Caenorhabditis elegans.Epilepsy affects around 1% of people, but existing antiepileptic drugs (AEDs) only offer symptomatic relief and are ineffective in approximately 30% of patients. Hence, new AEDs are sorely needed. However, a major bottleneck is the low-throughput nature of early-stage AED screens in conventional rodent models. This process could potentially be expedited by using simpler invertebrate systems, such as the nematode C. elegans with loss-of-function mutations in unc-49, which encodes a GABAA receptor. Given that epilepsy-linked mutations in human GABAA receptors are well documented, this could represent a clinically-relevant system for early-stage AED screens. However, the original agar plate-based assay is unsuited to large-scale screening and has not been validated for identifying AEDs. Therefore, we established an alternative streamlined, higher-throughput approach whereby mutants were treated with PTZ and AEDs via liquid-based incubation.Head-bobbing convulsions were previously reported to be inducible by pentylenetetrazol (PTZ) in unc-49 mutants were strongly inhibited by the established AED ethosuximide. This protective activity was independent of ethosuximide’s suggested target, the T-type calcium channel, as a null mutation in the worm cca-1 ortholog did not affect ethosuximide’s anticonvulsant action.Convulsions induced within minutes of PTZ exposure in Our streamlined assay is AED-validated, feasible for higher throughput compound screens, and can facilitate insights into AED mechanisms of action.C. elegans unc-49 model of seizure-like activity presents an ethical, higher throughput alternative to conventional rodent seizure models for initial AED screens.Based on an epilepsy-associated genetic background, this  EpilepsCurrent AEDs on the market were either discovered through screening in rodent seizure models, or developed as derivatives of pre-existing drugs . Acute sDrosophila melanogaster, and the zebrafish, Danio rerio, have been at the forefront of this area, providing new genetic models of epilepsy and the capacity to perform high-throughput drug screens  and lifespan (3 weeks), and is highly tractable genetically. This means that genetic models of epilepsy can be generated much more easily and on a shorter timescale than is achievable with rodent systems , except for DNA polymerase and restriction enzymes, which were from New England Biolabs .2.2C. elegans strains were obtained from the Caenorhabditis genetics centre : Wild type (WT) Bristol N2, unc-43 (n498n1186) IV, cca-1 (ad1650) X, unc-25 (e156) III, and unc-49 (e407) III. The unc-49 (e407) and unc-25 (e156) alleles are single point mutations that introduce premature stop codons and have been shown to be genetic nulls (unc-43 (n498n1186) allele combines both missense and nonsense mutations and is presumed to be a genetic null (cca-1 (ad1650) allele contains a 2.5 kb deletion within the coding region that removes multiple exons and introduces a frameshift and has been shown to be a null mutant  III and cca-1 (ad1650) X strains (described below). Worms were grown and maintained on OP50 E. coli-seeded nematode growth medium  agar in 60-cm plastic petri dishes at 20 °C  X-linked mutants were derived by mating wild type (WT) Bristol N2 males with self-fertilising homozygous cca-1 (ad1650) mutant hermaphrodites. The resultant cca-1 (ad1650) males were crossed with unc-49 (e407) hermaphrodites to derive unc-49;cca-1 double mutants, selected based on various phenotypic characteristics of the unc-49 mutation: PTZ sensitivity, reduced thrashes in liquid relative to cca-1 (ad1650) mutants, and a “shrinker” phenotype of body contraction and shortening in response to anterior and posterior touch stimuli (cca-1 (ad1650) mutation was verified with PCR primers  which generate differentially-sized products for WT (3310 bp) and mutant (930 bp) alleles. Genotyping of unc-49 (e407) homozygosity was performed by initial amplification of the point mutation-harbouring exon with PCR primers , followed by subsequent restriction digestion of products with MseI, which distinguishes between WT and mutant unc-49 alleles based on the number of T^TAA cleavage sites and the size of digested fragments . stimuli . Homozyg2.4g) and subsequent depositing of egg pellet onto seeded NGM plates. The developmental duration from egg to adulthood age day 1 of approximately 3.5 days at 20 °C was adjusted accordingly to attain synchronized populations of older adult worms of defined ages.Cultured populations on NGM plates wereage-synchronized by bleaching . Eggs were released from gravid adult worms through lysis by vortexing the mixture every 2 min. for 10 min., followed by pelleting via centrifugation  containing 0.1% bovine serum albumin (BSA). Droplets were applied to empty plastic petri dishes, with 0.1% BSA included to prevent worms sticking to the plastic. Assays to determine optimal PTZ exposure conditions for convulsion induction utilised PTZ concentrations up to 10 mg/ml for treatment durations up to 60 min. Unless specified otherwise, nematodes were exposed to 7 mg/ml PTZ for 15 min.Liquid-based administration of PTZ was performed by incubating individual young (1–3 days old) adult nematodes in 50 μl liquid droplets of PTZ dissolved in Dent’s Ringer solution  in the continued presence of the drug at the same concentration, by transferring nematodes to DRS/BSA droplets containing both PTZ and drug.2.8unc-49 model exhibits characteristic seizure-like head bobbing movements and a paralysed posterior in response to PTZ (http://www.mrc-lmb.cam.ac.uk/wormtracker) was used to record videos of seizure-like activity, which were then analysed manually to generate qualitative and quantitative data.The e to PTZ . We defi2.9Motility was assessed by quantifying the rate of thrashing in DRS/BSA as previously described . A thras2.10All datasets were initially assessed using the Shapiro-Wilk test and were found not to be normally distributed. Hence, the non-parametric Mann-Whitney and Kruskal-Wallis tests were used to determine statistical significance. Analyses were performed on GraphPad Prism version 6 . Data is presented as mean values, with standard error of the mean (SEM) where appropriate.33.1C. elegans GABAA receptor (unc-49), glutamic acid decarboxylase , and calcium/calmodulin-dependent serine/threonine kinase II  were observed to exhibit either anterior-type “head bobs” or full body contractions in response to the convulsant PTZ . As unc-49 mutants exhibited the highest incidence of seizure-like activity .Ethosuximide administration via a two-day agar plate-based exposure  is time-eriments . Howevereriments A and B. eriments B, we seleriments C and D. unc-49 platform to be further adapted for a broader screening applicability. Given that DMSO can have toxic effects on C. elegans  as a vehicle, necessitating the  elegans , it was nvulsant . This de3.3C. elegans model is the ability to use powerful genetic approaches to examine potential mechanisms of drug action in vivo. This possibility was therefore assessed with the new assay. Ethosuximide has been prescribed for 60 years and is still used as a first-line treatment against absence epilepsy in children, but its molecular mechanism of action remains unclear. Although ethosuximide has been suggested to exert its antiepileptic effect by inhibiting T-type voltage-gated calcium channels , and assayed to validate the reproducibility of responses to drug treatment and PTZ exposure. The single cca-1 mutant did not exhibit seizures in response to PTZ, similar to wild type strains . The anticonvulsant activity of 4 mg/ml ethosuximide was unaffected by mutation of cca-1, as both the proportion of convulsing worms , demonstrating that the anticonvulsant activity of ethosuximide was specific to the drug and not due to non-specific effects of the treatment conditions. We therefore conclude that ethosuximide does not prevent PTZ-induced convulsions in unc-49 mutants by inhibiting T-type calcium channels.One major advantage of using a channels , this ischannels . To inveng worms A and theng worms B were co mutants  or doubl4C. elegans mutants , so GABAA-receptor-binding drugs should still be able to exert effects  or a CAMKII-phosphorylated substrate protein(s) may be the molecular target of ethosuximide. However, there are no published data linking ethosuximide to CAMKII, so evidence for this proposition is lacking. Nevertheless, although we have not yet identified ethosuximide’s molecular target, the ease of conducting genome-wide genetic screens in C. elegans suggests that this could be feasibly achieved using our assay.The ease of genetic manipulation in d herein  and the 2 mutant  contain ilepsies . These lchannels , voltagechannels ; to actichannels ; and to channels . Our pro5C. elegans suitable for early-stage AED screening. We envisage that this could be used in future as the first pass in a pipeline for drug discovery, with promising compounds being prioritised for validation in conventional rodent models, thus reducing the ethical and financial costs of AED screening. In addition, the C. elegans system enables rapid identification of the mechanisms of action of such validated novel AEDs via chemical genetics.In conclusion, we have developed a streamlined assay in The authors declare no competing interests.SW, AJ, SD and DG performed the experiments. SW, AJ, AD, JWB, RDB, AGM, VTC GJS and AM analysed and interpreted the data. AM and GJS conceived and designed the experiments. SW and AM wrote the manuscript with input from all of the other authors.


