Background: Gastric cancer (GC) is one of the most aggressive malignant tumors worldwide. Ferroptosis is a kind of iron-dependent cell death, which is proved to be closely related to tumor progression. In this study, we aim at constructing a ferroptosis-related lncRNAs signature to predict the prognosis of GC and explore potential therapies.Methods: Ferroptosis-Related LncRNAs Signature for GC patients (FRLSG) was constructed through univariate Cox regression, the LASSO algorithm, and multivariate Cox regression. Kaplan–Meier analysis, receiver operating characteristic curves, and risk score plot were applied to verify the predictive power of FRLSG. Gene Set Enrichment Analysis (GSEA) and immune infiltration analyses were conducted to explore the potential clinical value of the FRLSG. In addition, drug sensitivity prediction was applied to identify chemotherapeutic drugs with potential therapeutic effect.Results: Five ferroptosis-related lncRNAs  were identified to construct FRLSG, whose expression level in GC were confirmed by experimental validation. Kaplan-Meier curve and ROC curve proved the reliability and effectiveness of the FRLSG in predicting the prognosis for GC patients. Several immune-related pathways were enriched in the high-FRLSG group, and further immune infiltration analyses demonstrated the high immune infiltration status of the high-FRLSG group. In addition, 19 and 24 candidate drugs with potential therapeutic effect were identified for the high- and low-FRLSG groups, respectively.Conclusions: FRLSG was an effective tool in predicting the prognosis of GC, which might help to prioritize potential therapeutics for GC patients. Gastric cancer (GC), as the fifth most common malignancy, leads to the fourth-highest cancer death worldwide . Over onLong non-coding RNAs (lncRNAs) are defined as non-coding RNAs with at least 200 bp in length, which are proved to be key regulators in the occurrence and development of malignancies , 6. AberThe past decade has witnessed an outbreak of ferroptosis-associated researches. Ferroptosis, featured in intracellular accumulation of the massive lipid peroxidation, is a kind of regulated necrosis in iron-dependent form, which is distinct from apoptosis, necroptosis, and autophagy . ExcessiPrevious studies reported that specific lncRNAs could induce or inhibit ferroptosis in GC cells under different circumstance. LncRNA-PMAN was upregulated in GC cells and inhibited Erastin- and RSL3-induced ferroptosis, leading to poor prognosis and peritoneal metastasis . A hypoxhttps://portal.gdc.cancer.gov/, accessed on Aug 3, 2021), and a total of 375 GC samples and 32 non-tumor tissues were obtained. Samples without complete clinical data and the OS < 30 days were extracted to maintain statistical power and reduce bias. Ultimately, a total of 334 GC patients were included and utilized for subsequent analyses.Transcriptome data of GC patients and corresponding clinical information were derived from the TCGA data portal  was obtained from FerrDb , which wFirst, identified FRLs were subjected to univariable Cox regression to select the lncRNAs associated with prognosis of GC patients. Then these prognostic FRLs were further screened using the LASSO penalty analysis located in the “glmnet” package in R . FinallyP test. The sensitivity and specificity of the FRLSG in predicting prognosis were compared with other clinical features using the receiver operating characteristic (ROC) analysis, and the result was visualized by the “survivalROC” R package. Moreover, principal component analysis (PCA) and t-distribution random neighbor embedding (t-SNE) were conducted based on five FRLs using R packages “stats” and “Rtsne”, respectively.GC patients were separated into the high- and low-FRLSG groups based on the median FRLSG score. Kaplan–Meier curve analysis was conducted to assess the survival difference between the high- and low-FRLSG groups with Log-rank Univariate and multivariate analyses were conducted on FRLSG and clinicopathological manifestations for the identification of independent prognostic factors. Based on the identified independent prognostic factors, the FRLSG-integrated nomogram was constructed for predicting of 1/3/5-year overall survival of GC patients, which was validated by the calibration curves. Gene Set Enrichment Analysis (GSEA) was applied to detect the different functional phenotypes between the low-FRLSG subgroup and high-FRLSG subgroup in the enrichment of pathways in Kyoto Encyclopedia of Genes and Genomes (KEGG). 1000 random gene set permutations were performed. In addition, Gene Set Variation Analysis (GSVA) was performed to investigate the difference of enrichment score in certain pathway between the high- and low-FRLSG groups.With CIBERSORT algorism, the infiltration of 22 different immune cells was evaluated for each GC patients . To asseUsing the R package “pRRophetic”, transcriptome data of hundreds of cancer cell lines and drug sensitivity data obtained from three large pharmacogenomic projects, including the Cancer Therapeutics Response Portal (CTRP), Repurposing dataset PRISM (PRISM) and the Genomics of Drug Sensitivity in Cancer (GDSC) were integrated to predict transcriptome data-based drug response with the ridge regression model . MoreoveThe human gastric epithelial cell (GES-1) and GC cell lines (AGS and HGC27) were purchased from the Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China. All cell lines were cultured in RPMI-1640 medium  supplemented with 10% fetal bovine serum  and 1% penicillin/streptomycin , at 37°C in a 5% CO2 atmosphere.® Green qPCR Master Mix . The amplification protocol was as follows: 95°C for 10 mins followed by 40 cycles of 95°C for 15 s and 60°C for 30 s. The internal reference 18s rRNA was utilized as an endogenous control to normalize the expression of each target lncRNAs, and the relative expression quantity was calculated by the following formula: 2 −ΔΔCt (ΔCt = ΔCt target –ΔCt β-actin). Indicated lncRNA expression was measured by qPCR methods with the LightCycler® 480 System . Sequences of primers and 18s rRNA were listed as follows:Total RNA from GC cells was isolated with TRIZOL reagent  according to the manufacturer protocol. The RNA samples were reversely transcribed to extract corresponding cDNA using Reverse Transcription Kit , and the Quantitative Real-time PCR (qPCR) was performed using SYBRAL049840.4: F:AAAACAGACGCCGAGGTGAT; R:ACATGACAGTGGCAAGCTGAAC005532.1: F:GAGTGGGGAGTTCTTGGGAA; R:GGCCACAGATAACTGCTGCTAC004816.1: F:CGCCTGGTTGCAGAGTGA; R:CTGGACGGAAAGGCTTGGACLINC01357: F:CAGTTCAGTGACCTCGGGAA; R:GGCAAGTTGCATGGGTTCTCAL355574.1: F:TGCTTTCCTCAGGCTCTAAGG; R:CCTGTCCACCTCGTGTTCTT18 s rRNA: F:GTAACCCGTTGAACCCCATT; R:CCATCCAATCGGTAGTAGCGTo verify the prognosis prediction ability of FRLSG, the 1 year, 3 years, and 5 years ROC values of FRLSG were compared with four previously published ferroptosis-related lncRNAs signatures for GC, including Wei signature , Pan sigP-value < 0.05 was considered statistically significant.Unless otherwise specified, all statistical analyses were conducted with R software (version 4.1.3). http://www.tcga.org).All data are publicly available. The transcriptome data in this paper are derived from TCGA database  were extracted from the FerrDb . MoreoveLINC01357) +  (0.143597 ×  expressionAC004816.1) + (0.108552 × expressionAC005532.1) +  (−0.448995 × expressionAL049840.4) + (0.150565 × expressionAL355574.1).Univariate Cox regression analysis identified 28 prognosis-associated FRLs, which were included into the LASSO regression analysis , 1B. 5 FP = 2.66E-6, The patient risk survival status plot showed FRLSG was proportional to the number of deceased GC patients . Kaplan–P < 0.001), gender (P = 0.013), stage (P < 0.001), N-Stage (P = 0.009) and M-Stage (P = 0.003) were independent risk factors for GC patients (P < 0.001), age  and grade  were independent prognostic indicators for GC patients  were considered to be effective. 19 kinds of compounds  were identified to be potential targeted therapies for the high-FRLSG group  containing drug response data and transcriptome profiles of multiple cancer cell lines were used to establish prediction model of drug response. The Venn plot showed the number of drugs of the datasets mentioned above and their intersection . DiffereSG group . Some ofSG group , which wSG group .p < 0.05), which was consistent with the immune- and CTLA4-related pathways enriched in the high-FRLSG group . Among these 5 FRLs, AC004816.1, AC005532.1 and AL049840.4 were risk genes, while LINC01357 and AL355574.1 were protective genes. The result of qRT-PCR assay verified the high expression level of these 5 FRLs in GC cell lines, which were first reported in GC. A recent study showed that AC004816.1, as one of the immune-related lncRNAs, could guide the treatment of prostate cancer  reportedin vitro experiment. For example, GSK4112, as an agonist of Rev-erbα, was proved to be able to decrease proliferation, glycolytic flux and the pentose phosphate pathway in human GC cells.Recently, ferroptosis in tumor tissues was reported to be tightly correlated to immune cell infiltration. Aberrant ferroptosis in tumor tissue could contribute to abnormal increase of granulocyte ratio . To our in vivo and in vitro experiments were needed to uncover more convincing evidences for the validation and development of FRLSG.Although FRLSG is proved to be reliable and effective, there are still two limitations. First, without external cohort verification, the universality of FRLSG needs to be further validated. Second, the underlying regulatory mechanisms of 5 lncRNAs in ferroptosis remain unclear. Therefore, comprehensive In conclusion, we proposed FRLSG composed of 5 FRLs, which demonstrated high prognosis predicting power for GC patients. FRLSG could also help the clinical decision-making of immunotherapy, offering an innovative route for the individualized treatment of GC patients.Supplementary Tables 1-3Supplementary Tables 4 and 5


Bone marrow mesenchymal stem cells (BMSCs) have been used in stem cell-based therapy for various diseases due to their self-renewing ability and differentiation potential to various types of cells and immunoprivileged properties. However, the proliferation capability and functionality of BMSCs are known to decline with aging, which severely limits the extensive applications of BMSC-based therapies. To date, the exact mechanism involved in the cellular senescence of BMSCs remains unclear. RNA is thought to be the initial molecular form of life on earth. It also acts as a transmitter and important regulator of genetic information expression. There are many kinds of small noncoding RNAs with different functions in cells that regulate important life activity processes in multiple dimensions, including development process, gene expression, genomic stability, and cellular senescence. In this study, a replicative senescence model of hBMSCs was established and the expression changes of small noncoding RNAs during senescence were detected by small RNA high-throughput sequencing analysis and qPCR. Small RNA sequencing results showed that there were significant differences in the expression of 203 miRNAs, 46 piRNAs, 63 snoRNAs, 12 snRNAs, and 7 rasiRNAs. The results of qPCR, which was performed for the verification of the sequencing results, showed that there were significant differences in the expression of 24 miRNAs, 34 piRNAs, 34 snoRNAs, and 2 snRNAs. These findings might provide a novel insight into hBMSC senescence and contribute to the development of new targeting senescence strategies. BMSCs ae needed . A previe needed . EarlierRecent studies have shown that small noncoding RNAs (SncRNAs), a class of important epigenetic regulatory molecules, play an important role in the regulating cellular senescence of mesenchymal stem cells –8. SncRNin vitro. To gain insights into sncRNA changes in hBMSC senescence, we used small RNA sequencing  to generate extensive small RNA data and identified differentially expressed sncRNAs. These findings might provide novel insight into hBMSC senescence and contribute to the development of corresponding targeting anti-senescence strategies.In the present study, hBMSCs were isolated and underwent ten additional passages to simulate replicative senescence The project has been approved by the ethics committee of Xinhua Hospital Affiliated with Shanghai Jiao Tong University School of Medicine (SJTUSM). The bone marrow was obtained from volunteer patients who accepted traumatic femoral neck fracture treatment by internal fixation surgery in the hospital. Informed consent was obtained from all donors. The upper fat drops were removed by centrifugation at 1500 r/min for 5 min, resuspend the remaining flushing solution and slowly inject it into the test tube pre-added with the same amount of lymphocyte separation solution (Percoll), centrifuge at 1500 r/min density gradient for 10 min, suck the middle monocyte layer, wash it twice with PBS, centrifuge at 1500 r/min for 5 min, discard the supernatant, precipitate, and use DMEM medium  to resuspend. The cells were inoculated into the culture plate, the culture medium was changed every 2 days, and the cells were subcultured after they grew into clonal clusters.According to the manufacturer’s instructions, the Cell Senescence β-Galactosidase Staining Kit  was used for aging staining analysis of hBMSCs. The cells were washed twice with PBS, added with a fixing solution from the kit, and fixed at room temperature for 15 min. We removed the fixed solution and washed the cells three times with PBS for 3 min each time. We added 1 ml of preheated dyeing solution to each well to cover the whole growth surface. Incubation occurred at 37°C for 24 h. The positive cells were blue, as observed and counted under an ordinary light microscope.