AND and NOT Boolean logic elements, which could ultimately be used to restrict the release of functionally relevant nucleic acid constructs to specific cellular environments defined by the high or low expression of particular RNA biomarkers. Each system is generalizable and designed with future therapeutic development in mind. Every construct assembles through nuclease-resistant RNA/DNA hybrid duplex formation, removing the need for additional 2′-modifications, while none contain any sequence restrictions on what can define the diagnostic trigger sequence or the functional oligonucleotide output.Several varieties of small nucleic acid constructs are able to modulate gene expression via one of a number of different pathways and mechanisms. These constructs can be synthesized, assembled and delivered to cells where they are able to impart regulatory functions, presenting a potential avenue for the development of nucleic acid-based therapeutics. However, distinguishing aberrant cells in need of therapeutic treatment and limiting the activity of deliverable nucleic acid constructs to these specific cells remains a challenge. Here, we designed and characterized a collection of nucleic acids systems able to generate and/or release sequence-specific oligonucleotide constructs in a conditional manner based on the presence or absence of specific RNA trigger molecules. The conditional function of these systems utilizes the implementation of  Deliverable nucleic acid-based systems present powerful methods to modulate specific gene expression and have the potential to be developed for therapeutic purposes, however, restricting their activity to a subset of intended cells remains challenging ,2,3. NumStrategies to date for cell-specific functions of nucleic acid constructs can largely be divided into two categories: targeted delivery and conditional activation. Targeted delivery most often involves the conjugation of a functionally active nucleic acid to a small molecule, protein, aptamer or other targeting agent that interacts with a receptor specifically expressed on the target cells of interest ,15,16,17Conditional activation represents an opposite approach to targeted delivery, in which the functional nucleic acid could be systemically delivered in an inactive state and only performs its active function in a subset of specified cells. This can be achieved through the implementation of nucleic acid logic elements that promote generation of a functional oligonucleotide construct through recognition of a specific cellular environment. The occurrence of disease can often be the result of, as well as result in, the mis-regulation of gene expression, and these differentially expressed genes can be used as biomarkers to distinguish corrupted cells from healthy tissue ,19,20. NHere, we present the design of several new systems for the conditional release of single-stranded (ss) and double-stranded (ds) nucleic acid constructs that are specifically tailored to meet these criteria of ideal characteristics, which many existing systems fail to adequately satisfy. These designs are influenced by several existing nucleic acid technologies such as cognate RNA/DNA hybrids, molecular beacons, and trigger-responsive multi-stranded switch constructs ,32,33,34The computational folding of individual strands and assembly of DNA/RNA constructs was assessed using Hyperfold , a nucleThe DNA and RNA oligonucleotides used to assemble the conditional RNA/DNA constructs, including those that were fluorescently labeled, were purchased from Integrated DNA Technologies  and reconstituted in nuclease-free water  for use. All AlexaFluor546, AlexaFluor488 and 6-carboxyfluorescein (6-FAM) fluorescently labeled oligonucleotides were purchased from IDT. For commercially purchased oligonucleotides, 10 nmol quantities were purified as needed by denaturing polyacrylamide gel electrophoresis (PAGE). Specifically, 10 nmol quantities were mixed with 100 uL urea loading buffer , 10% glycerol, 0.05% bromophenol blue) and heated to 90 °C for 2 min prior to loading on an 8% or 10% 19:1 acrylamide/bis-acrylamide denaturing gel , 6 M Urea) for purification. Following electrophoresis, bands were cut from the gel and eluted in an elution buffer  overnight at 4 °C while shaken at 850 rpm. Eluted oligonucleotides were ethanol precipitated and reconstituted in nuclease-free water.2, 0.5 mM MnCl2, 2.5 mM each NTP, 0.01 u/µL inorganic pyrophosphatase, 2 mM dithiothreitol, and 2 mM spermidine. Approximately 50 pmol of DNA template was added to the transcription mix along with an in-house produced T7 RNA polymerase and incubated at 37 °C for 4 h. Transcription was terminated by addition of DNase I  for 30 min. The transcription mix was combined with 1/2 volume of urea loading buffer and heated at 90 °C for 2 min before purification by denaturing PAGE and precipitation as described above.RNA trigger oligonucleotides either purchased from IDT or prepared from in vitro runoff transcription using T7 RNA polymerase. DNA templates for transcription were amplified by PCR using primers purchased form IDT. PCR was performed using MyTaq 2× mix  and purified using DNA Clean & Concentrator . Transcription was performed in 10 mM Tris pH 7.0 containing 6 mM MgCl2, 50 mM KCl, 1× TB . The assembly was then incubated an additional 25 min at 37 °C. Control dsRNA duplexes and RNA trigger molecules were assembled/folded using the same protocol.Conditional RNA/DNA constructs were assembled using equimolar concentrations of their component strands. Strands were combined in water, heated to 90 °C for 1.5 min, and then immediately placed on a 37 °C heat block for 5 min. After this, samples were briefly spun in a tabletop centrifuge to collect condensed solvent and assembly buffer was added to a final 1× concentration of 2 mM Mg(OAc)2, 1× TB). Electrophoresis was generally performed at 6 W for 2–3 h at 10 °C. Acrylamide concentrations and duration of electrophoresis were optimized on a case-by-case basis to achieve the necessary separation of species. In some instances, gels were subjected to total nucleic acid staining with ethidium bromide. In other instances, an individual molecule within a construct was fluorescently labeled . In both cases, gels were imaged using a Typhoon Trio variable mode imager  using appropriate excitation and emission filters. The amount of fluorescently labeled dsRNA output released from conditional systems was quantitated using ImageQuant 5.1 , Chicago, IL, USA). Unless otherwise noted, the fraction of dsRNA released for a given sample is reported as the ratio of fluorescence observed in the released dsRNA band to the total amount of fluorescence observed for the entire lane. Statistical significance between populations was determined by a two-tailed Student’s t-test performed using values from three distinct replicate experiments.Assembled constructs were examined for their ability to regulate conditional oligonucleotide release in the presence and absence of specific RNA trigger molecules. All constructs and triggers were initially prepared separately in 1× assembly buffer. From these bulk individual assemblies, various construct/trigger combinations were combined and incubated at 37 °C for either 30, 90 or 180 minutes. Individual controls were prepared from the same bulk assemblies and subjected to identical incubation conditions. Generally, the conditional constructs were present at a final concentration of 500 nM. In the case of the beacon switch and adjacent targeting hybrids, RNA triggers were present in a 1× concentration relative to the conditional constructs. For inducible and repressible hybrid systems, the RNA triggers were generally present at 2×–3× concentrations, as indicated in the text. Following this incubation, samples were transferred to ice, combined with 1/5 volume of loading buffer  and were loaded on non-denaturing PAGE gels RNA/DNA strand exchange between cognate partners of inducible and repressible hybrid systems were examined by FRET. Cognate hybrids were assembled separately, and pre-warmed to 37 °C. Hybrids were combined and added to the cuvette, at which point the RNA trigger molecule was spiked in, if appropriate. The cuvette was immediately placed in a FluoroMax-3 fluorimeter  at 37 °C and measurement was started. For FRET experiments where a fluorescence spectrum was measured at a given time point, the sense hybrid was assembled with an RNA sense strand containing a 3′ 6-FAM donor fluorophore, while the antisense hybrid was assembled with an RNA antisense strand possessing a 5′ AlexaFluor546 acceptor fluorophore. Hybrids were prepared to a final concentration of 250 mM and the trigger molecule was in three-fold molar excess, when present. Excitation was performed at 475 nm and emission measured between 480–620 nm at 1 nm increments using 0.5 s integration times and 2 nm slit widths. obs) were obtained by fitting the decrease in measured AlexaFluor488 donor fluorescence as a function of time to the equation y = y0 + Ae−k*t for single exponential decay.For FRET experiments where time courses were recorded, the 6-FAM donor fluorophore on the RNA sense strand was replaced with AlexaFluor488. Hybrid and trigger concentration mirrored the conditions of analogous non-denaturing PAGE experiments, with hybrids at a final concentration of 500 nM, and trigger concentrations in 2–3 fold molar excess, as indicated. Measurements were recorded every 60 s using excitation at 475 nm and emission was measured at 515 nm and 565 nm, using