Consistent with this recent knowledge, sRNAs and their double-stranded RNA precursor have been adopted to control diseases in crop plants, demonstrating a straight forward application of the new findings to approach agricultural problems. Despite the great interest in natural ck-RNAi, it is astonishing to find just a few additional examples in the literature since the first report was published in 2013. One reason might be that the identification of sRNA effectors is hampered both by technical challenges and lack of routine bioinformatics application strategies. Here, we suggest a practical procedure to find, characterize, and validate sRNA effectors in plant–microbe interaction. The aim of this review is not to present and discuss all possible tools, but to give guidelines toward the best established software available for the analysis.Small RNA (sRNA) molecules are key factors in the communication between hosts and their interacting pathogens, where they function as effectors that can modulate both host defense and microbial virulence/pathogenicity through a mechanism termed cross-kingdom RNA interference ( During  kinases . This siPuccinia striiformis (Ps), delivers fungal microRNA (miRNA)-like RNAs into host cells to suppress the defense response by targeting and downregulating wheat Pathogenesis-related 2 (PR-2) expression. Silencing of the sRNA precursor showed enhanced resistance to the virulent Ps isolate in wheat adult plants  starts with the preparation of suitable biological samples. When planning which and how many samples to sequence, control samples of uninfected plants and, when possible, axenic cultures of the microbe should be included in order to verify the infection-related upregulation/induction of the candidate ck-sRNAs in bidirectional fashion. The preparation also requires to fix the number of replicates and of reads per sample  are often shorter than the read length (36 bp), the machine is bound to read into the adapter. There are number of software programs designed to do the necessary trimming, such as Cutadapt or FASTX-Toolkit . At thisck-sRNA and its localization in the respective genome. Given that it is crucial to find the sRNAs from the source organism that target the interacting organism, this alignment step includes the removal of reads that align to both organisms. In particular, sRNAs are kept only if (i) they align 100% of the full read length to the source organism’s genome , and (ii) have at least two mismatches to the target organism’s genome or transcriptome (bowtie settings: -v1 –un). As an additional step, the removal of sequences aligning 100% to the source organism’s transcriptome can be done in order to select exclusively sRNAs originating from non-coding regions (bowtie settings: -v0 –un), removing short sequences derived from mRNA degradation. After the alignments, sRNAs can be additionally filtered based on their presence in the sample of the pure source organism as they are expected to be either upregulated in the sample from the interacting organisms compared to the control (pure organism), or present exclusively in that sample  and microRNA (miRNA) detection, originally tailored for mammal sRNAs. While these can be customized for plant and microbe studies, two well established tools are designed specifically for plants: psRNATarget and TAPIR . Both arck-sRNAs is the confirmation of target gene downregulation in the colonized tissue as a result of the cleavage of the corresponding mRNA by the RISC enzymatic complex. Plant and microbial mRNA levels can be checked by mRNA sequencing analysis from the same biological samples the sRNA was obtained from. Since the library preparation for sRNA libraries is based on size separation and excision of a specific nt length interval, the longer RNA fraction from the same samples can be used to prepare mRNA libraries. Read length and sequencing depth selected can vary depending on the experimental design and resources available, but the mRNA sequences are primarily obtained from the large RNA fraction after polyA affinity selection, as more than 90% of total RNA is comprised of ribosomal RNA (rRNA)  . In bactde novo assembly (reference-free) of the transcriptome can be computed from all RNAseq datasets, usually with a De Bruijn graph-based assembler like Trinity (Trans (Trans-AbySS (1) and FunctionAnnotator , RseQC , RseQC , and Qua), RseQC . Percent), RseQC .The first step for differential gene expression (DGE) is determining transcript abundances using program packages like Cufflinks  or htseqThe results of this target prediction and analysis pipeline can be visualized at several levels and by a variety of programs, some of which focus on sRNA-mRNA duplex conformation structure and others on a broader representation of cross-kingdom effects between genomes. ReadXplorer  and Inteck-sRNAs are investigated further. Alternative to mRNA sequencing, validation of ck-sRNA candidates requires confirmation of downregulation of their putative target by qRT-PCR.Having obtained information on differentially expressed genes in the treated sample, the ones which are significantly downregulated and predicted as targets of candidate in vivo validation of the interaction of ck-sRNA candidates with their targets can be based on genetic analysis, e.g., mutational knockdown (KO) strategies of target genes and/or precursor loci of candidate ck-sRNAs. Finally, we suggest that the following additional analyzes are required to unequivocally claim a ck-RNA-mediated target interaction in ck-RNAi: (i) verification of sRNA-target interaction in transient expression systems such as leaves of Nicotiana benthamiana; (ii) testing respective AGO and DCL mutants for a loss of ck-RNA function in RNAi-mediated target downregulation; and (iii) detection of direct association of ck-RNAs or their target mRNA with the respective microbial or plant AGO1 protein by immuno-purification techniques (Additional chniques .ck-RNAi, has been detected in a few natural plant – microbe systems, but the implications of a novel effector class of sRNA are significant. So far, there is no evidence that the activity of such RNA effectors would be restricted to certain microbial life styles as they were identified in plants interacting with both biotrophic and necrotrophic microbes. The recent finding that mammals also generate RNA effectors to combat parasites suggests that the phenomenon is widespread and prevalent in different types of host–parasite interaction. Besides the exciting discovering of a novel chemical communication strategy, the knowledge on ck-RNAs opens new avenues in sustainable and environmentally safe plant protection as sRNAs and their cellular precursors dsRNAs are natural molecules with an anti-microbial activity. However, the detection and validation of RNA-based communication and ck-RNAi still relies on the available data about model species and a narrow range of investigated systems. The present review tries to give a practical outline of a pipeline for ck-RNA detection focused on plant – microbe systems. A bioinformatics pipeline used to strengthen and accelerate the experimental approaches is of paramount importance for confirmation of sRNA communication between plants and microbes in a multitude of relevant systems.RNAi-based bidirectional communication between interacting organisms, also called SZ, K-HK, EŠ, and LJ wrote the text. SZ and EŠ designed the figure.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.


FIERY1 (FRY1), which is involved in 5′−3′ RNA degradation, regulates miRNA abundance and function by suppressing the biogenesis of ribosomal RNA-derived siRNAs (risiRNAs). In mutants of FRY1 and the nuclear 5′−3′ exonuclease genes XRN2 and XRN3, we find that a large number of 21-nt risiRNAs are generated through an endogenous siRNA biogenesis pathway. The production of risiRNAs correlates with pre-rRNA processing defects in these mutants. We also show that these risiRNAs are loaded into AGO1, causing reduced loading of miRNAs. This study reveals a previously unknown link between rRNA processing and miRNA accumulation.Plant microRNAs (miRNAs) associate with ARGONAUTE1 (AGO1) to direct post-transcriptional gene silencing and regulate numerous biological processes. Although AGO1 predominantly binds miRNAs in vivo, it also associates with endogenous small interfering RNAs (siRNAs). It is unclear whether the miRNA/siRNA balance affects miRNA activities. Here we report that  Arabidopsis AGO1 binds both microRNA (miRNA) and endogenous small interfering RNA (siRNA). Here the authors show that 5′−3′ RNA degradation suppresses siRNA biogenesis from ribosomal RNA to prevent overloading of AGO1 with ribosomal siRNA and maintain miRNA-directed post translational gene silencing. Like miRNAs, PTGS siRNAs are usually 21–22 nt long, but unlike miRNAs, they are derived from double-stranded precursors from transgenes, viruses, and endogenous loci, such as the TRANS-ACTING SIRNA (TAS) loci1. The machinery underlying the biogenesis and function of miRNAs and siRNAs contains shared and distinct components3. miRNA precursors are processed by DICER-LIKE1 (DCL1) into mature miRNAs4, whereas siRNAs from transgenes, viruses, and endogenous transcripts are generated by other DCLs6. Both miRNAs and siRNAs undergo 3′ terminal methylation by HUA ENHANCER1 (HEN1)8. In addition, both types of sRNAs associate with ARGONAUTE1 (AGO1) to form the functional RNA-induced silencing complex (RISC)3. The partial sharing of the silencing machinery imply crosstalk and potential mutual regulation between miRNAs and siRNAs.Small RNAs (sRNAs) serve as sequence determinants in post-transcriptional gene silencing (PTGS) in plants. The two major types of PTGS small RNAs are microRNAs (miRNAs) and small interfering RNAs (siRNAs)13. The sRNAs produced when these RQC genes are compromised are usually 21–22 nt long, phased, and dependent on the PTGS siRNA pathway12. Zhang et al. proposed that aberrant RNAs accumulated in these mutants are bound by SUPPRESSOR OF GENE SILENCING3 (SGS3)14 and serve as templates for siRNA biogenesis15. Interestingly, a study on the decapping complex demonstrated that DCP1, DCP2, and VCS are required for the accumulation of some miRNAs16.RNA quality control (RQC) suppresses siRNA production from many endogenous transcripts. Among the RQC genes are those encoding 5′-3′ EXORIBONUCLEASE3 (XRN3) and XRN4; the decapping complex subunits DECAPPING1 (DCP1), DCP2, and VARICOSE (VCS); the SUPERKILLER (SKI) complex components SKI2 and SKI3, which are involved in 3′-5′ exoribonucleolytic RNA degradation; Nonsense-mediated decay components UPFRAMESHIFT1/3 (UPF1/3); the 3′-5′ POLY(A)-SPECIFIC RIBONUCLEASE (PARN); and exosome subunits RIBOSOMAL RNA PROCESSING4 (RRP4) and RRP6L1Schizosaccharomyces pombe, defects in TRAMP-mediated RNA surveillance trigger the biogenesis of Ago1-associated, rRNA-derived siRNAs (rr-siRNAs)17. In Neurospora crassa, 20–21 nt qiRNAs are produced from aberrant rRNAs in an RdRP (RNA-dependent RNA polymerase)-dependent manner, are enriched in 5′ U, and are loaded into the AGO protein QDE-218. qiRNAs are thought to function in DNA damage repair. In Caenorhabditis elegans, 22-nt rRNA-derived siRNAs (risiRNAs) corresponding to both strands of rDNA are generated under conditions that induce pre-rRNA processing defects. C. elegans risiRNAs are enriched in 5′ G and are thought to regulate rRNA abundance20. In Arabidopsis, rDNA-derived 24-nt siRNAs were first described in 200621. These siRNAs are produced in a Pol IV-dependent and DCL3-dependent manner and guide DNA methylation22. Later studies also found 21-nt small RNAs originating from bidirectional transcripts from the intergenic spacers (IGS) of rRNA genes24. A recent report found that viral infections trigger the production of siRNAs from rRNAs, but the molecular or biological impacts of these ribosomal small RNAs remain unknown25.Ribosomal RNA (rRNA)-derived sRNAs have been observed in several organisms. In FIERY1 (FRY1) is isolated in a genetic screen aimed at uncovering new factors in the miRNA pathway. FRY1 encodes a dephosphorylating enzyme that converts 3′-phosphoadenosine 5′-phosphosulfate (PAPS) into adenosyl 5′-phosphosulfate (APS) in sulfur assimilation27. FRY1 also converts 3′-phosphoadenosine 5′-phosphate (PAP) into 5′ AMP and Pi. FRY1 functions in various biological processes, such as stress signaling27, drought