein of 473 amino-acids. It is not known if this putative protein belongs to the NALCN channel complex. Both NLF-1 and FAM155B have a cysteine-rich domain (CRD) involved in signal transduction in other proteins  but also in heart, adrenal gland, thyroid gland, lymph node, and islets of Langerhans (both in α- and β-cells) . In the CNS, NALCN is expressed mainly in neurons, to a lesser extent in oligodendrocytes, and at a very low level in astrocytes . The spatial expression of NALCN is also correlated with genes expressed in specific neural cell types such as CALB1 , CTGF and UNC-5C . In invertebrates, NALCN-orthologs are concentrated at the synapse in D. melanogaster, and along the axon in C. elegans and L. stagnalis  in C. elegans travels on a culture plate through the continuous and rhythmic propagation of sinusoidal body bends. A simultaneous loss of both nca-1 and nca-2, or the individual loss of unc-79, unc-80 or nlf-1 results in fainting, a unique motor deficit characterized by periodic halting during movement  and other anesthetic agents  in response to halothane, cyclopropane, or sevoflurane. However, a significant resistance to isoflurane-induced anesthesia was described  neuron that initiates the respiratory rhythm was found to be hyperpolarized by ~15 mV and its rhythmic firing was abolished. Thus, NALCN also plays a role in maintaining the respiratory activity in adult animal. It remains to be demonstrated if NALCN plays the same role in mammals by studying its functional properties in the preBötzinger complex and the retrotrapezoidnucleus/parafacial respiratory group that are involved in the respiratory rhythmogenesis  in na mutant flies are noticeably smaller than controls and their abdomens are more slender and elongated but no obvious deformity has been identified  and have a leaner body composition (increased lean tissue and decreased body fat) than wild-type mice  channels, NALCN is partly responsible for the SP-induced depolarization and regulation of the intestinal pacemaking activity in the interstitial cells of Cajal  enzyme, also designated iPLA2-VIA , creating a premature translational termination signal at codon 642 (Q642X) and truncated NALCN channel  is a rare neurodegenerative disease characterized by progressive motor, mental and visual deterioration that begins in infancy. Onset is usually between the age of 6 months and 3 years and death typically ensues before the age of 10 years  but a few clusters of possible association (defined as P < 5 × 10−6). Six SNPs within or in the vicinity of the NALCN gene with P-values ranging from 2.54 × 10−6 to 9.76 × 10−7 were found. Additional GWAS with larger cohorts of patients are required since the small sample size for this initial study was underpowered to detect loci with small disease effects.Dystonia is a “syndrome of sustained muscle contractions, frequently causing twisting and repetitive movements or abnormal postures”  is a chronic, severe disabling brain disorder characterized by abnormalities in the perception of reality. It most commonly manifests as auditory hallucinations, delusions, disorganized speech and thinking with significant social or occupational dysfunction  suggest that NALCN may play a role in these two disorders  revealed a significant association between NALCN and BD  with both SCZ and BD in cohorts of 1172 (SCZ) and 653 (BD) European-American patients  is a syndrome characterized by a number of behavioral, cognitive and emotional features. It is most commonly associated with a sad or depressed mood, a reduced capacity to feel pleasure, hopelessness, loss of energy, altered sleep patterns, weight fluctuations, difficulty in concentrating and suicidal ideation , but statistical significance was not reached for any gene  are neurodevelopmental disorders characterized by impairments in social interaction and communication, and the presence of restrictive and repetitive behaviors  was also reported by Grupe et al., Alzheimer's disease (AD) is the most common form of dementia and the most frequent degenerative brain disorder encountered in old age. The risk of developing AD substantially increases after 65 years of age  and the comorbidy of alcoholism and depression (marker DS1371) respectively  is a sensorimotor disorder characterized by abnormal sensations in the limbs that are both dependent on activity and time of day, such that symptoms are promoted by rest and relieved by activity and peak in the evening or at night -expansions in different proteins cause at least eleven neurodegenerative diseases including Huntington disease and spinocerebellar ataxias . Pathway analysis allowed not only the identification of genes involved in mechanisms already known to be involved in cancer but also genes known to be involved in axon guidance. This latter finding was strengthened by the inclusion of data from another study  sporadic pancreatic ductal adenocarcinoma  that alter the permeation properties and the gadolinium block (EEKA) or inhibit the observed currents in HEK-293 cells (EEEE) that gate NALCN have yet to be established. On one hand, NALCN channel is described as conducting a sodium leak current in neurons both in mammals and invertebrates . The physiological consequences of these alternative splicing events remain to be elucidated.Alternative splicing events were demonstrated in many ion channels and can significantly impact their biophysical properties, cellular localization, and functional regulations . Whether the FAM155B gene product belongs to the NALCN channel complex should be investigated. Also, the mechanisms involved in the regulation of the NALCN channel by CaSR are not known and could imply a co-inclusion in the same protein complex. Some studies indicate genetic interactions between nca-1;nca-2 and other genes in C. elegans. As a matter of fact, null mutants of stomatins (unc-1 and unc-24) and innexins (unc-7 and unc-9) were found to restore the altered sensitivity to GAs and ethanol  at cell membranes during synaptic vesicle recycling . The physiological relevance of the NALCN channelosome phosphorylation, as well as the identification of the kinases involved, remains to be explored.In addition to their