To perform a complete RNA 3D structure modeling analysis as proposed by the RNA-Puzzles community, researchers must familiarize themselves with a quite complex set of tools. In order to facilitate the processing of RNA sequences and structures, we previously developed the rna-tools package. However, using rna-tools requires the installation of a mixture of libraries and tools, basic knowledge of the command line and the Python programming language. To provide an opportunity for the broader community of biologists to take advantage of the new developments in RNA structural biology, we developed rna-tools.online. The web server provides a user-friendly platform to perform many standard analyses required for the typical modeling workflow: 3D structure manipulation and editing, structure minimization, structure analysis, quality assessment, and comparison. rna-tools.online supports biologists to start benefiting from the maturing field of RNA 3D structural bioinformatics and can be used for educational purposes. The web server is available at   Ribonucleic acid or RNA is a central type of molecule in a broad variety of biological processes throughout the central dogma ,2, RNA sDuring the last decade, a good number of RNA 3D structure prediction algorithms have been actively developed and improved. Improvements have been made in the efficiency and accuracy of RNA 3D structure prediction methods as reported in publications describing the RNA-Puzzles initiative . HoweverIn order to facilitate the processing of RNA sequences and structures, we previously developed the rna-tools package . The iniWe realized that the next step for making RNA 3D structure modeling workflows even more accessible was to provide these tools online. Using rna-tools requires the installation of a mixture of libraries and programs, basic knowledge of the command line and the Python programming language. To open opportunities for the wider community of biologists to take advantage of the new developments in RNA structural biology, we developed the rna-tools.online. The web server provides a user-friendly platform to perform many standard analyses required for the typical modeling workflow: 3D structure manipulation and editing, structure minimization, structure analysis, comparison analysis, and quality assessment. There are tools that provide some of these functions. However, RNApolis  is a cenrna-tools.online and all utility programs were implemented in Python 3. All the tools implemented in the server leverage the use of the standalone rna-tools package, to which we added a way to input the data from the web (a page form for each tool) and a way to return the results of the computation and of the command line outputs. The web server was developed using the Django framework for the backend, while the frontend uses the jQuery JavaScript library to send and retrieve the data from the backend. Each tool collects the user inputs within a form. The uploaded files and the supplementary data are sent through an Ajax request to the backend when the user presses the ‘Run!’ button to start the computation. In the backend, the original rna-tools package is run on the server command line to perform the job requested by the user. The output of this job is then sent back through an Ajax response to the page the user is visualizing. At the end when the computation has processed the original files, the result files, a log file and a bash script are returned to the user as links. The user can download them by clicking on these links. The bash script can be used to re-run the tool on the user's local machine . The user will be able to later return to the job and its results by using a unique link that will be generated and displayed on the tool page at the end of the computation. Some tools use JSMol  in orderThe rna-tools.online server is designed to facilitate various procedures required in structural files analysis and preparation in the field of RNA 3D structural bioinformatics. The user can take advantage of multiple groups of tools that were divided into sections to help the user understand which tool to use for a given task. All tools on the web page follow a very similar pattern Figure , are welThe first group of tools includes programs that aim to facilitate the analysis of RNA 3D structure. With ‘Get sequences’ the user can easily obtain RNA sequences for the uploaded PDB files. To obtain secondary structures from the PDB files the tool ‘Get secondary structures’ can be used based internally on 3DNA/DSSR  softwareThe next group of tools allows the user to edit PDB files, most of them are using BioPython . The ‘CoThis group of tools aims to facilitate operations on the standardization of RNA 3D structure. ‘Standardize PDB for RNA puzzle submission’ allows standardizing a PDB file to be compatible with the format proposed by the RNA-Puzzles community . The tooA common task in RNA bioinformatics is to remove steric clashes and optimize bonds and angles of an RNA model. We provide two tools: ‘Minimize with QRNAS’ which offers structural minimization based on QRNAS , a softwThe next group contains three tools that can be used to compare structural files. The ‘diffpdb’ tool is a simple program to perform a text-based comparison of two files of PDB format to identify the difference in the annotation of atoms, missing atoms, and missing fragments. ‘Calculate Root Mean Square Deviation (RMSD)’ can be used to calculate an RMSD  that is The last step of RNA 3D structure modeling is the assessment of the quality of a model. The web server provides two tools that are executed to obtain predicted quality scores: RASP  and DfirAs only a limited number of chains and atoms can be deposited in the PDB format, the mmCIF format ,36 has bhttps://rna-tools.online/docs), the user can find a detailed description of how the tools can be used and how to interpret the results. All tools are well documented and examples are provided to help the users to understand the tools. Advanced applications are possible after downloading output scripts and files to a local machine. The rna-tools website and its stand-alone version are rigorously maintained and we are open to providing additional tools and addressing requests from the general community. Moreover, we plan also to enhance the infrastructure to provide more computational power, especially for molecular dynamics-based functions. We hope that the user will be encouraged by the possibility to replicate the execution of these tools on their local machine to perform even more complex analyses using the tools provided by the rna-tools stand-alone version or similar packages, e.g. Barnaba (The rna-tools.online server offers a new user-friendly interface for the rna-tools package, delivering RNA 3D structure modeling tools to any user. The server accepts RNA structural files and enables various analyses. On the documentation page ( Barnaba . We encohttps://rna-tools.online. This website is free and open to all users and there is no login requirement.The web server is available at


Psychiatric diagnoses are derived from expert opinion (1). Since no objective tests or markers are on the horizon, clinical psychiatry is anchored to “the patient’s altered experience, expression and existence, associated with suffering in self and/or others”(2). Many studies have examined diagnostic stability over time. In the last years investigators have been reporting prospective and retrospective consistencies of diagnoses between two time points, specially in first episodes of psychosis (3).To examine the prospective and retrospective stability of diagnostic categories 2 years after the first episode of psychosisData were examined from the First Episode Psychosis Program of Navarra (PEPsNA), a prospective observational study of a cohort of patients with first-episode psychosis in Navarra (Spain). Diagnosis was assigned using DSM-IV-TR at baseline and 24 months later. Diagnoses were divided into 5 categories: Affective psychosis, Schizophrenia spectrum psychosis, Schizoaffective disorder, acute psychosis and other diagnoses. Diagnostic change was examined using prospective and retrospective consistencyA total of 78 first-episode psychosis cases with baseline and 24 months follow-up were identified. Table 1 shows the diagnosis movement matrix, and Figure 1 its graphical representation. Of cases, 71.8% (56/78) had the same baseline and 24 months follow-up diagnosis. Prospective and retrospective consistencies are shown in Table 2The prospective and retrospective consistencies of Schizophrenia spectrum psychosis and acute psychosis were higher than others. Affective psychosis and Schizoaffective disorder show very variable consistencies


Genome-wide association studies (GWAS) aim to correlate phenotypic changes with genotypic variation. Upon transcription, single nucleotide variants (SNVs) may alter mRNA structure, with potential impacts on transcript stability, macromolecular interactions, and translation. However, plant genomes have not been assessed for the presence of these structure-altering polymorphisms or “riboSNitches.”Arabidopsis genes, ZINC RIBBON 3 (ZR3) and COTTON GOLGI-RELATED 3 (CGR3), which are associated with continentality and temperature variation in the natural environment. These riboSNitches are also associated with differences in the abundance of their respective transcripts, implying a role in regulating the gene's expression in adaptation to local climate conditions. We then computationally predict riboSNitches transcriptome-wide in mRNAs of 879 naturally inbred Arabidopsis accessions. We characterize correlations between SNPs/riboSNitches in these accessions and 434 climate descriptors of their local environments, suggesting a role of these variants in local adaptation. We integrate this information in CLIMtools V2.0 and provide a new web resource, T-CLIM, that reveals associations between transcript abundance variation and local environmental variation.We experimentally demonstrate the presence of riboSNitches in transcripts of two Arabidopsis genomes and 269 additional climate conditions, which will greatly facilitate in silico studies of natural genetic variation, its phenotypic consequences, and its role in local adaptation.We functionally validate two plant riboSNitches and, for the first time, demonstrate riboSNitch conditionality dependent on temperature, coining the term “conditional riboSNitch.” We provide the first pan-genome-wide prediction of riboSNitches in plants. We expand our previous CLIMtools web resource with riboSNitch information and with 1868 additional The online version contains supplementary material available at 10.1186/s13059-022-02656-4. Natural genetic variation can give rise to variation in proximate molecular phenotypes that impact macroscopic physiological and morphological phenotypes. Perhaps the most obvious proximate molecular phenotype consists of alterations in protein sequence that arise from non-synonymous single nucleotide polymorphisms (SNPs), often with functional consequences. More recently, the influence of synonymous variants, which by definition do not alter the sequence of the encoded protein, has been increasingly appreciated, with one meta-analysis