−△△CT method. All primers used are listed in BMSCs were isolated from three patients for RNA extraction and qPCR detection. The patients were female, aged 19, 19, and 23 years, respectively. The liquid in the culture dish was discarded by the graduated straw, the PBS buffer was rinsed two times, 1 ml of Trizol reagent was added to the culture dish, and the cells were repeatedly beaten to make the cell lysis. The above cell lysate was transferred into an EP tube, 200 μl of chloroform was added, and the lysate was then placed on ice for 5–8 min. It was placed in a low-temperature high-speed centrifuge for centrifugation, the supernatant was transferred to a new EP tube, an equal volume of isopropanol was added to it, the RNA was precipitated, and it was placed on ice for 10 min. An equal volume of 75% ethanol was added, and it was immediately put into a low-temperature high-speed centrifuge for centrifugation. Pour out 75% ethanol. It was dried at room temperature, precipitated for 5–10 min, and the RNA was re-dissolved. The RNA was reverse transcribed into cDNA as described in the manufacturer’s instructions of PrimeScript™ RT Master Mix  and miRNA First Strand cDNA Synthesis . According to the manufacturer’s instructions of TB Green™ Premix Ex Taq™ II (Tli RNaseH Plus) , the liquid preparation of each component was carried out on ice and was operated away from light. After the liquid of each component was added into the EP tube, it was placed on the vortex oscillator for oscillation, and then the qPCR reactions were carried out. RNA from BMSCs of three patients were detected by qPCR, respectively. The standard PCR amplification procedure was as follows: Step 1: 95°C for 30 s; Step 2: 95°C for 5 s, 60°C for 30 s, 50 cycles; and Step 3: dissolution curve. After the cycle, the amplification and dissolution curves were analyzed, the expression values of different genes were recorded for each group, and then the expression of the target genes was recorded for each group according to the 2The BMSCs isolated from a 23-year-old female patient were used for small RNA isolation, purification, cDNA library preparation, sequencing, and bioinformatics analysis, which were completed by SANGON biotech (Shanghai). The experimental operation was carried out in strict accordance with the reagent and instrument instructions. The main experimental processes include isolation of small RNA from total RNA, 5 ‘connector connection, 3’ connector connection, RT-PCR amplification, purification of small RNA library, detection of the library, cluster amplification of DNA in cluster station, sequencing on an Illumina Hiseq 2000 sequencer, and bioinformatics analysis of clean sequences with GenomeStudio software. Expression profiles of sncRNAs in two groups of cells were analyzed using the same samples.t-test and ANOVA were used for comparing two groups by Excel 2017, and p < 0.05 was considered as a significant difference.All data were shown with mean ± S.D. of three independent experiments. in vitro.Cellular senescence is of great significance to individual health. Replicative senescence is an important form of senescence. In order to detect the expression changes of small RNA in the aging process of hBMSCs, we firstly established a replicative senescence model of hBMSCs. We subcultured hBMSCs and collected P1 and P10 hBMSCs, respectively. The microscopic observation results showed that compared with P1 group hBMSCs, the morphology of P10 hBMSCs shrank significantly   , 13. In e (SASP) . These uin vitro. We found that hBMSCs at passage 10 showed obvious senescence characteristics, including increased SA-β-Gal activity and senescence-related gene expression. Moreover, the expression profiles of miRNAs, snRNAs, snoRNAs, piRNAs, and rasiRNAs in passage 10 hBMSCs were significantly different from those in passage 1.SncRNAs, a large class of regulatory molecules, are involved in organism development and coordination of biological processes, including metabolism, maintaining genome integrity, and immune and stress responses . Recent MiRNAs, the most studied sncRNAs, exert their negative regulatory functions at the post-transcriptional level by partially or fully binding to the untranslated region at the 3’ end of target gene mRNA, representing a new level of gene expression regulation. The sequencing and qPCR results show that there were 23 miRNAs upregulated while one miRNA was downregulated in passage 10 hBMSCs. Some miRNAs that we determined were altered with subculture passage in hBMSCs have been demonstrated in previous studies to play a role in suppressing osteogenesis and inducing cellular senescence. For example, in the chondrocytes of aging mice induced by ionizing radiation or DNA damaging chemical agents, the expression of miR-204 is significantly upregulated, and has important regulatory effects on SASP factors such as IL-6 and MMP-3 . In addivia two route-dependent or independent “Ping-Pong” amplification pathways . The patients/participants provided their written informed consent to participate in this study.Conceptualization: XC and CW. Methodology: FX, JP, and YL. Software: XZ, DM, LD, and JY. Data curation: JP and YL. Writing, review, and editing: FX and CW. All authors contributed to the article and approved the submitted version.This work is supported by Shanghai Sailing Program (20YF1429100 and 19YF1431200), National Natural Science Foundation of China (82172473 and 81802191), Natural Science Foundation of Shanghai (19ZR1433100), Interdisciplinary of Medicine and Engineering Foundation of Shanghai Jiao Tong University (YG2019ZDA22), and Biomedical Technology Support Program of Shanghai (20S31900200). Natural Science Foundation of Shandong Province (ZR2019PH068).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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Nevertheless, the cross-talk among these RNA modification regulators and related effects upon the tumor microenvironment (TME), immune infiltrates, and immunotherapy in STS remain poorly understood.Soft-tissue sarcoma (STS) represents a rare and diverse cohort of solid tumors, and encompasses over 100 various histologic and molecular subtypes. In recent years, RNA modifications including mIn this study, we comprehensively investigated transcriptional and genetic alterations of 32 RNA modification regulators in STS patients from The Cancer Genome Atlas (TCGA) cohort and validated them in the Gene Expression Omnibus (GEO) cohort. Single-cell transcriptomes were introduced to identify regulators within specific cell types, with own sequencing data and RT-qPCR conducted for biological validation. Distinct regulator clusters and regulator gene subtypes were identified by using unsupervised consensus clustering analysis. We further built the regulator score model based on the prognostic regulator-related differentially expressed genes (DEGs), which could be used to quantitatively assess the risk for individual STS patients. The clinical and biological characteristics of different regulator score groups were further examined.A total of 455 patients with STS were included in this analysis. The network of 32 RNA modification regulators demonstrated significant correlations within multiple different RNA modification types. Distinct regulator clusters and regulator gene subtypes were characterized by markedly different prognoses and TME landscapes. The low regulator score group in the TCGA-SARC cohort was characterized by poor prognosis. The robustness of the scoring model was further confirmed by the external validation in GSE30929 and GSE17674. The regulator score was negatively correlated with CD4+ T cell, Th2 cell, and Treg cell recruitment and most immunotherapy-predicted pathways, and was also associated with immunotherapy efficacy.Overall, our study is the first to demonstrate the cross-talk of RNA modification regulators and the potential roles in TME and immune infiltrates in STS. The individualized assessment based on the regulator score model could facilitate and optimize personalized treatment. Soft-tissue sarcoma (STS) represents a rare and diverse cohort of solid tumors accounting for merely 1% of all adult cancers , 3. Prev6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), 7-methylguanosine (m7G), pseudouridine (Ψ), and adenosine-to-inosine RNA editing (A-to-I editing) , readers (binding proteins), and erasers (demethylase)  . In mostthylase) , 10. Duethylase) , 12.6A was first found within poly(A) RNA fractions in the 1970s, but growing interests have been paid to this field only from the 2010s with methylated RNA immunoprecipitation-sequencing (MeRIP-Seq) introduced (6A methyltransferase complexes are mainly composed of methyltransferase-like 3 (METTL3), METTL14, METTL16, Wilms’ tumor 1-associated protein (WTAP), zinc finger CCCH-type containing 13 (ZC3H13), RNA-binding motif protein 15 (RBM15), and the corresponding paralogue RBM15B (6A demethylases including fat mass and obesity-associated protein (FTO) and α-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5) were initially reported only in the recent decade  protein family, including seven members in human   . Likewis4 (WDR4) .6A, m5C, m1A, and m7G in the STS of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohort. Several RNA modification regulator-related patterns were identified, and relative tumor microenvironment (TME) characteristics were intensively studied. Moreover, we established the prognostic regulator-related scoring model for individual STS patients. The RNA modification regulator-related score could help predict chemoimmunotherapy response in STS patients. The findings demonstrated that the cross-talk among different patterns of RNA modification regulators potentially contributed to shaping TME and immune characteristics, which had significant implications for therapeutic guidance.However, the above-mentioned studies only focused solely on specific RNA modifications, while the cross-talk among different patterns of RNA modification regulators in STS remain unclear. In the present study, we comprehensively investigated the cross-talk among RNA modification regulators including mhttps://xenabrowser.net/)  . The mutvia the UCSC Xena Browser. The pan-cancer mutation annotation files were obtained from the GDC data portal . Furthermore, we also introduced the immunotherapy-treated cohort. The cohort of melanoma