regulation by binding partners, ion channels are known to be post-translationally modulated. For example, ion channel complexes can be phosphorylated by a variety of kinases which regulate their physiological roles (reviewed in Smart, NALCN, and probably UNC-79, UNC-80, and NLF-1, is widely expressed throughout the CNS in mammals (Lee et al., C. elegans and in synaptic regions in D. melanogaster (Nash et al., http://t1dbase.org; Swayne et al., NALCN is highly expressed in the dorsal spinal cord compared to the ventral spinal cord (Sun et al., To date, no specific pharmacology for NALCN has been reported and this clearly represents a significant hurdle in the study of NALCN properties and activity. The discovery of specific NALCN agonists/antagonists is critically needed. Such molecules would be tools to investigate NALCN's physiological roles and may also hold interest to develop innovative therapeutic strategies. Whether the NALCN channelosome represents a drug target of interest remains unclear at the present time. Considering that NALCN channel is expressed in pancreatic islets, both in α- and β-cells, and is possibly involved in the regulation of insulin secretion (Kutlu et al., The NALCN channelosome is vital in mammals: homozygous mutant mice exhibit neonatal lethal phenotype and NALCN plays a crucial role in neuronal excitability. NALCN is involved in the regulation of resting membrane potential and is modulated by hormones and neurotransmitters. In the present article, we provide an extensive review of the literature describing the molecular and functional properties of the NALCN channelosome, the various phenotypes observed in NALCN animal models, as well as the recent implications of NALCN in human diseases. We also discuss how NALCN could represent a therapeutic target to treat a wide variety of human diseases, especially neurological and psychiatric diseases. Unfortunately, the lack of specific pharmacology is clearly a brake to all the NALCN investigations. In the coming years, the expected development of selective agonists/antagonists, as well as new animal models, should foster our understanding of the functional properties and physiological roles of the NALCN channelosome.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 noncoding RNAs (lncRNAs), which form a diverse class of RNAs, remain the least understood type of noncoding RNAs in terms of their nature and identification. Emerging evidence has revealed that a small number of newly discovered lncRNAs perform important and complex biological functions such as dosage compensation, chromatin regulation, genomic imprinting, and nuclear organization. However, understanding the wide range of functions of lncRNAs related to various processes of cellular networks remains a great experimental challenge. Structural versatility is critical for RNAs to perform various functions and provides new insights into probing the functions of lncRNAs. In recent years, the computational method of RNA structure prediction has been developed to analyze the structure of lncRNAs. This novel methodology has provided basic but indispensable information for the rapid, large-scale and in-depth research of lncRNAs. This review focuses on mainstream RNA structure prediction methods at the secondary and tertiary levels to offer an additional approach to investigating the functions of lncRNAs. The term noncoding RNAs (ncRNAs) refers to RNA transcripts that do not encode proteins . Approxiet al. [Except for tRNAs and rRNAs, ncRNAs have been traditionally disregarded as “transcriptional noise” . Althouget al.  created et al. .Given the wide range of biological functions in which lncRNAs have been implicated, we predict that many more lncRNAs will be determined to have important functions. For many RNAs, there is a close relationship between structure and function ,24,25. TThis review focuses on lncRNAs, which comprise the least understood class of ncRNAs. Their functions, mechanisms, roles in epigenetics and relationships with diseases are introduced. Moreover, ncRNA structure prediction methods such as Foldalign , Pfold , Mfold , RNAfoldRecent advances in the study of ncRNAs have demonstrated the existence of ncRNAs in a wide variety of mammalian transcriptomes. miRNAs, siRNAs, lncRNAs and other ncRNAs have been found to play significant roles in various physiological and developmental processes in eukaryotes, furthering our knowledge of ncRNAs.A plethora of analyses have revealed that the majority of ncRNAs possess low rates of interspecies conservation at the primary sequence level as protein-coding RNAs . AnalyseVarious technologies have emerged to detect the stability and conservation of ncRNA. Transcriptome sequencing has been applied to the profiling of ncRNAs conservation. First-generation sequencing, proposed by Sanger , was basMany ncRNAs remain undiscovered, and the functions of the majority of previously discovered ncRNAs are not yet known. Furthermore, a low evolutionary conservation of these RNAs has been verified. All of these indications suggested that ncRNAs do not possess biological function. However, mounting evidence suggests that the lack of sequence conservation does not necessarily symbolize a deficiency in function . IncreasSeveral mechanisms by which ncRNAs regulate gene expression have been discovered. (1) Piwi-interacting RNAs (piRNAs) have been shown to play roles in the formation of heterochromatin ; (2) miRBecause ncRNAs regulate various levels of gene expression and are involved in numerous biological processes, the dysregulation of ncRNAs is linked to diseases. It has been reported that ncRNAs exert significant effects on the immune response, inflammatory lung diseases , neurodeIn general, abnormal tissues are obtained by invasive methods for the detection of biomarkers in the diagnosis or clinical treatment of tumors. However, due to the introduction of an external source, this is not the optimal choice for diagnostic and therapeutic applications. The characteristics of stability, specificity, sensitivity, predictability and accessibility are required for quantifiable indicators of diseases . Some ncLong noncoding RNAs (lncRNAs) consist of at least 