showing equal association of synonymous and non-synonymous mutations with human genetic disease .One mechanism by which synonymous SNPs, as well as non-synonymous SNPs and SNPs located in introns and UTRs, can play regulatory roles is by changing the structure of the RNA in which they reside. Variants that alter RNA structure have been named riboSNitches by Laederach and colleagues , a term Altered mRNA folding can impact mRNA splicing , mRNA tuThe groundbreaking analyses of Wan et al. point to the importance of riboSNitches in the control of gene expression, with fundamental whole-organism consequences. However, this study could obviously only evaluate those variants present in this family trio and so could not encompass the breadth of variation present in the multitude of human genome sequences currently available. Moreover, to date, this analysis of three individual humans remains the only large-scale experimental study of mammalian riboSNitches. Thus, the field still relies primarily on computational riboSNitch prediction. Leading riboSNitch prediction algorithms SNPfold , RNAsnp Arabidopsis thaliana (Arabidopsis) is a premier model plant species in molecular genetics, ecology, and evolutionary biology [Arabidopsis is naturally inbreeding, and the resultant homozygosity facilitates its use in association studies that seek to correlate genetic and phenotypic variation and thereby identify causative genes. Here, we rectify the absence of plant riboSNitch information. We first confirm the existence of climate-related riboSNitches through wet bench analyses. We then employ SNPfold to predict Arabidopsis riboSNitches across 879 Arabidopsis genomes, evaluate global properties of these riboSNitches, and incorporate this information in CLIMtools.By contrast, to our knowledge, there have been no riboSNitches identified in plants by either wet bench or computational approaches.  biology –35. Arabhttp://www.CLIMtools.org) [Arabidopsis accessions [Arabidopsis gene of interest (GenoCLIM) or based on any climate parameter of interest (CLIMGeno). Here, we expand the CLIMtools web resource through the inclusion of information on genome-wide riboSNitch prediction. We develop a new RNA-related tool, T-CLIM, which for the first time allows the community to query correlations between available RNA-seq data for 558 Eurasian accessions [Arabidopsis accessions with available whole-genome sequence information and 269 additional climate parameters.Because plants are sessile, they adapt to local climate conditions, and resulting signatures of selection can be observed as statistical associations between variation in climate parameters and natural genetic variation. Accordingly, we previously assembled CLIMtools V1 (ols.org) , a web rcessions . Users ccessions  and climZR3) and AT5G65810 (CGR3) were predicted to encompass local secondary structure surrounding the SNP, as expected for genuine riboSNitches. In ZR3, the variant is a synonymous substitution in the coding sequence while in CGR3, the variant is located in the 5′ UTR  SNP associated with lower expression values in each case  and AT5G65810 (CGR3) each have a G-to-A variant. If these SNPs change the structure of the RNA, then they likely change the thermodynamic stability of the local fold as well. To experimentally test this idea, we designed model RNA oligonucleotides containing the SNPs of interest and assessed their folding stability by UV-detected melts. We chose minimal sequences of 17 nt (for ZR3) or 23 nt (for CGR3) on the basis of including the predicted local RNA structures flanking the identified SNP in both the reference  and alternative  sequence.AT3G54826 (ZR3 was predicted to fold into a stem-loop with a six-base pair stem (five Watson-Crick pairs and a G•U wobble pair) and a five-nucleotide loop. This portion of the alternative ZR3 sequence was also predicted to form a stem-loop (hairpin), with the same four base pairs at the base of the stem but with two fewer base pairs at the top of the stem and thus a nine-nucleotide loop. This is because the G-to-A mutation changed the penultimate base pair at the top of the stem of the reference sequence from a Watson-Crick CG base pair to a CA mismatch. Indeed, free energies, widely available at 37 °C (ΔG°37), for the reference and variant sequences, gave a large ΔΔG°37 of + 4.4 kcal/mol in going from the reference to alternative sequence, as predicted by RNAstructure [As shown in Fig. tructure .Fig. 3SN2, which mimic in vivo conditions for plants. As shown in Fig. TM) of the reference sequence, revealed in the maximum in the first derivative plots  minimal sequences of 23 nt, which encompass the predicted local RNA structures flanking the identified SNP in both the reference and alternative allele. The reference 23 nt CGR3 sequence was predicted to form a stem-loop with a seven-base pair stem (six Watson-Crick pairs and a G•U wobble pair penultimate to the base of the stem) containing an AA mismatch, as well as a three-nucleotide loop  with a 5′-strand G bulge, as well as a four-nucleotide loop. Indeed, no base pairs were shared between the 23-nt reference and alternative structures despite them varying by only a single base; as such, this SNP is a potential riboSNitch for this portion of the sequence even at low temperatures, unlike the case of ZR3. To accommodate the two very different structures in the reference and alternative, our set of paired reference and alternative oligonucleotides resulted in a tail of four nucleotides found on the 5′-end of the reference sequence and a tail of six nucleotides found on the 3′-end of the alternative sequence  transition did not shift with RNA concentration and so is assigned to melting of a hairpin  than at the reference (TM ~ 60 °C), but on the other hand, both melting temperatures are well above biological values. Thus, the G-to-A SNP in CGR3 could lead to a riboSNitch throughout the standard temperature range of Arabidopsis, i.e., it has characteristics of a persistent or “classical” riboSNitch.As before, we tested the stability of this pair of sequences by UV-detected melts in in vivo-like salt conditions. As shown in Fig. ZR3. While in the previous experiment we melted only the minimal predicted structure encompassing the SNP, here, we designed a pair of RNAs with ZR3 sequences 51 nt upstream and 51 nt downstream of the SNP for sequences differing only in the identity of the SNP. As indicated in Fig. http://rna.informatik.uni-freiburg.de/MutaRNA/Input.jsp). This program presents probabilities of base pairing for multiple structures of a sequence and displays differences between a pair of sequences as differential heatmap-like dot plot representations. In Fig. Next, we assessed the effect of each SNP in a longer RNA context. We began with an RNA designed from Arabidopsis [We then turned to experimentally probing the effect of the SNP on the structure of these sequences. The structure of each RNA was probed with dimethyl sulfate (DMS), which covalently modifies unpaired As and Cs on the Watson-Crick face, resulting in reverse transcription DMS-induced “structure-stops,” which can be read out on sequencing gels. The structure-probing gels are provided in Additional file bidopsis . There aCGR3. Again, we designed a pair of RNAs based on the native CGR3 sequence, with 56 nt upstream and 58 nt downstream, differing only at the SNP. This pair of RNAs also had very different folds according to RNAstructure  methods to allow the identification of associations between natural variation in any gene of interest and the extracted environmental variables in AraCLIM. CLIMGeno conversely allows, for any geo-climatic variable of interest, the identification of genes with significant co-variation with that climate variable. In our updated version of these two tools, we maintain our focus on the same set of 879 Eurasian accessions from the 1001 Genome Project as used in CLIMtools V1.0, due to the superior genome quality of these accessions. However, GenoCLIM and CLIMGeno are quite significantly expanded due to the increase in climate variables in CLIMtools V2.0 and by the inclusion of riboSNitch predictions. Further, we provide new analyses in GenoCLIM/CLIMGeno arising from the incorporation of additional analytical methods. The results are now provided not only from a GWAS mixed-model approach that corrects for population structure , but alshttps://gramene.org/CLIMtools/arabidopsis_v2.0/), available in the Gramene portal (Gramene.org) [Table ene.org)  for easyArabidopsis exhibit hallmarks of adaptation to the local climate [Natural populations of  climate . The intZR3. In particular, the melt data on ZR3 clearly illustrate temperature conditionality of the SNP’s impact. Both reference and alternative oligonucleotides are fully unfolded at high temperatures and fully folded at low temperatures. However, over an intermediate temperature range, differential temperature unfolding of the reference and alternative sequences is seen, consistent with the onset of riboSNitch behavior. Similarly, melt analyses that focus on the higher temperature melt transition assignments to the CGR3 hairpin , and so we correspondingly used longer RNA sequences of ~ 100 nt , which strongly co-correlates with several temperature parameters that are drivers of selection in the Eurasian Arabidopsis population [ZR3 exhibits an Fst of 0.44 in our analyses. As the values for the majority of Fsts for the collection of SNPs within the 879 Eurasian accessions that we have evaluated for association with continentality and related climate variables is less than 0.3  , our analyses , i.e., there is no evidence for overall negative selection against riboSNitches in Arabidopsis in the set. Similarly, the distributions of allele frequencies were not significantly different, so there was no evidence of biased purifying selection on riboSNitches , possibly suggesting that alteration of protein structure, rather than RNA structure, has a greater influence on fitness in the case of non-synonymous SNPs. For synonymous SNPs, riboSNitches have a significantly lower Fst overall than non-riboSNitches in our climate databases . This does suggest that RNA structural differences engendered by riboSNitches can be maladaptive in coding sequences.It is also of interest to assess the distribution of riboSNitches among different genic regions, given the differing functional roles of the 5′ UTR, CDS, and 3′ UTR. Among our coding sequence riboSNitches, 28% were missense (non-synonymous) variants, and among non-synonymous SNPs in the CDS, there was again no difference in the selection strength (Fst) between riboSNitches and non-riboSNitches  or the 3′ UTR . These dichotomies between plant and animal datasets may indicate divergent regulatory architectures and adaptive strategies in mammals vs. plants.In further comparison with human riboSNitches, Gorodkin and colleagues  applied es Table . MoreoveOur provision of environmentally associated riboSNitches in CLIMtools V2.0 could, in the future, have a parallel in a human variant resource that would compile variant × environment interaction to identify environmentally induced illnesses and their interaction with genotype, i.e., a G×E×riboSNitch resource. The