a signal integration time of 0.5 s and slit widths of 2 nm. Observed rate constants  mRNA as a trigger and release an RNA antagomir output strand in a conditional fashion. Analysis of beacon switch assembly and conditional output release was performed by non-denaturing polyacrylamide gel electrophoresis (PAGE) C. AssembsH) and the antisense hybrid (aH), respectively. The “traditional” approach to cognate hybrid design utilized complementary single stranded toeholds emanating from sH and aH, with hybridization of these toeholds to one another initiating RNA/DNA strand exchange. Here, we have redesigned the toeholds to be complementary to adjacent regions of an RNA trigger sequence, rather than complementary to one another. As the toeholds can no longer drive strand exchange by hybridization to one another, release of the dsRNA product is conditional on the presence of the RNA trigger molecule.Cognate RNA/DNA hybrid pairs were previously designed that harbor split functional RNAs, devised to release a recombined functional dsRNA through recognition of complementary single stranded toeholds A 31,37,,37,38. TUPaH. Similarly, the sense hybrid is referred to as DOWNsH. Binding of the cognate hybrid pair to the trigger RNA positions the two RNA/DNA hybrid regions adjacent to one another in space. The close proximity of the trigger-bound cognate hybrids will induce strand exchange through progressive hybridization of the trigger-bound DNA strands to one another, forming a three-way junction with the RNA trigger, and leading to formation and release of a dsRNA product. Like the beacon-derived switch, this activatable RNA/DNA hybrid system could find use in instances where a cell population of interest can be distinguished by the high relative expression level of an endogenous RNA. However, this RNA/DNA hybrid system (and those that follow) could be of use in cases where conditional generation of a double-stranded RNA is desirable, which could take the form of an RNA interference substrate, saRNA, aptamer, or another functionally relevant dsRNA. In this instance, the dsRNA product was designed as a 25/27-mer DsiRNA.In this “adjacent targeting” incarnation of the RNA/DNA hybrid system, a fragment of the connective tissue growth factor (CTGF) mRNA was used as the RNA trigger sequence, acting as a template for DNA toehold binding which in turn initiates strand exchange B. Since UPaH/DOWNsH cognate pair did not induce strand exchange and dsRNA release when co-incubated with the CTGF trigger for 180 min  needed to facilitate strand exchange was altered based on the presence or absence of a specific RNA trigger sequence. Although the adjacent targeting hybrid system described above performs its designed conditional function to release dsRNA, the fraction of dsRNA release for the best performing hybrid pair topped out at 0.67 after three hours. This second approach was pursued in an attempt to improve the efficiency of strand exchange and increase conditional dsRNA release. The “traditional” RNA/DNA hybrid methodology requiring the hybridization of complementary toeholds to one another for strand exchange serves as the basis of the conditional activation. We designate these single stranded toeholds as “exchange toeholds”, since they are required to initiate strand exchange. To create a hybrid system responsive to conditional activation, a structured hairpin element was incorporated in the DNA strand immediately adjacent to the RNA/DNA hybrid duplex region of the sense hybrid A. This DA new single stranded toehold, termed the “diagnostic toehold”, is then implemented as a means to control the conditional activation of the hybrid by altering the accessibility of the exchange toehold imbedded within the DNA hairpin upon recognition of a specific RNA trigger sequence A. This s^CTGF.12/8sH, as the hybrid is designed to stimulate dsRNA release in the presence of CTGF (“^CTGF”) and contains a DNA hairpin composed of a 12 bp stem and 8 nt loop (“12/8”). The exchange toehold within ^CTGF.12/8sH is 12 nt in length and is initially completely sequestered within the DNA hairpin stem. The cognate partner hybrid is composed of an RNA/DNA hybrid duplex containing the DsiRNA antisense strand, with a 12 nt extension of the DNA strand at its 3′ end to encode the complementary exchange toehold. This hybrid is referred to as ^CTGF-cgnt.12aH to reflect that it contains a 12 nt exchange toehold (“12”) and is the cognate partner (“cgnt”) to the CTGF-triggered sH hybrid (“^CTGF”).To illustrate the function of this “trigger-inducible” hybrid system, conditional hybrid constructs were designed to release a 25/27-mer DsiRNA when triggered by a fragment of the CTGF mRNA. The DNA strand of the sense hybrid was designed to contain a central hairpin with a 12 bp stem and 8 nt loop. This sense hybrid is referred to as ^CTGF.12/8sH and induces the release of a dsRNA product when ^CTGF-cognt12aH is also present. Higher migrating species are also observed when both hybrids are co-incubated with the trigger RNA. One of the high migrating bands corresponds to the expected waste product as indicated by similar migration of a control assembled from the RNA trigger and two DNA strands. An even slower migrating band is also observed and is likely to be a 5-molecule intermediate complex. Förster resonance energy transfer (FRET) experiments were performed to further verify the generation of the expected double stranded RNA product in the presence of the trigger molecule  and was observed to marginally increase over time for each variant ^CTGFsH construct paired with ^CTGF-cgnt.12aH  between the unbound and CTGF trigger-bound states for each hybrid’s responsive DNA element (−1 for each) that the comparatively small differences in ΔΔG between the various ^CTGFsH hybrids becomes inconsequential. Alternatively, differences in the ΔΔG of trigger binding could be offset by differences in steric accessibility of the newly liberated exchange toehold once the DNA hairpin has opened. Increasing the loop size or length of the hairpin stem increases the distance between the exchange toehold and the region bound by the RNA trigger once hybridized . Larger scores indicated greater efficiency of conditional dsRNA release. Out of the eight pairs of CTGF-inducible hybrids and the five sets of adjacent-targeting hybrids, the ^CTGF.20/8sH/^CTGF-cgnt.12aH pairing displays the highest efficiency score for each time interval that was examined  displays a repressed ability to generate dsRNA in the presence of the CTGF trigger, as intended  present on each of the two hybrids, it is possible to generate a system in which the accessibility of each toehold is under the control of a different RNA trigger sequence. In the case of the trigger-repressible hybrids, such as ^CTGF.20/8sH was partnered with aH∨KRAS to generate a pair of conditional RNA/DNA hybrids whose function is dependent on the presence or absence of two RNA triggers, CTGF and KRAS  to KRAS trigger (deactivating) increases the extent of dsRNA release (The degree to which dsRNA could be conditionally released from this cognate hybrid pair was assessed by non-denaturing PAGE B and FRE release . When eq^CTGF.20/8sH hybrid. The 8 nt hairpin loop is removed, splitting the 20 bp hairpin into a duplex that assembles from two distinct DNA strands. One DNA strand retained the 5′ diagnostic toehold, while the other maintained the RNA/DNA hybrid region (^CTGF.20splitsH” and works in conjunction with ^CTGF-cgnt.12aH. Analysis by non-denaturing PAGE illustrates that the three-piece hybrid ^CTGF.20splitsH appears to function very similarly to that of ^CTGF.20/8sH, although the three-piece hybrid seems to have a slight increase in its degree of non-triggered dsRNA release (With both of the inducible and repressible conditional systems described above, the entirety of the hybrid construct containing the diagnostic toehold remains bound to the RNA trigger molecule following recognition and hybridization of the diagnostic toehold. However, one can imagine that there may be instances where the function of the conditional hybrid systems may benefit from allowing their RNA/DNA hybrid domains to freely diffuse away from their cognate trigger following hybridization through their diagnostic toehold/domain. A three-strand design approach was used to create an inducible hybrid that separates from the RNA trigger after hybridization. The design is based on that of the d region . This ne release . aH∨KRAS hybrid. A nick was positioned within the 5′ strand of the DNA hairpin, aiming to maintain stable formation of the initial 14 bp hairpin and allow strand exchange in the absence of the KRAS trigger. Four different variants were designed to identify a nick position that retained the greatest conditional function. The function of the four variants partnered with sH∨KRAS-cgnt was examined by non-denaturing PAGE (aH∨KRAS.nick14”, where the nick was placed immediately below the hairpin loop and preserves the entire 14bp stem, displayed the greatest degree of conditional function. Progressively moving the nick down the stem resulted in continued loss of the responsive function to the KRAS trigger.A similar approach was used to investigate a three-strand repressible hybrid construct based on the ing PAGE . Each ofDue to their ability to easily store and recognize information at the level of their primary sequence, nucleic acids serve as an excellent material for the construction of logic elements and performance of molecular computing ,40. NuclFor a conditional RNA-based therapeutic system to be considered for practical application, it likely needs to fulfill three essential criteria: first, the RNA components must be protected from potential ribonuclease degradation; second, the sequences of the trigger input and the oligonucleotide output must be functionally and structurally independent from one another, such that either can be altered without necessitating a change in the other; and, third, the systems must be cheap and easy to produce, meaning that the use of modified nucleotides should be kept to a minimum. Previous incarnations of conditional RNA therapeutic systems have struggled to simultaneously fulfill these criteria. An early scheme for conditional Dicer substrate generation by Masu et al. utilized a hairpin design similar to that of a molecular beacon, where trigger binding to the loop unpairs an adjacent stem and allows formation of the functional sense-antisense hybrid . This coA similar approach was designed by Xie et al. whereby an antisense strand was pre-annealed to a chemically modified “protector” strand and this complex was co-delivered with a single-stranded sense RNA. The protector strand contained significant overhangs on each end and was completely complementary to a trigger RNA, allowing hybridization to the trigger to drive antisense release and siRNA formation . This apAND gates, releasing a double stranded RNAi substrate based on the presence of a single RNA trigger. We demonstrate in this current work that these next-generation RNA/DNA hybrid systems can be based on AND gates, NOT gates and combinatorial systems able to sense multiple biomarker triggers. Furthermore, although the proof of principle demonstrations we have presented here release a single dsRNA duplex from each RNA/DNA hybrid system, it should be possible to release multiple different dsRNA products in a conditional fashion from a single pair of conditional RNA/DNA hybrids, as this has been demonstrated previously with the “traditional” hybrid approach [The original incarnation of split-function RNA/DNA hybrid pairs from Afonin et al. lacks a true diagnostic component that would be able to sense an RNA biomarker but was able to successfully separate the output oligonucleotide sequences from the toehold regions that controlled the conditional strand–exchange reaction. Importantly, they were able to demonstrate that formation of an RNA/DNA hybrid duplex both protected the RNA from degradation and prevented the initial duplexes from being processed by Dicer . As descapproach . As an a


RNAs (exRNAs) in biofluids have attracted great interest as potential biomarkers. Although extracellular microRNAs in blood plasma are extensively characterized, extracellular messenger RNA (mRNA) and long non‐coding RNA (lncRNA) studies are limited. We report that plasma contains fragmented mRNAs and lncRNAs that are missed by standard small RNA‐seq protocols due to lack of 5′ phosphate or presence of 3′ phosphate. These fragments were revealed using a modified protocol (“phospho‐RNA‐seq”) incorporating RNA treatment with T4‐polynucleotide kinase, which we compared with standard small RNA‐seq for sequencing synthetic RNAs with varied 5′ and 3′ ends, as well as human plasma exRNA. Analyzing phospho‐RNA‐seq data using a custom, high‐stringency bioinformatic pipeline, we identified mRNA/lncRNA transcriptome fingerprints in plasma, including tissue‐specific gene sets. In a longitudinal study of hematopoietic stem cell transplant patients, bone marrow‐ and liver‐enriched exRNA genes were tracked with bone marrow recovery and liver injury, respectively, providing proof‐of‐concept validation as a biomarker approach. By enabling access to an unexplored realm of mRNA and lncRNA fragments, phospho‐RNA‐seq opens up new possibilities for plasma transcriptomic biomarker development.Extracellular  This approach, which we refer to as “phospho‐RNA‐seq”, revealed a large, untapped space of mRNAs and lncRNA fragments present in plasma. These fragments comprised tissue‐specific signatures that reflected biological processes of bone marrow reconstitution and acute liver injury in hematopoietic stem cell transplant (HSCT) patients. We propose that this approach opens up new opportunities for disease biomarker discovery through transcriptomic analysis of exRNA fragments in circulation., we prepared small RNA libraries using this pool as input and following two different strategies: (i) standard ligation‐based methodology  and (ii) our modified phospho‐RNA‐seq approach . Libraries were multiplexed, sequenced on a NextSeq platform, and analyzed as described in To evaluate the performance of both standard and phospho‐RNA‐seq methods for recovering short oligonucleotides with varying end modifications likely to be found in human biofluids, we designed a synthetic reference pool comprising 476 ribonucleotides of different length (from 15 to 90 nt) and sequence . More sp, both strategies were able to recover the majority of sequences with 5′ P and 3′ OH in our pool, most of which are human microRNAs. In contrast, the phospho‐RNA‐seq approach recovered sequences that either lacked a 5′ P or had a 3′ P, which were largely undetectable by the standard methodology , we aimed to design and test a pipeline that could enable reliable evaluation of mRNA and lncRNA fragments in real plasma samples, where the exRNA composition is unknown and the risk of false‐positive calling is higher. To this end, we obtained platelet‐poor plasma from five healthy control individuals  red blood cell‐derived transcripts including several types of hemoglobin transcripts ; (ii) platelet‐derived transcripts such as platelet‐derived growth factors ; (iii) ubiquitous, highly expressed transcripts such as ferritin chains , mitoferrin‐1 , conventional non‐muscle myosin , multiple mitochondrial transcripts , and actin transcripts ; (iv) immune‐related transcripts such as MHC class I molecules , interleukins  and myosin IF (MYO1F); and (v) the lncRNAs MALAT‐1 and NEAT1 Fig . As expeAfter having demonstrated that phospho‐RNA‐seq combined with a stringent pipeline is critical for recovering mRNA and lncRNA fragments in plasma, we examined the efficiency of this strategy for capturing microRNAs from plasma by analyzing mature microRNA read counts from healthy donor plasma samples prepared with and without PNK treatment. The microRNA counts were obtained from the sRNAnalyzer alignment stage used in our exRNA processing pipeline. We found that while microRNAs were captured using the phospho‐RNA‐seq method, the standard small RNA‐seq method yielded approximately ten times more microRNA reads Fig A. Althoubona fide microRNAs were detected specifically in PNK‐treated samples, indicating that a small subset of microRNAs may be present in a modified form in plasma that prevents capture with traditional methods. Overall, however, our analysis indicates that standard methods are preferable over phospho‐RNA‐seq when the goal is to exclusively characterize microRNA profiles in plasma.We found that 21 of these additional microRNAs were seen exclusively using standard small RNA‐seq , prepared phospho‐RNA‐seq libraries from each time point, and performed multiplex sequencing using a HiSeq platform physiological processes would be reflected in the expression patterns of mRNA and lncRNA extracellular fragments. To this end, we collected serial plasma samples from patients undergoing allogeneic HSCT  samples. Our results clearly showed that PNK treatment vastly increased the recovery of fragments either lacking a 5′ P or having a 3′ P. This is consistent with the properties of PNK, which has both 5′ kinase and 3′ phosphatase activities  have been designed with a predominant focus on microRNA annotation. Perhaps not surprisingly, we found that when applied to phospho‐RNA‐seq data analysis for mRNA/lncRNA identification, there was a high rate of false‐positive annotation. It is possible that this phenomenon may have affected prior results of plasma exRNA profiling using non‐PNK‐based approaches which, although focused primarily on microRNAs, also commented on the finding of mRNA and lncRNA transcripts in plasma . We speculate that cancer tissue‐specific transcript gene sets could also be developed for detection and longitudinal monitoring of a variety of cancer types.et al, et al, Although most prior plasma exRNA studies have focused on microRNAs, mRNAs in plasma have been reported using methodology other than phospho‐RNA‐seq. In particular, a study using a long RNA‐seq random primer cDNA synthesis protocol detected mRNAs and lncRNAs in plasma , there are certainly still limitations of this approach. Although we expect that most of the cleavage products derived from mRNA/lncRNA in circulation will present 5′ OH and 3′ P due to the abundance of superfamily A RNases in plasma, it is possible that there are exRNAs in plasma with end groups that are not addressed by our methodology . Second, it is worth mentioning that the efficiency of phospho‐RNA‐seq for identifying mRNA/lncRNA fragments is affected by the recovery of other abundant plasma fragments such as ribosomal RNA and Y RNA that can dominate the sequencing data, thus reducing the depth of sequencing available for detecting mRNA and lncRNA fragments. To this end, we foresee that in the future, the sensitivity for detecting relevant mRNA and lncRNA fragments in plasma might be improved by designing specific methods for depleting abundant, undesired fragments such as fragments