tolerance28, cell elongation, flowering time29, leaf development30, root development31, and plant immunity32. fry1 mutant phenotypes resemble those of higher-order xrn mutants, possibly because accumulated PAP suppresses XRN enzymatic activity, thereby compromising 5′-3′ RNA degradation34. Several studies have shown that FRY1 and XRNs function in RNA degradation and suppress PTGS in Arabidopsis36. In a fry1 mutant, 21-nt sRNAs from the 5′ external transcribed spacer (ETS) of rRNAs accumulate in a DCL2/4-dependent manner37. In addition, miRNA processing intermediates accumulate in fry1, possibly due to compromised XRN activity38.In this study, a mutation in fry1 mutations lead to the accumulation of 21–22-nt siRNAs from mRNAs and rRNAs, transcripts that do not normally undergo siRNA biogenesis. The production of risiRNAs in fry1, as well as xrn2 xrn3 mutants correlate with pre-rRNA processing defects in these mutants. We show that the siRNAs depend on the PTGS siRNA pathway for biogenesis and are loaded into AGO proteins, AGO1 and AGO2. More importantly, risiRNAs compete with miRNAs for these AGO proteins, resulting in the compromised abundance of miRNAs. Removal of risiRNAs partially rescues both the miRNA abundance defects and the plant phenotypes of fry1. Collectively, the findings provide insights into the biogenesis of endogenous siRNAs and the crosstalk between siRNAs and miRNAs.We find that CTR1 is a negative regulator in the ethylene response pathway39. ctr1 mutants exhibit constitutive ethylene responses, resulting in shorter root and hypocotyl, tightened apical hook, and swollen hypocotyl40. We took advantage of this conspicuous “triple” response phenotype to construct a visual reporter of miRNA activity. We designed an artificial miRNA targeting CTR1 (amiR-CTR1) driven by a β-estradiol-inducible promoter  was identified and verified by genotyping. The mutation was in the acceptor site of the second intron and resulted in the skipping of exon 3 and the creation of an early stop codon  and SALK_151367 (designated as fry1-8 hereafter).The reduced accumulation of amiR-CTR1 in T5520 suggested that the fry1-6  had reduced accumulation, one (pri/pre-miR390b) had increased accumulation, and pri/pre-miR159b, pri/pre-miR166a, pri/pre-miR167a, pri/pre-miR168 and pri/pre-miR393b were unaffected in fry1-6 . In the fry1 mutants, miRNA abundance decreased, while the abundance of sRNAs from coding genes and rRNAs increased , respectively. We found that 21-nt hyper DSRs greatly outnumbered hyper DSRs of other lengths and hypo DSRs of all lengths in both mutants  indicated that FRY1 suppresses sRNA production from these genes. There were 228 21-nt hyper DSGs in both mutants combined, and although sRNAs derived from these DSGs constituted only ~4% of the total 21-nt sRNAs . First, we examined the 21-nt hyper DSRs in these mutants and confirmed the accumulation of aberrant 21-nt sRNAs from coding genes reported in the original studies  regions in fry1  arising from the sense strand were nearly equally abundant, suggesting that they correspond to rRNA degradation products. However, only 21-nt sRNAs from both strands dramatically accumulated in fry1  for the rRNA-derived ones. The biogenesis requirements of these rogue siRNAs are similar to those of another class of endogenous siRNAs, namely phasiRNAs, which exhibit a head-to-tail phasing signature3. Hence, we next investigated the phasing of rogue siRNAs using established methods52. Surprisingly, the phasing scores at TAS and genes known to generate phasiRNAs were slightly reduced in the two fry1 mutants, while those at the rDNA locus and many 21-nt hyper DSGs were drastically increased  of AGO1 in WT and fry1-6  and the 193 genes with AGO1-bound 21-nt sRNAs in WT suggested that the genes suppressed by FRY1 for sRNA production were distinct from those that generated sRNAs in WT. We also analyzed the sequence features of the 1224 IP-enriched genes in fry1-6, and the results supported the hypothesis that longer genes with fewer exons tended to generate 21-nt siRNAs in fry1  and recovered in fry1-6 rdr6-11 . These results indicated that in fry1-6 AGO1′s binding to miRNAs declined, and AGO1 associated with risiRNAs. The reduced miRNA abundance in fry1 mutants was likely due to the compromised loading of miRNAs into AGO1.Because most miRNAs associate with AGO1 under normal conditions, the miRNA-binding capacity of AGO1 might be compromised by the excessive accumulation of risiRNAs and siRNAs from other coding genes in ble Fig.    Fig. . This wa WT Fig. . This alfry1-6, fry1-6 rdr6-11, and fry1-6 rdr1-1 to understand if the siRNAs affected gene expression. Despite the large numbers of upregulated and downregulated genes  and T-DNA insertion lines of FRY1 , XRN2 , XRN3 , XRN4 , PRMT3 , RDR1 , RDR2 , RDR6 , DCL2 , DCL3 , and DCL4  were used in this study. Seeds were germinated on 1/2 MS medium under short-day conditions (8 h light and 16 h dark) at 22 °C, and seedlings were either collected for analyses or transferred to soil for phenotypic observation on day 12.http://wmd3.weigelworld.org/cgi-bin/webapp.cgi) then inserted into the MIR319a backbone58. The amiR-CTR1 fragment was recombined into the plasmid pER10 containing a β-estradiol-induction cassette using the Xho1 and Spe1 restriction sites , we determined that the insertion was between nucleotides 18214427 and 18214448 on chromosome 5. We also confirmed that there was only a single T-DNA insertion in the genome, as no chimeric reads from two T-DNA borders (LB/RB) were found. About 2 mL freshly collected amiR-CTR1 seeds were used for ethyl methanesulfonate (EMS) mutagenesis. Seeds were washed in 0.1% Tween-20 for 15 min then treated with 50 mL 0.1% EMS overnight on a rotator in a fume hood. The seeds were transferred to 0.5 M NaOH and incubated overnight, rinsed with ddH2O several times, then washed in ddH2O for 4 h. Finally, the seeds were sown in soil.amiR-CTR1 (CGGGUUGGGAAUAAUAUGUAU) was designed using WMD tools . From the NGM result, we narrowed the location of the mutation to a region consisting of 10 candidate genes  that contained SNPs with discordant chastity scores over 0.95. We designed dCAPS primers for all of the candidate genes and analyzed another batch of F2 plants with the mutant phenotype60. This analysis pinpointed the mutation to AT5G64390 (FRY1).To find the causal mutation in T5520, the CTAB method was used to extract DNA from ~50 plants with the T5520 phenotype from the F2 population of the T5520 x Col-0 cross. A DNA library was constructed with the NEBNext Ultra™ II DNA Library Prep Kit for Illumina  according to the manual. The library was sequenced on the HiSeq 2000 platform at the genomics core facility at UCR, and the PE150 reads were mapped to the 2HPO4 at pH 7.2, 7% SDS, 2× Denhardt’s solution) and incubated with the membrane at 55 °C overnight. After two wash steps  to remove excess probe, the membrane was processed using the Chemiluminescent Nucleic Acid Detection Module Kit  according to the instruction manual with probes described in Supplementary Data 61.Total RNA was extracted from 12-day-old WT and mutant seedlings using TRI reagent  according to the manufacturer’s instructions. For each sample, 10 μg total RNA was run on a 15% urea-PAGE gel and transferred to a Hybond NX membrane. The RNA was cross-linked to the membrane with the EDC cross linking buffer  at 65 °C for 90 min. Biotin-labeled probes were added to the hybridization buffer  of 12-day-old seedlings were harvested for protein extraction using 1× SDS buffer . The samples were loaded onto a 10% SDS-PAGE gel and proteins were then transferred to a nitrocellulose membrane after electrophoresis. Anti-AGO1 antibody  was used to detect the AGO1 protein, and the 60S ribosomal protein L13 was detected with its antibody  and served as the internal control.fry1-6, and fry1-8 was resolved on a 15% urea-PAGE gel, and the sRNA fraction (15–40 nt) was excised. sRNAs in the excised gel were recovered in 0.4 M NaCl, followed by ethanol precipitation. sRNA libraries were constructed using the NEBNext Small RNA Library Prep Set for Illumina  according to the manufacturer’s instructions. The libraries were pooled and sequenced to generate 75-bp single-end reads on an Illumina NextSeq CN500 platform at Berry Genomics .Total RNA (20 μg) from WT (Col-0), GSE57936, GSE65056, GSE95473) were analyzed using a publicly available pipeline, pRNASeqTools v0.6. The sRNA-seq raw reads were trimmed to remove the 3′ adapter sequences (AGATCGGAAGAGC) then size-selected (18–42 nt) using cutadapt v1.9.162. The trimmed reads were mapped to the Araport11 genome using ShortStack v3.463 with parameters ‘-bowtie_m 1000-ranmax 50-mmap u-mismatches 0′. To calculate and compare sRNA abundance in the WT and mutant libraries, the Arabidopsis genome was tiled into 100-bp bins , and reads whose 5′ end nucleotides mapped to a given bin were assigned to that particular bin. Normalization was conducted by calculating the RPM value (reads per million mapped reads) for each bin, and comparison was performed for each category of bins using the R package DESeq264. The significance of overlap was calculated using the R package SuperExactTest65. sRNA target prediction was performed by psRNATarget66 using the 2017 scheme with expectation ≤2.Our sRNA-seq data and published datasets . AGO1 antibody (8 μL/g) or AGO2 antibody  and protein A Dynabeads  were sequentially added to the supernatant to obtain the AGO protein complex. For WT, fry1-6, and fry1-6 rdr6-11, the immunoprecipitation, RNA extraction, library construction, sequencing, and data analysis were performed in three independent experiments as described above for total sRNAs.Total protein was extracted from WT, 67 with the parameters “--alignIntronMax 5000 --outSAMmultNmax 1 --outFilterMultimapNmax 50 --outFilterMismatchNoverLmax 0.1”. Mapped reads were counted by featureCounts v1.6.468 and comparison was performed using the R package DESeq264.RNA-seq libraries were constructed using NEBNext® Ultra™ RNA Library Prep Kit for Illumina®  following manufacturer’s recommendations, and pooled and sequenced on the Illumina NovaSeq 6000 system  at Berry Genomics . The RNA-seq data were analyzed using the pRNASeqTools. Briefly, raw reads were mapped to the Araport11 genome using STAR v2.6Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Supplementary Data 9Reporting SummarySource Data


Furthermore, RNA co-aggregates with rPrP and thereby gains partial protection from RNase digestion. Our results also indicate that rPrP interacts with the RNAs with its N-terminus. In summary, this study elucidates the proposed adjuvant role of RNA in prion protein aggregation and propagation, and thus advocates an auxiliary role of the nucleic acids in protein aggregation in general.Recent studies have proposed that nucleic acids act as potential cofactors for protein aggregation and prionogenesis. By means of sedimentation, transmission electron microscopy, circular dichroism, static and dynamic light scattering, we have studied how RNA can influence the aggregation of the murine recombinant prion protein (rPrP). We find that RNA, independent of its sequence, source and size, modulates rPrP aggregation in a bimodal fashion, affecting both the extent and the rate of rPrP aggregation in a concentration dependent manner. Analogous to RNA-induced liquid-liquid phase transitions observed for other proteins implicated in neurodegenerative diseases, high protein to RNA ratios stimulate rPrP aggregation, while low ratios suppress it. However, the latter scenario also promotes formation of soluble oligomeric aggregates capable of seeding  The agents responsible for those fatal conditions are commonly referred to as prions or prion proteins (PrP). Mammalian prions are ubiquitous proteins, which share the chemical properties of all polypeptides, but surprisingly can maintain several, marginally stable, conformational states at once. In the case of TSEs, the infectious form of the prion is called scrapie (PrPSc). This disease-associated conformation is amyloidogenic and self-sustaining over time and across cell divisions3. In recent years the number of proteins suspected of prion-like behavior has grown significantly. Some of those clearly serve a physiological purpose and are considered as functional prions5. Others are toxic in their prion-like state and have been linked to other non-infectious, degenerative