200 nucleotides . The stret al. [Ken C. Pang et al.  investiget al. . Some spet al. ,51,52.The known mechanisms involved in the function of lncRNAs are as follows : (a) To It is reported that lncRNAs participate in the epigenetic regulation of gene expression ,105,106,As mentioned above, an increasing number of studies have demonstrated that lncRNAs participate in th As previously mentioned, an increasing number of studies have demonstrated that lncRNAs participate in the regulation of protein coding genes at the transcriptional and posttranscriptional levels . It is rSimilar to mRNAs, distinct mature ncRNAs can be obtained from primary non-protein coding RNA transcripts via alternative splicing in various differentiated cells, developmental stages or physiological states. It has been estimated that 95% of human primary transcripts of genes containing multiple exons are regulated by alternative splicing . AlternaIt is currently accepted that the explanation for the various functions of lncRNAs lies in their multiple structures. Mounting evidence has revealed that some lncRNAs and circRNAs can serve as miRNA sponges and inhibit the binding of miRNAs to their target mRNAs to perform their functions . MaternaTo elucidate the functions of lncRNAs and to further investigate the question of whether nucleotide sequences serve as functional units or simply linkers of different functional modules, it is necessary to study the structures of lncRNAs and the interaction between their structure and sequence. RNA possesses a unique ability to form complex secondary and tertiary folds . It has The folding process of the majority of RNA molecules represents a transition from secondary to tertiary structure . TherefoMethods based on comparative sequence analysis rely on the fact that the structural conservation is greater than the sequence conservation of RNA ,151. Comhttp://rth.dk/resources/foldalign/ [Foldalign , simplifldalign/ .Dynalign , which iwww.daimi.au.dk/~compbio/pfold [Pfold  is basedio/pfold .http://rna.tbi.univie.ac.at/cgi-bin/RNAalifold.cgi [The Alifold service ,165, an fold.cgi .http://rna.informatik.uni-freiburg.de/MARNA/Input.jsp [MARNA , a non-pnput.jsp .A large number of studies and experiments have demonstrated that comparative sequence analysis processes higher prediction probabilities when the RNA sequence templates have high similarity . Howeveret al. [When no prior knowledge is available and only a single sequence is offered, an accurate and popular method is to search the minimum free energy model through thermodynamic computation . This moet al.  developeet al. [http://unafold.rna.albany.edu/?q=mfold [Mfold  divides et al.  discover?q=mfold .et al. [http://rna.tbi.univie.ac.at/cgi-bin/RNAfold.cgi [RNAfold , which iet al.  discoverfold.cgi .http://bibiserv.techfak.uni-bielefeld.de/rnashapes [RNAshapes , based onashapes .et al. [in vivo with predicted structures (determined by RNAstructure) in silico and revealed that mRNAs related to stress responses have structural features, such as longer maximal loop length and more single strandedness, that allow for easy conformational changes under various environmental conditions. SPRY4-IT1, the lncRNA that regulates invasion and apoptosis, was predicted to contain long hairpin motifs (by RNAstructure), suggesting that SPRY4-IT1 may function as an RNA molecule [http://rna.urmc.rochester.edu/RNAstructure.html [RNAstructure  utilizeset al.  comparedmolecule . The pacure.html .et al. [The information regarding the methods described above is summarized in et al. ,173 stilThe formation of specific tertiary structures is essential for the functioning of noncoding RNAs in many biological processes . RNAs caet al. [FARNA , derivedet al.  have inthttps://simtk.org/home/nast [NAST (The Nucleic Acid Simulation Tool) , based oome/nast .iFoldRNA  uses disBARNACLE , a probaThe CG model  models Ret al., and the RMSD reached 7 Å [RNA2D3D , differeched 7 Å ,206,207.The Vfold model  is a phyhttp://www.github.com/ jpbida/rsim [RSIM , a fullyida/rsim .http://biophy.hust.edu.cn/3dRNA/3dRNA-1.0.html [3dRNA , based o1.0.html .The methods mentioned above are widely used to predict RNA tertiary structure. Furthermore, MC-Fold/MC-Sym , based oWith an increasing number of studies focused on lncRNAs, an increased understanding of lncRNAs has been achieved. lncRNAs play biological roles in organisms, and their dysregulation is strongly linked to the occurrence and development of various diseases . However


Lepas anatifera , atypical or sub-optimal rRNA profiles that were apparently degraded were observed on a bioanalyser electropherogram. It was subsequently discovered that the rRNA was not degraded, but arose due to a ‘gap deletion’  in the 28S rRNA. An apparent excision at this site caused the 28S rRNA to fragment under heat-denaturing conditions and migrate along with the 18S rRNA, superficially presenting a ‘degraded’ appearance. Examination of the literature showed similar observations in a small number of older studies in insects; however, reading across multiple disciplines suggests that this is a wider issue that occurs across the Animalia and beyond. The current study shows that the 28S rRNA anomaly goes far beyond insects within the Arthropoda and is widespread within this phylum. We confirm that the anomaly is associated with thermal conversion because gap-deletion patterns were observed in heat-denatured samples but not in gels with formaldehyde-denaturing.The requirement for high quality/non-degraded RNA is essential for an array of molecular biology analyses. When analysing the integrity of rRNA from the barnacle  Anomalies in the gel migration of the 28S subunit rRNA in denatured samples have mostly appeared in the older literature . More reα’ and ‘β’  are similar in size and form a single band on RNA gels, approximately at the 18S position. State-of-the-art RNA profile analysis using bioanalyser electropherograms can also display a ‘degraded’ appearance in RNA due to the presence of a single peak ∼ at the 18S position, as previously described by In most animals, RNA denaturation generates 28S and 18S rRNA fragments  respectively), which migrate separately on the denaturing gel. It