patients treated with the combination of anti-PD-1 and anti-CTLA-4 was used to evaluate the association between the regulator score and prognosis after immunotherapy  was applied to conduct pairwise comparisons in gene expression among distinct patterns. The lmFit and eBayes functions were utilized to ensure accuracy. Multiple comparisons were corrected by using the Benjamini–Hochberg method . The GO annotation analysis was also conducted by utilizing the R package “clusterProfiler” (version 4.0.5), with false discovery rate (FDR) < 0.05 to determine significant enrichments  was conducted by utilizing the R package “GSVA” (version 1.40.1) . Similarichments .The interaction of RNA modification regulator expression in STS was assessed by the Spearman correlation test and visualized by the R package “corrplot” (version 0.90). The network of RNA modification regulator combined with prognostic data was further constructed and visualized by utilizing the R package “igraph” (version 1.2.6).Single-sample gene set enrichment analysis (ssGSEA) was utilized for quantifying specific immune cell infiltration. Marker genes of specific immune cell types for ssGSEA were retrieved from the published study . Levels Furthermore, signatures related to immunotherapy-predicted pathways and cancer-immunity cycles were extracted from published studies 5 51, 5, 551, 52PC1i + PC2i) where i represents the expression of the final determined prognostic DEGs.The RNA modification regulator-related scoring system was established as follows. First, distinct RNA modification regulator clusters were identified by the unsupervised clustering, and the overlapping DEGs among these clusters were filtered and selected. Then, the univariate Cox regression analysis was used to estimate the prognostic relevance for each DEG. The significantly prognostic genes were extracted, and the principal component analysis (PCA) was further performed based on these prognostic DEGs. Both PC1 and PC2 of prognostic DEGs were selected to serve as the signature scores. This scoring method has significant strength in focusing on the score of the set with the largest block of well-correlated (or anticorrelated) genes, while downweighing contributions from genes unrelated to most set factors, which was applied in previous studies , 55. Thehttps://satijalab.org/seurat/). In the current study, the quality control (QC) metrics were consistent with those in the published study. We conducted gene expression normalization by LogNormalize . Then, 2,000 highly variable genes (HVGs) were identified with the FindVariableGenes function. Following the results of the ElbowPlot, 25 PCs were selected. Then, cell clustering and t-distributed stochastic neighbor embedding (t-SNE) were further performed based on the above analysis. Moreover, we used the same labels from the data resource to annotate specific cell clusters, and detailed annotation approaches were present in corresponding parts in that study (Single-cell RNA-seq data were acquired from one published study (GSE131309) . Based oat study . The genhttps://www.cancerrxgene.org/downloads/anova) (50 and drug sensitivity score were used based on the R packages “pRRophetic” (version 0.5) and “oncoPredict” (version 0.2)  was accessed to collect drug response data (s/anova) . The druion 0.2) , 59. Mor2 atmosphere.The human synovial sarcoma cell line (SW-982) and liposarcoma cell line (SW-872) were purchased from Procell Life Science & Technology Co., Ltd. The human skin fibroblast cell line (HSF) was purchased from Fenghui Biotechnology Co., Ltd. The primary human synovial sarcoma cells (hSS-005R) were established as previously described . The aboTotal RNA of cell lines was extracted using the RNA Express Total RNA Kit . The cDNA synthesis was performed by utilizing the RevertAid First Strand cDNA Synthesis kit . The RT-qPCR was performed as previously described . The seqWe validated related gene expression level with our own sequencing data including 4 tumor samples and 4 paired normal tissues. Full-length transcriptome analysis was performed by Biomarker Technologies . All operations were in accordance with Oxford Nanopore Technologies . The analysis platform (BMKCloud) performs correlation analysis based on reference sequences and nanopore transcriptome sequencing data.t-tests for parametric comparisons and Wilcoxon signed-rank test for nonparametric comparisons. Similarly, one-way ANOVA and Kruskal–Wallis test were applied when over two groups were analyzed. Survival curve comparison was conducted by Log-rank test. Univariate and multivariate Cox regression were utilized to identify significant prognostic factors, with hazard ratio (HR) and 95% confidence interval (CI) calculated. Receiver operating characteristic (ROC) curves were performed to assess the accuracy of the model by utilizing the R package “timeROC” (version 0.4). The function “surv_cutpoint” of the package “survminer” (version 0.4.9) was repeatedly conducted to determine the optimal cutoff values of the regulator scores in the datasets. The patients in the datasets were further dichotomized into low and high regulator score subgroups. We also used chi-square or Fisher exact tests to compare clinical characteristics between two distinct groups. Statistical significance was assigned with two-sided p-value < 0.05.Statistical analysis was performed by using R software (version 4.1.0). The Spearman correlation test was conducted to calculate the correlations of RNA modification regulators. For pairwise comparisons, data were compared by utilizing Student’s In this study, a total of 32 RNA modification regulators were selected. The somatic mutation frequency of RNA modification regulators in STS was first assessed. The mutations were concentrated within 14 RNA modification regulators, and only 18 of 237 STS patients (7.59%) displayed regulator-associated mutations  (p < 0.001) and OS of GSE17674 (p = 0.003) with that in the TCGA-SARC cohort (p < 0.001)   (p < 0.001)  can be found below: NCBI GEO, accession no: GSE198568. LQ and ZL conceived and designed this study. WZ, XR, LQ, and ZY performed the data analysis, plotting of figures, and writing. RX, RC, and CT were responsible for the critical reading of the manuscript. All authors participated in interpreting the results and revision of the manuscript and approved the submitted version. All authors read and approved the final manuscript.This work was supported by grants from the National Natural Science Foundation of China , the Hunan Provincial Research and Development Program in Key Areas (2020DK 2003), and the China Postdoctoral Science Foundation (No. 2021M693557).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.The reviewer YZ declared a shared parent affiliation with the authors LQ, WZ, XR, RX, RC, CT and ZL to the handling editor at the time of review.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The structure shows how the RNA is recognized and suggests how ExoN specifically removes mismatched nucleotides. It also provides clues for designing nucleotide analogs that may evade excision. —VVAlthough vaccines provide protection against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there remains a need for antivirals to treat COVID-19. Nucleotide analog drugs such as remdesivir, which target the viral RNA polymerase, have potential but are compromised by exoribonuclease (ExoN) activity that removes incorrect nucleotides from newly synthesized RNA. Liu  Structures of SARS-CoV-2 exonuclease–RNA complex provide insight into proofreading for potential antiviral development. Coronavirus 3′-to-5′ exoribonuclease (ExoN), residing in the nonstructural protein (nsp) 10–nsp14 complex, boosts replication fidelity by proofreading RNA synthesis and is critical for the virus life cycle. ExoN also recognizes and excises nucleotide analog inhibitors incorporated into the nascent RNA, undermining the effectiveness of nucleotide analog–based antivirals. Here we present cryo–electron microscopy structures of both wild-type and mutant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nsp10-nsp14 in complex with an RNA substrate bearing a 3′-end mismatch at resolutions ranging from 2.5 to 3.9 angstroms. The structures reveal the molecular determinants of ExoN substrate specificity and offer insight into the molecular mechanisms of mismatch correction during coronavirus RNA synthesis. Our findings provide guidance for rational design of improved anticoronavirus therapies. Although several SARS-CoV-2 vaccines are now available (Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the COVID-19 pandemic, has infected more than 160 million people and led to more than 3 million deaths worldwide  activities . The N-t2  that contains a template strand  with three initiating guanosines followed by the 32 nucleotides (nts) at the 3′ end of the SARS-CoV-2 genome [excluding the poly(A) tail] and a 31-nt product strand  ending with a cytidine-5′-monophosphate (CMP), resulting in a C-U mismatch at the 3′ end . The pre2 . To obtaThe reconstituted nsp10-nsp14-RNA complexes were purified by size-exclusion chromatography (SEC) and analyzed by single-particle cryo–electron microscopy (cryo-EM). The final cryo-EM maps for the wild-type (WT) and mutant nsp10-nsp14-RNA complexes were refined to 3.9 Å (figs. S1 and S3) and 3.4 Å (figs. S2 and S3), respectively. With the exception of minor differences in the conformations of the RNA substrate and protein residue side chains, the two structures are almost identical, with a root mean square deviation of 0.39 Å across all protein Cα atoms (fig. S4). The ExoN active site, which is located in the nsp14 ExoN domain and supported by the N terminus of nsp10, binds the 3′ end of the RNA, separating it from the 5′ overhang . Most ofTo explore the possible link between SARS-CoV-2 RdRp and ExoN, SARS-CoV-2 nsp8 was included in the reconstitution of the complex and was found to be coeluted with the nsp10-nsp14-RNA complex on the SEC column (figs. S1A and S2A). However, it did not form a stable complex with nsp10-nsp14-RNA in the cryo-EM sample and was observed in only a small fraction of the particles (fig. S2C), indicating that association of nsp8 with the nsp10-nsp14-RNA complex is weak and dynamic. Although further in silico classification of the nsp8-bound class did not yield a map with high-resolution features of nsp8, the 6-Å low-pass–filtered map showed strong extra density along the solvent exposed region of the RNA duplex (fig. S2C). When docking nsp8 from the SARS-CoV-2 RdRp complex structure (The cryo-EM sample reconstituted with the use of mutant ExoN contained a class that represents a tetrameric form of the nsp10-nsp14-RNA complex (P (nucleotide numbering shown in P (Compared with the apo form of the SARS-CoV nsp10-nsp14 complex . Substraown in P .The nucleoprotein (NP) of Lassa virus (LASV) in the Arenaviridae family represents the only other group of ExoNs found in RNA viruses  ε subunit. This subunit has a much narrower DNA binding pocket, partially because of its tight association with the Pol III α subunit, and can fit only a single-stranded DNA substrate , at the +1 position of the P-strand . The modOur study offers insights into the mechanism of mismatch correction during SARS-CoV-2 RNA synthesis and reveals the structural features in the substrate that are essential for ExoN recognition and catalysis, providing a basis for structural-guided design of specific and potent ExoN inhibitors. Coadministration of such ExoN inhibitors with nucleotide analog–based viral RdRp antivirals could constitute a more effective treatment for COVID-19. Additionally, our study sheds light on the development of ExoN-resistant nucleotide analog inhibitors. In particular, we show that a free 3′-OH of the RNA substrate is critical for exonucleolytic degradation by ExoN. It has been shown that 3′-deoxy ribonucleotides can be efficiently incorporated into nascent RNA by RdRp from other positive-strand RNA viruses, such as hepatitis C virus and poliovirus, and can subsequently block RNA extension (20210727-1Click here for additional data file.