disorders, such as Alzheimer’s, Parkinson’s disease and cancer7.Prion diseases such as Transmissible Spongiform Encephalopathies (TSE) are a group of infectious disorders, which irreversibly cripple the nervous system of humans and other mammals9. The outstanding characteristic of every prion is its ability to exist in two distinct physical states at the least10. In the case of TSEs, conversion of the cellular prion protein (PrPC) to its infectious form (PrPSc) is the hallmark of disease onset. The two states of the protein remain chemically identical but differ significantly in their biophysical properties. Whereas PrPC is mostly α-helical, soluble and susceptive to protease digestion and chaotropic agents, PrPSc favors a β-sheet rich conformation14, which renders it amyloidogenic, partially protease-resistant and insensitive to chaotropes1.While the prevalence of proteinopathies becomes more evident, the necessity to understand the prion nature and evolutionary significance growsC/PrPSc discrimination, is the ability of the oligomeric scrapie protein to recruit native PrPC and induce further aggregation. This ability is at the center stage of prion self-replication and maintenance of heritable phenotypic change15. It is also the inspiration behind the “protein-only” hypothesis, which states that the misfolded PrPSc alone is sufficient for PrPC to PrPSc conversion18. This theory has been widely accepted in the field and even a study demonstrating propagation of an infectious prion in the absence of any cofactors has been recently published19. Despite that, a number of reports have emerged suggesting nucleic acids as the putative cofactors for prion formation and propagation23. A recent study has characterized the interaction between PrP and nucleic acids24. Furthermore, studies on RNA dependent phase separation of other neurodegenerative disease-related proteins have also been reported26. Apart from demonstrating that nucleic acids could facilitate prion conversion35, we recently reported that DNA and RNA modulate the aggregation of the tumor suppressor protein p5338. It is, therefore, becoming evident that nucleic acids, particularly RNA, have pronounced effect on protein folding, misfolding and aggregation, in some cases inhibiting and in other cases stimulating the processes40.The most decisive of the criteria, commonly employed in PrP42. Another type of membraneless structure – an organelle-like ribonucleoprotein particle, is formed when cytosolic PrP co-aggregates with RNA43. RNA is also detected in highly infectious brain isolates from TSE-positive Syrian hamsters44. Together with the demonstrations that RNA can induce scrapie phenotype in vitro46 this suggests a strong possibility for macromolecular interplay between RNA and PrP, in vivo. Transcriptome extracts of murine neuroblastoma (N2a) cells are shown to co-aggregate with rPrP to form large, partially protease resistant complexes, in vitro47. Finally, Maharana et al.25 show that high protein to RNA ratios promote phase separation and aggregation of the prion-like RNA binding proteins such as TDP43 and FUS, whereas low ratios prevent it. In accordance with these findings, the emerging concept is that the amyloid fibrils arise from more dynamic liquid droplets and glassy-solid states49, where RNA acts as phase modulator50. These observations hint at an auxiliary, previously unassumed function of RNA, in addition to its traditional role in the central dogma of molecular biology.When PrP is overexpressed in the cytoplasm of the cells treated with proteasome inhibitors, it converts to an alternative isoform and accumulates in the perinuclear organelles (aggresomes), together with RNA23–231 variant, referred hereafter as rPrP) by using static light scattering (LS), dynamic light scattering (DLS), sedimentation, transmission electron microscopy (TEM) and circular dichroism (CD). Furthermore, we follow the aggregation kinetics of rPrP, alone and in the presence of various RNAs, by monitoring the time-dependent increase in LS in a stopped-flow instrument. Our results suggest a modulatory role of RNA in rPrP aggregation, where high protein to RNA ratios lead to the formation of large amorphous aggregates of rPrP, whereas low ratios prevent it, and in turn, generate soluble, oligomeric species that can seed de novo rPrP aggregation. Furthermore, we observe that RNA co-aggregates with rPrP and gets partial resistance to RNase digestion. We therefore propose that RNA is an active player in rPrP aggregation, capable of modulating the outcome by direct interaction.In the present study, we investigate the role of RNA in the aggregation of the full-length, recombinant, murine PrP (rPrPin vitro transcribed mRNAs for dihydrofolate reductase (DHFR) from Escherichia coli and Green Fluorescent Protein + (GFP+), domains V, IV and II from 23S ribosomal RNA (rRNA) of E. coli and bulk-tRNAs isolated from E. coli MRE600.Equilibrium aggregation of rPrP (5 μM) alone or in the presence of various RNAs and ribonucleoside tri-phosphates (rNTPs) was studied by recording LS at 400 nm after incubating the samples for at least 10 minutes at room temperature. The RNAs include 36. However, unlike p53C, at the highest RNA concentration tested here, LS values still remained ~two-fold higher than the protein only reaction. Similar results obtained with different RNAs also suggest that RNA interaction for rPrP aggregation is not dependent on any particular sequence or secondary structure.All rRNA domains and mRNAs tested here stimulated aggregation of rPrP in a concentration dependent manner Fig. . At low 36, free rNTPs up to a rPrP to rNTP ratio = 1:100 exerted no effect on the aggregation of rPrP (data not shown). Thus, we conclude that the modulation of rPrP aggregation is a function of the structured RNAs.Interestingly, tRNAs showed the strongest impact on the aggregation of rPrP among all RNAs tested here. Even though a relatively higher concentration of tRNAs was needed to stimulate rPrP aggregation, the addition of tRNAs led to a 20-fold increase in rPrP aggregation Fig. . Despite90–231), which lacks the octapeptide repeats in the N-terminal domain, to the aggregation assay in the presence of DHFR mRNA and domain V rRNA. In comparison to rPrP, rPrP90–231 aggregated to a much lesser extent on its own, as reflected by the LS values  and size distribution of the rPrP aggregates that are formed in the presence of low concentration of RNA (rPrP:RNA = 1:0.05) by employing DLS. Regardless of the type of RNA, all aggregated species displayed low polydispersity and yielded good correlation functions, demonstrating high sample homogeneity. The Rh values of different samples were on average ~100 nm, which indicated the presence of high molecular weight aggregates Table . At highkobs = 0.007 s−1  at a rPrP to RNA ratio of 1:0.01. In line with the steady-state LS measurements . Also, SN from low RNA reaction (rPrP to RNA = 1:0.2) did not show any stimulation of rPrP aggregation (kobs = 0.02 ± 0.005 s−1). In contrast, SN from a high RNA reaction (rPrP to RNA = 1:0.5) increased the rate of rPrP aggregation more than two-fold (kobs = 0.026 ± 0.005 s−1). However, a much more dramatic increase of the rate of de novo rPrP aggregation occurred when SN from a 1:1 rPrP to DHFR mRNA reaction was used for seeding  from rPrP aggregation reactions, prepared without or with DHFR mRNA, was treated with RNAse A and rapidly mixed with native rPrP in a stopped-flow instrument at a 10-fold dilution. The time-dependent change in LS was recorded to obtain the kinetics of seeded rPrP aggregation. SN from the protein only sample did not enhance the rate of ion Fig.   and high RNA (rPrP:RNA = 1:0.5) concentrations were briefly incubated at room temperature. The experiments were conducted with both GFP+ mRNA and domain IV rRNA. As shown in Fig. To test whether RNA interacts with rPrP during aggregation, we incubated rPrP with DHFR mRNA at 1:0.2, 1:0.1 and 1:0.05 rPrP to RNA ratios, which according to our sedimentation assay induce high levels of rPrP aggregation Fig. . In thisDHFR mRNA alone (without rPrP) was perfectly soluble Fig. . HoweverTo further investigate the nature of the RNA-rPrP complexes we performed RNase protection assays at rPrP to RNA ratio of 1:0.05, with both DHFR mRNA and domain IV rRNA at 1 μM concentration. The reactions were treated with 25 μg/mL RNase A for 30 minutes at 37 °C. While RNase treatment completely digested the RNAs in the absence of rPrP, partial resistance to RNase was observed for both the RNAs coaggregated with rPrP Fig. . These rTo further elucidate the nature of interaction between RNA and rPrP during co-aggregation, we conducted CD experiments at a 1:0.05 protein to RNA ratio using domain V rRNA Fig. , DHFR mR51. Also, it has gradually become evident that nucleic acids are involved in the propagation of prions52. Of the nucleic acid pool available in an eukaryotic cell, RNA was categorically proven to stimulate prion protein conversion and formation of protease resistant prion fibrils53. RNA isolated from scrapie associated fibrils was shown to aggregate recombinant PrP to a prion-like conformation46. It was also demonstrated that certain anti-prion compounds specifically target the RNA-mediated protein folding activity of the ribosome57. These arguments support the proposal that one of the putative factors involved in mediating prion protein conversion is RNA.Since the description of PrP as the infectious agent behind scrapie, its biological function and implication in a variety of human proteinopathies, ranging from amyloidosis to cancer, have been reportedin vitro transcribed RNAs to clarify the role of RNA in the aggregation of rPrP. In line with previous reports31 we observed that rPrP hardly aggregates at physiological pH and salt concentration. However, RNAs of various source and length, significantly influence rPrP aggregation in a concentration dependent manner. Small amounts of RNA, 50–100 times lower in concentration than rPrP dramatically enhance its aggregation – both in terms of the amount and the rate  is completely insensitive to RNA . Likely the LCR of rPrP has a hybrid function, acting as a mediator of RNA-based phase transition60. We have previously found that shortening the N-terminal domain destabilizes rPrP and promotes irreversible denaturation and aggregation61. The N-domain could, therefore, be a site for interaction with different ligands. While heparin binding has a stabilizing effect on it62, RNA binding leads to destabilization, condensation and aggregation. It remains to be established whether or not the rPrP-RNA complexes display any infectious behavior in vivo. There is mounting evidence showing that RNA, among other polyanions, can trigger the in vitro conversion of PrP into scrapie-like PrP species65. As long as PrPSc can be formed, it can amplify the infectious process by itself, but the role of the endogenous cofactors e.g. RNA in the propagation of infectivity of synthetic prion strains cannot be ruled out66. It has been described that different prion strains require different RNAs for efficient conversion27. However, demonstrating de novo infectivity using rPrP and RNA condensates is not straightforward64 and will require special laboratory set up beyond the scope of this work. One possibility would be to employ rPrP and RNA in the protein misfolding cyclic amplification (PMCA) assay under our reaction conditions, which will be a goal for future investigations.Since different RNAs tested in our study exerted analogous effect on rPrP aggregation, we speculate that the process depends more on the physical properties of RNA than on its sequence or structural motifs. As the process is virtually insensitive to free rNTPs and an inverse relationship between the size of the RNA and its effective concentration can be observed, our results highlight the significance of a defined polynucleotide surface for rPrP aggregation. On the other hand, our data suggest that rPrP interacts with RNA with a specific site. Since the N-terminally truncated rPrP variant  and its N-terminally deleted variant rPrP90–231 was conducted by high affinity column refolding in a ÄKTA Prime Plus  as previously described72.Heterologous expression in in vitro with T7 RNA polymerase using PCR amplified DNA templates as described in73. These include mRNAs for DHFR (E. coli) and GFP + , and domains