of rRNAs and Y RNAs, or for enriching fragments corresponding to panels of selected transcripts. It is clear that there is still room for method improvement and there may be many more mRNA and lncRNA fragments in plasma than we have identified here. It is also worth noting that new ligation‐free strategies have been recently developed for small RNA‐seq  286 human microRNAs and (ii) a set of 190 additional, custom‐synthesized RNA oligonucleotides, to generate the pool in which each of the 476 RNA oligonucleotides is present at equimolar concentration. The latter set of 190 RNA oligonucleotides comprises microRNAs and non‐microRNA sequences of varied length from 15 to 90 nt, which were synthesized, HPLC‐purified, and quantified spectrophotometrically by IDT . The pool of RNA oligonucleotides is available to qualified investigators seeking to reproduce the synthetic equimolar for non‐commercial purposes, by request of the corresponding author (as long as supplies last). The resulting equimolar pool was aliquoted in prelabeled DNA‐, DNase‐, RNase‐, and pyrogen‐free screw‐cap tubes with low adhesion surface and stored immediately at −80°C. The complete list of RNA sequences comprising the equimolar pool is provided in et al, g at room temperature for 10 min with high brake; and (ii) 1,940 g at room temperature for 10 min without brake. Plasma was stored at −80°C until RNA isolation. The University of Michigan IRB approved the study protocol to consent participants and collect samples. Informed consent was obtained from all subjects, and the samples were subsequently de‐identified before distributing to the laboratory personnel generating the libraries. The studies conformed to the principles set out in the WMA Declaration of Helsinki and the Department of Health and Human Services Belmont Report.Plasma samples from five healthy donors and serial plasma sample from two patients undergoing allogeneic HSCT were collected in 10‐ml K2EDTA plasma tubes  and processed within one hour of blood draw following a two‐centrifugation protocol to obtain platelet‐poor plasma as previously described  according to the manufacturer's protocol with the following modifications. Plasma samples were mixed with five sample volumes of QIAzol reagent and vortexed for 10 s. Samples in QIAzol were incubated at room temperature for 5 min to inactivate RNases. Next, 0.2 volumes of chloroform were added to each sample. At that point, the manufacturer's protocol was followed.The input for library preparation was 10 femtomoles of RNA for the synthetic equimolar pool and 5 μl of eluted RNA for the biological plasma samples.Standard ligation‐based small RNA libraries were prepared using the TruSeq small RNA kit  according to the manufacturer's instructions. Size selection was performed using pre‐cast 6% acrylamide gels  including all products from 140 to 200 bp plus any additional visible bands of greater size. To perform phospho‐RNA‐seq, synthetic and plasma RNA samples were pretreated with T4 polynucleotide kinase  using an RNA input of 7 μl in a final reaction volume of 10 μl and incubated at 37°C for 30 min following the manufacturer's instructions. After the enzymatic treatment, synthetic RNA samples were heat‐inactivated at 65°C for 20 min and biological RNA samples were purified by performing sequential washes in silica columns : (i) 900 μl of buffer RWT ; (ii) 900 μl of buffer RPE ; (iii) 900 μl of ethanol 200 proof, molecular biology grade ; and (iv) 900 μl of 80% ethanol. Libraries were then prepared using the TruSeq small RNA kit according to the manufacturer's instructions. Size selection was performed as described above. For the libraries generated from patients undergoing HSCT, we narrowed the range of size selection to 140–165 bp to reduce the abundance of contaminants such as Y RNAs.Libraries were multiplexed and sequenced using the Illumina NextSeq 500 (synthetic equimolar pool) and Illumina HiSeq 2500  specifying 75 and 50 bp single‐end runs, respectively.et al, et al, TruSeq adapters and stop oligo sequences were trimmed with cutadapt (v 1.91) using processing steps adapted from the sRNAnalyzer workflow  using STAR  was used to align the preprocessed reads to the equimolar pool sequences. The following alignment parameters were altered from default: outFilterMultimapNmax = 1000000; outFilterMismatchNoverLmax = 0.1; outFilterMatchNmin = 15; outFilterMatchNminOverLread = 0.9; outMultimapperOrder = Random; outSAMtype = BAM Unsorted; outSAMunmapped = Within; outSAMattributes = All; outSAMprimaryFlag = AllBestScore; alignIntronMax = 1; alignIntronMin = 2; alignSJDBoverhangMin = 999. Read alignments were loaded into R for processing and analysis. Alignments were further filtered, requiring the alignment to match at least 90% of the synthetic pool sequence in the sense orientation, and be at least 15 nt in length after soft‐clipping. Read counts were scaled for multi‐mapping, dividing the counts by the number of valid alignments obtained from the “NH” tag in the bam alignment file.Read counts for mature human microRNAs were taken from the sRNAnalyzer “.profile” counts generated in the processing pipeline. Only read counts with ≤ 1 mismatch in the sense orientation were used. Read counts for each microRNA were summed across technical replicates. Library size‐adjusted read counts were calculated as counts per million.http://www.mirbase.org/). Accession numbers missing from the coordinate gff files corresponded to microRNAs removed from miRBase due to lack of functional evidence and were annotated as “missing from miRBase”. Transposon and repeat‐associated microRNAs were annotated by overlapping microRNA coordinates with the RepeatMasker coordinates , requiring a minimum of 1 nt overlap in either orientation.MicroRNA genomic coordinates (GRCh38) were obtained from miRBase V22  was used to process and analyze healthy control samples for a healthy control (ULMC135), prepared using both the standard TruSeq small RNA library protocol and the modified phospho‐RNA‐seq method. Default exceRpt pipeline parameters were used, except to set the minimum read length to 16, and to specify TruSeq small RNA adapters for trimming. Read counts from GENCODE transcripts were obtained from the post‐processed exceRpt output files and were compared with the ULMC135 read counts from our pipeline collected at: (Stage 1) after adapter trimming and size filtering, (Stage 2) after sRNAnalyzer alignment and contaminant removal, and (Stage 3) after genome alignment and removal of RepeatMasker and various endogenous non‐coding RNA coordinate‐based annotations. Reads from each stage were aligned to the human genome with STAR, using the same alignment parameters described above. These parameters were largely copied from those used by the exceRpt pipeline to make the alignments as comparable as possible. Comparison was limited to genes detected by both pipelines. Because the exceRpt pipeline output included only summarized gene abundance, the percent of various endogenous non‐coding RNA or repeat‐aligned reads were based on the alignments from our pipeline. An alignment was considered “sRNA or Repeat‐Aligned” if any alignments for that read overlapped RepeatMasker or GENCODE various endogenous non‐coding RNA coordinates (minimum 1 nt overlap on either strand). Fragments were summarized at the gene level using multi‐mapping‐weighted exon‐aligned fragments, comparable to that used by the exceRpt pipeline for gene‐level quantification.The exceRpt small exRNA analysis pipeline (v 4.6.2) implemented on the Genboree Workbench  coordinates were extracted from GENCODE (v27) protein‐coding and long non‐coding RNA annotations. RepeatMasker and sRNA‐filtered genomic alignments from the five healthy individuals were intersected with these coordinates, requiring a minimum of 1 bp of overlap in either orientation. Ambiguous annotations were allowed, but counted only once per unique combination of read and feature. Read alignments were considered “Sense” or “Antisense” based on the relative orientation of the read alignment and the mRNA or lncRNA feature. Read length distributions and gene abundance were calculated based on sense‐aligned exonic reads.et al, et al, n = 5) to test a range of fold‐change estimates . The estimate that maximizes the log likelihood was then used for a second run of the algorithm with a higher number of iterations (100). Significantly altered genes were selected at an FDR cutoff of 0.01  method, suitable for sparse data sets (Chen et al, Databases of tissue‐enriched genes were obtained from GTex and Human Protein Atlas data curated by the TissueEnrich R package (Jain & Tuteja, MDG and MTe conceived of the project. MDG and AE designed and performed the experimental work. MDG, RMS, AE, SWC, DJG, and MTe interpreted the results. MDG, RMS, and MTe wrote the manuscript. RMS designed and implemented the computational pipeline and performed the data analysis. MTe, SWC, and MTu designed the human subject studies. MTu and AJG carried out human subject studies, and AJG performed clinical data abstraction. All authors read the manuscript and provided input.The authors declare that they have no conflict of interest.AppendixClick here for additional data file.Expanded View Figures PDFClick here for additional data file.Table EV1Click here for additional data file.Table EV2Click here for additional data file.Table EV3Click here for additional data file.Table EV4Click here for additional data file.Review Process FileClick here for additional data file.