Epitranscriptomic modifications alter the targeting, regulation, and biogenesis of miRNAs, increasing the complexity of miRNA regulation. In addition, emerging studies have revealed crosstalk between these modifications. In this review, we will summarize the epitranscriptomic modifications—focusing on those relevant to miRNAs—examine the recent crosstalk between these modifications, and give a perspective on how this crosstalk expands the complexity of miRNA biology.The epitranscriptome encompasses all post-transcriptional modifications that occur on RNAs. These modifications can alter the function and regulation of their RNA targets, which, if dysregulated, result in various diseases and cancers. As with other RNAs, miRNAs are highly modified by epitranscriptomic modifications such as m The central dogma depicts a straightforward transfer of genetic information from DNA to RNA to proteins . However6A), 2′-O-methyl, 5-methylcytidine (m5C), 7-Methylguanosine (m7G), poly-uridine (poly-U), and adenosine-to-inosine (A-to-I) nucleotide substitutions [Many RNA processing events have been characterized within cells, including N6-methyladenosine  over other m6A sites [6Am is the combined methylation of m6A and 2′-O-methly that occurs adjacent to the 5′ cap site of mRNAs. FTO can demethylate m6Am and render the mRNA susceptible to decapping and degradation [6A readers  [6A site and can alter the stability of mRNAs, as well as promote protein translation, splicing, and mRNA export [6A can target a wide range of mRNA targets, leading to the regulation of various cellular processes. Dysregulation of m6A is associated with various diseases [6A modification controls cardiac homeostasis, as it is improved in response to hypertrophic stimuli and is required for the normal response of cardiomyocytes [6A is also important in brain development; in fact, METTL3 silencing provokes severe movement disorders and brain dysplasia [mleotides . Researc6A sites . m6A is of mRNAs . m6A hassplicing , the CDSsplicing , and thesplicing ,26. The /METTL14 , METTL5 /METTL14 , METTL16/METTL14 ,30, WTAP/METTL14 , VIRMA [/METTL14 ,33, ZC3H/METTL14 , HAKAI [/METTL14 , and RBM/METTL14  methylatsers FTO  and ALKBsers FTO . Recentl6A sites . m6Am isradation . m6A reaNRNPC/G)  bind to A export . m6A candiseases  such as diseases , osteopodiseases , metaboldiseases , and vardiseases . METTL3 diseases ,48,49, oysplasia .6A writers, erasers, and readers disrupt the regulation of oncogenes and tumor suppressors, leading to an increase in cancer cell proliferation, tumor growth, and migration [6A modification can induce tumor-suppressive or oncogenic pathways with different effects and have been proposed as a potential therapeutic target. For instance, METTL3 is upregulated in acute myeloid leukemia (AML) and is a necessary gene to preserve the undifferentiated phenotype in AML [In cancer, migration . Based oe in AML . In lunge in AML .6A is found in pri-miRNAs, where it enhances the recognition and binding of DGCR8 to promote miRNA processing [6A in HEK293 cells identified 239 enriched miRNAs; 20.9% of all miRNAs contain the consensus METTL3 motif RRACH [6A eraser FTO altered the steady-state levels of miRNAs [6A-dependent manner, and the downregulation of METTL14 in HCC results in a reduction of miR-126 [In miRNAs, mocessing . RNA immif RRACH . Knockdoif RRACH . Likewisif RRACH . Overexpif RRACH . Knockdof miRNAs . A recenf miRNAs . Moreove miR-126 .6A enzymes are also targets of miRNAs [6A levels in non-small-cell lung cancer (NSCLC) and gastric cancer, respectively. miR-145 targets the m6A reader YTHDF2; their expression is inversely correlated in ovarian cancer cells [6A modifications increase miRNA processing, while miRNAs themselves can target m6A enzymes.The mf miRNAs , which if miRNAs  and miR-f miRNAs  target Mer cells . Furtherer cells . Taken t2′-O-methyl is a modification commonly found in rRNAs , animal 7-guanosine cap. The first and second nucleotide of the 5′ end of pre-mRNAs can be further methylated with 2′-O-methyl, forming the cap1 and cap2 structures, respectively [In mRNA, 2′-O-methyl can be found either internally within the gene body  or at thectively . The capectively , where tectively . mRNAs tectively .Furthermore, 2′-O-methyl has been detected internally in mRNAs ; its bioDrosophila, 2′-O-methyl was detected in specific isoforms of miRNAs [Drosophila, suggesting miRNA 2′-O-methyl impacts aging in Drosophila [2′-O-methylation of miRNAs has been primarily reported in plant and drosophila miRNAs ,78. In pRecently, 2′-O-methylation of miRNAs was detected in NSCLC and paired distal non-cancerous lung tissues, with a differential 2′-O-methyl status of miRNAs in both tissues . HENMT1 5C was discovered almost 50 years ago [5C methylation is a dynamic and reversible process driven by several factors, described as writers, readers, and erasers [5C methyltransferases (RCMTs) are mainly represented by the NOL1/NOP2/SUN domain (NSUN) family and DNA methyltransferase 2 (DNMT2), which transfer the methyl group from the donor S-adenosylmethionine to the cytosine, forming m5C [mears ago , and yet erasers . The RNAming m5C .5C methyltransferase identified as a mediator of m5C in mRNA and non-coding RNA [5C methylation in mRNA through a methyl-specific RNA-binding motif and mediates the export of m5C-containing RNA [The NSUN family of proteins comprises seven members, named NSUN1 to NSUN7 . While Nding RNA . The mRNning RNA ,87. Addi5C in the 38th cytosine of tRNAs [AspGUC and, depending on the species, tRNAGly, tRNAVal, and tRNAGlu [AspGUC is important for the amino acid charging of the tRNA [AspGUC and reduced the synthesis of proteins containing poly-Asp [DNA methyltransferase 2 (DNMT2) is a methyltransferase that catalyzes mof tRNAs . DNMT2 m tRNAGlu . C38 metthe tRNA . Knockdopoly-Asp .5C modifications in RNA include bisulfite sequencing, m5C-RIP-seq, Aza-IP-seq, and miCLIP-seq, which are discussed later in the review . In 201ular RNA . The dis5C methylation affects mRNA transport, stability, and translation [5C methylation of tRNA prevents its degradation from oxidative stress [5C in several types of RNA are critical for the physiological function of the cell, and its deregulation is related to pathological features [urothelial carcinoma pathogenesis [mnslation . Additioe stress . The disfeatures . Mutatiofeatures , mitochofeatures , and stefeatures . NSUN2 hfeatures . NSUN2 cogenesis .5C methylation has been recently reported as present in microRNAs. Using a non-targeted mass spectrometry sequencing technique, Konno et al. identified methylated cytosines in mature sequences of miR-21-3p and miR-200c-3p in gastrointestinal cancer cells [mer cells .5C on miRNA inhibits the formation of miRNA/mRNA duplexes, thus impairing the miRNA’s ability to bind to the target mRNA. miR-181a-5p is frequently under-expressed in glioblastoma [5C from miR-181a-5p abolishes its tumor-suppressive function [The mechanisms involved in cytosine methylation have only recently been elucidated. In a pivotal study, Cheray et al. demonstrated that the complex DNMT3A/AGO4 is responsible for the cytosine methylation of miR-181a-5p . m5C on blastoma , and itsblastoma . The remfunction .5C [5C in other miRNAs.Interestingly, the cytosine methylation of miR-181a-5p was also associated with a poor prognosis of glioblastoma, which indicates the novel usefulness of cytosine-methylated miRNAs as a prognostic biomarker for cancer . A signi5C . However7G is an abundant modification found in the 5′ guanosine cap of mRNAs, as well as internally in mRNAs, tRNAs, rRNAs, and miRNAs [7G is critical for the complete maturation of the 5′ guanosine cap found in all RNAs transcribed by RNA pol II [7G to the cap, forming the cap0 structure [md miRNAs . m7G is A pol II . In the tructure . RNMT-RAtructure ,105. Protructure .The enzymatic activity of RNMT-RAMAC is regulated during embryonic stem cell differentiation . ERK1/2 7G in various RNAs. METTL1/WDR4 modifies m7G at the G46 site of a tRNA variable loop, stabilizing the tertiary structure of tRNAs [7G was recently detected internally in mRNAs. Internal m7G is catalyzed by METTL1/WRD4 and is associated with increased translation efficiency [7G is catalyzed by the WBSCR22/TRMT112 complex, where G1639 in 18S rRNA is methylated. This methylation participates in the biogenesis of 18S rRNA [METTL1 and WDR4 catalyze mof tRNAs . Disruptof tRNAs . m7G wasficiency . In rRNA18S rRNA .7G modification in the 5′ guanosine cap of mRNAs has been widely studied, yet there are few papers researching this in miRNAs. In their effort, Xie et al. developed a small RNA Cap-seq protocol to identify a group of m7G-capped pre-miRNAs, including a subset whose 5′ ends coincide with the RNA pol II transcription start site (TSS) [7G-capped pre-miRNAs undergo a non-canonical biogenesis pathway that bypasses Drosha and exportin-5 and instead goes through PHAX-dependent exportin-1 [7G-capping of shRNAs and the subsequent selection of a single 3p siRNA for targeted silencing [7G-capped miRNAs and mRNAs into extracellular vesicles [The presence of mte (TSS) ,115. Theportin-1 ,115. Theportin-1 ,115. In ilencing . Intriguvesicles .7G-capped, they have detectable trimethylguanosine  caps that are added at the pri-miRNA stage [7G-capped TSS small RNA (sRNA) transcript [7G-capped TSS sRNA is enriched in AGO2-containing RISC, unlike the aforementioned 5′-extended 5p miRNAs, and is capable of repressing complementary pTP and Adpol mRNAs, consequently suppressing viral DNA replication [Martinez et al. observed a subset of miRNAs whose expression was induced in response to quiescence despite a marked reduction of exportin-5 . The quiNA stage . A reducNA stage . Kamel aanscript . In humalication .7G modification at internal positions [7G mutational profiling sequencing (m7G-MaP-seq) but could not find evidence for the m7G modification in any human miRNAs, including let-7e [Kouzarides et al. used two complementary techniques, RNA immunoprecipitation sequencing (RIP-seq) and borohydride reduction sequencing (BoRed-seq), to identify a high-confidence group of mature miRNAs that contain the mositions . In a seositions . In compg let-7e .Poly-U is an epitranscriptomic modification in which a short string of non-templated uridines is added to the 3′ end of RNAs by Terminal Uridylyl Transferases (TUTases) . Poly-U In mRNAs, poly-U is added to mRNAs with a short (~25nt) poly-A tail and leads to the degradation of the mRNA ,127. KnoIn select pre-miRNAs, poly-U blocks Dicer cleavage and marks the pre-miRNA for degradation ,130. ThiIn addition, poly-U has been reported in mature miRNAs . The 3′ Xenopus laevis oocytes [It has been several decades since researchers uncovered an RNA editing event in which adenosine residues are converted to inosines, such as the mechanism behind the double-stranded RNA (dsRNA) unwinding observed in  oocytes ,135. An  oocytes . The ADA oocytes . Each co oocytes . ADARs c oocytes . A-to-I  oocytes ,141. Add oocytes .A-to-I nucleotide conversions of mRNAs can alter the amino acid sequence, thus creating various protein isoforms ,143. Fro2+ permeability of the AMPA receptor, and it is essential for producing a functional protein. Consequently, deficiency in this single point of editing is lethal in mice [2+ signaling mediated by the AMPA receptor activates Akt, thus inducing growth and motility in glioblastoma cells [Aberrant regulation of ADAR-mediated editing results in many human diseases, such as Aicardi–Goutières syndrome ,148, neu in mice . It has  in mice , and Ca2ma cells . The levma cells . The HCCADARs recognize and bind to dsRNA substrates, including all forms of miRNAs , with minimal sequence specificity . Based oThese nucleotide substitutions can also alter miRNAs’ functions . SpecifiAs mentioned previously, the inosine residue is interpreted as guanosine by the host translational machinery . When KuIn recent years, high-throughput sequencing technologies have uncovered the widespread dysregulation of edited miRNAs across human malignancies, including neurological diseases, infections, and cancer . For exa6Am [6A/m5C [6A and A-to-I editing) [6A interacting with other modifications, as these interactions have been the focus of recent studies.Each epitranscriptomic modification has its respective