E. coli, we found similar efficiencies in rRNA depletion for riboPOOLs and the self-made depletion method; both comparable to the former RiboZero, followed by RiboMinus, succeeded by MICROBExpress. Further, our in-house protocol allows customized species-specific rRNA or even tRNA depletion or depletion of other RNA targets. Both, the self-made biotinylated probes and riboPOOLs, were most successful in reducing the rRNA content and thereby increasing sequencing depth concerning mRNA reads. Additionally, the number of reads matching to weakly expressed genes are increased. In conclusion, the self-made specific biotinylated probes and riboPOOLs are an adequate replacement for the former RiboZero. Both are very efficient in depleting rRNAs, increasing mRNA reads and thus sequencing efficiency.Current methods of high-throughput RNA sequencing of prokaryotes, including transcriptome analysis or ribosomal profiling, need deep sequencing to achieve sufficient numbers of effective reads  in order to also find weakly expressed genetic elements. The fraction of high-quality reads mapping to coding RNAs  is mainly influenced by the large content of rRNA and, to a lesser extent, tRNA in total RNA. Thus, depletion of rRNA increases coverage and thus sequencing costs. RiboZero, a depletion kit based on probe hybridisation and rRNA-removal was found to be most efficient in the past, but it was discontinued in 2018. To facilitate comparability with previous experiments and to help choose adequate replacements, we compare three commercially available rRNA depletion kits also based on hybridization and magnetic beads, i.e., riboPOOLs, RiboMinus and MICROBExpress, with the former RiboZero. Additionally, we constructed biotinylated probes for magnetic bead capture and rRNA depletion in this study. Based on  However, just sequencing total RNA is ineffective, since most reads will map to rRNA or tRNA. For example, bacterial total RNA contains at least 80–90% rRNA when harvested during exponential growth, which limits data output6. While RNA-seq without previous depletion of rRNA have been conducted using deep sequencing , investigation of weakly expressed mRNAs or regulatory RNAs is still limited9. Thus, depletion of rRNA is needed to enrich the fraction of desired mRNA reads and thereby increase their coverage. For instance, a sequencing depth of about 2 million effective reads  seems to be sufficient for analysing gene regulation of annotated genes in RNA sequencing , whereas about 20 million effective reads are suggested for ribosome-profiling assisted detection of novel protein-coding ORFs and analysing weakly expressed genes11. While sequencing prices are still dropping slightly, a plateau has been reached15 and still, more useful data is generated for less money if mRNA is enriched by rRNA depletion.High-throughput sequencing of mRNA or ribosomal profiling provides detailed insight into cellular transcriptomes and translatomes19. The second is based on annealing of complementary oligonucleotides and enzymatic digestion of the duplex hybrids by specific nucleases21. The third method limits cDNA synthesis to non-rRNA templates using a non-random primer mixture in cDNA production devoid of those matching to rRNA22.Three major strategies to achieve rRNA depletion are used. The first is based on the hybridization of oligonucleotides to rRNA and subsequent capture and separation with magnetic beads29. Its method was based on the first technique mentioned. However, the production of this kit was discontinued. In 2020, the kit re-entered the market with the same name, but with a substantial change in method. Now it is based on enzymatic digestion of rRNA hybridization complexes . Interestingly, for this method a bias was reported when compared to sequencing of undepleted total RNA30. This bias seems to be even stronger in ribosome profiling28. Some of the nucleases used here seem to have off-target activity. Thus, results about ribosome position and information about the A-site status can be blurred in final results. Furthermore, both 5’ and 3’ ends of mRNA fragments can be digested unspecifically32. The complete change in methods makes comparison of sequencing results obtained using RiboZero before and after 2019 more difficult. To provide scientists with an informed choice, we compared the previous RiboZero  with three other commercially available rRNA depletion kits: RiboMinus Transcriptome Isolation Kit, bacteria ; MICROBExpress Bacterial mRNA Enrichment Kit , and riboPOOLs . Furthermore, we constructed biotinylated probes (designated BP) for a species-specific depletion method following the patent US 2011/0,040,081 A133. All five depletion protocols are based on hybridization and magnetic bead capture. For comparability, we only chose this depletion strategy. The oligonucleotides used in RM, RP, and ME are short DNA probes of 20–30 nt antisense to the respective rRNAs. Additionally, it is known that the oligonucleotides contained in RM and ME do not cover the full length of the 16S rRNA38. In contrast, oligonucleotides used in RZ are antisense rRNA sequences covering the entire length of the rRNAs. Further, RM and ME target 16S and 23S rRNA but not 5S rRNA, whereas RP and RZ capture 5S rRNA as well. In order to provide the possibility of effective physical capture and (magnetic) depletion, the rRNA-targeting probes are labelled. All kits, except ME, use biotin, either at the 5’-end, the 3’-end or internally by introducing biotin-labelled UTP. Biotin is bound by streptavidin, which is the