Na+leak channel, non-selective) is a conserved, voltage-insensitive cation channel that regulates resting membrane potential and neuronal excitability. UNC79 and UNC80 are key regulators of the channel function. However, the behavioral effects of the channel complex are not entirely clear and the neurons in which the channel functions remain to be identified. In a forward genetic screen for C. elegans mutants with defective avoidance response to the plant hormone methyl salicylate (MeSa), we isolated multiple loss-of-function mutations in unc-80 and unc-79. C. elegans NALCN mutants exhibited similarly defective MeSa avoidance. Interestingly, NALCN, unc-80 and unc-79 mutants all showed wild type-like responses to other attractive or repelling odorants, suggesting that NALCN does not broadly affect odor detection or related forward and reversal behaviors. To understand in which neurons the channel functions, we determined the identities of a subset of unc-80-expressing neurons. We found that unc-79 and unc-80 are expressed and function in overlapping neurons, which verified previous assumptions. Neuron-specific transgene rescue and knockdown experiments suggest that the command interneurons AVA and AVE and the anterior guidepost neuron AVG can play a sufficient role in mediating unc-80 regulation of the MeSa avoidance. Though primarily based on genetic analyses, our results further imply that MeSa might activate NALCN by direct or indirect actions. Altogether, we provide an initial look into the key neurons in which the NALCN channel complex functions and identify a novel function of the channel in regulating C. elegans reversal behavior through command interneurons.NALCN ( Na+leak channel, non-selective) channel is a non-selective, voltage-independent cation channel broadly expressed in the animal kingdom  phenotype, disrupted circadian rhythm and resistance to the volatile anesthetics halothane  as key regulators the NALCN channel  mutants of unc-79 or unc-80 phenocopy nca-2(lf); nca-1(lf) double mutants  is the volatile methyl ester of salicylic acid produced by many plants, and is widely used in medicated oils or mouthwash . InteresC. elegans exhibits a strong avoidance response to MeSa and can be useful for understanding the neuronal effects of MeSa  for 1 min.0) were mutagenized with EMS (ethyl methane sulfonate) as described , group two containing three mutants  and group three containing one mutant (mac387) (Table S1). We selected mac379, mac382 and mac388 from group one, and mac383 from group two for genomic sequencing as described  as co-injection marker.For genomic transgene rescue experiments, transgenic mixtures contained 10 to 20 ng/μl genomic PCR fragment and 20 ng/μl pPD95_86 , and 20 ng/μl pPD95_86 (Pmyo-3::GFP) or 2.5 ng/μl pCFJ90 (Pmyo-2::mCherry) as co-injection marker.For neuron-specific knockdown experiments, we used a previously described method with minor modifications (Promoter::unc-80_cDNA and 20 ng/μl pPD95_86 (Pmyo-3::GFP) or 2.5 ng/μl pCFJ90 (Pmyo-2::mCherry) as co-injection marker.For neuron-specific rescue experiments, transgenic mixtures contained 10 to 20 ng/μl sunc-79P-expressing neurons. Images of fluorescence-positive neurons in transgenic animals expressing GFP and/or mCherry reporters were captured using a 63X DIC/fluorescent Leica TCS SP5 II laser confocal microscope and neuronal identities were inferred by overlapping fluorescence signals and by comparing to the anatomical and morphological characteristics of neurons described in Wormatlas (www.wormatlas.org).We used DiI-labeled sensory neurons  as landmP values were determined by Paired two-tailed Student’s t-test or Bonferroni’s multiple comparison using GraphPad Prism 7.0 software.https://doi.org/10.25387/g3.10060007.Strains and plasmids are available upon request. Supplemental Materials and Methods, supplemental Figures and Tables, and raw data for the behavioral experiments (File S1) and raw images for the neuronal labeling (File S2) can be accessed at figshare: To identify novel genes affecting the MeSa avoidance behavior, we performed a genetic screen for mutants that failed to avoid MeSa, from which 15 strains were isolated . Geneticmac379, mac383 and mac387, respectively) for chemotaxis. mac379 and mac383 mutants exhibited wild type-like responses . A comparison of candidate genes found that unc-80 was the only affected gene shared by mac379, mac382 and mac388, with W1524stop, W220stop and W1967stop as the respective mutations (Table S1). Besides W1524stop, mac379 also carried a missense mutation (G927R) in unc-80 . Sanger sequencing identified distinct nonsense or splice site mutations in unc-80 from other mutants of group 1 (Table S1).To identify the causal mutations leading to the defective MeSa avoidance, we determined the genomic sequences of unc-79 among the candidate genes for mac383 (group 2) . Considering that unc-80 and unc-79 interact with nca to affect C. elegans behavior .Meanwhile, we identified an R885stop mutation in unc-79 is required for the MeSa avoidance behavior, we performed transgene rescue experiments. Driven by a long endogenous promoter , an unc-79a gDNA transgene (unc-79(mac383) mutants , the unc-79a gDNA transgene only recued the defective MeSa avoidance but not the defective locomotion  and found that it failed to rescue either defective behavior  driven by an unc-80 endogenous promoter  can significantly rescue the defective locomotion and MeSa avoidance of unc-80(mac379) mutants  and unc-80(e1272) animals, two previously described loss-of-function mutants (unc-79(mac383) or unc-80(mac379) mutants . Together, these results suggest that unc-79 and unc-80 are specifically required for C. elegans MeSa avoidance behavior and we isolated loss-of-function mutations in unc-79 and unc-80.C. elegans nca-1 and nca-2 encode functionally redundant NALCN channels  or nca-2(gk5lf) single mutants exhibited wild type-like MeSa avoidance (nca-2(lf); nca-1(lf) double mutants were strongly defective in avoiding MeSa (nca-1 gDNA transgene (Pnca-1), an nca-2 gDNA transgene (Pnca-2), or both transgenes together can strongly rescue the defective MeSa avoidance of the double mutants (unc-79(lf) or unc-80(lf) mutants, nca(lf) double mutants exhibited normal responses to other attractants and repellents  in affecting the MeSa avoidance, we generated double mutants. Consistent with previous findings (unc-79(lf) or unc-80(lf) completely suppressed the “coiler” phenotype of the nca-1(gf) mutants. The double mutants also exhibited defective MeSa avoidance (A gain-of-function (gf) mutation in voidance .NLF-1) is required for axonal localization of NCA proteins  using a CRISPR/Cas9 method (nlf-1(mac409) as the representative loss-of-function allele (nlf-1(mac409lf) itself, or together with nca-1(lf), nca-2(lf) or nca-1(gf), did not cause obviously defective MeSa avoidance (nlf-1(lf) can suppress the “coiler” phenotype of nca-1(gf) mutants, consistent with previous findings  and unc-80(lf) single mutants, or double mutants carrying either unc-79(lf) or unc-80(lf), all exhibited severely defective locomotion  single mutants exhibited weakly defective locomotion, while nca-2(lf) single mutants were moderately defective (nca(lf) double mutants had severely defective locomotion similar to that of unc-79(lf) or unc-80(lf) mutants (nlf-1(lf) mutants exhibited a moderately defective locomotion, which can be enhanced by nca-1(lf) or nca-2(lf) (nlf-1(lf) mutants appeared to be partially improved by nca-1(gf)  mutants . We founca-2(lf) . Howeverca-1(gf) .unc-80, unc-79 and nca are broadly expressed in C. elegans neurons    . The expression of nlf-1 in AVA and AVE was also described previously  mutants (Punc-80). Still, the locomotion was partially rescued while the MeSa avoidance was more strongly rescued. The nlf-1 promoter had a similar rescuing effect as the unc-80 promoter (Pnlf-1), consistent with the result that unc-80 and nlf-1 were co-expressed in multiple neurons .To understand the function of  mutants , Punc-80promoter , Pnlf-1,unc-80 transgene might be effective in a subset of unc-80-expressing neurons, we tested the nmr-1 promoter (Table S3). The Pnmr-1::unc-80 transgene significantly rescued the defective MeSa avoidance but not the defective locomotion of unc-80(lf) mutants (Pnmr-1). The glr-1 promoter (Table S3), which also drives transgene expression in AVA, AVE and AVG neurons (Pglr-1).To examine whether the  mutants , Pnmr-1. neurons , Pglr-1.unc-80 transgene can be effective in a smaller set of neurons, we tested three other promoters, flp-1, flp-18 and unc-7b (Table S3) . However, when injected together, the three transgenes can significantly rescue the defective MeSa avoidance of unc-80(lf) mutants (Pflp-1/Pflp-18/Punc-7b). Similar to the nmr-1 or the glr-1 promoter, the defective locomotion was not rescued (Pflp-1/Pflp-18/Punc-7b).To determine whether the mgl-1 promoter, which drives overlapping expression with Punc-80 in RMD, I3, I4 and NSM neurons (Pmgl-1::unc-80 transgene failed to rescue either the defective MeSa avoidance or the defective locomotion of unc-80(lf) mutants (Pmgl-1). The sra-11 promoter (Table S3) (Psra-11), consistent with our finding that its expression did not obviously overlap that of Punc-80 .To understand whether other neurons might be involved in the MeSa avoidance behavior, we tested the  neurons  and 3D.  mutants , Pmgl-1.able S3) , Psra-11unc-80 expression in specific neurons is essential for its function, we used a CRISPR/Cas9-based method  mutants.To investigate whether unc-80-targeting sgRNAs (Table S4) and Cas9 driven by the pan-neuronal unc-119 promoter (Table S3) (Punc-119). Limiting the expression of Cas9 to a subset