function in RNAs. They do not occur in isolation; RNAs can have multiple epitranscriptomic modifications occurring simultaneously throughout the body of the RNA. These epitranscriptomic modifications can establish crosstalk that is either cooperative (m6Am  and m6A/ [6A/m5C ) or reguediting) ,172,173 6A and A-to-I editing was suggested in [6A-negative transcripts preferentially. Of note is that suppression of the m6A writers METTL3 and METTL14 increased global A-to-I editing levels in HEK293T cells. ADAR1 is predicted to be a target of m6A methylation. This prediction was confirmed in [6A site is recognized by the m6A reader YTHDF1 to upregulate the protein expression of ADAR1. Knockdown of YTHDF1 in interferon-induced cells decreases global editing of RNAs [6A and A-to-I editing. As described earlier, miRNAs undergo A-to-I editing, which raises the question of whether METTL3 can modulate A-to-I editing in miRNAs, which could be studied in future investigations.Crosstalk between mested in , where tirmed in  and [171irmed in , in both of RNAs . The dif6Am is a combination of two methylation events, 2′-O-methyl and m6A. The first nucleotide of a pre-mRNA in mammals contains a 2′-O-methyl in addition to the 5′ methyl-guanosine cap [6Am. m6Am is highly abundant in mRNAs initiating with adenosine; 92% of mRNAs that begin with adenosine contain m6Am in HEK 293 cells [6A event is generated by a specific methyltransferase, CAPAM, which interacts with RNA pol II and is coordinated with mRNA capping [6Am are resistant to mRNA decapping by DCP2 and are thus more stable. Because of the resistance to decapping, m6Am mRNAs are also resistant to miRNA downregulation [6Am are more resistant to miR-155-induced degradation than other mRNAs [6A modification in m6Am can be removed by FTO, acting as a possible on/off switch for miRNA targeting and degradation [6Am in miR-155 targets and FTO could be a possible regulatory mechanism exploited in cancers.msine cap . If the 93 cells . This m6 capping ,176. mRNgulation . For inser mRNAs . The m6Aradation . Both miradation ,178, and6A modification by METTL3/METTL14 was shown to facilitate the addition of m5C by NSUN2 and vice versa, suggesting a cooperative addition of both modifications [6A and m5C were shown to enhance its protein translation cooperatively [6A and m5C [6A and m5C statuses of host cells, changing the methylation of host and viral RNAs [6A and m5C are enriched at the 3′UTR of mRNAs, close to predicted miRNA binding sites [5C, in particular, is enriched at AGO binding sites [mications . In the ratively . Certain and m5C ,180. Virng sites . m5C, inng sites . Given tEpitranscriptomic modifications were initially identified in the 1970s using two-dimensional thin-layer chromatography to identify RNA methylations . AlthougTLC is a technique that separates chemical compounds in mixtures based on chemical properties such as polarity . The samA version of TLC that allows for two-dimensional separation (2D-TLC) was used to initially identify RNA methylations present in cells . TypicalLC-MS is a powerful technique for detecting and quantifying epitranscriptomic modifications in RNA . It combDue to the fragmentation of the RNA sample prior to analysis, LC-MS cannot directly determine the sequence context or identity of the modified nucleotide. To determine the RNA sequence, a ladder with known fragmentation patterns is included in the LC-MS analysis . This liRNA sequencing combined with immunoprecipitation or chemical modification is one of the most used approaches for profiling the methylation of nucleic acids. Several methods have been developed during past years to detect epitranscriptomic modifications.6A distribution of RNA [6A antibody which recognizes and enriches RNA fragments carrying the modified nucleotide [5C RNA methylation (m5C-RIP-seq) and m7G methylation (m7G-MeRIP) [A commonly used method for studying the epitranscriptome is methylated RNA immunoprecipitation (RIP) coupled with high-throughput sequencing (MeRIP-seq). This method was applied for the first time in 2012 to study the mn of RNA . In thiscleotide ,189. SubG-MeRIP) ,190. ThiG-MeRIP) .6A-individual nucleotide resolution crosslinking and immunoprecipitation (miCLIP-m6A) is an immunoprecipitation-based sequencing method that includes UV crosslinking of the anti-m6A bound to the m6A site [6A, allowing for the identification of the exact m6A site. An alternative method called photo-crosslinking-assisted m6A sequencing (PA-m6A-seq) utilizes 4-thiouridine (4SU) that is incorporated into the RNA [6A antibody and crosslinked using UV. Subsequently, the RNA is digested into 25–30 nucleotide fragments and sequenced [5C. The methylation-individual nucleotide resolution crosslinking and immunoprecipitation (miCLIP) approach can be modified to use an NSUN2 antibody for detecting RNA fragments targeted by NSUN2 [5C positions are recognized as truncation sites along with the transcriptome [RNA-binding proteins can be covalently linked to RNA through treatment with UV radiation and immunoprecipitated to identify the binding sites of their respective RNA targets. RNA crosslinking and immunoprecipitation (CLIP)-based methods and their derivations have been utilized to identify the sites of epitranscriptomic modifications . The addm6A site . The cro the RNA . The RNAequenced . Given tequenced . Crossliby NSUN2 . An overby NSUN2 . An overby NSUN2 . Immunopcriptome ,192.6A-level and isoform-characterization sequencing (m6A-LAIC-seq) is a high-throughput technique that permits the evaluation of methylation status in the whole transcriptome [6A antibody is used to ensure the pull-down of methylated RNA, and m6A-positive and m6A-negative spike-ins are added to quantify m6A pull-down efficiency. After m6A enrichment, ERCC spike-ins are added to the input, supernatant, and eluent RNA pools as an internal standard for library preparation. The levels of m6A are quantified as the ratio of RNA abundance in eluent/(eluent + supernatant) [mcriptome . An excernatant) .5C sites are identified as C-to-G conversions, which results from a ring-opening of 5-azaC during the protocol [Another antibody-based sequencing technology utilizes the cytidine analog 5-azacytidine (5-azaC). Cells expressing RCMT or transfected with a tagged RCMT are incubated with the modified nucleoside, which is randomly incorporated into RNA. Due to the nitrogen substitution at the C5 position, when RCMT recognizes 5-azaC, it forms an irreversible covalent bond at the C6 position of its RNA targets, and therefore it cannot be released from the RNA . IP is tprotocol . One limprotocol ,198, perRNA bisulfite sequencing technology (RNA-BisSeq) was initially used for detecting methylated cytosines in DNA . At an a5C) [This approach has remarkable advantages that include single-nucleotide resolution and not requiring high concentrations of RNA. However, it fails to react with base-paired cytosines and cannot distinguish 5-methylcytosine from 5-hydroxymethylcytosine (hm5C) . Additio5C) ,200,201.2′-O-methyl sequencing (2′-O-Me-Seq) is a method used to map 2′-O-methyl sites in RNAs . Under l2′-O-methylated nucleotides can be detected with a sequencing method named RiboMeth-seq. 2′-O-methylated nucleotides are less sensitive to alkaline degradation when compared to unmethylated nucleotides . RiboMetThe sequence is mapped to the reference sequence, and the first and last nucleotides of the library fragments sequence are recorded as 3′ and 5′. The nucleotides at the 3′ ends depend on their 2′OH function, while the 5′ ends depend on the 2′OH function of the neighbor fragment. The two reads are merged, and 5′ read ends are shifted one nucleotide upstream; thus, the reads refer to the same phosphodiester bond. Given that the 2′-O-Me nucleotide is resistant to degradation, it does not generate read ends, so the positions that correspond to a methylated nucleotide will be underrepresented. This creates a “negative image” that is converted to a peak diagram .This method starts with RNA fragmentation by the endonuclease Benzonase, which generates small RNA fragments; 2′-O-methylated nucleotides are resistant to fragmentation . OxidatiSimilar to RibOxi-seq, Nm sequencing is another method to detect 2′-O-methylation with base precision. Unlike RibOxi-seq, which relies on the random occurrence of fragmented 3′-end 2′-O-methyl, Nm-seq uses oxidation–elimination–dephosphorylation (OED) cycles to remove 3′-unmodified nucleotides and enrich RNA fragments with 3′ ends carrying 2′-O-methyl . A finalTAIL-seq is a sequencing method that is designed for the sequencing of the 3′ poly-A tail of mRNA, can identify dynamic changes in the poly-A tail length, and can detect nucleotides added to the poly-A tail such as poly-U . Prior t7G which takes advantage of the nucleoside hydrolysis of m7G when treated with NaBH4 [7G cap and treated with NaBH4 at a low pH to generate abasic sites at m7G nucleotides. The RNA is then treated with biotin-coupled aldehyde-reactive probe which will tag biotin to the abasic site. Streptavadin pulldown is used to enrich biotinylated RNA, which is sequenced. This method was used for the initial observation of m7G in miRNAs [BoRed-seq is a method for detecting internal mth NaBH4 . Total Rn miRNAs .1-cyanoethylinosine (ce1). Ce1 inhibits retrotranscription and truncates the cDNA at the site of RNA editing. The resulting cDNA is sequenced to identify sites of A-to-I editing. ICE-seq was initially used to identify A-to-I editing sites in human brain tissues [Inosine chemical erasing sequencing (ICE-seq) is used to identify A-to-I editing sites in RNA . This me tissues .Most epitranscriptomic modifications cannot be directly detected via RNAseq without alterations to the RNAseq protocol, as described above. When the RNA is reverse-transcribed into cDNA, the information of the modification site is lost . A-to-I 6A, m5C, A-to-I editing, m7G, poly-U, and 2′-O-methyl [This approach was first used on RNA in 2018 by Gerald et al. , and it O-methyl ,223,224.O-methyl ,217. ThiO-methyl . ImproveO-methyl . A deviaO-methyl . NIPSS cIn the past decade, there have been substantial advancements in the epitranscriptomics field due to the improvement of high-throughput methods for detecting and targeting epitranscriptomic modifications. These modifications can alter the functionality, structure, and regulation of their respective coding and non-coding RNAs, representing a novel, intricate regulation of the gene expression. In particular, miRNA regulation can be fine-tuned by epitranscriptomic modifications occurring on either the miRNA molecule or the targeted gene transcript. Several miRNAs that are well characterized in cancers can be regulated by epitranscriptomic modifications, modulating the biogenesis of these miRNAs or the efficiency of targets gene downregulation .6A and A-to-I editing being the most studied of these modifications. Current pharmacological studies have identified small molecular inhibitors for METTL3 [5C and HEN1 for 2′-O-methyl could be potential therapeutic targets for cancer. The poly-U enzymes TUT-4 and TUT-7 are being explored as potential therapeutic targets due to their role in let-7 miRNA maturation [There is a wide range of regulatory networks under the control of epitranscriptomic modifications, many of which are involved in human physiology and pathology. Several of the enzymes involved in epitranscriptomics are suitable therapeutic targets, with mr METTL3 , showingr METTL3 . Other eturation ,229.6A levels in peripheral blood RNA of gastric cancer patients. Other studies have found elevated levels of m6A in the serum of cancer patients [5C have also been found in the urine of colorectal cancer patients [Another importance of these epitranscriptomic modifications in cancer lies in their possible detection in circulation as potential new-generation biomarkers, evolving a new, quick, inexpensive, and non-invasive method for cancer diagnosis. Recently, Ge et al. reported a significant upregulation of mpatients ,232,233.patients .miR-17-5p shows increased methylation levels in cancer tissues compared to normal tissues, and its methylation level in serum could distinguish early pancreatic cancer patients from healthy patients . Additio6A itself can regulate or cooperatively interact with other epitranscriptomic modifications such as A-to-I editing, 2′-O-methylation, and m5C in RNAs. The interaction between m6A and A-to-I editing poses a possible mechanism whereby RNA editing can be fine-tuned by m6A regulation. The recently characterized METTL3 inhibitor could affect RNA editing activity, contributing to its effect on tumor cells. m6Am at the first nucleotide of an mRNA renders the mRNA resistant to miRNA downregulation. m6Am has its writer, CAPAM, and can be removed by the m6A eraser FTO [6Am and vice versa for tumor suppressors. Future studies will need to consider these modifications to fully understand their scope in miRNA biology and their potential in human diseases.To add to this complexity, maser FTO . It woul