II, IV and V from 23S rRNA (E. coli). The pGEM4Z plasmid encoding the complete 23S rRNA sequence of E. coli K1274 was used as the template for different domains of rRNA. The templates for DHFR and GFP+ mRNAs were generated from their respective DNA clones in pET-24b (Novagen). The bulk-tRNA was extracted from E. coli MRE600 cells by phenol-chloroform treatment using laboratory protocol. All RNAs were quantified using Nanodrop™ 1000 spectrophotometer (Thermo Scientific V3.6).Almost all RNAs included in this study were transcribed rPrP  was diluted in 10 mM Tris-HCl (pH 7.5) and 100 mM NaCl (buffer A) prior to addition of the RNAs or rNTPs. For all equilibrium aggregation measurements such as LS, DLS, TEM and sedimentation, the reactions were incubated 10 minutes at room temperature. The rPrP stock was centrifuged at 20,000 g for 30 minutes prior to sample preparation. Aggregation assays were done without agitation or stirring.90–231 proteins (5 μM) was followed by Rayleigh light scattering (both excitation and emission at 400 nm) in an Infinite M200 PRO multimode microplate reader . Each experiment was repeated three times and averaged for presentation in the figures, where background LS for the various RNA concentrations was subtracted. Further, fast kinetics of rPrP (2 μM) aggregation without or with various RNAs were recorded under the same conditions in a SFM-3000 stopped-flow instrument  by monitoring the increase in LS for up to 150 seconds with 500 μs increments. The data were fitted with single exponential function for rate estimation.Equilibrium aggregation of rPrP and rPrPFor seeding, rPrP (2 μM) samples at varying rPrP to DHFR mRNA ratios were incubated at room temperature for 10 minutes and then treated with 25 μg/mL RNase A (ThermoFisher Scientific) for 2 hours at 37 °C. Larger aggregates were removed by centrifugation at 20,000 g for 30 minutes. A fraction of the resulting supernatant (10% v/v) was rapidly added to a fresh preparation of rPrP (2 μM) in a stopped-flow instrument and the fast kinetics of aggregation were recorded as described above. Rates were estimated by fitting the data with a single-exponential function.75. The bands in each supernatant-pellet pair, corresponding to each rPrP:RNA ratio, were assumed to have a combined intensity of 100%.rPrP at a final concentration of 10 μM was incubated at room temperature without and with RNAs at various ratios for sedimentation analysis using SDS-PAGE. After 10 min, the reactions were centrifuged at 20,000 g at 4 °C and the supernatants were removed in fresh tubes. Pellets were then solubilized in buffer A and the volume was made equal to the corresponding supernatant. Further, fixed volumes of pellet and supernatant from each sample were run in 15% SDS-PAGE. After completion, gels were visualized by Coomassie blue staining and the protein bands were analyzed in pairs by Image J 1.51j8 software75.For quantitative estimation of RNA in pellet and supernatant, a sedimentation assay was conducted with fixed concentration of RNA (1 μM) and rPrP concentration was varied to achieve various ratios. After 10 min incubation the pellet and the supernatant were separated in the same way as described above. The pellets were re-solubilized with buffer A supplemented with 0.1% SDS and then subjected to 1% agarose gel electrophoresis. The band intensities were quantified with Image J 1.5 software75.rPrP (20 μM) was mixed with DHFR mRNA (1 μM) or domain IV rRNA (1 μM) to achieve 1:0.05 (rPrP:RNA) ratio and incubated at room temperature for 10 minutes. After that, the reactions  were subjected to RNase digestion by incubation with 25 μg/mL RNase A (ThermoFisher Scientific) at 37 °C for 30 minutes. Then the samples were supplemented with 1 U/μL of RiboLock RNase inhibitor (ThermoFisher Scientific) and RNA was extracted by phenol-chloroform to ensure complete nuclease inactivation. The RNAs were run in 1% agarose gel and quantified with Image J 1.5 softwareFor TEM measurements, rPrP (5 µM) was incubated with GFP+ mRNA and domain IV rRNA to achieve rPrP:RNA ratios of 1:0.02 and 1:1. All samples were incubated at room temperature for 10 minutes and then 20 μL of each sample were applied to a carbon coated copper grid. After 5 min the grids were washed with sterile water, stained with 2% (w/v) uranyl acetate for 1 minute and washed again with water. Images were collected on a Jeol 1200 microscope  operating at 80 kV.The hydrodynamic radius (Rh) of samples at a rPrP to RNA ratio of 20:1, aggregated in buffer A for 10 minutes at room temperature was evaluated using DynaPro Nanostar , equipped with a 662 nm laser in quartz cuvette at 25 °C. The DLS data for each sample were collected one to three times, with ten cumulates in each measurement, the mean of which lead to respective Rh values. Population distributions were analyzed by correlation function graphs.rPrP (5 μM) was mixed with domain V rRNA, DHFR mRNA and GFP+ mRNA to 1:0.05 ratio (rPrP:RNA) in buffer A and incubated from 5 to 10 min at room temperature before each measurement. CD spectra were collected with a Chirascan CD Spectrometer  from 250 to 200 nm at 70 nm/min rate using a 1 mm-path length quartz cuvette. The spectra for protein and RNAs alone at their respective final concentrations were recorded separately.


The importance of three-dimensional chromatin organisation in genome regulation has never been clearer. But in spite of the enormous technological advances to probe chromatin organisation in vivo, there is still a lack of mechanistic understanding of how such an arrangement is achieved. Here we review emerging evidence pointing to an intriguing role of nuclear RNA in shaping large-scale chromatin structure and regulating genome function. We suggest this role may be achieved through the formation of a dynamic nuclear mesh that can exploit ATP-driven processes and phase separation of RNA-binding proteins to tune its assembly and material properties. Current Opinion in Cell Biology 2019, 58:120–125Cell NucleusThis review comes from a themed issue on Naoko Imamoto and Daniel LarsonEdited by Issue and the EditorialFor a complete overview see the Available online 19th April 2019https://doi.org/10.1016/j.ceb.2019.03.007http://creativecommons.org/licenses/by/4.0/).0959-440X/© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license  , nowadayNuclear extraction experiments in the 20th century suggested the existence of an extensive “nuclear matrix” which would permeate the cell nucleus even in the absence of chromatin  Figure a. These The family of heterogeneous nuclear ribonucleoproteins (hnRNP) was found to have a key role in forming the nuclear matrix and, in particular, scaffold attachment factor A  was identified as one sub-family of proteins with the highest affinity to scaffold attachment regions in the genome . This prOne recent development in this direction was the suggestion that nuclear RNAs can themselves act as regulatory factors and nuclear organisers . For insA role for nuclear RNA in regulating chromatin structure is not well established, however much RNA is not exported to the cytoplasm  and must presumably be degraded in the nucleus . This imHnRNP proteins have been shown to associate non-coding and intronic RNAs ,18. For The eukaryotic nucleus is a complex and heterogeneous environment in which a multitude of biological processes occur simultaneously. One requirement for the viability of a cell is that these processes should not interfere with one another: one way to achieve this is to compartmentalise operations . By staiWhile some nuclear bodies show liquid-like properties such as coarsening c, their A recent intriguing development in this picture is that RNA plays a non-trivial role in determining the phase separation properties of a multitude of proteins. In particular, low concentration of RNA appears to promote the phase separation of RNA binding proteins or proteins with intrinsically disordered regions such as FUS •• and hnAs mentioned previously, the hnRNP family of proteins possesses RNA-binding domains and SAF-A also has an AAA+ domain with ATPase activity ••. This The bimodal nature of SAF-A, i.e. displaying both a specific RNA-binding domain and an intrinsically disordered region which can drive phase separation through non-specific interactions , is partWhile this model remains to be proved both in vivo and in vitro, it is tempting to connect it to other recent findings. Indeed, SAF-A depletion has been shown to mainly affect euchromatin compaction and to leave heterochromatin-rich loci largely unaffected ••, 23•]•23•]. BeThe final proof of the presented model would be to test the phase separation and material properties of hnRNP proteins and SAF-A in vitro. The “rheology”  of the self-assembled material, whether liquid, solid or something in between, under different RNA conditions will shed much light into the functional role of this class of proteins. The biophysical characterisation of RNA-dependent phase separation would open a new mechanistic understanding of how hnRNPs, and other RNA-binding proteins, may regulate chromatin structure and genome function through the interaction with nuclear and non-coding RNAs.In conclusion, we argue that nuclear RNA and associated proteins, such as SAF-A, are key regulators of genome architecture which need to be better understood to achieve a comprehensive picture of nuclear organisation. We believe that the concept of arrested phase separation via non-equilibrium (ATP-driven) mechanisms and interactions with nuclear RNA is a powerful model to describe the formation of ever-recycling membraneless compartments with self-limiting sizes, i.e. nuclear bodies. Furthermore, we speculate that similar mechanisms may underlie the self-assembly of a dynamic nuclear hydro-gel which supports and defends large-scale chromatin structure and transcriptionally-active micro-environments.The authors declare no conflict of interest.


DEAH-box adenosine triphosphatases (ATPases) play a crucial role in the spliceosome-mediated excision of pre-mRNA introns. Recent spliceosomal cryo-EM structures suggest that these proteins utilize translocation to apply forces on ssRNAs rather than direct RNA duplex unwinding to ensure global rearrangements. By solving the crystal structure of Prp22 in different adenosine nucleotide-free states, we identified two missing conformational snapshots of genuine DEAH-box ATPases that help to unravel the molecular mechanism of translocation for this protein family. The intrinsic mobility of the RecA2 domain in the absence of adenosine di- or triphosphate (ADP/ATP) and RNA enables DEAH-box ATPases to adopt different open conformations of the helicase core. The presence of RNA suppresses this mobility and stabilizes one defined open conformation when no adenosine nucleotide is bound. A comparison of this novel conformation with the ATP-bound state of Prp43 reveals that these ATPases cycle between closed and open conformations of the helicase core, which accommodate either a four- or five-nucleotide stack in the RNA-binding tunnel, respectively. The continuous repetition of these states enables these proteins to translocate in 3′-5′ direction along an ssRNA with a step-size of one RNA nucleotide per hydrolyzed ATP. This ATP-driven motor function is maintained by a serine in the conserved motif V that senses the catalytic state and accordingly positions the RecA2 domain. In eukaryotes, the removal of non-coding intron sequences in pre-mRNAs is performed by the spliceosome, a multimegadalton molecular machine composed of numerous RNA and protein components . The splThe key triggering components of the spliceosome driving the transition from state to state are a set of so-called RNA helicases . The firThe release of the mature messenger RNA (mRNA) after intron cleavage is performed by the DEAH-box ATPase Prp22 ,16. It hin vitro helicase activity, none of the recent cryo-EM structures containing one of these so-called helicases shows an RNA duplex that could serve as a direct target  was identified as an homolog of Saccharomyces cerevisiae Prp22 (scPrp22) using the NCBI BLAST search tool . About 200 μl protein samples were flash frozen in liquid nitrogen and stored at −80°C. ctPrp43, ctPrp43-S387A, ctPrp43-S387G, ctPrp22-S837A, ctPrp22-S837G and ctPrp22-S837P were expressed and purified using the same protocol as described for ctPrp22.Prp22 from −1 (32.76 