creation of such a G×E×riboSNitch resource could be impactful not only for humans but also for their pathogens. RiboSNitches have been identified in pathogenic viruses, including HIV , hepatitHowever, there also remain considerable and ongoing challenges to riboSNitch prediction. The very concept of the conditional riboSNitch, by definition, implies that whether or not a SNP is a riboSNitch is a function of the dynamic microenvironment of the RNA. Corley and Laederach have correspondingly suggested that riboSNitch designations at the tail ends of score distributions will be most accurate . Future ZR3 and CGR3, as a function of flanking sequence lengths, we found significant sensitivity of the prediction to flanking sequence length , over 1800 h of total compute time were required to complete the SNPfold analysis of the > 3.83 million SNPs in our pan-structurome, running in parallelized fashion with 20 cores on up to 9 nodes on Penn State’s supercomputing clusters. When we analyzed riboSNitch prediction for our two specific wet bench candidates, Arabidopsis has an advantage as it is naturally inbred, avoiding the need for disambiguation of alleles within an accession.In terms of predicting functional consequences, GWA analysis of riboSNitches, as for all GWA studies, is susceptible to issues of linkage disequilibrium , whereinWe have experimentally demonstrated the existence of plant riboSNitches and have contributed to the still small pool of robustly validated riboSNitches in any species. Our analyses introduce and validate the concept of conditional, climate-dependent riboSNitches. Our CLIMtools resource makes possible a new approach to identify and prioritize candidate functional riboSNitches through their statistical associations with environmental parameters and transcript abundance.The potential mechanistic impacts of riboSNitches are varied yet to date remain largely unexplored. RiboSNitches can control mRNA accessibility to the spliceosome and the ribosome, as well as to polymerases and nucleases. RNA turnover is also controlled through polyadenylation/deadenylation, which are in turn controlled by RNA structure , 70; as Arabidopsis and will foster the identification of genes and variants that confer adaptive responses to climate conditions. A fundamental understanding of the contributions of riboSNitches to stress tolerance can contribute to future biodesigns for improved climate-resilient crop germplasm.In conclusion, our CLIMtools V2.0 resource integrates information on the transcriptome and the local environment for studies of natural variation in The SNPfold program  was usedArabidopsis accessions studied here. These accessions also formed the basis of CLIMtools V1.0 and were chosen from the original 1001 sequenced genomes [SNPfold was applied to the 3,830,264 natural variants of protein coding genes (including introns) of the 10,293,854 SNPs within the 879 Eurasian  genomes  as those genomes . Each SNrs| ≥ 0.3). We obtained 123 SNPs that uniquely met these conditions  and AT5G65810 (CGR3) in particular showed local structural differences, as expected for riboSNitches [We selected a subset of 48 temperature-related environmental variables  containing 150 mM KCl. After cooling to room temperature, 0.5 mM MgCl2 was added, and the samples were incubated at 55 °C for 3 min. Samples were again cooled to room temperature and then pipetted into 0.1 or 1 cm pathlength quartz cuvettes, slowly filling from the bottom to avoid introducing bubbles. Cuvettes were then placed in the spectrophotometer, which had been prechilled to 5 °C. RNA absorbance was monitored from 5 to 95 °C over a wavelength range of 200 to 600 nm with a data point acquired approximately every 0.5°. N2 gas was passed around the cuvettes from 5 °C to approximately 40 °C to minimize condensation build-up outside of the cuvettes, which would have interfered with accurate absorbance readings. A buffer reading was taken at each temperature and wavelength. We found that 260 nm gave the optimal signal. The absorbance values were buffer-subtracted and further normalized by dividing each value by the average of the five maximum absorbance values obtained for each melt. In addition, the first derivative of the normalized 260 nm absorbance values was taken, and the resultant data smoothed with 11 point moving averages.UV-detected thermal denaturations, or “melts,” were performed on an Olis refurbished HP 8425 diode array spectrophotometer. Melts were performed at three different RNA concentrations. Concentrations for the ZR3) and AT5G65810 (CGR3) were ordered from IDT. The sequences contained the T7 polymerase binding site and an additional upstream 6 nucleotides found to promote transcription. For AT3G54826 (ZR3), a GG sequence was added downstream of the T7 binding site to improve T7 transcription efficiency; for AT5G65810 (CGR3), two Gs were available from the nearby sequence. Additional file ZR3 and CGR3 in order to keep the SNP centered in the transcript. gBlocks were resuspended in 1X TE buffer to a concentration of 10 ng/μL per the manufacturer’s (IDT) instructions and PCR amplified using Q5 High-Fidelity DNA Polymerase (NEB) to avoid the incorporation of additional mismatches during amplification. PCR reactions (200 μL) were performed containing 40 ng gBlock template, 1 μM forward and reverse primers , NTPs (4 mM) and additional GTP to a final concentration of 8 mM GTP, in-house prepared T7 RNA polymerase solution , which was added at 2 μL per 100 μL reaction, and water. The transcription reaction proceeded at 37 °C for 4 h and was quenched by the addition of an equal volume of 2X formamide EDTA loading buffer . Transcription products were gel-purified on a 1-mm-thick denaturing PAGE gel containing 8.3 M urea and 10% acrylamide; prior to loading the samples were denatured at 95 °C for 3 min. T7 transcription products were visualized in the gel using UV-shadowing and the bands were cut out. The excised gel fragments were crushed, weighed, and incubated overnight in a rotator at 4 °C in 2× the weight by volume of TEN250 buffer . Next, the gel fragments were pelleted by centrifugation at 3000×g for 3 min. The resulting supernatant containing the in vitro transcribed RNA was then ethanol precipitated by adding 2× the volume of 100% ethanol, 1 μL GlycoBlue (ThermoFisher), and then incubating at − 80 °C for 2 h. The precipitated RNA was pelleted by centrifugation at 4 °C and 10,000×g for 30 min. The supernatant was decanted and the pellet allowed to dry before eluting in 500 μL water.Resultant DNA was then used in a T7 transcription to produce in vitro T7 transcribed RNA. The template DNA was denatured at 90 °C for 2 min then allowed to cool to room temperature before adding transcription buffer  was added, and samples were equilibrated at either 20 °C or 37 °C for 15 min before addition of DMS (diluted in methanol) to a final concentration of 75 mM or addition of an equal volume of methanol to minus DMS (control) samples. All DMS work was done in a hood, with proper personal protective equipment. In vitro DMS reactions were allowed to proceed at either 20 or 37 °C for 3 min. and were quenched with 2-fold excess DTT. Samples were then ethanol precipitated by adding a 2× volume of ethanol, 300 mM sodium acetate, and GlycoBlue, followed by incubation at − 80 °C for 1 h. RNA was pelleted by centrifugation at 4 °C, washed 2× with ice cold 70% ethanol, and allowed to dry before eluting in water. Resultant RNA (1 μg) was then subjected to in vitro DMS probing at 20 °C or 37 °C. Samples were prepared by initially denaturing the RNA at 65 °C for 90 s, cooling on ice for 90 s, and allowing equilibration to room temperature for 5 min. RiboSNitch reaction buffer  and heated to 75 °C for 3 min. Samples were first pre-cooled to 35 °C and then 2 μL of reverse transcription reaction buffer and 1 μL dNTPs were added to yield final concentrations of 20 mM Tris (pH 8.3), 1 mM DTT, 8 mM MgCl2, and 1 mM of each dNTP, and the reaction was incubated at 35 °C. The reaction was then pre-heated to 55 °C for 1 min, and 0.5 μL of SuperScriptIII (Invitrogen) reverse transcriptase  was added. Reverse transcription was allowed to proceed for 30 min at 55 °C. The reaction was terminated and the remaining RNA hydrolyzed by heating to 95 °C and addition of NaOH to a final concentration of 100 mM. The reactions were cooled to 4 °C prior to the addition of an equal volume of 2X formamide loading buffer . Sequencing lanes were prepared simultaneously for A, C, G, and T for both AT3G54816 (ZR3) and AT5G65810 (CGR3) sequences, by incorporating the corresponding ddNTPs to a final concentration of 1 mM in addition to 0.5 mM dNTPs and 1X transcription reaction buffer.For each gene, a DNA gene-specific primer  . First, ZR3) and AT5G65810 (CGR3) mRNAs were extracted from the data of Tack et al. [ZR3 and CGR3.In vivo DMS reactivity values for the AT3G54816 . The stronger the association between climate and transcript variation, the closer the Pearson correlation coefficient, rs, will be to either + 1 or − 1. For the evaluation of our candidates to select predicted riboSNitches for experimental work, we imposed a threshold based on this correlation coefficient: |rs| ≥ 0.3.Transcriptome-wide association (TWA) analysis of correlations between transcript abundance and each of the more than 400 environmental variables in this study was performed using the set of 558 accessions within the set of 879 Eurasian accessions that had information on transcript abundance from rosette leaves available from a previous study  (GEO dathttp://gwas.gmi.oeaw.ac.at/) was employed using an accelerated mixed model (AMM) [http://ftp.ensemblgenomes.org/pub/plants/release-52/). We used the “consensus transcript” as the variant with the longest transcript, and predicted the effect of each individual SNP within protein-coding genes using SnpEff [For the calculations of genotype × environmental associations, we used a GWAS approach to identify polymorphisms in protein-coding genes (including introns) and their corresponding 1 kb promoter region that are associated with each of the 465 numerical environmental parameters included in this study. The online tool GWAPP (el (AMM) . The AMMel (AMM) . Becauseel (AMM) , to compg SnpEff  after inhttps://1001genomes.org/data/GMI-MPI/releases/v3.1/). We used VCFtools [π) and Tajima’s D using a sliding window of 1 kb [We downloaded the multi-VCF for the sequenced accessions included within the 1001 Genomes Project (VCFtools  to subseVCFtools  to annot of 1 kb .Additional file 1: Table S1. Subset of environmental variables selected to explore candidates for melts.Additional file 2: Table S2. Overlapping associations retrieved from GWAS and TWAS on subset of climates selected to explore candidates for melts.Additional file 3: Table S3. Final list of candidates for melts.Additional file 4. This file contains Figures S1-S6.Additional file 5: Table S4. Environmental data descriptors and summary statistics.Additional file 6: Table S5. List of climate-associated SNVs used for riboSNitch prediction as a function of flanking sequence length (see Additional file Additional file 7: Table S6. Oligonucleotide and primer sequences.Additional file 8. Review history.