is widely accepted that, in intact rRNA, the 28S and 18S peak ratios must be close to 2:1 . But thi and ‘β’  with thi and ‘β’ . At the Caenorhabditis elegans in Phylum Nematoda  and giant Asian centipede Scolopendra subspinipes (Myriapoda). Both of these organisms are not easily obtained and so we were limited to one individual specimen for each (n = 1); however, RNA was extracted from three replicate tissue samples from each individual. For barnacles (Crustacea), three species in different taxonomic orders were sampled, this time with tissues from three individuals of each species (n = 3). Specimens were instantly killed and frozen by immersion in liquid nitrogen. Immediately afterwards, specimens were left to thaw for a few minutes before being dissected. Approximately 2 cm3 of tissue was excised from the muscle mass surrounding the fovea on the lateral parts of the cephalothorax of Grammostola porteri and divided into three samples for analysis. Approximately 1 cm3 of tissue was recovered from the deep oblique and lateral longitudinal muscles of Scolopendra subspinipes and then divided into three samples. Approximately 1 cm3 of prosoma and peduncle tissues were dissected from each of three individuals of Lepas anatifera . Next, total RNA was extracted with QIAGEN RNeasy Mini Kit including DNase I treatment , according to the manufacturer’s instructions. For the analyses of quality and integrity, RNA (100–200 ng) was electrophoretically separated with an Agilent 2100 Bioanalyser using an RNA 6000 Nano Chip Kit according to manufacturer’s instructions. Each sample was heat-denatured at 70 °C for 3 min prior to separation. Aliquots from the same RNA samples without heat-denaturation were also run together with heat-denatured samples on the same Bioanalyser chip.Tissues were homogenized using the IKA® 10X Gel Buffer  was added to the agarose gel solution and mixed. The gel was poured to a thickness of 0.6 cm and allowed to set. The gel was run at 60 V using 1X NorthernMax® MOPS Running Buffer  for 90 min. Aliquots from the same RNA stock were run in both heat-denatured (70 °C for 3 min) and non-heated form, along with RiboRuler High Range RNA Ladder . The procedure was also carried out on a stronger denaturing gel (2X), i.e., 20 ml of NorthernMax® 10X Gel Buffer was added to 1 g of agarose and 80 ml of nuclease free water and this was run as before with the respective RNA samples.Samples were also run on a formaldehyde-denaturing RNA gel. One gram of agarose was added to 90 ml of nuclease free water and transferred to a 50 °C water bath until equilibrated. In a fume hood, 10 ml of NorthernMaxLepas anatifera RNA was carried out as part of a parallel study . Transcriptome analysis for this species was carried out on an Illumina Hi-Seq 2000 sequencing platform by Source BioScience LifeSciences, UK. Sequence alignments of 28S rDNA gene sequences were carried out using the Lepas anatifera 28S gene sequence from the transcriptome study, along with all available sequences from GenBank database. The GenBank accession numbers for sequences were: Scolopendra subspinipes (HQ402538.1), Dosima fascicularis (KF781345.1) and Pollicipes pollicipes (EU370441.1). The online tools Clustal Omega  and T-COFFEE Multiple Sequence Alignment Server (http://tcoffee.crg.cat/apps/tcoffee/index.html) were used to align sequences and search for common motifs.Deep sequencing by RNA-seq of Lepas anatifera and Dosima fascicularis (Order Lepadiformes) as well as Pollicipes pollicipes  in heat-denatured samples in all cases . These sIn all groups that displayed the rRNA gap deletion, heat-denaturation affected the 28S rRNA so that this resembled the 18S rRNA in size and therefore appeared with 18S as a single peak on the bioanalyser, or as a single band on a gel . SuperfiThe Agilent 2100 Bioanalyser is an established method for determining RNA quality and integrity for the purpose of downstream transcriptomic analysis. But several authors have remarked on a degree of puzzlement in interpreting bioanalyser electropherograms where gap deletions are involved  and new Haliclona indistincta) (Schistosoma mansoni (Dugesia japonica (The literature to date has either suggested that the gap deletion (or hidden break) is very narrowly focussed e.g., within ‘insects’ , or thatstincta) . Meanwhi mansoni  and Dugejaponica  containejaponica ; Table 1japonica  as do ceTetrahymena spp.) and amoeboid LSU rRNA  is where cleavage occurs by a ‘late enzyme dependent cleavage event’ to expose the loop (in stem and loop structure). Furthermore, in aphids the absence of the gap deletion can be explained by an absence of the UAAU-rich sequence necessary for gap processing  was proposed initially by position . Here thposition . Thus, Gposition . Recentlocessing . From trAAGGG-3′  , Lepas anatifera Dosima fascicularis (KF781345.1) and Pollicipes pollicipes (EU370441.1). Shading in black signifies bases conserved across two or more species. Percent (%) IdentityMatrix—created by Clustal2.1. is also shown.Species aligned were Click here for additional data file.10.7717/peerj.1436/supp-2Figure S2Samples lacking gap deletion display detectable RNA Integrity numbers (RINs) when heat denaturation is conducted prior to analysis.Click here for additional data file.