μM) and incubated with a 10-fold molar excess of ADP, a 20-fold molar excess of BeSO4, a 60-fold molar excess of NaF and a 2.5-fold molar excess of U12-RNA  for at least 30 min at 4°C. Crystallization was performed via the sitting-drop vapor-diffusion technique by mixing 1 μl complex solution with 1 μl crystallization buffer. ctPrp22 Apo crystals were obtained in 100 mM Bis-Tris propane (pH 6.5), 400 mM K-Thiocyanate and 20% (w/v) PEG3350 and ctPrp22+RNA and ctPrp22-S837A+RNA crystals in 100 mM Bis-Tris propane (pH 8.5), 250 mM NaF and 22% (w/v) PEG3350. All crystals were obtained after 2–3 days at 20°C. ctPrp43-S837A and ctPrp43-S387G crystals were obtained as described in Tauchert et al.  of 1.5 and a minimum CC1/2 of 60% as cutting criteria  PEG400 and 5% (w/v) glycerol and flash-cooled in liquid nitrogen prior to data collection. Crystals of ctPrp43-S387A and ctPrp43-S387G were not additionally cryoprotected prior to flash-cooling. X-ray diffraction data were collected at 100 K on beamline P13 (ctPrp22) and beamline P14 (ctPrp22-S837A and ctPrp43-S387A), PETRA III, DESY , as well as on Rigaku MicroMax-003 equipped with a Dectris Pilatus 2K detector (ctPrp43-S387G). The criteria .Phaser with the structure of ctPrp2 (PDB ID: 6fa5) used as a search model  and Chimera . ctPrp22 was used at a concentration of 0.4 μM and ctPrp43 at 5 μM. Km and kcat were calculated by fitting the experimental data according to the Michaelis and Menten equation using QtiPlot (v.0.9.8.9).The ATPase activity measurements of ctPrp22 and ctPrp43 were conducted with a nicotinamide adenine dinucleotide (NADH) dependent coupled enzymatic assay . The dec20-RNA to up to 70 μM ctPrp22 and 120 μM ctPrp43 was monitored in 20 mM Tris/HCl (pH 7.5), 200 mM NaCl, 5% glycerol and 3 mM MgCl2. Measurements in presence of ADP/adenylyl imidodiphosphate (AMPPNP) were performed with a 50-fold molar excess of the nucleotide over ctPrp22 or ctPrp43, except for ADP-dependent measurements of ctPrp22 where a constant concentration of 3.5 mM of the nucleotide was used throughout all measurements. All reactions were performed in 50 μl and measured as a set of triplicates. For all measurements an excitation wavelength of 480 nm was set and the emission was detected at 530 nm for 500 ms. The measured fluorescence polarization was normalized and fitted according to Rossi and Taylor (The RNA binding in dependence of different adenosine nucleotides was performed via fluorescence polarization measurements using a VICTOR Nivo Multimode Microplate Reader (PerkinElmer). The binding of 6 nM 3′ 6-carboxyfluorescein-labeled Ad Taylor  using Qt−1. For each construct, 15 spectra of 1 s accumulation were averaged for the final spectrum. The CD data are presented as mean residue ellipticity (θ) and fitted using QtiPlot (v.0.9.8.9)  of this mutant protein and the wild-type protein were recorded using a Chirascan CD spectrometer (Applied Photophysics). Measurements were performed in 20 mM Na-phosphate buffer at 20°C with a protein concentration of 0.1 mg ml0.9.8.9) .C. thermophilum (ctPrp22). Previous studies on other closely related spliceosomal DEAH-box members, Prp2 and Prp43, have demonstrated that proteins from this organism are suited for crystallographic investigations as they might have an increased tendency to crystallize when compared with orthologs from S. cerevisiae or Homo sapiens . Th. Th20-RNe Figure . Howevere Figure . Neverthe Figure .kcat, Km and Kd values deviate from the ones measured for Prp22, both ATPases are stimulated by the presence of RNA and the binding of ssRNA in dependence of the adenosine nucleotide exhibits the same tendencies  was subjected to the same basic biochemical characterization. Although s Figure  and C. Ds Figure ,55. Sinc12-RNA was used, of which nine nucleotides were traceable in the electron density map , enough portions of the domain were traceable in the electron density to unambiguously place it with respect to the RecA1 and C-terminal domains  ,51,56,57versus RecA1: 3) and the mechanical aid of the β-hairpin, the RNA stays stably attached to the RecA2 domain and does not backlash. Instead, the few RecA1 interactions need to be broken and subsequently replaced by the succeeding sugar-phosphates pushed into that position. A cycling of the described events enables DEAH-box ATPases to translocate along an ssRNA in 3′-5′ direction at a step-size of one RNA nucleotide per hydrolyzed ATP  is improved by a factor of ∼1.7. Since mainly the mainchain of the motif V serine interacts via water-mediated hydrogen bonds with the adenosine nucleotides, we tested if a higher flexibility of the mainchain at this position has an effect on catalysis. The substitution by a glycine in Prp22-S837G has no significant effect on kcat compared to the alanine mutant, but significantly improves the Km, especially in the presence of RNA. The catalytic efficiency increases 2.3-fold in the absence of RNA and 3.7-fold in the presence of RNA. The gain in flexibility at this position in motif V appears to improve the binding/sensing of ATP rather than stimulating the turnover rate. In contrast to an increase in flexibility of the mainchain at this position, we tested a decrease in flexibility by mutating the serine to a proline. Prp22-S837P did not show any significant ATPase activity (data not shown). In order to exclude misfolding as a reason for the lack in activity, we subjected Prp22 and Prp22-S837P to circular dichroism spectroscopy measurements and could verify the structural integrity of Prp22-S837P , the sensing function is completely abolished at minimum flexibility (proline).In eukaryotes non-coding introns in precursor mRNAs are excised via the spliceosome. One key player during pre-mRNA splicing is the DEAH-box ATPase Prp22, which is critical for the release of mature mRNAs. In this study, we determined the first crystal structures of the spliceosomal DEAH-box ATPase Prp22 in the adenosine nucleotide-free but RNA-bound state, as well as in absence of any ligand. Prp22 shares a conserved architecture of the catalytic unit with other spliceosomal DEAH-box ATPases and interacts with RNA in a comparable manner as Prp43. In the absence of RNA and adenosine nucleotide, the RecA2 domain has an increased ability to move independently as a rigid body and a serine in motif V ensures the proper positioning of this domain in dependence of the bound ligand state. A comparison with the ATP-bound state of Prp43 shows that these ATPases toggle between a closed conformation of the helicase core, which accommodates a stack of four nucleotides in the RNA-binding tunnel, and an open conformation with a bound five-nucleotide stack. A cycling of these events enables these proteins to translocate in 3′-5′ direction along a single-stranded RNA with a step-size of one RNA nucleotide per hydrolyzed ATP . The proTwo different models for the translocation of DEAH-box ATPases have been proposed in the past ,14,51. TEven for more distant relatives of the SF2 helicase family this translocation mechanism seems to be conserved. Using structural and biophysical approaches like smFRET a translocation step-size of as well one RNA nucleotide could be determined for NS3 helicases . These h6I3O - ctPrp22 Apo6I3P - ctPrp22 + RNA6QIC - ctPrp22-S837A + RNA3−6QID - ctPrp43-S387A + ADP-BeF3−6QIE - ctPrp43-S387G + ADP-BeFThe coordinates and structure factors have been deposited in the PDB, with following accession numbers:Supplementary DataClick here for additional data file.


This article has been corrected: In the Materials and Methods section, regarding the Isolation of RNA, production of cRNA, array hybridization and scanning, the correct microarray GEO information is given below:Isolation of RNA, production of cRNA, array hybridization and scanninghttp://www.ncbi.nlm.nih.gov/geo).Total RNA was extracted using the Qiagen RNA isolation kit according to the manufacturer’s instructions  and copy RNA was prepared according to the Affymetrix Gene Chipâ Expression Analysis Technical Manual . Further details are given in our recent report [6]. The microarray study is MIAME compliant, and the raw data have been deposited in GEO database (GSE54829; 101808-101831. https://doi.org/10.18632/oncotarget.21981Original article: Oncotarget. 2017; 8:


Biophysical relationships did not decouple at inhabited islands, indicating that abiotic influences remain important macroscale processes, even at chronically disturbed reefs. However, spatial autocorrelation among inhabited reefs was substantial and exceeded abiotic and grazing influences, suggesting that natural constraints on reef benthos were superseded by unmeasured anthropogenic impacts. Evidence of strong abiotic influences on reef benthic communities underscores their importance in specifying quantitative targets for coral reef management and restoration that are realistic within the context of local conditions.Our ability to understand natural constraints on coral reef benthic communities requires quantitative assessment of the relative strengths of abiotic and biotic processes across large spatial scales. Here, we combine underwater images, visual censuses and remote sensing data for 1566 sites across 34 islands spanning the central-western Pacific Ocean, to empirically assess the relative roles of abiotic and grazing processes in determining the prevalence of calcifying organisms and fleshy algae on coral reefs. We used regression trees to identify the major predictors of benthic composition and to test whether anthropogenic stress at inhabited islands decouples natural relationships. We show that sea surface temperature, wave energy, oceanic productivity and aragonite saturation strongly influence benthic community composition; overlooking these factors may bias expectations of calcified reef states. Maintenance of grazing biomass above a relatively low threshold (~ 10–20 kg haThe online version of this article (10.1007/s00338-018-01737-w) contains supplementary material, which is available to authorized users. Coral reef benthic communities are influenced by abiotic and top-down controls operating across a range of spatial scales , as well as turf and fleshy macroalgae. Hard coral and crustose coralline algae deposit calcium carbonate to form a structural reef architecture, whereas turf and fleshy macroalgae occupy coral settlement space and overgrow dead coral structures, although some macroalgal species also deposit carbonate  that disrupt abiotic and top-down controls  of NOAA’s Pacific Island Fisheries Science Center. Underwater visual censuses (UVC) and benthic photoquadrats (PQs) were carried out at 34 US-affiliated tropical Pacific islands and atolls, encompassing the Hawaiian and Marianas archipelagoes, American Samoa and the Pacific Remote Island Areas (PRIAs); this region spans gradients of human population density, sea surface temperature and oceanic productivity , positive values indicate sites dominated by calcifying organisms  and negative values indicate sites dominated by algal organisms  . Benthic substrate composed of sand and sediment was omitted from these calculations, and thus, the reef-builder index represents the relative cover of major benthic taxa rather than absolute abundances. The index also combines benthic taxa that have distinct ecological functions. For calcifiers, positive values may represent high cover of coral or CCA and thus represents calcification potential rather than directly correlating to calcification rates , fleshy algal organism cover  and, as an integrated measure of reef benthic state, the ratio of calcifier to fleshy algal cover. After transforming the ratio onto a logOur biotic grazing predictor, herbivorous fish grazing pressure, was represented by site-level biomass estimates calculated from the UVC fish observations. Biomass is linked to energy expenditure and, as bite and foraging rates scale allometrically with body size, grazing biomass is widely used as a proxy for grazing pressure . Net primary productivity (mg C m−2 d−1) estimates were extracted from NOAA CoastWatch based on satellite measurements of photosynthetically available radiation (NASA’s SeaWiFS), SST  and chlorophyll a concentration (NASA Aqua MODIS) and were estimated every 8 d between 2002 and 2013 at a ~ 4.6 × 4.6 km resolution (http://coastwatch.pfeg.noaa.gov/erddap/griddap/erdPPbfp28day.graph)  were mapped to a global extent by data interpolation of