DMD gene, which encodes a membrane-linked cytoskeletal protein to protect muscle fibers from contraction-induced injury. Patients with DMD inevitably succumb to muscle degeneration and atrophy early in life, leading to premature death from cardiac and respiratory failure. Thus far, the disease has thwarted all curative strategies. Transcriptomic manipulation, employing exon skipping using antisense oligonucleotides (ASO), has made significant progress in the search for DMD therapeutics. Several exon-skipping drugs employing RNA manipulation technology have been approved by regulatory agencies and have shown promise in clinical trials. This review summarizes recent scientific and clinical progress of ASO and other novel RNA manipulations, including RNA-based editing using MS2 coat protein-conjugated adenosine deaminase acting on the RNA (MCP-ADAR) system illustrating the efficacy and limitations of therapies to restore dystrophin. Perhaps lessons from this review will encourage the application of RNA-editing therapy to other neuromuscular disorders.Approval of therapeutic RNA molecules, including RNA vaccines, has paved the way for next-generation treatment strategies for various diseases. Oligonucleotide-based therapeutics hold particular promise for treating incurable muscular dystrophies, including Duchenne muscular dystrophy (DMD). DMD is a severe monogenic disease triggered by deletions, duplications, or point mutations in the   Pharmaceuticals are small compounds that bind to pockets of target proteins, including receptors, enzymes, or other proteins, commonly as antagonists that control a target disease. It is estimated that 3,000 of 20,000 human proteins are targeted by conventional therapeutics . SurprisDMD gene located at Xp21.2–p21.1 on the X chromosome that affects one out of 3,600–5,000 boys worldwide  that is required for muscle-fiber integrity and protection from contraction-induced injury  , gene-adman body . DMD hasman body ; therefoman body . Though man body . The dysman body . On the man body . Thus, tman body .DMD transcript is engineered to restore the function of dystrophin by repairing the translation reading frame. Modes of action, progress, and limitations of RNA-manipulation therapeutic strategies are discussed below.Despite the hurdles mentioned above, considerable effort has been devoted to developing gene therapies for patients with DMD. The leading gene therapy strategy is RNA-manipulation therapy, in which an interrupted DMD gene. Eteplirsen is a broad-spectrum drug covering ∼20.5% of deletion mutations in this gene, which account for ∼13% of all DMD patients . Although the United States Food and Drug Administration (FDA) advisory committee voted not to approve eteplirsen in the beginning, the FDA administratively overrode that and gave accelerated approval in 2016 as the first genetic medicine for DMD . It is apatients .Dmd KO mouse carrying the human DMD gene (p ≤ 0.002) at 24 weeks, in comparison with the placebo control group (p ≤ 0.001).Eteplirsen hybridizes with the complementary sequence of exon 51, leading the spliceosome to skip exon 51 in the ORF during pre-mRNA splicing, ultimately restoring functional, albeit shortened, dystrophin  Lim et . The effDMD gene . Based ool group . The samNCT01396239 and other eteplirsen clinical trials found only a delay in disease development rather than any substantial improvement in disease symptoms, with relatively low efficiency, based on muscle biopsy results . One conDMD , Tokyo (Viltolarsen (code name: NS-065/NCNP-01) is a single-stranded, antisense PMO complementary to exon 53 of ), Tokyo . Viltola), Tokyo . Targeti), Tokyo . As such), Tokyo .Like golodirsen, viltolarsen exhibits a similar mode of action for skipping exon 53 . Watanabde novo dystrophin increased on average 5.7% and 5.9%, respectively. The 6 MWT showed substantial progress in which ambulation of the treatment group was ∼29 m compared to -65.3 m for the control group, as reported by In a Phase II intervention involving 16 boys, viltolarsen (NCT02740972) was administered intravenously at 40 mg/kg/week and 80 mg/kg/week doses for up to 24 weeks . CompareThe FDA granted another therapeutic RNA drug called Casimersen (Amondys 45) in February 2021 as an accelerated approval for treatment of DMD in patients who harbor confirmed mutations amenable to exon 45 skipping  FDA, 20. The basmdx mouse model to skip exons 19–25 to restore dystrophin expression lost due to a premature stop codon in exon 23  study in an mdx52 mouse model  able to skip exon 51 (NCT03375255). The purpose of this study was to profile the safety, acceptability, and pharmacokinetics of a single-dose intravenous infusion (IV) in 12-year or older patients with DMD. Recently, the same pharmaceutical company recruited 60 subjects age 4 or older in Phase I/II clinical study (NCT03675126) to evaluate the safety, tolerability, and doses of SRP-5051 in patients with DMD amenable to skipping exon 51.The main hurdle for future clinical intervention for peptide-conjugated ASO therapy is toxicity, including lethargy, weight loss, tubular degeneration in the kidney . Factorsmdx mouse model . This adverse effect in the clinical study led to further structural modifications for ASO therapy.In the second era of ASO modification, three structural alterations were widespread, including 2ʹ-methyl phosphorothioate (2ʹ-OMe) and 2ʹ-methoxyethylene (2ʹ-MOE), 2ʹ-fluoro nucleotides, in which the 2ʹ-hydroxyl group of RNA is substituted, thereby resisting nuclease activity . IncreasPMOs, locked nucleic acids (LNAs), peptide nucleic acids (PNAs), tricyclo DNAs, and ethylene-bridged nucleic acids (ENA) belong to the third generation of structural ASO modifications . PMOs arThe field of therapeutic RNA manipulation continues to develop and represents a revolutionary treatment paradigm for many muscular dystrophies, including DMD. The potential benefits of using RNA manipulation rather than DNA manipulation therapy include a) no chance of a permanent error, whereas DNA manipulation could potentially create a new permanent problem  b) sinceDespite these tremendous advantages, several issues must be addressed for further clinical success of RNA-manipulation therapy. First, how can the efficacy of RNA manipulation therapy be improved for DMD? A precise drug delivery system could be one answer. To address this issue, a cell-penetrating peptide-conjugated PMO is being developed  and a clSecond, how can the toxicity of morpholino ASO be reduced? Though all approved genetic medicines for DMD are well tolerated, there are still toxicity concerns . One of Currently, manipulation of pre-mRNA using exon-skipping therapy is deliberated as the most promising strategy for DMD treatment. Within the last few years, the accreditation of exon-skipping drugs by the FDA and PMDA as a novel therapeutic modality has moved them to the forefront of next-generation genetic medicines for muscular dystrophies, including DMD. The optimization of exon skipping has sparked great interest and can significantly change the lives of the many affected individuals by a wide range of incurable genetic diseases. As the progress continues, we are optimistic about the success of this strategy and are eager to see what the future hold.While this paper has focused on RNA-manipulation therapy to correct DMD mutations, various exciting genome editing approaches using CRISPR/Cas9 are being developed to repair out-of-frame mutations. Collectively, we are venturing into unprecedented territory for rare genetic neuromuscular medicine, with the hope of treatments for ultrarare incurable diseases. It is worth noting that despite this significant progress, there is still an enormous unmet need to understand pathogenic mechanisms of disease progression better and to enhance drug delivery strategies. Finally, lessons learned from DMD should be applicable to other neuromuscular disorders and numerous life-threatening genetic diseases for which no effective therapy currently exists.