Pseudomonas syringae, or treated with the flagelin-derived elicitor peptide flg22 from P. syringae. This work investigates sRNAs that are regulated by elicitors from the fungus Fusarium oxysporum in Arabidopsis.Small RNAs (sRNAs), including small interfering RNAs (siRNAs) and microRNAs (miRNAs), have emerged as important regulators of eukaryotic gene expression. In plants, miRNAs play critical roles in development, nutrient homeostasis and abiotic stress responses. Accumulating evidence also reveals that sRNAs are involved in plant immunity. Most studies on pathogen-regulated sRNAs have been conducted in Arabidopsis plants infected with the bacterial pathogen MIR168 by fungal elicitors. Furthermore, transgenic plants expressing a GFP-miR168 sensor gene confirmed that the elicitor-induced miR168 is active. MiR823, targeting Chromomethylase3 (CMT3) involved in RNA-directed DNA methylation (RdDM) was also found to be regulated by fungal elicitors. In addition to known miRNAs, microarray analysis allowed the identification of an elicitor-inducible small RNA that was incorrectly annotated as a miRNA. Studies on Arabidopsis mutants impaired in small RNA biogenesis demonstrated that this sRNA, is a heterochromatic-siRNA (hc-siRNA) named as siRNA415. Hc-siRNAs are known to be involved in RNA-directed DNA methylation (RdDM). SiRNA415 is detected in several plant species.Microarray analysis revealed alterations on the accumulation of a set of sRNAs in response to elicitor treatment, including miRNAs and small RNA sequences derived from massively parallel signature sequencing. Among the elicitor-regulated miRNAs was miR168 which regulates ARGONAUTE1, the core component of the RNA-induced silencing complex involved in miRNA functioning. Promoter analysis in transgenic Arabidopsis plants revealed transcriptional activation of MIR168 expression. This finding highlights the importance of miRNA functioning in adaptive processes of Arabidopsis plants to fungal infection. The results of this study also lay a foundation for the involvement of RdDM processes through the activity of siRNA415 and miR823 in mediating regulation of immune responses in Arabidopsis plants.Results here presented support a transcriptional regulatory mechanism underlying The online version of this article (doi:10.1186/1471-2164-15-1083) contains supplementary material, which is available to authorized users. The genomes of higher eukaryotes encode small RNAs (sRNAs) that direct transcriptional and post-transcriptional gene silencing –3. In plMiRNAs are derived from primary miRNA (pri-miRNA) transcripts that form an imperfect fold-back structure . The priThe second major class of sRNAs, includes siRNAs that are generated from long double-stranded RNAs (dsRNAs) resulting from the activity of RNA-dependent RNA polymerases (RDRs) that are sliced by DCL activities into siRNA duplexes , 14. ThuMiRNAs and siRNAs are further distinguished by their dependency on DNA-dependent RNA polymerases for their production. MiRNAs are typically transcribed by Pol II whereas hc-siRNA sequences are transcribed by Pol IV. The Pol IV transcripts serve as templates for RDR2 to generate dsRNAs that are processed by DCL3 into 24-nt hc-siRNAs and then loaded onto AGO4-containing complexes –24. The http://microrna.sanger.ac.uk) has dramatically increased, this expansion being largely a benefit of the adoption of next-generation high-throughput sequencing technology. Although the early criteria for miRNA annotation based on expression and biogenesis still provide a broadly accepted standard for miRNA annotation [During the last years the number of plant miRNAs registered in miRBase  induces miR393 accumulation which, in turn, silences the expression of the TIR1 (TRANSPORT INHIBITOR RESPONSE1) auxin receptor. Repression of auxin signaling then contributes to bacterial resistance [R genes and trigger production of phased secondary siRNAs have been characterized in Solanaceae and Leguminosae species in relation to antiviral and antibacterial resistance [Magnaporthe oryzae[Traditionally, studies on plant immunity focused on the transcriptional regulation of protein-coding genes. Along with this, host-encoded receptors recognize pathogen-associated molecular patterns . This recognition elicits the PAMP-triggered immunity (PTI), or basal disease resistance, a process in which regulation of immune-response genes occurs through the coordinated regulation of hormone signals . Some pasistance . MiRNAs sistance , 37. In e oryzae. Indeed,Pseudomonas syringae, or treated with the flagelin-derived elicitor peptide flg22 from P. syringae[MIR168a promoter is transcriptionally activated by fungal elicitors in transgenic Arabidopsis plants harboring the promMIR168a::GFP (green fluorescent protein) fusion gene. Using transgenic plants expressing a GFP-miR168* sensor construct, we further demonstrated that the elicitor-induced miR168 is active. Microarray analysis also revealed elicitor responsiveness of a small RNA currently annotated as miR415 in miRBase. The status of this sequence has been, however, questioned (http://microrna.sanger.ac.uk). Using Arabidopsis mutants impaired in small RNA biogenesis and function, we show that production of this particular small RNA depends on Pol IV, DCL3 and RDR2 activities. Based on these findings, we conclude that this small RNA is a hc-siRNA, and can no longer be considered a miRNA. Microarray experiments also revealed elicitor-responsiveness of miR823, this miRNA targeting the plant-specific methyltransferase involved in DNA methylation . These findings further support a role for hc-siRNAs, potentially acting in RdDM processes, in the response of Arabidopsis plants to fungal elicitors.Most studies on pathogen-regulated sRNAs have been conducted in Arabidopsis plants infected with the bacterial pathogen syringae. HoweverFusarium oxysporum[Caenorhabditis elegans, Drosophila melanogaster) were also included in the microrray. The complete list of probes represented in the microarray is presented in Additional file In this work, we examined alterations in the accumulation of Arabidopsis small RNAs in response to treatment with elicitors obtained from the fungus xysporum. Towardsxysporum, 43, 44 xysporum, 46. ProF. oxysporum, and mock-inoculated plants, at different times of treatment (from 5 min to 120 min of treatment). Three independent biological replicates were prepared for each time point and condition. Samples harvested at 5, 30, 60 and 120 min of elicitor treatment were used for microarray experiments. Elicitor-induced alterations in small RNA accumulation we identified by determining the ratio of the hybridization signal intensities between treated and control plants.Total RNA was isolated from Arabidopsis seedlings that had been treated with elicitors obtained from the fungus Among the small RNAs interrogated in the microarray, 15 miRNAs corresponding to 13 miRNA families, and 81 predicted miRNAs showed elicitor-responsiveness (up- or down-regulation) at one or more time points of elicitor treatment  transcription factors. Two members of the miR156 family, miR156a and miR156h, were