CO2 chemistry samples collected from 724 large-scale oceanographic cruises between 1972 and 2013  estimates from the National Oceanographic Data Center’s Coral Reef Temperature Anomaly Database (CoRTAD), based on AVHRR Pathfinder data between 1982 and 2008 at a ~ 4.6 × 4.6 km resolution  and high disturbance groups (inhabited islands and near to population centers) using criteria developed for previous analyses of the CREP dataset  over an ocean basin extent. BRT models are regression tree ensembles constructed by building ‘trees’ sequentially where, at each stage, the next tree attempts to minimize the deviance of the residuals of the previous tree  to examine the relative strength of each covariate and all pairwise interactions in predicting the reef-builder index, calcifier cover and fleshy algal cover at fine scales  and 100% (strong influence). Additionally, relationships between the reef-builder index and predictors were visualized using partial dependency plots that show the fitted function while holding the effect of other predictors at their mean .All analyses were performed using R version 3.4.1 , such that six islands in Hawaii  and seven islands in the Marianas  lacked any calcifier-dominated sites. In contrast, algal-dominated sites occurred on every island, rendering this the more common state across the Pacific  at 20 islands; i.e., > 50% calcifying cover; 0.03 < reef-builder index < 2.06) to algal-dominated (1129 sites (72.09%) at 32 islands; i.e., > 50% fleshy algal cover; − 3 < reef-builder index < − 0.01) . The remaining 13.9% of sites were dominated by neither hard coral nor fleshy algae, but rather by calciferous 2 d−1) . Wave energy also had a moderate influence on the reef-builder index, which decreased as wave energy increased  and algal cover highest at high wave energy sites  . Aragonite saturation state had the weakest abiotic influence on the reef-builder index, but was a strong predictor of both calcifier cover and fleshy algal cover when these were modeled separately. Models predicted a gradual increase in calcified dominance with aragonite saturation state  aragonite saturation states and predicted fleshy algal cover reaching a peak of 65% at low (3.5 Ωa) saturation states .Abiotic covariates were strong predictors of benthic community composition. Regions of high SST, oceanic productivity and aragonite saturation state, and low wave energy, were associated with higher reef-builder values  Fig. a–c. Alon−1), and herbivore biomass above this threshold had no further effect  or increased  by ~ 5% . Browsers had the weakest effect, with calcifier cover remaining steady across the browser biomass gradient  . Interactions were strongest between abiotic covariates and site depth, with higher SST, oceanic productivity and aragonite state values at shallower depths, while grazing covariates interacted weakly with each other  .Deviance explained was ~ 45–58% for all models, indicating that BRTs performed equally in predicting fine-scale patterns in the reef-builder index, calcified cover and fleshy algal cover across different disturbance regimes . Unexplained deviance was partly attributable to inaccurate predictions of the highest and lowest reef-builder index values, although there were no residual patterns in any benthic cover model . Autocovariates were important predictors (relative importance: 3.9–43.1%) and were effective in reducing spatial autocorrelation in all BRTs  and algae ] was primarily predicted by natural variation in temperature, productivity, wave energy and aragonite saturation state. Calcifier-dominated reefs occurred in warm, productive regions on reefs with low wave energy and high aragonite concentrations. Herbivorous fishes were important influences on the reef benthos, with a loss of grazing pressure at low cropper and scraper and excavator biomass levels corresponding with a transition toward algal-dominated reefs. Our analyses suggest that abiotic conditions outweigh or match grazing pressure as predictors of the relative abundances of calcifying and algal organisms at the site-level scale and provide evidence of the nonlinear influence of grazing pressure on reef benthic community composition.We found that abiotic factors were important predictors of benthic community state, with the influence of sea surface temperature stronger than all other covariates. Shifts from negative  to positive  reef-builder values tracked increases in sea surface temperature, as in Williams et al. , represeWave energy was moderately important in predicting reef-builder values, consistent with evidence that habitat suitability is a key influence on benthic community composition between sites Supplementary material 2 (XLSX 40 kb)Supplementary material 3 (DOCX 119 kb)Supplementary material 4 (XLSX 38 kb)Supplementary material 5 (XLSX 31 kb)Supplementary material 6 (DOCX 107 kb)Below is the link to the electronic supplementary material.


Saccharomyces cerevisiae, which is an organism lacking miRNA machinery. Here we examined the subcellular localization of sdRNAs in yeast. Our findings reveal that both sdRNAs and their precursors, snoRNAs, are present in the cytoplasm at levels dependent upon stress conditions. Moreover, both sdRNAs and snoRNAs may interact with translating ribosomes in a stress-dependent manner. Likely consequential to their ribosome association and protein synthesis suppression features, yeast sdRNAs may exert inhibitory activity on translation. Observed levels of sdRNAs and snoRNAs in the cytoplasm and their apparent presence in the ribosomal fractions suggest independent regulation of these molecules by yet unknown factors.In recent years, a number of small RNA molecules derived from snoRNAs have been observed. Findings concerning the functions of snoRNA-derived small RNAs (sdRNAs) in cells are limited primarily to their involvement in microRNA pathways. However, similar molecules have been observed in  The mechanistic details of these non-canonical functions are largely unknown. Moreover, it has recently become evident that mature, functional snoRNAs undergo processing to form stable short fragments, termed psnoRNAs, for processed snoRNAs4 or sdRNAs for snoRNA-derived RNAs5. The presence of processed forms of snoRNAs has been demonstrated in several organisms, including the primitive protozoan Giardia lamblia6, Epstein-Barr virus7, the budding yeast Saccharomyces cerevisiae8, and mammals13.snoRNAs are noncoding RNAs that contribute to ribosome biogenesis and RNA splicing by modifying ribosomal RNA and spliceosomal RNAs, respectively. However, recently emerging evidence suggests that some snoRNAs have non-canonical functions in RNA editing, alternative splicing or maintenance of chromatin structure4 as well as their microRNA–like abilities, have been described in several organisms15. Recently, it has been postulated that FUS-dependent sdRNAs in human cell lines might regulate gene expression, affecting transcript stability and translation16. As the majority of miRNA-targeted, and thus translationally repressed, mRNAs are distributed in the cytoplasm, miRNA-like sdRNAs are expected to co-localize within the cytoplasm. Indeed, a subset of small RNAs derived from snoRNAs have been detected in the cytoplasm in G. lamblia14 and humans10; however, their nucleolar localization has been reported as well11. Our recent work presented another possibility of sdRNA localization within the cytoplasm by association with ribosomes8. These studies were performed in S. cerevisiae, an organism lacking miRNA machinery; hence, one might suspect a distinct role for non-miRNA sdRNAs in yeast.Concerning possible functions of small RNAs derived from snoRNAs, their potential to regulate alternative splicing events17, lipotoxic conditions18 or heat shock19. Knowledge concerning snoRNA expression regulation, however, is sparse. In 2002, it was shown for the first time that snoRNAs are involved in cancer development20. Since that time, a growing body of evidence has emerged linking both full-length snoRNAs and their derivatives to oncogenesis (reviewed in21). Considering both localization and the potential functions of full-length snoRNAs and sdRNAs, one might suspect that snoRNAs and their derivatives orchestrate responses to environmental stress outside of the nucleus. Surprisingly, studies aimed at revealing the abundance and subcellular localization of sdRNAs in stress have yet to be reported.It is now commonly accepted that full-length snoRNAs are not exclusively localized within the nucleus but are also present in the cytoplasm. Moreover, their cytoplasmic abundance is dynamically regulated in various stress conditions, such as oxidative stress8. However, their regulatory potential cannot be excluded, as recent studies demonstrated that even relatively small levels  of ribosome-associated noncoding RNA  are sufficient to substantially influence global ribosome activity and regulate translation22. We recently demonstrated that due to sdRNA low abundance, conventional techniques, such as northern hybridization, are not sensitive enough to detect the full repertoire of cellular sdRNAs23. Poor sensitivity and low throughput of hybridization-based technologies can be overcome by sensitive, amplification-based detection methods, such as stem–loop reverse transcription PCR (SL-RT-PCR), originally described by Chen et al.24 and successfully implemented by our group for detection of yeast sdRNAs from as little as 50 ng of low molecular weight cellular RNA23.Yeast sdRNAs are observed in limited numbers during the sequencing of ribosome-associated small RNAs, with a maximum of 15 copies in the rancRNA libraryS. cerevisiae, we used this amplification-based method. To enable absolute quantification of RNAs, we implemented digital droplet PCR (ddPCR) technology. Our comprehensive analysis of sdRNA and snoRNA abundance and localization was performed under 12 different yeast growth conditions. Herein, we present the first evidence that snoRNA levels and the localization of sdRNAs within the cell, including association with ribosomes, are dependent upon stress conditions. As a consequence of sdRNA binding to ribosomes, an inhibition of in vitro and in vivo translation occurs. Moreover, for the first time, we present experimental data suggesting that both the expression and ribosome association of two types of related RNAs, namely, snoRNA-derived small RNAs and full-length snoRNAs, are independent from each other during multiple growth conditions.Therefore, to investigate the subcellular localization of both full-length snoRNAs and snoRNA-derived small RNAs in S. cerevisiae8. Sequences of sdRNAs are shown in Table Three snoRNAs  and 3 corresponding sdRNAs  were chosen for analysis based on the highest read coverage observed in ribosome-associated small RNA sequencing in Saccharomyces cerevisiae strain BY4741 was grown in YPD medium with 2% glucose at 30 °C. Environmental stress was induced as previously described25 in two biological replicates. Briefly, cells were grown to mid-log phase, and stress conditions were applied for 15 min. Next, cells were pelleted and stored at −20 °C. Stress conditions were as follows: heat shock (37 °C), cold shock (15 °C), high salt conditions (1 M NaCl), high pH conditions (pH 7.9), low pH conditions (pH 4.0), UV exposure (120 J/m2 UV), hyperosmotic shock (1 M sorbitol), hypoosmotic shock (cells grown to mid-log phase in YPD supplemented with 1 M sorbitol were transferred to YPD without sorbitol), amino acid starvation, sugar starvation, and anaerobic and normal growth.27. Briefly, cell pellets were washed with ice-cold water and resuspended in buffer  at 4 °C. Equal volumes of glass beads (400 μm in diameter) were added, and cells were broken using 8 pulses of vortexing (30 sec each) punctuated by cooling on ice. Cell debris was precipitated at 11,300 × g for 2 min at 4 °C in F-34-6-38 Eppendorf rotor. Lysate was further clarified by centrifugation at 11.300 × g for 10 min at 4 °C in F-34-6-38 Eppendorf rotor. After clarification, 1/10 of the total lysate volume was used to isolate total cellular RNA (S30). Subsequently, ribosomes were pelleted (P100) from lysates by centrifugation at 160,000 × g for 90 min at 4 °C in Beckman 70.1 Ti rotor and suspended in the storage buffer (2 mM Mg(OAc)2, 100 mM KOAc, 20 mM HEPES, pH 7.4, 0.1 mM PMSF, 1 mM DTT, 20% glycerol). The top two-thirds of the post-ribosomal