The origin of RNA interference (RNAi) is usually explained by a defense-based hypothesis, in which RNAi evolved as a defense against transposable elements (TEs) and RNA viruses and was already present in the last eukaryotic common ancestor (LECA). However, since RNA antisense regulation and double-stranded RNAs (dsRNAs) are ancient and widespread phenomena, the origin of defensive RNAi should have occurred in parallel with its regulative functions to avoid imbalances in gene regulation. Thus, we propose a neutral evolutionary hypothesis for the origin of RNAi in which qualitative system drift from a prokaryotic antisense RNA gene regulation mechanism leads to the formation of RNAi through constructive neutral evolution (CNE). We argue that RNAi was already present in the ancestor of LECA before the need for a new defense system arose and that its presence helped to shape eukaryotic genomic architecture and stability. Where does RNA interference come from? This Essay describes a new step-by-step evolutionary model of how RNA interference might have originated in early eukaryotes through neutral events from the molecular machinery present in prokaryotes. In animIntegrating a range of viewpoints is becoming increasingly viewed as necessary to understand complex biological phenomena ,13. AlthWe begin by discussing some shortcomings of the defense-based hypothesis. To avoid confusion, we refer to the RNAi “defensive role” as its direct effect on viruses and TEs, and to the RNAi “regulatory role” as its general activities on the host genome. However, it is worth noting that a defensive role may be a mixture of different virus-specific or TE-specific processes depending on the species, whereas the regulatory role may also have important immunological functions, such as those related with tissue repair or inflammation. This section will highlight the close interaction between genomic defense and genomic regulation.Based on phylogenetic evidence, it is generally accepted that LECA had a functional RNAi pathway composed of the core components: Dicer, an RNase III-like endonuclease that processes double-stranded RNAs (dsRNAs); Argonaute and PIWI, 2 classes of the same family of endonucleases that use sRNAs as guides; and the RNA-dependent RNA polymerase (RdRP), which catalyzes the synthesis of the dsRNA ,8. The dAs several unicellular eukaryotes have lost the ancestral RNAi system, it has been proposed that it must have been dispensable for LECA. This would be incompatible with RNAi performing essential functions in LECA, including defense ,8.Saccharomyces cerevisiae, one explanation for the loss of RNAi is that the evolution of pointed centromeres (centromeres determined by a genetic signature) made RNAi-dependent centromere formation obsolete [S. cerevisiae [If RNAi is dispensable, why would a defensive function be more likely than a regulatory one? Furthermore, dispensability also casts questions on whether RNAi arose through an “adaptive” evolutionary process or not. Regulatory networks in eukaryotes are often redundant and prone to experience shifts ,24 and mobsolete ,27. Desprevisiae , this evPlasmids are generally considered parasitic elements ,30. TherSynechoccus elongatus pAgo shows no preference for targeting plasmid versus chromosomal DNA, has no effect on plasmid maintenance, and may instead participate in the process of chromosome replication, targeting the origin and terminus of replication [Thermus thermophilus also seems to be related to DNA replication, helping to disentangle the concatenated circular chromosomes in the absence of topoisomerases [Clostridium butyricum, pAgo has a defensive role against phages and plasmids, yet also targets multicopy genetic elements , sites of double-strand breaks, and the region of the replication terminus, displaying a broad variety of genomic regulatory activities [Despite some questions about whether plasmids should be thought of as “parasites” per se , pAgo calication . The priomerases . Furthertivities . The factivities  may be ativities . In supptivities ,38–41. Itivities . Finallytivities , suggestRegulatory functions of RNAi specifically rely on the presence of miRNAs that are likely to have originated independently after the divergence of animals and plants. Therefore, it is likely that the siRNA pathway, which is mainly dependent on RdRP, would originally have had a defense-based function ,8.Schizosaccharomyces pombe, the primary role of the siRNA pathway is the formation of heterochromatin for centromere determination and gene regulation, whereas TEs are mainly eliminated through an RNAi-independent process [Giardia lamblia [Paramecium tetraurelia [Paramecium bursaria, the siRNA pathway is also important for the maintenance of a symbiotic relationship with the green algae Chlorella, through a process called RNA collision, which may have profound implications for the evolution of endosymbiosis, predatory behavior, and avoidance of cannibalism in early eukaryotes [Oxytricha trifallax, a special Dicer-dependent siRNA pathway has a pivotal role in dosage compensation and the maintenance of chromosome copy number [Paramecium and Tetrahymena there is an additional, ciliate-specific, RNAi pathway that physically removes TEs during the formation of the macronucleus [Caenorhabditis elegans, WAGO-dependent 22G-siRNAs indiscriminately silence TEs, pseudogenes, certain genes, and other aberrant transcripts [Oxytricha and Stylonychia, the RNAi system uses a special group of 27-nucleotide-long small RNAs to select and protect the coding regions of the genome during the formation of the macronucleus [C. elegans that indirectly favor the holocentromere organization by targeting euchromatin [The common view on the origin of miRNAs has been recently challenged and may actually predate the plant–animal divergence –45, and  process ,61. In 2 process , the can lamblia  and tranraurelia ,65. In Pkaryotes . In the y number . In cilionucleus . Howeveronucleus –70. Siminscripts . Curiousonucleus ,72, remihromatin ,74. Thushromatin ,75. Whilhromatin –78.The patterns of RNAi-mediated gene regulation are so diversified and poorly conserved among eukaryotes that they are probably lineage-specific. By contrast, the defense function of RNAi against TEs and viruses is broadly conserved and constitutes strong evidence to infer its evolutionary origin ,8,10,57.Identifying the most conserved role of a given process among a range of taxa may suggest the most parsimonious hypothesis about its origin and function, but not necessarily the correct one, as can occur with exaptation, when a trait’s function switches through evolution .Moreover, the proposed antiviral defensive role of RNAi seems poorly conserved across taxa. Recent studies failed to find evidence of an antiviral effect of RNAi in several basal metazoans, suggesting that it was potentially absent in the common ancestor of earthworms, sponges, and sea anemones and might be a later acquisition in metazoa . InteresCould the loss of RNAi in several unicellular eukaryotes relate to their small genome size and low complexity, meaning that the RNAi-dependent mechanisms were redundant ? In the Compared with prokaryotic genomes, the genomes of eukaryotes contain many more TEs ,89. TherAn increase in genome size in eukaryotes with a small effective population size is predicted by the laws of population genetics ,88. DecrThere is a threshold in genome size (and an inversely correlated effective population size) that allows TE persistence. Near or below this threshold, TEs struggle to maintain themselves in a population ,97. UnfoDrosophila [It is possible that the effective population size of LECA or its ancestor was smaller than anticipated. Or that physiological conditions changed such that LECA needed to evolve a defensive RNAi system. For example, selfish elements such as plasmids in prokaryotes are often self-regulated. For their maintenance, it is important to support a rate of replication that does not compromise survival of the host but is also not so low as to risk extinction ,101. Forosophila . Third, osophila ,108 befoosophila ,109,110.As there was potentially no strong selective pressure to maintain a new defensive system  , it is pIs it more likely that RNAi evolved as a defense against parasitic genetic elements at the cost of disrupting or altering gene regulation, or as a multifunctional process that can regulate gene expression, favor heterochromatin formation, and inhibit TEs and viruses? When addressing this fundamental question, one should bear in mind that biological complexity can emerge by neutral events and may become essential even if it is useless ,113–116;Trypanosoma. In the production of a functional protein, the mRNA of these cryptogenes undergoes substantial RNA editing [In recent years, CNE has been used to explain the evolution of several molecular processes, biological structures and genomic features, including scrambled genes in ciliates, RNA editing, multimeric protein formation, the spliceosome, and the ribosome ,118–121. editing . It is u editing ,119. TheCNE theory can be applied to the RNAi system . If the In the rest of this section, we propose a step-by-step route by which molecular system drift from prokaryotic RNA antisense regulation could have led to eukaryotic RNAi through CNE, and how this affected genome evolution.Although it is generally assumed that dsRNA is a hallmark of nonself, antisense transcription and dsRNAs are widespread in prokaryotes –126. As cis-acting antisense RNAs (asRNAs) when they are produced close to the gene or the structure that they regulate  and when they work with perfect complementarity or as trans-acting small RNAs (sRNAs) when they do not need perfect complementarity and can work in trans, often in association with chaperones that increase the affinity for their target [Escherichia coli [Long before the discovery of RNAi, antisense RNA regulation was considered an ancient and widespread form of gene regulation in prokaryotes ,101,128.r target ,124,129.r target , or by br target . This kir target ,129,132.r target ,101,128.hia coli . Thus, tDespite its analogies with RNAi, it was assumed that it is unlikely that the siRNA pathway could have evolved from the prokaryotic antisense regulatory process owing to the lack of homology between the protein machineries . HoweverSelection acts at the level of the phenotype, not the genotype, and these 2 hierarchical levels are evolutionarily dissociable ,137–139.How may such qualitative system drift have occurred to move from prokaryotic RNA regulation to eukaryotic RNAi? Although it is impossible to know the correct answer, we can hypothesize on the basis of studies of gene regulation in extant organisms. For example, in organisms that lack an RdRp, such as fruit flies and mice, regulatory siRNA can originate from naturally occurring dsRNAs ,51,52. CG. lamblia and P. tetraurelia [In some eukaryotes ancestors of LECA, the interaction between Argonaute and these short RNAs derived from the degradation of dsRNAs may have led to an amplification of the interference phenomenon carried out by asRNAs or sRNAs . During raurelia –65.Through such a transition, the eukaryotic RNAi system would have been able to take over the physiological effects of prokaryotic interference, including the ability to control TE and virus replication. In this scenario, no specific function was selected. Instead, qualitative system drift occurred that changed the molecular components and processes without changing