STRIKE-GOLDD is a toolbox that analyses the structural identifiability and observability of possibly non-linear, non-rational ODE models that may have known and unknown inputs. Its broad applicability comes at the expense of a lower computational efficiency than other tools.STRIKE-GOLDD 4.0 includes a new algorithm, ProbObsTest, specifically designed for the analysis of rational models. ProbObsTest is significantly faster than the previously available FISPO algorithm when applied to computationally expensive models. Providing both algorithms in the same toolbox allows combining generality and computational efficiency. STRIKE-GOLDD 4.0 is implemented as a Matlab toolbox with a user-friendly graphical interface.https://github.com/afvillaverde/strike-goldd.STRIKE-GOLDD 4.0 is a free and open-source tool available under a GPLv3 license. It can be downloaded from GitHub at  A model is structurally identifiable  if it is theoretically possible to determine its parameters  by observing its output . https://eng.ox.ac.uk/non-lineardynamics/resources/. Unlike ProbObsTest, it does not assume polynomial inputs.STRIKE-GOLDD 4.0 includes a third algorithm, ProbObsTest, which is based on the algorithm presented by A second new feature of STRIKE-GOLDD 4.0 is its implementation as a Matlab toolbox with a graphical interface, a screenshot of which is shown in STRIKE-GOLDD is arguably the most generally applicable toolbox for local SIO analysis, being able to handle ODE models that may be non-rational and not affine in the inputs, and which may admit unknown external inputs. Previously, this generality came at the expense of high computation times for larger rational models. STRIKE-GOLDD 4.0 provides a method for a faster analysis of such models, along with a more generally applicable one. The coexistence of both algorithms, as well as the other features of the toolbox (searching for Lie symmetries and suggesting reparameterizations), makes it a convenient multi-purpose tool for the analysis and reformulation of systems biology models. Its usability is enhanced by its implementation as a Matlab app with a user-friendly graphical interface.btac748_Supplementary_DataClick here for additional data file.


Further investigations revealed that the RNA G-quadruplex of CapG exhibits a structural polymorphism, suggesting a possible mechanism that ensures the translation repression in a KCl concentration range of 25–100 mM. The approach described in the present study sets the stage for further discoveries of RNA G-quadruplexes.Tandem repeats of guanine-rich sequences in RNA often form thermodynamically stable four-stranded RNA structures. Such RNA G-quadruplexes have long been considered to be linked to essential biological processes, yet their physiological significance in cells remains unclear. Here, we report a approach that permits the detection of RNA G-quadruplex structures that modulate protein translation in mammalian cells. The approach combines antibody arrays and RGB-1, a small molecule that selectively stabilizes RNA G-quadruplex structures. Analysis of the protein and mRNA products of 84 cancer-related human genes identified Nectin  G-quadruplexes are highly stable nucleic-acid structures involved in a myriad of biological processes . The str3-N1–7-G3-N1–7-G3-N1–7-G3) in the 5′-untranslated regions (5′UTR) in the human genome  for RGB-1 was calculated to be 43 100 M−1⋅cm−1 from the average value. The maximal solubilities of RGB-1 in 1% and 10% DMSO/H2O were estimated by measuring the maxϵ of the solution. The maximal solubilities of RGB-1 in 10% and 1% DMSO/H2O were 26 and 11 μM, respectively.The solubility of RGB-1 was determined by UV absorption analysis. 1.196, 0.597 and 0.598 mg of RGB-1 were dissolved in 100 μl of DMSO. The UV absorbance of each RGB-1 solution was analyzed by a UV-1650PC (SHIMADZU). RNA samples for UV and CD measurements and footprinting assay were solubilized in 10 mM Tris–HCl (pH 7.5) buffer containing 100 mM KCl or LiCl. Prior to use, the samples were heated to 90°C for 5 min and gradually cooled to room temperature over 60 min in the same buffer.2 incubator. On Day 0, MCF7 cells were added to medium A in a 35 mm dish at 4.0 × 105 cells per well. On Day 1, the cells were treated with 1% DMSO (control) or 10 μM RGB-1 in 1% DMSO. After 2 days of culture, the cells were washed three times with cold Phosphate-Buffered Saline (PBS), and lysed with buffer 17 . Blotting assays were performed according to the manufacturer's protocol as follows. Array membranes were treated with 2.0 ml of Array Buffer 6 for 1 h for blocking. After blocking, the membranes were incubated with the cell lysates overnight at 4°C on a rocking platform shaker. Each membrane was washed with 1× Wash Buffer for 10 min for a total of three washes. The membranes were treated with 1.5 ml of Detection Antibody Cocktail and incubated for 1 h. The membranes were treated with 2.0 ml of 1× streptavidin–HRP and Incubated at room temperature for 30 min, and then washed each membrane. After washing, the membranes were treated with 1.0 ml of the Chemi Reagent Mix. and incubated for 1 min. After squeezing out the excess Chemi Reagent Mix, the membranes were placed in an autoradiography film cassette with the identification numbers facing up, and the X-ray film was exposed for 10 min for protein expression analysis.The Human XL Oncology Array Kit (R&D Systems) was used for the parallel determination of relative levels of 84 human cancer-related proteins. MCF7 cells were maintained in medium A  fetal bovine serum) at 37°C in a humidified 5% CO2 incubator. On Day 0, MCF-7 cells were added to medium A in a six-well plate at 3 × 106 cells per well. On Day 1, the cells were treated with 1% DMSO (control) or 10 μM RGB-1 in 1% DMSO. After 48 h incubation, the cells were washed three times with cold PBS, and lysed with buffer A . The cell lysates were passed 10 times through a 25G needle and centrifuged at 4°C for 10 min. The supernatants were transferred to new tubes and mixed with 0.20 volume of 6× sodium dodecyl sulfate (SDS) sample buffer . The samples were separated on a 15% sodium dodecyl sulfate poly-acrylamide gel electrophoresis (SDS-PAGE) gel, and blotted using antibodies against CapG , Nectin-4 , p53  or actin . The specific bands were visualized using enhanced chemiluminescence  on an ImageQuant LAS 500 .MCF7 cells were maintained in medium A  fetal bovine serum) at 37°C in a humidified 5% COTm was set to half the temperature of the maximum signal decrease.The melting temperatures of G-quadruplexes were estimated by monitoring Ultraviolet Visible (UV) absorbance on a UV-1650PC (SHIMADZU) under nitrogen atmosphere, as previously described . TemperaThe CD experiments were performed on a J-725 (JASCO) CD spectrophotometer equipped with a Peltier temperature controller. The spectra were recorded from 220 to 340 nm with a scanning speed of 200 nm/s. This experiment was performed for RNA G-quadruplexes (2.5 μM) in 10 mM Tris–HCl buffer (pH 7.6) containing 100 mM KCl.Fluorescein (FAM)-labeled RNA oligomers (1.5 μM) were solubilized in 10 mM Tris–HCl (pH 7.5) buffer containing 100 mM KCl or LiCl. The RNA oligomers were ensured to be folded by a heat/cooling process before the subsequent experiments. The RNA samples were treated with 0.05 U/μl RNase T1 (Thermo Fisher Scientific) at room temperature for 3 min, and then a urea-based buffer was added to terminate the reaction. Aliquots of the resulting solution were loaded onto a 15% Tris-borate EDTA (TBE)–urea (7 M) polyacrylamide  gel and electrophoresed at 1500 V for 2 h in 1× TBE running buffer. The FAM-labeled RNAs on the gels were visualized using a Typhoon Trio .2O was estimated to be 11 μM. We therefore decided to use 10 μM of RGB-1. To simplify the task of identifying biologically important RNA G-quadruplexes, we focused on cancer-related human genes. Their protein products in the cell lysates were analyzed with an array of antibodies against the protein products of 84 cancer-related human genes. Side-by-side comparison of the blotting data revealed both up-regulated and down-regulated gene products , in which one can detect the location of RNA G-quadruplex sites as RTase stop signals during the reverse transcription reaction of mRNAs .,53.-4 ans Figure  and furts Figure . Overall-4 mRNA contains four guanine tracts  that are located close to each other. To our surprise, RTase stop assays of its six mutants (mutant1-6) revealed that a G-quadruplex is formed not by the four consecutive G-tracts but by a combination of three of them and a distant G-tract  generated the less preferable G-quadruplex structure of the four consecutive G-tracts , exhibited even more complex patterns Figure . The sto-4 or CapG, while Renilla luciferase (RL) translation is mediated by IRES   is controlled by the 5′UTR of Nectin Figures . CompariThe reporter gene controlled by the CapG 5′UTR displayed an interesting property. RGB-1 similarly reduced the translation of the mRNA bearing wild-type CapG 5′UTR. However, this RGB-1- mediated translation repression was maintained even when either G-tracts 1 or 5 was replaced by an A-tract . Replacement of both G-tracts 1 and 5 abolished the ability of RGB-1 to repress the FL translation (CapG mutant3) . These rThe RTase stop assays showed that the proportion of the two CapG G-quadruplexes depends on KCl concentrations Figure . To esti-4 and CapG, we conducted footprinting. RNase-T1 footprinting experiments depicted clusters of protected guanine residues in the presence of KCl, indicating that these residues are involved in the G-quadruplex formation of Nectin-4 and CapG mRNA  RNA G-quadruplex structure , whose translation is suppressed by the RNA G-quadruplexes. These two non-canonical yet functional RNA G-quadruplexes have not been precisely detected by the previous computational or experimental studies.RNA G-quadruplexes are usually found in the G-rich sequences and have been proposed to play roles in various biological processes encompassing translation ,37,55,56-4 and CapG are well-established oncogenes that drive proliferation, metastasis, and angiogenesis in cancerous cells 4 motif that can form RNA G-quadruplex structures. This motif was identified as a hallmark of RNA transcripts whose translational levels are dependent upon eIF4A RNA helicase, suggesting that RNA G-quadruplexes control eIF4A-dependent oncogene translation  DNA sequence forms a set of two overlapping, interchangeable DNA G-quadruplex structures that regulate gene transcription , whose translation is suppressed by the RNA G-quadruplexes. These two RNA G-quadruplexes have not been detected by previous computational predictions or experimental screening. Interestingly, the CapG RNA G-quadruplex represents the first RNA G-quadruplex structure that combines two mutually exclusive G-quadruplex structures exchangeable in response to potassium concentrations. Our analysis suggested that this polymorphism plays a role in persistent translation repression. A limitation of our study is that RNA G-quadruplex structures were searched only from the protein products of 84 cancer-related genes. It is unlikely that RNA G-quadruplex structures are unique to oncogenes. A combination of proteome and transcriptome analyses with RGB-1 would permit the quick discovery of uncharacterized, non-canonical RNA G-quadruplexes structures that suppress translation in potassium-dependent and independent manners.In conclusion, our small-molecule-based screening has identified two human cancer-related genes (Nectingkac580_Supplemental_FileClick here for additional data file.