found to be sequentially regulated by elicitors (Table ARF6 and ARF8), miR164 and miR169 . This observation points to a possible miRNA-mediated regulation of auxin signaling by fungal elicitors.Elicitor-regulated miRNAs mainly target transcription factors involved in the control of developmental processes. For instance, miR156 is known to target Chromomethylase 3 (CMT3) encoding an enzyme involved in DNA methylation and gene silencing [Of interest, miR168 was found to be up-regulated by fungal elicitors at all the time points of elicitor treatment examined here. We also noticed a significant increase in miR823 accumulation FC, 10.66) at 30 min of elicitor treatment. This particular miRNA has been reported to target transcripts of .66 at 30Arabidopsis thaliana, Medicago truncatula, Glycine max, Populus trichocarpa, and Solanum tuberosum are the dicot species with the highest number of miRNAs annotated in the miRBase registry. As for monocots, Oryza sativa, Zea mays, Sorghum bicolour and Brachypodium distachyon have the highest number of miRNAs annotated in miRBase. In this work, conserved miRNAs were designated as those having identical sequences with the miRNA sequences annotated in miRBase for all the above mentioned plant species. Based on the information available on miRBase, both conserved and non conserved miRNAs were identified among the subset of elicitor-responsive miRNAs . As it is shown in Figure AGO1 expression remained at lower level in elicitor treated tissues compared to control plants at all time points, although these differences gradually decreased during the period of elicitor treatment  of control and elicitor-treated Arabidopsis plants. Despite the relevance of MIR168 in controlling AGO1 homeostasis, little attention has been paid to MIR168 expression or activity in tissues of Arabidopsis plants other than leaves. Towards this end, a sensor gene was obtained in which the miR168 target sequence was inserted into the 3’-UTR of the GFP reporter gene . Along with this, mature miR168 accumulated in response to abiotic stress and ABA treatment in Arabidopsis [It is generally assumed that most ng genes , 49. Prebidopsis .MIR168 promoter region for the presence of known cis-elements related to biotic stress and defence-related hormones. The sequence upstream of the precursor structure for either pre-miR168a or pre-miR168b was extracted from the NCBI database and the transcription start site (TSS) was identified by using the transcription start site identification program for plants (http://linux1.softberry.com/berry.phtml?topic=tssp&group=programs&subgroup=promoter). cis-acting elements present in the 2 Kb DNA region upstream of the TSS were searched using the PLACE database (http://www.dna.affrc.go.jp/PLACE/) [MIR168a and MIR168b promoters were found to contain several pathogen-responsive cis-elements  gene, a key regulator of salicylic acid (SA)-mediated defence responses in Arabidopsis [MIR168 promoter. This regulatory element was initially characterized in the pathogen and elicitor inducible potato pathogenesis-related gene PR-10a gene, and later on in the promoter of several other defence-related genes, including PR genes. Additional regulatory elements identified in the MIR168 promoter are associated with defence-related hormones such as ethylene (ET) and methyl jasmonic acid (MeJA)  allowed us to compare the frequency of each motif identified in the miR168 promoter with the frequency of the same motif in the promoter regions of all known genes from Arabidopsis [cis-motifs were significantly enriched in the MIR168 promoter relative to the Arabidopsis background set   . Interesbidopsis . The SEBbidopsis . ExcludiMIR168 promoter was performed, focusing on the MIR168a promoter. For this, the MIR168a promoter region was fused to the GFP gene and the resulting construct . An apparent discrepancy occurs in leaves of non treated plants as miR168 activity  and another in rice (aacagaacagaagcagagcag). This small RNA sequence was detected by Northern blot analysis in Arabidopsis flowers [The current release of miRBase contains a sequence annotated as miR415 with two entries, one in  flowers , 55. HowOur microarray analysis revealed a significant increase in the accumulation of this particular small RNA at 30 min of elicitor treatment , dcl2-1, dcl3-1, and dcl4-2, as well as mutants with defects in a RDR gene for which a function has been established, namely rdr1-1, rdr2-1 and rdr6-15 mutants [dcl1-9 (Ler background), all the dcl and rdr mutants were in the Col0 genetic background. The small RNA under study was detected in wild-type plants of the two accessions, its level of accumulation being slightly lower in Ler plants than in Col0 plants  , its accumulation being also significantly reduced in the nrpe1 mutant (largest subunit of Pol V). Together, results obtained in the analysis of dcl, rdr, and pol mutants were consistent with the interpretation that the 24-nt small RNA under study is produced by the PolIV/RDR2/DCL3 pathway, a typical feature of hc-siRNAs. Finally, hc-siRNAs are known to function in association with AGO4 [ago4-2 mutant (Col 0 background), this observation supporting that this small RNA associates with AGO4.Evidence exists that 24-nt hc-siRNAs function in RNA-directed DNA methylation (RdDM) in the chromatin silencing pathway. In this work we examined the accumulation of the 24-nt small RNA in Pol IV and Pol V mutants. As previously mentioned, RdDM requires the concerted action of Pol IV and Pol V, the Pol IV being required for hc-siRNA biogenesis (through the RDR2/DCL3 pathway), and Pol V being responsible of targeting siRNAs to loci controlled by RdDM. Pol IV and Pol V each has a unique largest subunit  and share the second largest subunit (NRPD2/NRPE2) . As it iith AGO4 , 58. As dcl3-1 and rdr2-1 mutants [dcl3, rdr2. siRNA1003 production was also impaired in the nrpd2 (second largest subunit of Pol IV and Pol V) mutant, while showing an important reduction in the nrpe1 mutant (Pol V largest subunit) compared to wild type Col0 plants  in the panel of Arabidopsis mutants. Previous studies demonstrated that production of siRNA1003 is Pol IV- and Pol V-dependent , 60 and  mutants , 