the regulatory outcomes of the process. This transition may have been neutral, but the long-term evolutionary consequences would not have been. As with all processes originated by CNE, RNAi systems forced eukaryotes on an irreversible evolutionary trajectory that has shaped their genome architecture ever since ,82 Fig  and engeArabidopsis thaliana, 25% of the transfer RNA (tRNA)-derived sRNAs that immunoprecipitate with Argonaute-1 come from plastid tRNAs, suggesting the presence of a retrograde signaling pathway [CFLAR [Mycobacterium marinum produces an sRNA where the secondary structure is processed like an miRNA by the host cells, and which interacts with the RNA-induced silencing complex [Drosophila, where hairpin RNAs are processed to produce siRNAs [The connection between sRNAs in prokaryotes and organelles on the one hand, and eukaryotic RNAi on the other, may provide support for this hypothesis. In the thale cress  pathway . In humay [CFLAR . The int complex . Notably complex ,101. Thee siRNAs .Drosophila melanogaster, there is evidence of cross-talk between the miRNA and siRNA pathways during biogenesis of snoRNA-derived small RNAs [Another example of the connection between prokaryotic sRNA and RNAi is given by small nucleolar RNAs (snoRNAs). snoRNAs are a widespread class of eukaryotic small RNA with an archaeal origin and can carry out a broad variety of functions, including posttranscriptional RNA modification –156. Owiall RNAs . Furtherall RNAs ,158. TheEntamoeba hystolytica [Neurospora crassa [Crucially, as an evolutionary process, molecular system drift of RNAi is still in action. For example, in budding yeast (which did not lose its RNAi system), Dicer is replaced by another enzyme that evolved from the RNAse III RNT1 (confusingly named DCR1) . Other stolytica  and Dicea crassa .Gene regulation based on noncoding RNA is ancient and might even precede the origin of cellular life ,162,163.These examples highlight the complexity of biological processes and the importance of combining different perspectives to apply the best research methodology to understand them ,13,114.C. elegans, an organism composed of 959 cells  and with a genome size 30 times smaller than that of humans.Eukaryotic regulatory processes have indeed complex architectures, to the point that they have been described as “baroque structures”  or “RubeIn this Essay, we propose a step-by-step route which explains “how” RNAi could have emerged, without adaptive driving forces, from the molecular machineries present in the ancestor of the LECA through a qualitative system drift caused by CNE. We expect that our model can help to understand eukaryotic genome architecture evolution and the relationship between genome regulation and genome defense.


Background: Lung adenocarcinoma (LUAD) has a significant tendency to metastasize to the bone, with severe comorbidities. Recent studies have reported that circular RNAs (circRNAs) are involved in various cancer metastasis-related physiological cellular processes. However, their role in LUAD with bone metastasis (LUAD-BM) remains unknown.Methods: Bone metastasis (BM) circRNAs were identified using high-throughput sequencing and validated by quantitative reverse transcription-PCR (qRT-PCR). Bioinformatic analyses were used to predict the potential functions of the differentially expressed circRNAs. The effects of circ_0096442 on the growth and metastasis of A549 cells were detected in a co-culture system of A549 and bone marrow-derived cells.Results: There were 598 (238 upregulated and 360 downregulated) 390 (187 upregulated and 203 downregulated) and 644 (336 upregulated and 308 downregulated) differentially expressed circRNAs between LUAD-BM and LUAD, LUAD-BM and healthy individuals, and LUAD and healthy individuals, respectively. These differentially expressed circRNAs play important roles in cellular components, biological processes, and molecular functions. Moreover, they map several pathways related to BM, including DNA repair, DNA damage, and osteoclast differentiation. The results validated by qRT-PCR for the five most dysregulated circRNAs are consistent with the sequencing data. Additionally, circ_0096442 was found to promote the growth and metastasis of LUAD in a bone microenvironment.Conclusion: Our findings provide a novel and important circRNA expression profile of LUAD-BM and suggest that circ_0096442 may be a biomarker for LUAD-BM. Bone is the third most common target organ for advanced cancer metastasis . In advaGenomic studies have indicated that each step of BM is related to a series of molecular events . It is cAs the leading cause of cancer morbidity and mortality, lung cancer is usually diagnosed after developing locally or systematically , with luThe study was approved by the ethics committee of our hospital, and all participants provided consent for blood donation. All LUAD patients were diagnosed based on histopathologic tests and had no history of other tumors. The emission-computed tomography of bone scintigraphy showed multiple lesions in patients with BM. Control patients were matched in age, sex, body mass index, and region  and stored under strict standard operating procedure conditions temporarily at −80°C before batch analysis. Hipure PX Blood RNA Kits (Magen) were used to extract total RNA. Concentrations of isolated RNA were detected using a Qubit 3.0 fluorometer . Isolated RNA integrity was detected with an Agilent 2100 bioanalyzer . KAPA RNA HyperPrep Kits with RiboErase for Illumina  were used to prepare a high-throughput sequencing library with 2 μg of total RNA. Illumina Hiseq X ten was used to perform paired-end (PE150) sequencing.Twenty-five pairs of clinical samples from patients with LUAD-BM or LUAD were used to validate five candidate circRNAs by quantitative reverse transcription-PCR (qRT-PCR). Primer sequences and back-splicing sites of the candidate circRNAs are shown in 2 incubator under humidified conditions. The co-culture system was set up using 6-well Transwell inserts  with a 0.4-µm pore size.The human lung adenocarcinoma (HLA) A549 and bone marrow stromal HS-5 cells were purchased from the American Type Culture Collection  and cultured in Dulbecco’s Modified Eagle’s medium  containing 10% fetal bovine serum  and 1% penicillin/streptomycin at 37°C in a 5% COCirc96442-wt and circ96442-mut were inserted into the psiCHECK2 dual-luciferase vector . Hsa-miR-326 mimic and negative control miRNA (miR-NC) were synthesized by GenePharma . After co-transfection of the reporter vector and miR-326 mimic or negative control in A549 cells for 48 h, Renilla luciferase activity was measured using a dual-luciferase assay kit  against that of Firefly luciferase.in situ hybridization (FISH) kit  according to the manufacturer’s instructions.A549 cells were seeded on cell slides at the bottom of a 24-well plate and fixed with 4% paraformaldehyde. The CY3-labeled probe targeted the hsa_circ_0096442 junction site, and the FITC-labeled hsa-miR-326 probes were designed and synthesized by Geneseed . Nuclei were stained with 4,6-diamidino-2-phenylindole (DAPI). The signals of the probes were detected using a fluorescence t-test. Statistical analyses were performed using GraphPad Prism 8  and SPSS v.20.0 . Differences with p < 0.05 were considered as statistically significant and were noted by asterisks .All values are expressed as the mean ± standard error of the mean (SEM). Statistical significance was determined using the Student’s More method details .There were 598 (238 upregulated and 360 downregulated) 390 (187 upregulated and 203 downregulated) and 644 (336 upregulated and 308 downregulated) differentially expressed circRNAs between LUAD-BM and LUAD, LUAD-BM and healthy individuals, LUAD and healthy individuals, respectively. Notably, 54 consistently dysregulated circRNAs were identified in the LUAD-BM group than in both control groups, including 19 previously unknown circRNAs . DiffereThe most significant enrichment pathways of Gene Ontology (GO) Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome analyses of differentially expressed circRNAs between LUAD-BM and LUAD, LUAD-BM and healthy individuals, and LUAD and healthy individuals are shown in Five candidate circRNAs were validated by qRT-PCR to verify the RNA-seq data. Expression patterns consistent with the sequencing data were found . Among tTo further confirm the function of circ_0096442 in lung cancer, we constructed stable A549 cells overexpressing circ_0096442 and A549 cells expressing short hairpin RNA (shRNA); the efficiency of circ_0096442 overexpression and knockdown was verified by qPCR . A549 ceThe binding sites between circ_0096442 and hsa-miR-326 were predicted by the miRanda algorithm. Next, we designed and generated psiCHECK2 vectors carrying wild-type and mutant miRNA-target sites in the circ_0096442 sequence, enabling validation of the direct binding of miR-326 and circ_0096442 . The duaAs microarray analyses can only identify hundreds of circRNAs, this study adopted high-throughput sequencing to analyze all circRNAs attained from blood samples of patients with LUAD-BM, LUAD alone, or healthy individuals. After strict filtering of approximately 270 million reads, 40,207 circRNAs were detected, including 598 differentially expressed circRNAs between LUAD-BM and LUAD, 390 differentially expressed circRNAs between LUAD-BM and healthy individuals, and 644 differentially expressed circRNAs between LUAD and healthy individuals. These circRNAs may play important roles in regulating the pathological processes of BM.in vivo and in vitro, Recently, miRNAs have become a subject of interest in lung cancer with BM, mainly presenting as osteolytic bone destruction due to enhanced osteoclast activity. For example, The molecular mechanisms underlying the interactions between circRNAs, miRNAs and mRNAs in BM are still unclear. Therefore, a circRNA-miRNA-mRNA network of BM was constructed based on 35 consistently dysregulated circRNAs in patients with LUAD-BM compared with both control groups. The results indicate that the identified circRNAs could potentially interact with the miRNAs in the aforementioned studies. For example, according to our coexpression analysis, miR-326 can potentially bind to hsa_circ_0111889,hsa_circ_0096438,hsa_circ_0000657 and hsa_circ_0058988.Although differentially expressed circRNAs in patients with BM were identified, the underlying mechanisms remain poorly understood. Each molecular pathway contributing to BM is regulated by various factors, through closely-controlled genes expressed by cancer cells and interactions between cells within the bone microenvironment . Functioin situ hybridization, and demonstrated that the circular inhibitor of nuclear factor-kappa B kinase subunit beta (circIKBKB) was upregulated significantly. They further revealed a plausible mechanism for circIKBKB-mediated nuclear factor-kappa B (NF-κB) hyperactivation in bone-metastatic breast cancer. In a transcriptome sequencing study, Bone is the most common metastatic site for primary breast and lung tumors . HoweverBM is a complex, multistep process requiring tumor cells to detach from their original sites, intravasate into blood vessels, and subsequently survive and proliferate in the bone . TherefoThis study is the first to systematically characterize and annotate circRNA expression in patients with LUAD-BM. Our findings provide a novel and important circRNA expression profile of LUAD-BM and suggest circ_0096442 as a possible biomarker for LUAD-BM.