The role of extracellular vesicles (EVs) in interkingdom communication is widely accepted, and their role in intraspecies communication has been strengthened by recent research. Based on the regulation promoted by EV-associated molecules, the interactions between host and pathogens can reveal different pathways that ultimately affect infection outcomes. As a great part of the regulation is ascribable to RNA contained in EVs, many studies have focused on profiling RNAs in fungal and host EVs, tracking their accumulation during infection, and identifying potential target genes. Herein, we overview the main classes of RNA contained in fungal EVs and the biological processes regulated by these molecules, portraying a state-of-the-art picture of RNAs loaded in fungal EVs, while also raising several questions to drive future investigations. Our compiled data show unambiguously that EVs act as key elements in signaling pathways, and play a crucial role in pathosystems. A complete understanding of the processes that govern RNA content loading and trafficking, and its effect on recipient cells, will lead to improved technologies to ward off infectious agents that threaten human health. Extracellular vesicles (EVs) are cell-derived structures delimited by lipid bilayers unable to auto-replicate. These are produced by organisms from virtually every kingdom, reverberating their conserved origin. These structures transport different cargoes, including polysaccharides, toxins, lipids, proteins, pigments, and nucleic acids ,2.According to their origin and size, EVs comprise different entities, such as apoptotic bodies, exosomes, and microvesicles ,4. ExosoCryptococcus neoformans [The first identification of fungal EVs was reported in 1973, through freeze-etching of oformans . This woHistoplasma capsulatum, Sporothrix schenckii, Candida parapsilosis, Saccharomyces cerevisiae, Malassezia sympodialis, Paracoccidioides brasiliensis, Candida albicans, Pichia fermentans, Cryptococcus gattii, Sporothrix brasiliensis, Paracoccidioides lutzii, Candida glabrata, Candida tropicalis, Talaromyces marneffei, and Candida auris [Exophiala dermatitidis, Alternaria infectoria, Trichophyton interdigitale, Rhizopus delemar, Fusarium oxysporum f. sp. Vasinfectum, Trichoderma reesei, Aspergillus fumigatus, Aspergillus flavus, and Penicillium digitatum [Currently, EVs have been isolated from many different cell types and fluids , as wellda auris ,20,21,22igitatum ,28,29,30The discovery that RNAs are contained in EVs, mainly related to microRNA (miRNA) specimens in the years 2006–2007, paved the way for investigating the role of EVs as mediators of cell-to-cell communication ,32. ThisC. albicans [Recently, the participation of EVs in environmental signaling has been proposed . Milieu albicans . Anotheralbicans .Many aspects of the pathophysiology of fungal infections might be influenced by the transport of RNA molecules within EVs. The uptake of fungal RNA-EVs by host cells or even fungal cells is conceivably involved in gene regulation and, consequently, triggers changes in the responses of the recipient cells. From this perspective, the involvement of EVs in bidirectional communication has been proposed ,43 and, In this review, we describe the current knowledge on RNA content within EVs, along with the influence of these molecules on two-way systems, such as the fungus–host interactions and intraspecies regulation. We also discuss the challenges in RNA-EV work and raise hypotheses of the cellular strategies underlying this RNA export system.The presence of RNAs within extracellular vesicles was first described in 2007 . The autC. albicans, C. neoformans, and P. brasiliensis (isolate Pb18)—as well as the yeast model S. cerevisiae was conducted.The first study addressing fungal EV RNA content was reported in 2015 . In thisP. brasiliensis, 344 for C. neoformans, 423 for C. albicans, and 532 for S. cerevisiae. In addition, 47 miRNAs exhibited differential distribution, with higher levels of miRNA transcripts in C. neoformans, followed by P. brasiliensis, C. albicans, and S. cerevisiae. Only 20 miRNAs were shared among all studied species. Unique miRNA sequences were detected in P. brasiliensis, including has-mir5685, cre-MIR905, dre-MIR-125-a2, and has-mir-5583-1; and in S. cerevisiae, with ame-mir-3797 and cin-mir-4104. Of the 114 identified sRNA sequences, 11 were common among all studied species. Additionally, eight sequences corresponding to the lncRNAs were identified. Among these, ICR1 and PWR1 are involved in upstream signaling circuits that regulate yeast transition, whereas short non-coding RNAs (sncRNAs) play a role in mRNA and rRNA modifications that ultimately affect cell growth. Moreover, four sncRNAs have been described  as components of the spliceosome core, with functions in pre-mRNA processing. Indeed, the spliceosome machinery and pre-mRNA processing are critically involved in fungal adaptation to different niches, as well as their pathogenic capability [This solid comparative analysis of RNA-containing vesicles in pathogenic and non-pathogenic fungal species revealed the presence of RNAs with heterogeneous sizes, mostly shorter than 250 nt, primarily corresponding to small non-coding RNA sequences and miRNA-like sequences, while also demonstrating the co-purification of a small percentage of mRNAs (approximately 10%) . Accordipability .H. capsulatum [C. auris [M. sympodialis [This comparative analysis opens new paths for investigating fungal pathophysiology by tracking differences in EV-associated RNA molecules derived from species of fungi with different abilities in terms of human association and pathogenicity. These analyses allow the determination of peculiarities in composition and abundance, which may reflect the levels of regulation for niche preferences, adaptation, and virulence. Since then, EV RNAs from other fungal species—including psulatum , C. auriC. auris , and M. podialis —have beeP. brasiliensis (Pb18 and Pb3) and P. lutzii (Pb01 isolate) [In this context, another comparative study was performed to assess the RNA content of EVs from different isolates of iensis Pb and Pb3 iensis Pb and Pb3 isolate) .P. brasiliensis [P. brasiliensis (Pb18) and, potentially, its EVs in an elegant model. The data showed downregulation of transcription factors such as Gabpb2 and Pknox1, which are involved in lymphopoiesis [C. albicans, A. fumigatus, and P. brasiliensis [The listed exonic-sRNA-targeted genes described in iliensis  include opoiesis  and hemaopoiesis . From thiliensis . HoweverH. capsulatum (G186AR and G217B) [H. capsulatum is the causative agent of histoplasmosis, and represents a global concern, affecting both immunocompetent and immunocompromised patients. The strains G186AR and G217B show differences in virulence properties and cell wall composition. In this study, the authors revealed the occurrence of mRNAs and ncRNAs, with differences in their abundance between the studied isolates. Among ncRNAs, a large set of tRNAs was identified. Moreover, miRNA-like RNAs with regulatory functions were predicted by analyzing the putative development of secondary structures within the EV RNA content. Another query addressed by Alves et al. (2019) [Furthermore, another study reported the EV RNA content of two isolates of d G217B) . H. caps. (2019)  was the M. sympodialis under different pH ranges, in an attempt to mimic the pH changes during atopic eczema (AE)—a disease commonly triggered by this fungus. Although the approach was very interesting, no significant difference in RNA-associated EVs was shown for the assessed conditions, although more than 300 non-coding features were mapped for this species [In another line of investigation, Rayner et al. (2017)  assessed species .C. auris [C. auris (B8441 and MMC1) were used, and their RNA content was evaluated after fungal exposure to caspofungin. The authors demonstrated that EV concentration was twofold higher during caspofungin treatment than that in untreated conditions. Although mRNA molecules were identified, the bulk comprised sRNAs (<200 nt in length), including ncRNAs, tRNAs, and fragments of mRNA. The authors also demonstrated a different profile of EV transcripts in caspofungin treatment versus untreated conditions. Moreover, a 10x higher yield of RNA was observed for caspofungin treatment.Recently, a study profiled the cellular and EV transcriptomes of C. auris —a fungusC. albicans, C. neoformans, S. cerevisiae [C. auris [H. capsulatum [M. sympodialis [P. brasiliensis, and P. lutzii [C. auris, wherein tRNA was the most abundant molecule. A proper understanding of the RNA content in EVs, the changes in the signaling pathways that regulate these transcripts, and the targeted genes may reveal strategies employed during the interaction between systems, and also shed light on alternatives to tackle fungal arming during the infection.Herein, we intended to summarize the current information about the RNA contents in EVs, and with this purpose we carried out a deep survey of the published data about RNAs loaded in fungal EVs, and our data shed light on the prevalence of regulatory RNAs (about 65.5%) in comparison with mRNAs (about 34.5%), as shown in revisiae , C. auriC. auris ,55, H. cpsulatum , M. symppodialis , P. bras. lutzii . MoreoveH. capsulatum contain RNA-binding proteins, one of which belongs to the RNAi machinery [The role of EVs in cross-kingdom communication is unambiguously accepted, and it is conceivable that this mechanism is mainly achieved because EVs work as vehicles for hijacking sRNAs in a two-way manner; therefore, EVs are also termed “Trojan horses” . The funachinery . Thus, tHeligmosomoides polygyrus neutralizes host responses and favors infection [Arabidopsis and Botrytis cinerea. In this study, the authors tracked the accumulation of plant EVs in fungal cells, profiled the sRNAs produced during infection, and showed that the target silenced genes were related to fungal virulence traits. Moreover, other studies have shown the enhancement of sRNAs in cotton plants after fungal infection, reinforcing their role in regulating the expression of opponents and warding off infection [S. sclerotiorum spores were taken up by fungal cells and, as a result, these EVs had a significant impact on fungal morphology and hyphal development. EV-treated cells presented a strong reduction in hyphal growth, abnormalities in hyphal shape with a decrease in length followed by curly/wave hyphae, and the presence of non-germinated spores [Botrytis cinerea co-cultured with Arabidopsis and tomato, the hijacking of Bc-sRNAs promoted the suppression of host genes, including mitogen-activated protein kinase (MPK), oxidative stress responsive gene, peroxiredoxin (PRXIIF), and cell-wall-related kinase (WAK), leading to an enhancement in plant susceptibility, ascribed to a tight involvement of host immunity against fungal infection [Botrytis cinerea attenuates its virulence in different recipient cells, including fruits, vegetables, and flower petals. Moreover, the authors developed a Bc-DCL1/2–RNAi Arabidopsis plant system, and the RNAi plants displayed lower susceptibility to B. cinerea. These results provide insights into the development of strategies to control plant diseases using RNAi effectors and delivery systems.Previously, it was demonstrated that the secretion of exosome-containing miRNA and AGO protein by the gastrointestinal parasite nfection . Howevernfection  using a nfection . Similard spores . Conversnfection . Taking nfection  showed tBeauveria bassiana secretes a miRNA-like RNA (bba-miR1) loaded into its vesicles, targeting the Anopheles stephensi mosquito to suppress the expression of Toll receptor ligand Spätzle 4 (Spz4), attenuates the immune response, and favors fungal infection [In addition, the entomopathogenic fungus nfection . Once agUndoubtedly, the investigations of sRNAs within EVs