18. ConTaken together, analysis of Arabidopsis mutants affected in biogenesis and functioning of small RNAs revealed that mutations in any of the genes in the Pol IV/RDR2/DCL3 pathway affect the accumulation of this small RNA species. This piece of evidence strongly supports that the 24-nt small RNA investigated here is indeed a hc-siRNA and not a miRNA. This sequence may therefore be removed in subsequent data releases from miRBase. We have named this small RNA siRNA415.Zea mays, Sorghum bicolour, Oryza sativa), and dicotyledonous  species. As it is shown in Figure Finally, we examined whether siRNA415 occurs in plant species other than Arabidopsis. For this, we examined its accumulation in several monocotyledonous  might be regulated at time points of elicitor treatment not assayed in this work. Clearly, regulation of multiple miRNAs exhibiting regulatory links with auxin signaling during PTI responses might provide a fine tune regulation of gene expression in controlling resistance to different types of plant pathogens.MIR168a promoter in transgenic Arabidopsis further supports that MIR168 is regulated at the transcriptional level. The observed transcriptional activation of MIR168 is consistent with the presence of various pathogen- and elicitor-responsive cis-elements in the MIR168 promoter. Finally, by using GFP-miR168* sensor plants we demonstrated that the elicitor-induced miR168 is active.On the other hand, our study revealed that miR168, a miRNA that is deeply conserved among plant species, is transcriptionally regulated by fungal elicitors. Several lines of evidence support this conclusion. Firstly, we demonstrated that mature miR168 rapidly accumulates in response to elicitor treatment. Secondly, expression of miR168 precursors is also up-regulated upon elicitor treatment. Thirdly, functional analysis of the MIR168 and AGO1 and preferential stabilization of miR168 by AGO1 [AGO1 transcripts in elicitor-treated tissues relative to control tissues (i.e. differences between elicitor and control plants progressively diminished during elicitor treatment). On the basis of these data, we can hypothesize that a transcriptional regulation of MIR168 might be responsible for the control of AGO1 accumulation early during elicitor treatment. If so, the transcriptional regulation of MIR168 would represent another layer of control of the refined regulatory system that controls miR168 levels and AGO1 levels. Presumably, an elicitor-regulated adjustment of miR168 levels might contribute to the maintenance of the appropriate levels of AGO1, and accordingly of miRNA functioning, during the plant defense response to pathogen infection.It is well established that miR168 plays a critical role in miRNA functioning by controlling AGO1 homeostasis. Thus, AGO1 homeostasis entails coexpression of  by AGO1  .In thisBrassica napus) infected with the soil-borne pathogenic fungus Verticillium longisporum (at 6 days after inoculation). Furthermore, Weiberg et al. [Botrytis cinerea hijack the host RNAi machinery by binding to AGO1 and selectively silencing host immunity responses. Together, these pieces of evidence strongly support that miR168/AGO1 modulation might play an important role in shaping host responses to pathogen infection, including infection by fungal pathogens. In other studies, miR168 was reported to be induced by abiotic stresses  [In the literature there are several reports on the involvement of AGO1 in plant antiviral defense . AGO1 alg et al.  demonstry, cold) . Then, ibona fide hc-siRNA that is dependent on Pol IV/RDR2/DCL3/AGO4 for its biogenesis and function. This small RNA sequence was incorrectly annotated as a miRNA and, accordingly, this entry may be removed from future database releases.On the other hand, our microarray analysis of Arabidopsis small RNAs allowed us to identify a small RNA (24-nt in length) that transiently accumulates in response to fungal elicitors. Most importantly, analysis of mutants impaired in the small RNA biogenesis pathways revealed that production of this 24-nt siRNA is dependent on the DCL3/RDR2/Pol IV pathway, its accumulation being also reduced by mutations in Pol V and AGO4. As previously mentioned, biogenesis of hc-siRNAs begins with the transcription by RNA Pol IV, which is then followed by RDR2-catalyzed synthesis of dsRNA. Then, si-RNAs (24-nt) are processed from the dsRNAs by DCL3, and loaded into AGO4-containing RISCs. Besides, the function of the AGO4-assembled hc-siRNAs requires the production of a scaffold transcript by Pol V which recruits the AGO4-bound hc-siRNAs. Based on the results obtained in this work, it is concluded that siRNA415 is a In plants, hc-siRNAs are involved in transcriptional gene silencing by guiding DNA methylation at target genomic loci through RNA-directed DNA methylation (RdDM) , 58. A mCMT3 transcripts. The CMT3 gene encodes CHROMOMETHYLASE3, a protein involved in RdDM. The finding that miR823 is affected by fungal elicitors raises interesting questions concerning the mechanisms by which this particular miRNA might exert its regulatory role in plant immunity by controlling CMT3 expression and RdDM.The scaffolding model for the function of AGO4-associated hc-siRNAs in RdDM implies recruiting DNA methyltransferase enzymes by transcripts being transcribed by Pol V. In this context, DNA methylation in RdDM is maintained by the overlapping functions of Methyltransferase 1 (MET1) and CMT3 in Arabidopsis. Of interest, microarray analysis revealed elicitor-regulation of miR823, this particular miRNA targeting A. thaliana immune system by DNA demethylation whereby DNA methylation imparts persistent control over some defence genes during non stressful conditions, but can change dynamically to alter gene expression in response to biotic stress [Concerning the involvement of RdDM in mediating regulation of plant immune responses, this issue has only recently come to light . Recent c stress . The conc stress , 73. Becc stress .In summary, results here presented will help in understanding the contribution of small RNAs, both miRNAs and siRNAs, in the Arabidopsis response to pathogen infection while providing new opportunities to elucidate the molecular events