To investigate the risk factors for lymph node (LN) metastasis in low and middle rectal tumors, construct a predictive model and test the model's diagnostic efficacy.The clinical and pathological data of 172 patients with rectal cancer confirmed by surgery were retrospectively evaluated, among whom 61 patients were finally included in this study. Patients were divided into positive groups and negative groups based on LN metastasis, and risk factors that might affect LN metastasis were analyzed. Finally, a risk predictive model was constructed based on the weights of each risk factor.p = 0.049), conventional ultrasound features diagnosis of LN metastasis  and SR  were independent risk factors for LN metastasis. These risk factors were included in logistic regression analysis and the model was established, Y = −7.3 + 1.9 X10 + 2.1 X11 + 1.6 X13 . The receiver operating characteristic (ROC) curve was used to test the model's predictive efficacy, the area under the curve was 0.95, sensitivity: 95%, specificity: 87%. Hosmer–Lemeshow goodness of fit test showed X2 = 6.015, p = 0.65 (p > 0.05), indicating that the model had a high predictive value.Compared with pathology, the efficacy of diagnosing LN metastasis only according to conventional endorectal ultrasonography (ERUS) features of LN was not high, with sensitivity 67%, specificity 86%, positive predictive value 76%, negative predictive value 80%, and accuracy 79%. Univariate analysis showed that circumferential angle of the tumor, ultrasonic T‐ stage (UT stage), conventional ultrasound features diagnosis of LN metastasis, strain ratio (SR) of tumor were risk factors for LN metastasis, while vascular resistance index of rectal tumor was protective factor. Multivariate analysis showed that UT stage . The ROC curve was used to test conventional ultrasound and the model's predictive efficacy, the area under the curve was 0.76 , 0.95 , respectively. Hosmer–Lemeshow goodness of fit test indicated this model had a high predictive value. The cutoff of the model was −0.80.Multivariate analyses showed the independent risk factors for LN metastasis was UT stage, conventional ultrasound features diagnosis of LN metastasis and SR. These independent risk factors were included in logistic regression analysis and the model was established,  Unfortunately, there are no clinical findings or imaging examinations that are very accurate in assessing LN metastases before surgery. Endorectal ultrasonography (ERUS) and MRI are the preferred examinations for rectal tumors. Previously, these tests were used to determine whether a LN was metastatic by morphologic characterization of the LN, however the accuracy was not high.22.1This study was approved by the Hospital Ethics Council (number: 2021MCZQ12). From January 2019 to December 2021, 172 patients confirmed rectal cancer pathologically were recruited into this study. Patients received neoadjuvant therapy, did not undergo ERUS examination or with incomplete data were excluded, 61 patients were finally included in this study, including 31 males and 30 females, with an age range of 33–86 years. The workflow of screening patients is shown in Figure Inclusion criteria: (1) ERUS was performed within 2 weeks before surgery; (2) rectal tumor within 10 cm from the anal margin; (3) No neoadjuvant chemoradiotherapy was performed before examination; (4) Histopathological diagnosis was performed postoperatively.Exclusion criteria: (1) incomplete ERUS results due to intestinal stenosis or high tumor location; (2) recurrent rectal cancer; (3) complicated with other types of malignant tumors; (4) the patient had a history of pelvic infection; (5) pregnancy.2.22.2.1HITACHI ARIETTA 70 ultrasonic instrument was used, with a 360° transrectal probe and a biplane probe, frequency: 5–10 MHz, the frequency could be adjusted. In addition, one‐time retention enema bags and physiological saline were prepared.2.2.2(1) Applied the couplant to the surface of the rectal ultrasound probe and covered it with a clean condom. (2) In order to get the patient's cooperation, before the examination, the sonographers explained to the patient about the purpose of the examination to eliminate the patient's tension. (3) Two days before the examination, patients should eat less residue diet, one day before, take some liquid food, before the examination, warm water enema one to two times to remove the residue in the rectum. At the time of examination, 100–200 mL of normal saline was kept in the rectum.The patient was placed in the comfortable left decubitus position and the anus was exposed. First, the examiner performed an anal finger examination to see whether there was lumen stenosis, then the probe was slowly inserted into the anus, and the patient was instructed to relax the abdomen and anus during the insertion. After the probe entered the anal canal, the rectum was scanned layer by layer. After the routine ERUS examination, we switched to real‐time elastography mode. The patient was instructed to do Valsalva action to pressurize the probe, adjusted the force according to the displayed pressure index, controlling the pressure between 2 and 3, stored the stable elastic image for 30–60 s, and measured the strain ratio (SR) value of the tumor through the software that came with the instrument, measured three times in a row and took the average value. The diagnosis of each patient was completed by the same two doctors, who had 5 years of experience in ERUS. The operator was unaware of pathological diagnosis, laboratory examination results, and other imaging examination results, but knew the patient's clinical symptoms. The intraclass correlation coefficient was used to evaluate the reproducibility of the examination results of the two sonographers.2.32.3.1Ultrasonic T‐ stage (UT stage) Figure 2.Diagnosis of perirectal LNs metastasis by conventional ultrasound morphological features3.Other indicators recorded are tumor orientation, size, morphology, tumor distance from anal margin, circumferential angle of the tumor, peak systolic velocity (PSV), vascular resistance index (RI), SR The diagnosis of UT stage was based on Beynon's staging criteria.2.3.2Gender, age, carbohydrate antigen 19‐9 (CA19‐9), carcinoembryonic antigen (CEA), and other related data. Pathological results of LNs: the patient received surgical treatment within 2 weeks after the ultrasound examination, and the specimen was taken during the operation and sent for pathology examination quickly.2.4T test was used for comparison between the two groups for data conforming to normal distribution, while the Mann–Whitney U test was used for nonnormally distributed data. Spearman correlation was used for correlation analysis. X2 test was used for comparison of counting data. The diagnostic accuracy was calculated using surgical pathology as the gold standard. The variables with differences in univariate analysis were incorporated into Logistic regression analysis and the diagnostic model was established. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficiency of model. p < 0.05 was considered statistically significant.SPSS 26.0 statistical software was used for analysis. The measurement data were tested for normality first, and the 33.13.23.3r = 0.54, p = 0.000.Table 3.4p < 0.05). Other factors  had no significant effect on LN metastasis.Table 3.5p = 0.049). The risk of LN metastasis was increased if LNs were assessed as metastatic by conventional ultrasound features . For every unit increase in SR, the risk of LN metastasis from rectal cancer increased fivefold approximately .Table 3.6Y = −7.3 + 1.9X10 + 2.1X11 + 1.6X13 . The −2logarithm likelihood ratio of the model was 34.336, Cox & Snell R Square = 0.54, N Agelkerke R Square = 0.73.These independent risk factors were included in logistic regression analysis and the model was established, 3.7p = 0.000), 0.95 , respectively. Hosmer–Lemeshow goodness of fit test showed X2 = 6.015, p = 0.65 (p > 0.05), indicating that the model had a high predictive value. The point nearest the upper left of the ROC curve corresponded to a sensitivity of 95% and specificity of 87%, the prediction probability (p) corresponding to this point was the cutoff, where Y(Logit(P)) was −0.80. When Y > −0.80, the model predicted that there would be metastasis, when Y < 0.80, the model predicted that there would be no metastasis.The ROC curve Figure  was used4ERUS has been recognized as the preferred imaging diagnostic method for patients with rectal cancer, and it is also one of the most accurate methods to evaluate the depth of rectal tumor invasion. Previous literature reported that the accuracy of ERUS in the evaluation of T stage of rectal cancer reached 86%,According to previous research,On the basis of previous research,The results of this study showed that there was a close relationship between the depth of rectal tumor invasion and metastatic LNs, and the probability of LN metastasis was greater in patients with deeper invasion, and UT stage was an important risk factor for perirectal LN metastasis. Previous studies References In addition, this study found that the stiffness of rectal tumors was also related to LN metastasis, and SR was higher in rectal tumors with LN metastasis than in tumors without LN metastasis, and the difference was statistically significant. Elastography reflects the stiffness of the lesion and has proven to be valuable in multiple organs such as the liver, breast, and prostate,Limitations and prospects of this study: First, this model could not predict the LNs of T4 rectal cancer, which was a limitation of this study, but the most important significance of preoperative determination of LN metastasis was to choose the appropriate treatment plan, whether conservative treatment or radical surgery? As T4 rectal cancer was not suitable for radical surgery, the metastasis of LNs was not the most important for the choice of treatment direction. Second, as an important feature of tumor, the circumferential angle of the tumor showed no statistically significant difference in univariate analysis. Although RI of the tumor was different in the univariate analysis, it had no statistically significant effect on the results when entering the multivariate analysis. Such a result may be related to the insufficient sample size of this study. Third, it has been noted that the closer the LNs were to the primary tumor, the greater the chance of metastasis,5P) = −7.3 + 1.9 X10 + 2.1 X11 + 1.6 X13  had good assessment efficacy and had certain clinical application value.Evaluation of lateral LN metastasis only based on conventional ERUS features of LNs was not effective enough. The three variables  were screened by logistic regression as independent risk factors for LN metastasis. After integrating these independent risk factors, the predictive model established greatly increased the diagnostic efficiency, comparisoning with that based on the morphology and size of LNs observed by conventional ultrasound alone. The predictive model . The requirement for individual consent was waived by the committee because of the retrospective nature of the study.