of interneurons, e.g., AVA, AVE and AVG, using the nmr-1 promoter also caused defective locomotion (Pnmr-1). However, Punc-80::Cas9 failed to cause obviously defective locomotion (Punc-80). We postulate that the expression of Punc-80::Cas9 might not be sufficient in disrupting the unc-80 locus in these animals.Transgenic animals expressing two able S3)  exhibitecomotion , Pnmr-1.comotion , Punc-80Interestingly, different from the locomotion, the MeSa avoidance response was not affected in any of the knockdown lines . Using Lunc-79aP to drive an unc-79a_cDNA::GFP transgene , we found similar expression of the UNC-79a::GFP fusion protein in head neurons , ventral nerve cord , vulval muscles , motor neurons  and tail neurons . This transgene also significantly rescued the defective MeSa avoidance and locomotion of unc-79(lf) mutants , similar to that of the unc-79a_gDNA transgene , a pattern similar to that described by Humphrey et al.  was likely non-specific as Lunc-79aP::GFP was not detected there .We next examined the expression of the unc-79 and unc-80 were expressed in the same neurons, we generated transgenic animals co-expressing Lunc-79aP::GFP and Punc-80::mCherry. In these animals, GFP and mCherry co-labeled a large number of head neurons (Lunc-79aP::unc-80 cDNA transgene could significantly rescue the defective locomotion and MeSa avoidance of unc-80(lf) mutants (Lunc-79aP), consistent with the overlapping expression of the two genes.To investigate whether  neurons , the vul neurons  and a fe neurons . One or Sunc-79aP promoter  and its partial rescuing strength  (Psra-6::mCherry (Table S3) (Sunc-79aP::GFP (Pglr-3::mCherry (Table S3) . Unlike the Lunc-79aP promoter, a Sunc-79aP::unc-80 transgene failed to rescue the defective locomotion or MeSa avoidance of unc-80(lf) mutants (sunc-79aP), consistent with the finding that Sunc-79aP::mCherry and Punc-80::GFP did not appear to co-label neurons .In with DiI . The expunc-79 in neurons. Transgenic animals expressing two unc-79-targeting sgRNAs (Table S4) and the pan neuronally expressed Punc-119::Cas9 exhibited significantly defective locomotion (Punc-119). Cas9 driven by the long or short unc-79 promoter also caused defective locomotion (Lunc-79a and PSunc-79aP). However, none of the unc-79-knockdown lines exhibited obviously defective MeSa avoidance . Interestingly, all these mutants displayed wild type-like responses to other attractants or repellents, suggesting they had largely normal odorant sensation and forward/reversal behaviors. Therefore, MeSa might trigger an avoidance response that is specifically mediated by the NALCN channel complex.unc-80 expression in a subset of unc-80-expressing neurons, e.g., in the command interneurons AVA and AVE and the anterior guidepost neuron AVG defined by the nmr-1 or glr-1 promoter, is sufficient for eliciting the MeSa avoidance. However, unlike the endogenous unc-79, unc-80 or nlf-1 promoters, the nmr-1 or glr-1 promoter did not rescue the defective locomotion. This result is consistent with the study of nlf-1, in which Xie et al.  mutants, while a combination of Pnmr-1::nlf-1 and Psra-11::nlf-1 transgenes would do. Therefore, broader expression of unc-80 in more interneurons might be necessary for generating a normal locomotion.Our genetic and neuronal analyses suggest that nlf-1 was expressed in AVA and AVE to regulate C. elegans locomotion . Recent studies suggest that MeSa is synthesized by many plants to signal the systemic acquired resistance to multiple pathogens   mutants, suggesting that NALCN expression in interneurons shared by these promoters but not in other neurons might be sufficient for MeSa to elicit the reversal behavior. Second, unc-79 transgene expression driven by the sunc-79aP promoter could strongly rescue the defective MeSa avoidance of unc-79(lf) mutants, suggesting that a limited restoration of NALCN function, potentially only in sensory neurons ASH and ASJ and two pairs of interneurons (RIA and RMF/RMH) but not in other classes of neurons, might be sufficient for MeSa to trigger the reversal behavior. Third, only the locomotion but not the MeSa avoidance behavior was significantly affected by neuron-specific knockdown of unc-80 or unc-79, suggesting that partial expression of the genes due to incomplete knockdown is sufficient for MeSa to elicit a strong avoidance response.We made a few intriguing findings in this study. First, restoring e.g., a group of neurons, of a multi-component neural network controlling the reversal behavior. In this network, the expression of the NALCN complex in any MeSa-responding components would be sufficient for triggering the avoidance behavior. Only when the NALCN complex is absent in all MeSa-responding components, the animals would exhibit a defective avoidance response. In addition, a remote possibility derived from these findings is that MeSa might act on the NALCN complex as an agonist. Therefore, a continuing investigation on the molecular mechanism underlying the MeSa avoidance behavior is warranted for further understanding of the function of the NALCN complex.There results prompt us to postulate that MeSa might cause the avoidance behavior by acting on more than one component, Finally, that MeSa might activate the NALCN channel complex provides a potential molecular explanation on why MeSa can repel herbivores and attract beneficial insects. For example, herbivores might express NALCN on neurons that promote avoidance behavior, while beneficial insects might express NALCN on neurons that promote attraction behavior.unc-79, unc-80 and nca genes are specifically required for C. elegans avoidance response to the plant hormone MeSa. We verified that unc-79 and unc-80 are co-expressed and function in overlapping neurons. The command interneurons AVA, AVE and the guidepost neuron AVG can be sufficient for unc-80 regulation of the MeSa avoidance. Our results suggest a novel function of the NALCN complex expressed in command interneurons as a regulator of C. elegans reversal behavior.In short, we found that


Nephotettix cincticeps and Oryza sativa infected with Rice dwarf phytoreovirus and analyzed the distinct accumulation of vsiRNAs in these two hosts. The results suggested a potential branch in the evolution of antiviral RNA silencing of insect and plant hosts. The rice vsiRNAs were predominantly 21 and 22 nucleotides (nt) long, suggesting that OsDCL4 and OsDCL2 are involved in their production, whereas 21-nt vsiRNAs dominated in leafhopper, suggesting the involvement of a Dcr-2 homolog. Furthermore, we identified ~50-fold more vsiRNAs in rice than in leafhoppers, which might be partially attributable to the activity of RNA-dependent RNA polymerase 6 (RDR6) in rice and the lack of RDR genes in leafhoppers. Our data established a basis for further comparative studies on the evolution of RNA silencing-based interactions between a virus and its hosts, across kingdoms.RNA silencing has evolved as a widespread antiviral strategy in many eukaryotic organisms. Antiviral RNA silencing is mediated by virus-derived small RNAs (vsiRNAs), created by the cleavage of double-stranded viral RNA substrates by Dicer (Dcr) in animals or Dicer-like (DCL) proteins in plants. However, little is known about how the RNA silencing mechanisms of different hosts respond to the same virus infection. We performed high-throughput small RNA sequencing in  RNA silencing, or interference (RNAi), is a gene regulatory mechanism of eukaryotic organisms that acts as an innate antiviral immune response in invertebrates, plants, fungi, and mammals ,2. DurinMany plant viruses are transmitted by insects and are thus capable of replicating in both plant and insect vector hosts. Persistent propagative plant viruses can be disastrous for agriculture ,10 but cReoviridae, replicates O. sativa in its plant host. RDV is transmitted by the leafhopper insect vector Nephotettix cincticeps in a propagative manner. The RDV genome comprises 12 dsRNA segments (S1–S12) encoding seven structural proteins and five nonstructural proteins  from which to generate OsRDR6 antisense transgenic plants (OsRDR6AS), as described previously [N. cincticeps) were maintained in cages and reared on rice seedlings (Zhonghua11). Vector cells in monolayer (VCMs) derived from N. cincticeps were maintained in Kimura’s insect medium at 25 °C, as described previously [eviously . Rice pleviously .