controlling plant disease resistance.AGO1 transcripts. We demonstrated that MIR168 is transcriptionally regulated by fungal elicitors. These finding suggest that miR168 contributes to the maintenance of the appropriate levels of AGO1, and hence miRNA functioning, in the response of Arabidopsis plants to fungal elicitors. Additionally, we identified an elicitor-regulated hc-siRNA (named siRNA415) which was incorrectly annotated as a miRNA. These results, toghether with the observation that miR823 (targeting CHROMOMETHYLASE3 transcripts) further support a function of RNA-directed DNA methylation processes in mediating plant immune responses. This work represents an effort to identify relevant small RNAs regulating the Arabidopsis response to pathogens that may have relevance to study other pathosystems.In this study microarray analysis was used to identify small RNAs, miRNAs and siRNAs whose accumulation is regulated by treatment with fungal elicitors in Arabidopsis. Among the elicitor-regulated miRNAs was miR168, this miRNA controlling the level of A. thaliana was used for this study. Plants were grown on MS0 solid medium at 22 ± 2°C during 15 days under neutral day conditions (12 h light/12 h dark). Fungal elicitors were prepared from the fungus Fusarium oxysporum (strain 247) as previously described [dcl1-9, dcl2-1, dcl3-1, dcl4-2, rdr1-1, rdr2-1, rdr6-15, ago4-1, nrpd2 , nrpe1[Landsberg erecta  and Columbia 0 .Columbia 0 (Col 0) accession of escribed . For thim strain 7 as prev), nrpe1, 73. TheGFP-miR168* sensor construct was prepared as previously described [GFP coding region by PCR. Amplified fusions were cloned into pGEM-T Easy and then inserted into pBIN61 binary vector under the control of the 35SCaMV promoter. For preparation of the miR168 promoter-GFP construct, a 2 kb fragment upstream of the miR168a precursor was amplified from Arabidopsis genomic DNA and cloned into pMDC110 binary vector upstream of the GFP reporter gene. Primers used for PCR are listed in Additional file Agrobacterium tumefaciens strain GV3013 and introduced into Arabidopsis sde1 mutants (C24 background) [The escribed . Essentikground)  by the fFor microarray analysis, three sets of RNA samples representing the three biological replicates for each time point  and condition (control and elicitor-treated) were prepared. Equal amounts of total RNA from each biological replicate were pooled and used for isolation of the small RNA fraction using the miRVana™ miRNA Isolation kit (Ambion®).http://microrna.sanger.ac.uk), 553 predicted miRNAs, and 1096 small RNA sequences generated by MPSS [C. elegans and D. melanogaster miRNAs  were included in the array.The array contained 2,382 probes encompassing: 166 Arabidopsis miRNAs currently annotated in miRBase  for normalization and error correction. Averages of three biological replicates of normalized values were taken to calculate the expression ratios between elicitors and controls prior to log10 transformation. P-values for differential expression calculated by Rosetta Resolver Biosoftware were further adjusted for multi-hypothesis testing using the Benjamini & Hochberg procedure, as implemented in the Bioconductor multtest package in R (http://www.bioconductor.org/packages/bioc/stable/src/contrib/html/multtest.html) as described [http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59978).Probe labeling and array hybridization were performed using the NCode™ miRNA Labeling System , according to the manufacturer´s instructions. Hybridized arrays were scanned with a GenePix 4200A scanner  as previously described , 77. Rawescribed , 77. Pro18 . A specific stem-loop primer was used for miR168 amplification  gene was used as the internal control for normalization. The average cycle threshold (Ct) values from triplicate PCRs were normalized to the average Ct values for the Ubiquitin-10 gene from the same RNA preparations yielding the ΔCt value. Two independent biological replicates were analysed. T-Student tests were used to evaluate differences in gene expression. Controls of the qRT-PCR reactions without adding the reverse transcriptase enzyme were systematically included in our experiments.Reverse transcription reactions were performed using total RNA from Arabidopsis seedlings. The same plant material used for small RNA extraction was also used for total RNA extraction. First-strand cDNA was synthesized from DNase-treated total RNA (3 μg) with SuperScript III reverse transcriptase (Invitrogen GmbH) and oligo-dT32P-ATP end-labelled oligonucleotides complementary to the small RNA sequence under study. Probes used for Northern blot analysis are indicated in Additional file Total RNA was extracted using the TRIzol® reagent (Invitrogen™) according to the manufacturer’s instructions. For small RNA Northern blot analysis, total RNAs were fractionated in a 17.5% polyacrylamide gel containing 8 M urea. As probes we used γhttp://www.ncbi.nlm.nih.gov). In each case, the 2 kb upstream sequence from the start of the miRNA precursor was scanned for the presence of cis-elements using the web-based analysis tool PLACE, Plant Cis-acting Regulatory DNA Elements (http://www.dna.affrc.go.jp/PLACE/). The overrepresentation of known promoter cis-elements and motifs was assessed using the POBO application (http://ekhidna.biocenter.helsinki.fi/poxo/pobo/pobo) [The DNA sequences upstream of the start of the miRNA precursor structure of miR168a and miR168b were extracted from NCBI (bo/pobo)  Statistihttp://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59978).The microarray data obtained in this study have been deposited in NCBI's Gene Expression Omnibus (GEO) database under the accession number GSE59978 (Table S2. cis-elements identified in the MIR168a and MIR168b promoters. Table S3. Sequences of oligonucleotides used in this study. (PDF 183 KB)Additional file 1: Table S1: Arabidopsis small RNAs represented in the microarray. http://ekhidna.biocenter.helsinki.fi/poxo/pobo/pobo). Figure S2. Accumulation of siRNA415 in control (c) and elicitor-treated (e) Arabidopsis plants. (PDF 222 KB)Additional file 2: Figure S1: Frequency of occurrence of defence-related cis-elements in the MIR168a promoter generated in POBO (