Relative Ct values obtained for mRNAs in degraded preparations strongly correlated with the corresponding levels in non-degraded RNA, both for each ACL as well as for the pooled results from all six ACLs. Nuclease-mediated degradation produced similar, strongly correlated losses of housekeeping and non-housekeeping gene mRNAs. RNA degraded in situ yielded comparable results, confirming that in vitro digestion effectively modeled degradation by endogenous ribonucleases in frozen and thawed ACL. We conclude that, contrary to conventional wisdom, PCR-based expression analyses can yield valid mRNA profiles even from RNA preparations that are more than 90% degraded, such as those obtained from connective tissues subjected to biomechanical studies. Furthermore, legitimate quantitative comparisons between variably degraded tissues can be made by normalizing data to appropriate housekeeping transcripts.Correlating gene expression patterns with biomechanical properties of connective tissues provides insights into the molecular processes underlying the tissue growth and repair. Cadaveric specimens such as human knees are widely considered suitable for biomechanical studies, but their usefulness for gene expression experiments is potentially limited by the unavoidable, nuclease-mediated degradation of RNA. Here, we tested whether valid gene expression profiles can be obtained using degraded RNA from human anterior cruciate ligaments (ACLs). Human ACL RNA (N = 6) degraded in vitro by limited ribonuclease digestion resemble highly degraded RNA isolated from cadaveric tissue. PCR threshold cycle (C Profiles of expressed mRNAs reflect the physiological states of cells and tissues ,2. ConseRNA profiling studies using fresh or fresh–frozen tissues have characterized the molecular responses of connective tissues to injury in non-human animals ,9, and iLimited RNase digestion of ACL RNAs yielded degraded preparations with electrophoretic properties similar to highly degraded RNA isolated from human cadaveric intervertebral disc . Notwitht pairs  for all 89 genes in RNA from the six ACLs revealed a strong linear relationship (Pearson correlation coefficient r = +0.80) provided by the following equation:The expression profiling by real-time RT-PCR quantified mRNAs of 89 extracellular matrix components, including 13 MMPs, 12 collagens, and 3 TIMPs . Using ht irrespective of an individual RNA’s abundance, with a possible trend toward a proportionally greater loss of higher abundant mRNAs.The line intercept  reflected an increase in the number of PCR cycles required to reach the threshold signal as a consequence of degradation-induced decreases in the amounts of amplifiable mRNAs for the 89 targets. The line slope near, but slightly below, 1.0  revealed that degradation produced a generally uniform increase in CA hierarchical analysis of individual regression lines for the six RNA preparations  had strot increase ranged from 0.75 cycles for the 86 targets detected in degraded ACL 104 RNA to 5.2 cycles for the 80 targets detected in degraded ACL 105 RNA, corresponding to 40% and 97% average losses of amplifiable target, respectively, as calculated using the following formula:In contrast to the common slopes of the regression plots, randomly distributed intercepts ranged from 2.93 to 7.48, possibly reflecting a stochastic variation in the extent of RNA degradation between preparations. Mean Ct increased because of RNA degradation, more targets were lost and the scatter of the data increased. Nonetheless, even at the highest levels of degradation , profiles from individual degraded RNAs strongly correlated with those from the corresponding intact RNAs (r ≥ +0.86). Likewise, the coefficients of determination (R2) ranging from 0.75 to 0.96 indicated that 75–96% of the variation in target signals from degraded RNAs reflected the biologically relevant distribution of target signals from corresponding intact RNA.The randomly distributed y-intercept (b) values inversely correlated with the number of quantified targets (N) and with the magnitude of the Pearson coefficient (r), indicating that, as the average C2 = 0.92). Furthermore, in situ digestion produced a slope of the degraded vs. intact regression line . Furthermore, a regression analysis revealed a strong correlation , comparable  than is generally thought to be acceptable for such studies. Our findings are consistent with those of prior studies examining smaller gene sets in degraded RNAs from various tumor cells and tissues ,24,25,26E. coli that cleaves between any two ribonucleotides, whereas human cellular ribonucleases exhibit more restricted nucleobase specificities  the tissues for storage at −80 °C. Additionally, per IRB# L06-154, clinical staff removed protected health information  to de-identify specimens prior to transfer to the research lab. For a cadaveric comparison tissue, we excised the L4-5 disc from the frozen (−20 °C) spine of a willed body . As is commonplace for donated bodies, no information was available regarding the time between donor death and freezing of the spine, or the specific conditions of its storage prior to receipt in the lab. Finally, for additional, RNA-rich comparison tissue, we used cadaveric human testes (N = 6), acquired with consent for use in research by the National Disease Research Interchange , and frozen within 6 h of donor death.Tissue acquisition. With patient consent and per IRB-approved protocol (TTUHSC IRB# L06-154), we recovered human ACLs normally discarded during total knee arthroplasty , and immediately froze [N2 (l)], thoroughly pulverized tissues  or the guanidinium thiocyanate/acidic phenol extraction [RNA isolation. We isolated RNA from frozen [Ntraction ,8 methodtraction : AgilentRNA degradation. For in vitro degradation of ACL RNA, we digested paired aliquots  either with RNase ONE™  to produce “partially degraded” RNA, or with no added enzyme to produce a mock-digested, “intact” control RNA, and assessed extent of degradation by formaldehyde/agarose gel electrophoresis (1 µg RNA/lane) .For the in situ degradation of ACL RNA, we incubated 1 g of thawed, pulverized ACL for 5, 10, 15, and 20 min at 23 °C to permit the autolytic degradation of RNA by endogenous RNAses, isolated RNA by the guanidinium thiocyanate/acidic phenol extraction method ,8, and tt) values at threshold = 0.4 from amplification plots , and omitted from further analysis any genes that the software identified as “undetermined” because they were not sufficiently amplified during the exponential phase. All five housekeeping genes in the array were successfully amplified in all profiles; therefore, downstream correlation analyses (see below) included Ct values from the full complement of these genes.Quantitative PCR. We used first-strand complementary DNA (cDNA) synthesized from 500 ng of RNA with combined oligo-dT and random hexamer priming  as a template for real time PCR , with SYBR Green detection. We calculated threshold cycle (Ct values obtained from degraded RNAs and non-degraded RNAs using hierarchical regression models. We first established a linear relationship by analyzing all data from the six ACL RNA preparations, then produced individual regression equations for ACL RNAs by treating them as random samples from the population regression, and examined the assumption of randomness of the regression coefficients by fitting hierarchical linear regressions with random slopes and random intercepts. To analyze the variation in degradation, we averaged the differences in Ct values between intact and degraded RNAs for each gene in each of the six ACLs, then plotted the averages for housekeeping and non-housekeeping genes against each other to test for correlations. Finally, we performed two-tailed t-tests to identify differences in extent of degradation between the housekeeping and non-housekeeping groups.Data analysis. To determine the effect of RNA degradation on expression profiles, we correlated C