‘Zhonghua11′ rice plants were inoculated with RDV, as described previously . In brieTotal RNAs from each group were extracted using a Trizol reagent , according to the manufacturer’s instructions and were resolved on a 15% denaturing agarose gel. Gel slices containing fragments of 18 to 28 nt were excised, and the RNAs were eluted and purified for library construction . Each library replicate contained RNA samples pooled from 200 leafhoppers, four plates of leafhopper VCMs, and 30 plants, respectively. Small RNA library preparation for sequencing using the Illumina platform was essentially performed as described previously . A bioinformatics analysis was also performed as described previously . SequencNorthern blot analysis of virus-derived small RNAs and RDV genomic RNA was performed as described previously . Probes http://www.ncbi.nlm.nih.gov/sra) under the accession number PRJNA541035. RNA-seq data of rice was obtained from Zhao et al. [Small RNA data sets generated in this study have been deposited in the NCBI sequence read archive . The qPCR was performed using SYBR Green Real-Time PCR Master Mix . OsEF-1a of rice and profilin of the leafhopper gene was used as an internal control for the assay, respectively. The Primers were: S2-F:5′-GCTATACACATCATCGCCGTGGTGT-3′; S2-R:5′-AACTTTGCTTCGGTGGTTGCCCCTG-3′; vsiRNA-F:5′ACATTTCTGACGTCGTTAGGA-3′; Profilin-F:5′GTGTTACCAAAGCCGCCATC-3′; Profilin-R5′TTGCCGAGTTTGGCTCTGAT-3′; OsEF1a-F 5′-ACATTGCCGTCAAGTTTGCTG-3′; OsEF1a-R 5′-AACAGCCACCGTTTGCCTC-3′.Total RNA samples were prepared from rice and leafhoppers at differernt infectious stage, age, and tissues. Total RNA samples (2 µg) were treated with DnaseI  to remove genomic DNA contamination and were used for cDNA synthesis  50-fold higher levels of RDV vsiRNA in rice than in leafhoppers and VCMs; (2) a substantially different distribution of vsiRNA in RDV genomic RNAs in insect and plant hosts—more vsiRNAs produced from S1 in leafhopper, S11 in VCMs, and S9 in rice than from other genomic segments, with an almost equal accumulation of positive- and negative-strand RDV genomic RNAs; and (3) vsiRNAs of predominantly 21 nt in leafhoppers and VCMs, and 21 and 22 nt in rice. The positive- and negative-strand RDV vsiRNAs were mapped at a nearly 1:1 ratio to RDV genomic RNAs in leafhopper, VCMs, and rice. Therefore, we propose that the dramatically different characteristics of RDV vsiRNAs in rice and insects are more likely due to differences in molecular interactions between the RNA silencing machinery and the viral RNAs in these hosts than due to differences in viral genomic RNA levels. In plants, vsiRNAs are amplified by a family of related host RNA-dependent RNA polymerases known as RDRs . The proDCLs  are more susceptible to RSV infection than the WT plants, indicating a critical role for DCLs in rice antiviral defense [Antiviral RNAi defense against FHV in Drosophila involves 21-nt vsiRNAs produced by Dicer-2. However, in Arabidopsis, DCL4 and DCL2 produce 21- and 22-nt vsiRNAs, respectively . A Dcr-2 defense . TherefoAnother possible, and not necessarily mutually exclusive, explanation for the low accumulation of RDV vsiRNAs in leafhoppers and VCMs is the action of RDV VSR Pns10. Co-expression of FHV-encoded VSR B2 in SINV-injected mosquitoes causes a great reduction in the abundance of vsiRNAs . Pns10 iIn summary, our work provides the first insight, to our knowledge, into vsiRNA profiles in an insect vector infected by a plant virus. Comparison of vsiRNA profiles in natural plant and insect hosts of the virus showed major quantitative and size differences of these vsiRNAs. Such differences suggest that there are distinct molecular pathways for the biogenesis of vsiRNAs from the same virus in hosts belonging to different kingdoms. Our findings establish a basis for further cross-kingdom comparative studies on the evolution of RNA silencing-based molecular interactions between a virus and its hosts.


The spatial and temporal regulation of transcription initiation is pivotal for controlling gene expression. Here, we introduce capped-small RNA-seq (csRNA-seq), which uses total RNA as starting material to detect transcription start sites (TSSs) of both stable and unstable RNAs at single-nucleotide resolution. csRNA-seq is highly sensitive to acute changes in transcription and identifies an order of magnitude more regulated transcripts than does RNA-seq. Interrogating tissues from species across the eukaryotic kingdoms identified unstable transcripts resembling enhancer RNAs, pri-miRNAs, antisense transcripts, and promoter upstream transcripts in multicellular animals, plants, and fungi spanning 1.6 billion years of evolution. Integration of epigenomic data from these organisms revealed that histone H3 trimethylation (H3K4me3) was largely confined to TSSs of stable transcripts, whereas H3K27ac marked nucleosomes downstream from all active TSSs, suggesting an ancient role for posttranslational histone modifications in transcription. Our findings show that total RNA is sufficient to identify transcribed regulatory elements and capture the dynamics of initiated stable and unstable transcripts at single-nucleotide resolution in eukaryotes. Transcription decodes the regulatory signals inscribed in the genome to initiate gene expression in response to cellular or external cues. At its heart lies the transcription start site (TSS), where RNA polymerase II starts gene transcription. Transcriptional regulators bind to specific DNA sequences near the TSS to remodel chromatin and recruit the molecular complexes necessary to start transcription. Annotation of genes and regulatory elements and the analysis of the underlying molecular mechanisms regulating transcription therefore depend on the identification of TSSs and the measurement of their activity genome-wide.The advent of nascent RNA sequencing methodologies has revealed a plethora of unstable transcripts. Such transcripts arise from divergent transcription of promoter regions , antisenRNA stability presents a continuum spanning RNA half-lives of less than a minute to several hours, which impacts their detection . UnstablSupplemental Fig. S1A,B). Using total RNA as input to reliably determine the TSS of promoters and distal regulatory elements at single-nucleotide resolution enables accurate annotation of genes and regulatory elements and the study of dynamic gene regulation and regulatory networks in any fresh or frozen eukaryotic sample or tissue from which total RNA can be extracted.It was previously shown that sequencing newly initiated RNA polymerase II transcripts can accurately define stable and unstable TSSs . These tSupplemental Fig. S1C–E). By using this approach, we were able to define TSSs from csRNA-seq libraries generated from highly fragmented RNA with RINs as low as two. In addition to controlling for degradation-induced artifacts, input libraries represent a resource for discovery as they capture all small uncapped RNAs, including microRNAs, Piwi-interacting RNAs (piRNAs), small interfering RNAs (siRNAs), and other small, processed RNAs present . Ribosomal RNA–depleted RNA-seq or genome annotations can be integrated to further limit false-positive TSS clusters found in highly expressed exons  and to assign stable and unstable transcript status to TSS clusters . csRNA-seq data are highly consistent and quantitatively reproducible across independent replicate experiments (r = 0.91) . Sequencing csRNA-seq libraries to a depth of approximately 15 million reads efficiently covered regulatory features in the human genome  and identified 54,000 candidate TSS clusters. Comparing these csRNA-defined TSS clusters with existing annotations and other data generated in K562 cells revealed a global overlap with known features of transcription initiation . Ninety-four percent of the TSSs mapped to promoter or enhancer regions as defined by ChromHMM  as well as distal regulatory elements such as putative eRNAs in super-enhancers .To evaluate the sensitivity and reproducibility of csRNA-seq, we generated duplicate csRNA-seq and small RNA input libraries using 10 µg of total RNA from separate cultures of human K562 myelogenous leukemia cells . Transcript initiation levels among csRNA-seq and GRO-cap were overall correlated (r = 0.61)  with a strong preference for A at the +1 site and the canonical Initiator motif  and had lower levels of nascent transcription, open chromatin, H3K27ac, and RNA polymerase II recruitment relative to TSSs identified by both methods . Clusters specific to csRNA-seq were more frequently found at small nuclear RNA genes  and correspondingly enriched for a PSE motif . Most of these observations suggest that the differences in TSSs called by either method might be more reflective of laboratory-specific differences (subclone or cell culture conditions) than the technical differences between the methods. Together these data show that csRNA-seq captures the TSSs of active promoters and distal regulatory elements with high fidelity and accuracy, bearing a high degree of similarity to profiles derived from nascent transcription initiation techniques.Initiated transcript profiles generated by csRNA-seq bear a resemblance to nascent initiation profiles generated by GRO-cap in K562 cells . TSS clu = 0.61) E with 78or motif . Method-SE motif . GRO-capERRFI1 locus . These results substantiate that analysis of total RNA by csRNA-seq combined with RNA-seq can be used to profile stable and unstable transcripts and identify their cognate TSSs.The transcriptome encodes an abundance of short-lived transcripts that are rapidly degraded by the DIS3 exoribonuclease component of the exosome . SensitiI1 locus A and sumI1 locus B, both tCell identity is informed by distal regulatory elements that in concert with promoters drive cell-type–specific gene expression . To bettWe next performed DNA motif analysis using HOMER  to probeSupplemental Fig. S5A), consistent with histone acetylation being closely associated with transcription . A vast majority of regulated csRNA-seq TSSs were associated with unstable transcripts (88%) located at promoter-distal regulatory elements (71%). Although the function of many of these transcripts is speculative  activated by the TLR4 agonist Kdo2-lipid A (KLA) . csRNA-sculative , eRNA trculative . De novoculative E, which culative .r = 0.48), followed by H3K27ac ChIP-seq (Pearson's r = 0.38) and ATAC-seq signal (Pearson's r = 0.19). Additionally, csRNA-seq displayed a fourfold higher dynamic range than ATAC-seq or H3K27ac ChIP-seq . Together, these findings establish csRNA-seq as a highly sensitive method to quantify changes in transcription initiation at both promoters and distal regulatory elements from total RNA to study gene regulatory networks.To assess if quantitative changes in transcription initiation at putative enhancer regions are predictive of regulation of nearby genes, we compared KLA-induced changes in csRNA-seq, H3K27ac, and ATAC-seq at distal regulatory elements