supernatant were collected and frozen, and designated as the S100 fraction. P100, S100 and S30 fractions were mixed with TRI Reagent (MRC), flash frozen in liquid nitrogen and subjected to RNA isolation following the manufacturer’s instructions. The purity of P100 and S100 fraction was verified with Agilent Bioanalyzer 2100 with the use of RNA Nano 6000 kit.Yeast ribosomes were prepared as previously described23. Standard RT primers for snoRNA amplification were designed using the Primer3Plus tool. All reverse transcription reactions were performed in a multiplex manner. Reverse transcription reactions contained 10 or 100 ng RNA from P100, S100 or S30 fractions, 50 nM of each stem-loop RT primer for sdRNAs and spike-in RNA, 50 nM of each standard RT primer for snoRNAs, 1 × RT buffer, 0.25 mM of each dNTPs, 50 U SuperScript SSIII reverse transcriptase (Invitrogen), 5 U RiboLock RNase Inhibitor (Thermo Scientific), 10 mM DTT and 500 fM spike-in RNA . The reaction mixture was composed of 10 µl of 2x QX200™ ddPCR™ EvaGreen Supermix, 200 nM specific forward and universal reverse primers , 100 mg soluble protein factors isolated from yeast grown under optimal and stress conditions, 25 mg deacylated yeast tRNA and 0.3 nmol [3H]-phenylalanine. The reaction was performed at 30 °C for 30 min. Products were precipitated in TCA, recovered on Whatman glass fibre GF/C filters and subjected to scintillation counting. In vitro translation assays were performed in triplicate. Reported values are corrected for control samples lacking ribosomes, which were typically 0.5% to 1% of the total probe counts applied.Translation of poly(U) templates was performed as describedS. cerevisiae cell-free extracts were prepared in the cold-room, as previously described in29 with modifications. To prepare S. cerevisiae S30 extract, yeast culture was grown to a final OD600 of 1.2 at 30 °C in YPD medium. Cells were chilled on ice, harvested by centrifugation at 1,500 × g for 5 min at 4 °C in F-34-6-38 Eppendorf rotor and washed five times with 30 ml of ice-cold buffer A 2, 2 mM DDT, 0.5 mM PMSF) supplemented with 8.5% (w/v) mannitol. Subsequently, cell pellet was resuspended in 1.5 ml of buffer A (supplemented with 8.5% mannitol and 0.5 mM PMSF) per 1 g of the cell pellet and six-time weight of cold glass beads (400 µm in diameter) was added.2 and treated with 50 U/ml micrococcal nuclease at 26 °C for 10 min in order to eliminate endogenous mRNAs. The reaction was stopped by adding 2.5 mM EGTA. Both types of S30 extracts were aliquoted, snap-frozen in liquid nitrogen and stored at −80 °C.Cells were broken by performing eigh-1 min cycles of vortexing (30 sec) and handshaking . To remove the glass beads, the lysates were centrifuged at 120 × g for 2 min at 4 °C in F-34-6-38 Eppendorf rotor, transferred to a fresh tube, and centrifuged at 30,000 × g for 7 min at 4 °C in Hettich ROTINA 380 R rotor. The resulting S30 supernatant was purified on a G-25 Sephadex column. A portion of purified S30 extract was supplemented with 1 mM CaClin vitro translation assays, 4 µl master mix , 4 U Ribonuclease Inhibitor, 500 nCi 35S-methionine ) was mixed with 5 µl cell-free extract. Synthetic sdRNA or control RNA oligomers (10–500 pmol) or cycloheximide (7.5 μg/μl) was added to reach a final volume of 14 μl and mixtures were incubated at 26 °C for 40 min. The labeled proteins were precipitated by adding four volumes of ice-cold acetone and incubating at −20 °C for 30 min. Then, samples were centrifuged at 16 300 × g for 15 min at 4 °C in Eppendorf FA-45-24-11 rotor. The precipitate was dissolved in 15 µl 1x loading buffer  SDS, 0.1% (w/v) bromophenol blue, 10% (v/v) glycerol, 100 mM DTT). Proteins were resolved on 10% SDS-polyacrylamide gels using 1xTGB running buffer and visualized on phosphor – storage intensity screen (Fujifilm) overnight. Screens were scanned using Fujifilm Fluorescent Image Analyzer FLA – 5100. We have measured the intensity of labelled proteins within the gel and subtracted background screen intensity. All measurements were performed at least in triplicate and standard error (SE) has been calculated. p-value has been calculated using t-test.For In vitro translation reactions were performed in wheat germ (Promega), rabbit reticulocyte (Promega), and human  systems according to the manufacturers’ instructions. The reactions were incubated for 90 min. at 25 °C (wheat germ extract) or at 30 °C (rabbit reticulocyte and human systems). In all cases, an uncapped in vitro-transcribed luciferase mRNA containing a 30-base poly(A) tail was used as a template. 35S-labeled proteins were resolved using SDS-PAGE and visualized on a storage phosphor intensity screen (Fujifilm) overnight. Screens were scanned using a Fujifilm Fluorescent Image Analyzer FLA-5100. All reactions were performed in triplicate and standard error (SE) has been calculated.22. Spheroplasts were combined with synthetic sdRNA (10–100 pmol) or 100 pmol control RNA oligomers  and electroporated. For controls, translation was inhibited by adding 7.5 μg/μl cycloheximide to the spheroplasts. Electroporated spheroplasts were incubated at 30°C with 1 μl 35S-methionine  for 1 h. Labelled proteins were precipitated in TCA, recovered on Whatman glass fibre GF/C filters and subjected to scintillation counting. Metabolic labelling measurements were performed at least in triplicate, and standard error (SE) was calculated. Statistical significance was determined using t-test.Yeast spheroplasts were prepared from a 50-ml culture grown to an OD600 of 0.8 by adding 350 U of zymolyase (Zymo Research) and incubating at 30 °C for 25–30 min as previously described23, we decided to employ an optimized stem-loop reverse transcription (SL-RT) followed by ddPCR. The ddPCR system measures fluorescence intensities of droplets after completion of all thermal cycling. The copy number of target genes is determined based on the number of fluorescent-positive and -negative droplets in a sample well. ddPCR provides an absolute number of RNA copies present in the sample. To define the minimum number of sdRNA copies that can be detected using the pulsed SL-RT-ddPCR method, we spiked 0.5 pg of an exogenous synthetic RNA  to total RNA isolated from S. cerevisiae. Total RNA was subjected to the SL-RT method. Various dilutions of cDNA were amplified using ddPCR technology. These analyses demonstrated the ability of ddPCR to detect small RNA input levels, as low as 0.005 pg  from post-ribosomal supernatant (S100) and to verify the cellular distribution of sdRNAs between these two fractions. The purity of P100 and S100 fraction was verified with Agilent Bioanalyzer 2100 with the use of RNA Nano 6000 kit Fig. . The actFor accurate quantification of snoRNAs and sdRNAs within P100 and S100 fractions, we employed ddPCR technology. Spiked-in synthetic RNA was used as a control for experiments, as previously described for total cellular RNA pools. Absolute concentrations of spike-in reference RNA in different cDNA samples derived from ribosome-associated RNA pools were uniformly distributed, with a mean value of 7,573 (±11) copies/µl in P100 and 20,125 (±122) copies/µl in S100 fraction. Therefore, we concluded that possible differences in snoRNA or sdRNA concentrations in different pools derive from their differential association with ribosomes and not from biases due to experimental design.The first observation was that both full-length snoRNAs and sdRNAs are present in ribosome-containing fractions Fig. . MoreoveAmong investigated sdRNAs Fig. , sdR67 win vivo interactions with ribosomes, we compared the differential accumulation of both snoRNAs and sdRNAs in ribosome-associated RNA fractions  reduced in vitro translation to 40% and 75%, respectively. The highest inhibitory effect was observed for sdR128. Even small concentrations of sdR128, such as 0.7 µM , observably reduced in vitro protein synthesis. Conversely, the addition of the highest tested dose of the scrambled sdRNA128 (scr-sdR128) or 18nt-long control RNA oligomer (scr-ranc18), 35.7 µM, did not have any influence on translation efficiency.The observation that sdRNAs accumulate in ribosomal fractions in a stress-dependent manner led to speculation of their potential function as regulatory ncRNAs during protein biosynthesis. To clarify this, we set up an out Fig. . In the in vitro effects have a physiological significance in yeast we used electroporation to introduce synthetic sdRNAs into S. cerevisiae cells. Conditions for small RNA electroporation were optimized in our previous studies, where quantification of the uptake efficiency of the synthetic 18-mer into spheroplasts indicated the presence of about 200,000 molecules per cell, thus roughly equaling the ribosome concentration22. We measured 35S-Met incorporation into newly synthetized proteins in the presence and absence of sdR128, sdR83 and sdR67. As controls, we have used RNA oligomers with similar length to tested sdRNAs: scr-sdR128 (22 nt) as a control for sdR128, scr-ranc18 (18 nt) for sdR67 and spike-in RNA (44 nt) for sdR83. Control oligomers did not affect in vivo translation  or in the presence of synthetic sdRNAs. The addition of S. cerevisiae sdRNAs reproducibly inhibited in vitro protein biosynthesis in the wheat germ system  is upregulated during heat shock, amino acid starvation and sugar starvation and downregulated under high salinity and hyperosmotic conditions31. Interestingly, the expression pattern of snoRNAs studied herein do not resemble those of snR17. In Chinese hamster ovary (CHO) cells U14 snoRNA, which corresponds to yeast snR128, is strongly upregulated during heat shock19. In yeast, however, we observed almost 2-fold downregulation of snR128 during heat stress. Such observations suggest that different snoRNAs possess distinct expression patterns during stress responses, which might be related to their functions.It has been already shown that snoRNAs play crucial roles in adaptation to stress conditions33. Expression analysis of sdRNAs has been performed in several types of cancer with the conclusion that accumulation of sdRNAs is associated with malignant transformation and that increased global production or accumulation of sdRNAs is already occurring in the early stages of cancer. Surprisingly, there is no data reporting sdRNA levels in canonical stress conditions. To our knowledge, differential expression of sdRNAs has not previously been reported. Here, we report for the first time that sdRNAs in S. cerevisiae are present under a wide repertoire of growth conditions, though in some cases in limited amounts. So far, sdRNAs have been reported to localize in the cytoplasm in organisms where they act within microRNA pathways14. Here, we present new data demonstrating cytoplasmatic localization of sdRNAs in an organism that lacks miRNA pathways.Despite the fact that dysregulation of snoRNAs is involved in adaptation to stress conditions, only a few publications have reported the roles of sdRNAs in tumour development, which may be considered a stress for human cellsMoreover, for the first time, we present data showing that snoRNAs and sdRNAs are differentially abundant in both the cytoplasmatic and in ribosomal fractions. Such observations indicate that sdRNAs and snoRNAs might perform distinct cellular functions in response to stress conditions, probably during translation regulation. These observations strongly support the hypothesis for separate roles of both snoRNAs and sdRNAs during stress conditions.22 and tRNA-derived fragments26 previously described by our lab.The presence of both sdRNAs and snoRNAs in ribosome-associated RNAs indicates the possible existence of a novel, yet to be discovered stress-dependent translation regulation mechanism. The data presented herein strongly suggest that possible interactions between yeast ribosomes and sdRNAs downregulate translational activity during optimal growth conditions. Moreover, the observation of the inhibition of protein synthesis by yeast sdRNAs in the wheat germ system suggests the mechanism of translation regulation by sdRNAs is evolutionarily conserved. This suggests that the mode of action and, thus, also the ribosomal target site, is conserved in a range of eukaryotic species. In this aspect, sdRNAs could be classified as an example of ribosome-associated noncoding RNAs (rancRNAs), next to an mRNA exon-derived 18-residue-long ncRNASupplementary information