break paradigms and challenge researchers in many respects regarding RNA quality inspection and the strategies employed to validate that these molecules are not loosely aggregated with EV membranes, but are loaded within these vesicles. In this respect, controls employing EVs undergoing RNAse treatment before sRNA extraction, or the rupture of EVs with Triton X-100 followed by nuclease digestion, were used to track some features of these molecules, and to prove that they were packaged within EVs ,57. NotaP. brasiliensis and P. lutzii, a higher abundance was observed for regulatory RNAs, such as sRNAs, miRNAs, and tRNAs, and it is highly conceivable that these molecules interact with the owner and/or host AGO proteins coordinating the host RNAi machinery. Understanding these tightly regulated processes that underlie EV content and trafficking opens new paths for investigation. Tracking of EV RNA can shed light on the plasticity, virulence, and niche preferences of some fungal species or strains. By exploiting this knowledge, researchers might be able to “edit” the framework mechanism in RNA production and transference that ultimately alters the circuit of information to disarm and ward off pathogens. A great improvement in systems such as host-induced gene silencing (HIGS) technology might be achieved for safer use in the biological pest control of crops, as well as an enhancement in therapeutic strategies to control infectious agents that threaten human health. However, the mechanistic framework for the regulation of fungal EV-containing sRNAs requires further investigation. Several questions arise from the current data: What determines RNA sorting in EVs? Which signaling pathways may cross to activate EV production and sorting? Which molecular mechanism underlies the EV RNA regulation of target genes in recipient cells? A schematic overview of EV RNA transference knowledge and the queries that await for further investigation is shown in Although RNA-containing EVs are protagonists during signaling and communication between cells, the precise regulation promoted by these molecules is not clearly understood. It is possible to speculate on some points when examining the content of these molecules loaded in EVs. First, packing and transferring rRNA is not the goal, since the recipient cells might be responsible for the translation task in a more efficient and energetically favorable manner. Second, although the presence of functional mRNAs was identified in EVs from


RNA-seq has become a state-of-the-art technique for transcriptomic studies. Advances in both RNA-seq techniques and the corresponding analysis tools and pipelines have unprecedently shaped our understanding in almost every aspects of plant sciences. Notably, the integration of huge amount of RNA-seq with other omic data sets in the model plants and major crop species have facilitated plant regulomics, while the RNA-seq analysis has still been primarily used for differential expression analysis in many less-studied plant species. To unleash the analytical power of RNA-seq in plant species, especially less-studied species and biomass crops, we summarize recent achievements of RNA-seq analysis in the major plant species and representative tools in the four types of application: (1) transcriptome assembly, (2) construction of expression atlas, (3) network analysis, and (4) structural alteration. We emphasize the importance of expression atlas, coexpression networks and predictions of gene regulatory relationships in moving plant transcriptomes toward regulomics, an omic view of genome-wide transcription regulation. We highlight what can be achieved in plant research with RNA-seq by introducing a list of representative RNA-seq analysis tools and resources that are developed for certain minor species or suitable for the analysis without species limitation. In summary, we provide an updated digest on RNA-seq tools, resources and the diverse applications for plant research, and our perspective on the power and challenges of short-read RNA-seq analysis from a regulomic point view. A full utilization of these fruitful RNA-seq resources will promote plant omic research to a higher level, especially in those less studied species. RNA-seq and its-derived techniques have been commercially available and routinely used by biological scientists, largely owing to the rapidly increased outputs of major sequencing platforms, improved sequencing accuracy and ever reduced costs . RNA-seqe.g., Pacific Bioscience, PacBio and Oxford Nanopore, ONT) provide long, uninterrupted sequencing of a single RNA or DNA molecules, constituting the third generation of real-time fluorescence sequencing paradigm  detection of new transcripts or correction of existing gene structures based on RNA-seq evidence; (3) to obtaining the expression profiles at gene or transcript levels and to construct the expression atlas covering a range of conditions and tissue types; (4) to identify alternative splicing and alternative 5’ or 3’ untranslated regions ; (5) to construct gene co-expression networks (GCNs) and predict gene regulatory relationships in a large scale . Here, GCN stand for a network that can be constructed from a large set of RNA-seq data and includes multiple clusters or modules. The module represents a group of genes determined statistically with high correlation in their expression profiles and usually associations in their functions  e.g., tomato, wheat, maize and soybean)  and other major crops (soybean) Table 1.olerance , justifyThe limited utilization of RNA-seq in the minor plant species has been partly due to: (1) the limited genomic resources; (2) lacking bioinformatic tools that are user friendly, with a graphical user interface, or well adapted to the omics data of various species. In this context, we summarize a variety of bioinformatic tools covering the diverse applications of bulk RNA-seq analysis to facilitate the full use of short-read RNA-seq data, and to help unleash the power of bulk RNA-seq in studies of plants, especially in the minor and under-utilized crops Figure 1e.g., TopHat, STAR, HISAT and HISAT 2; e.g., HTSeq  The first stage takes the raw sequencing reads to quality control and maps the quality-controlled reads to the transcriptome, which can be obtained from a reference genome or be assembled from transcriptomic data; (2) The second stage quantifies the number of reads mapped to each gene or transcript, producing an expression matrix; (3) The third stage modifies the expression matrix by normalization between samples, accounting for technical differences, and removing lowly expressed genes/transcripts; (4) The last stage calculates differentially expressed genes or transcripts by statistical models. Particularly, the number of computational tools for analyzing RNA-seq data has been increased dramatically in the recent decade . As such., HTSeq  and feat., HTSeq ]; (3) th., HTSeq ; (4) the., HTSeq ]; and  . While t(1) to assembly transcripts first and then to quantify expression; (2) to simultaneously construct transcripts and to quantify expression. For the genome-guided transcriptome analysis, multiple pipelines have been established that differ in the algorithms used and the speed and computational resources required, including the classic TopHat-Cufflink-Cuffdiff pipeline  The expression atlas website includes a number of useful functions, from the visualization, comparison and functional enrichment of the omics data to comprehensive annotations of genes or gene families and useful functions such as primer design, BLAST and ortholog identification. (2) The RNA-seq data are further utilized to construct co-expression modules and integrated with other types of omics data, for example epigenomic data sets. In addition, major plant genomics websites  across stem elongation, thus making possible to identify co-expressed modules associated with stem growth or straw biomass accumulation  analysis of time-course expression data, (2) inference of gene regulatory networks (GRNs) from the co-expression data, and (3) comparison of co-expression modules between plant species.First, clustering or co-expression analysis particularly for time-course data emphasizes on capturing the nonstationary time dependence in the data, for which multivariate clustering algorithms or nonlinear regression modelling methods usually perform better than the traditional clustering approaches . Thus, ce.g. the nonparametric Bayesian and Markov clustering methods  and enabling the query of upstream regulators of genes  Alternative splicing (AS), a phenomenon in which particular exons of a gene may be included or excluded from the processed messenger RNA (mRNA), leading to multiple proteins encoded from a single gene; (2) Alternative polyadenylation (APA), a phenomenon in which a transcript is processed to produce multiple isoforms differing in their untranslated regions (UTRs), in most of the cases, 3’UTRs. Both AS and APA greatly increase the complexity of transcriptome or the repertoire of proteins, and are involved in the molecular, physiological and developmental pathways . In humaficiency .i.e., DEXSeq  , and thfSplice) . NotablyfSplice) . Also, nfSplice) , enrichiFor alternative polyadenylation, user-friendly tools compatible with the genomes of non-model plant species are relatively limited, whereas major efforts have been made to capture 3’UTRs by specific experimental protocols, such as PAT-seq , 3’READsMany of the short-read, bulk RNA-seq data accumulated today from less-studied plants may be under utilized. Thus, making full use of these data by integrating RNA-seq tools presents an exciting yet challenging prospect. Still, improvements can be made in the following aspects: (1) to integrate with the long-read RNA-seq data; (2) to develop tools or optimize the current pipelines to adapt to complex plant genomes.ab initio and protein evidence-based prediction and long-read sequencing data (PacBio isoform sequencing (Iso-seq) has been the main choice for identifying full-length transcripts. Besides, high-quality full-length isoform sequencing has greatly expanded our understanding in genome annotation, isoform phasing, detection of fusion transcript and alternative splicing and alternative polyadenylation (APA). For example, automated annotation pipelines have been developed to combine the advantages of different annotation methods, including ing data . Howevering data Figure 1In addition, expression quantification may be complicated by other difficulties associated with plant genomes. Polyploid, including both allopolyploid and autopolyploid, are widespread in land plants. Polyploid species are frequent in biomass crops, such as the allopolyploid Miscanthus species  and autoNotably, short-read RNA-seq also has major merits in other plant-related research areas, especially single-cell/single nuclear RNA-seq and meta-transcriptome analysis, owing to the compatibility and cost affordability. Short-read RNA-seq facilitates meta-transcriptome characterization, profiling gene expression in a microbial community and providing a snapshot for functional exploration . In partMore recently, short-read RNA-seq has been pushed to single-cell resolution due to a series of technological advancements, including robotics, microfluidics and hydrogel droplets . In a feIn summary, our work discusses a representative collection of RNA-seq analysis tools covering gene annotation, construction of expression atlas, gene regulation and alternative splicing. We emphasize that the integration of these tools will unleash the power within RNA-seq analysis, uncover the gene regulatory complexity for many less-studied plant species, and, ultimately, promote the functional genomics of these species.MT and JiZ developed the conceptual outline and drafted the manuscript. All authors contributed to the article and approved the submitted version.