with those of the nearest expressed gene as quantified by GRO-seq . This anChIP-seq F. These d1 locus B. Consisd1 locus , many ofNematostella vectensis (metazoa), the fungus Neurospora crassa, rice plant leaves (Oryza sativa), and the protist Capsaspora owczarzaki . Across the species, TSSs were enriched at annotated promoters and underrepresented within gene bodies . The nucleotide frequency preferences near TSS showed a strong preference for the Initiator motif and prominent TATA signature in plants and metazoa . These data show how csRNA-seq captures initiating transcripts across diverse eukaryotic samples and tissues and thereby open up new avenues and organisms to study.By capturing stable and unstable transcripts from total RNA, csRNA-seq overcomes limitations of methods that require nuclei isolation or other manipulations that are difficult in nonmodel organisms or tissues. This advance enables the characterization of the initiating transcriptome in any fresh or frozen eukaryotic sample or tissue for which total RNA can be extracted. To illustrate this, we profiled the starlet anemone czarzaki . These sDrosophila. Taking advantage of csRNA-seq and total RNA-seq profiling, we annotated TSS transcript stability and found significant variation in the prevalence of RNA stability and promoter types across species . Similarly, unstable promoter-distal TSSs found in Neurospora and rice resemble bilaterian eRNAs, and many cluster in regions with highly transcribed genes, analogous to mammalian super-enhancers  and previous findings in Drosophila  .Here we introduce csRNA-seq to quantitatively capture initiated transcripts and define their TSSs directly from total RNA. The transcription initiation patterns at gene promoters and distal regulatory elements discovered by this approach are similar to the results of nascent RNA profiling methods  . TSSs deSupplemental Fig. S2C).csRNA-seq identifies changes in activity at regulatory elements with higher dynamic range and better correlation with neighboring gene transcription changes than assays such as ATAC-seq or H3K27ac ChIP-seq. Furthermore, unlike these assays, csRNA-seq determines TSSs (akin to peaks) with single-nucleotide resolution. This precision boosts the sensitivity of motif finding approaches for identifying motifs for key lineage-determining and signal response transcription factors and enables accurate genome annotation. The fact that it uses total RNA as starting material makes csRNA-seq broadly applicable across eukaryotes. For example, csRNA-seq enables the characterization of transcripts in species in which physiological constraints such as cell walls and secondary metabolites or biosafety  hinder nuclei isolation for nascent RNA sequencing methods. Its focus on sequencing 5′ ends of initiated transcripts efficiently concentrates sequencing power to active promoters and enhancers, enabling the profiling of promoter and enhancer regulation in complex genomes such as humans with as few as 15 million single-end reads . Although we have generated libraries from <1 µg total RNA, sufficient starting material improves data quality and reproducibility.Supplemental Fig. S6D). The ability to use total RNA as input allows researchers to source samples from around the world with minimal biosafety risk and at moderate costs. Exploiting this feature, we investigated stable and unstable RNAs across five eukaryotes that together span more than 1.6 billion years of evolution. This analysis revealed common themes among TSSs throughout evolution. We observed strong fluctuations in nucleotide frequencies near TSSs and a preference to initiate transcription from YR(+1) dinucleotides common to all five eukaryotic species . Differences in TATA box usage between species and evidence for an expanded Initiator motif in Capsaspora suggest that core promoter sequence elements and their usage have diverged throughout evolution. The chromatin architecture at TSSs, with a nucleosome-depleted region centered on the proximal promoter flanked by nucleosomes with active histone modifications , is similar between the eukaryotic species assayed . The levels of H3K27ac found upstream of the TSSs are indicative of the levels of bidirectional transcription in each organism. Across evolutionarily distant eukaryotes, promoter-distal regions with unstable transcripts shared common features with mammalian enhancers, whereas unstable transcripts near promoters resembled promoter upstream transcripts (PROMPTs)  . Clear eThroughout the eukaryotic kingdoms, H3K27ac is associated with all active TSSs, whereas H3K4me3 is largely confined to the promoters of stable transcripts. Acetylation and methylation are prevalent and dynamic posttranslational modifications of transcription factors and RNA polymerases common to all three domains of life . Given tIn summary, csRNA-seq is a simple, versatile, and highly sensitive method to profile transcription initiation and regulation from RNA alone. By yielding single-nucleotide resolution TSS location data, csRNA-seq represents an alternative to H3K27ac ChIP-seq or methods that profile open chromatin to identify active regulatory elements and could empower the annotation of GWAS risk variants with regulatory functions in different tissues.Supplemental Methods as well as at http://homer.ucsd.edu/homer/ngs/csRNAseq/. Small RNAs of ∼20–60 nt were size-selected from 2–15 µg of total RNA by denaturing gel electrophoresis . A 10% input sample was taken aside and the remainder enriched for 5′-capped RNAs with 3′-OH. Monophosphorylated RNAs were selectively degraded by Terminator 5′-phosphate-dependent exonuclease (Lucigen). Subsequent 5′ dephosporylation by CIP (NEB) followed by decapping with RppH (NEB) augments Cap-specific 5′ adapter ligation by T4 RNA ligase 1 (NEB). The 3′ adapter was ligated using truncated T4 RNA ligase 2 (NEB) without prior 3′ repair to select against degraded RNA fragments. Following cDNA synthesis, libraries were amplified for 11–14 cycles and sequenced SE75 on the Illumina NextSeq 500.A comprehensive description of the method and analysis software can be found in the homerTools trim”) and aligned using HISAT2  Peaks of strand-specific csRNA-seq reads found within 150 bp with a minimum read-depth of seven reads per 107 aligned reads and greater than twofold reads per base pair than the surrounding 10 kb were considered for further analysis. This step eliminates loci with minimal numbers of supporting reads or regions with high levels of diffuse signal. (2) Short RNA input libraries  were integrated and the appropriate enrichment thresholds for csRNA-seq reads over input or total RNA-seq libraries calculated. The optimal threshold is defined as the ratio that generates the largest difference in cumulative distributions of putative TSS regions in annotated TSS regions  relative to putative TSSs identified in downstream exons . This semisupervised threshold detection approach is most needed when RNA quality is low. By using this approach, we were able to successfully call TSSs from libraries generated from RNA with RIN numbers as low as two.Sequencing reads were trimmed for 3′ adapter sequences (AGATCGGAAGAGCACACGTCT) using HOMER , and the closest annotated gene promoters were also identified to assess their distal annotation . TSSs from alternative transcription initiation methods were analyzed using the same pipeline as described for csRNA-seq to ensure a fair comparison among assay types. Modifications were made to adapter trimming as needed per data set to remove the correct 3′ adapter, and for assays that use paired end sequencing, only the read encoding the 5′ initiation site was used in downstream analysis.To estimate the likely stability of transcripts initiating from each TSS, total RNA-seq reads (sense strand) are quantified from  relative to the TSS. “Stable TSSs” were defined as TSS clusters containing at least two per 10Strand-specific total RNA-seq libraries from ribosomal RNA–depleted RNA were prepared using the TruSeq kit stranded total RNA library kit (Illumina) and sequenced PE100 on Illumina HiSeq 2500.N. vectensis (planula stage) was kindly provided by Drs. James Gahan and Fabian Rentzsch (University of Bergen) and shipped on dry ice but arrived defrosted. N. crassa was provided by Dr. Jason Stajich  and grown in Vogels media under constant light and gentle agitation . Gene and promoter annotations were based on the accompanying Ensembl GTF file.General NGS analysis was performed using HOMER  unless sg HISAT2  with deffindPeaks.pl in either “histone”  or “factor”  mode to identify broad or focal peaks, respectively, using ChIP input experiments as a control for both types of analysis. Identification of overlapping or specific peaks/TSS, as well as overlaps between TSS and genome annotations or ChromHMM annotations, were calculated using HOMER's mergePeaks command. Overlapping TSS clusters were defined by TSS clusters located within 150 bp on the same strand. Differentially regulated TSS/peaks were calculated by first merging features from each condition (or assay) into the union of nonredundant features using mergePeaks. Then raw read counts associated with each feature across all experiments was quantified with annotatePeaks.pl and significantly differentially enriched TSS/peaks  determined by DESeq2  (Known motif enrichment and de novo motif discovery were performed using HOMER's ter 3.0)  and visuter 3.0) .https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE135498. The updated HOMER software is available at http://homer.ucsd.edu/ and as Supplemental Code.All sequencing data generated in this study have been submitted to the NCBI Gene Expression Omnibus (GEO;