strongest non-covalent biological binding known39. Thus, magnetic beads covered with streptavidin are used for depletion. In contrast, probes in ME are polyA-tailed and, captured by poly-dT covered magnetic beads40. A short overview of the properties and differences for each kit is given in Supplementary table 43. In any case, concerning the kits tested here, the oligonucleotides in the kits RM, ME, and the former RZ, are designed to hybridize to many different bacterial rRNAs. They are pan-prokaryotic in their target rRNAs. For RP, in the beginning, only a species-specific version was available. Thus, the Escherichia coli specific edition of the RP kit is used in this study. Meanwhile, a broader range of different variations is available for the RP kit, pan-prokaryotic and several species-specific editions. However, our self-designed oligonucleotides are species specific for E. coli following the patent, which is the basis for the former RZ. Furthermore, the probes of the ME and RZ were developed in the beginning on the basis of E. coli rRNA33. Finally, as stated in the protocols for RM and ME, quality control of depletion success is performed using total RNA isolated from E. coli. We assume, therefore, that all commercial kit should be optimized for E. coli RNA. Consequently, this model organism was chosen to compare the depletion kits in this study.In any case, the first strategy is most commonly used and shows consistent results in depleting rRNA without introducing major bias. Until November 2018, the RiboZero Gold rRNA depletion Kit from Illumina was available, which was superior in rRNA depletion according to several publicationsIn this study, we aimed to find a suitable replacement for the former RiboZero to preserve comparability to previous experiments. Further, new kits like RP, have entered the market and were compared to RZ and a self-made method using RZ´s principle to determine the best rRNA depletion method(s) available. Fully optimized depletion of rRNA (and perhaps tRNAs) allows reducing costs in sequencing experiments like RNA-seq and Ribo-seq, while retaining the ability to get high-quality mRNA expression data.E. coli TOP10 (Invitrogen) and E. coli DSM 30083 T  were cultivated at 37 °C in LB medium, either overnight for DNA isolation or until OD600nm = 0.6 and 1.0 for RNA isolation. Cells were harvested at 12,000 × g at 4 °C for 5 min.All primer used are listed in Supplementary table 44. For RNA isolation, cell pellets were resuspended in 1 mL Trizol (Thermo Fisher) and mixed with approx. 0.2 mL 0.1-mm zirconia beads . Cells were disrupted using the Ribolyzer (MP FastPrep) for bead beating (thrice at 6.5 m/s for 45 s). After incubation for 5 min at room temperature (RT), 0.2 volumes chloroform per mL Trizol were added and mixed for 15 s, followed by centrifugation at 12,000 × g at 4 °C for 15 min. The upper aqueous phase was transferred into new tubes and RNA was precipitated with isopropanol (Carl Roth). The RNA pellet was carefully dried at RT and solved in RNase-free water. Afterwards, DNA digestion was performed . Complete DNA removal was tested with PCR using Taq DNA polymerase  and/or by the Qubit 2.0 Fluorometer  according to the Qubit RNA HS Assay Kits and Qubit dsDNA HS Assay Kit. Genomic DNA was isolated according to a CTAB (cetyltrimethylammonium bromide)-based protocol as described 33. Following this patent, primers amplifying the full length of 5S, 16S and 23S rDNA were selected. Since, the 23S rRNA is around 2,700 bp, the first and second part of this gene (designated 5′ 23S and 3′ 23S) were amplified separately to ease amplification. For later in vitro transcription of complementary rRNA, the reverse primer included the sequence of the T7 promoter. All primers are listed in Supplementary table The former RiboZero was based on patent US 2011/0,040,081 A145.In contrast to the patent, we started with gDNA of the organism of choice instead of using reverse-transcribed rRNA, i.e., cDNA for final production of complementary rRNA probes. rRNA genes were amplified from gDNA in a PCR using Q5 High-Fidelity Polymerase  were used. The optimal amount of beads necessary for best removal of the biotinylated rRNA oligonucleotides was determined before (not shown). A volume of 225 µL magnetic beads (10 mg/mL) was found to give the best results when using 4 µg rRNA probes as follows. Beads were primed before use according to manufacturer and resuspended in 65 µL 2 × binding and wash buffer .All biotinylated complementary rRNA probes  were mixed in a total volume of 8 µL RNase-free water each with 2 µg absolute amount. In a volume of 40 µL, 2.5 µg total RNA isolated from the bacteria was mixed with 4 µL 10 × hybridization buffer  and 8 µL mixture of the biotinylated rRNA-probes. Denaturation and hybridization were performed by incubation at 68 °C for 10 min, following 5 min at RT. For removal of the captured rRNAs, 65 µL primed magnetic beads were added and the mixture (105 µL) was vortexed for 10 s. Biotin-streptavidin binding was conducted for 5 min at RT and 5 min at 50 °C. Next, the magnetic beads were pulled by using rare-earth magnets in a magnetic rack for 1 min. The supernatant, with the remaining rRNA-depleted RNA, was transferred into a fresh tube and an ethanol precipitation was performed as before.rRNA depletion was performed in triplicates of 2.5 µg total bacterial RNA for each kit tested. Depletion with the RiboZero Magnetic Kit for Bacteria , the RiboMinus Transcriptome Isolation Kit 1.0 , and MICROBExpress Kit  were performed according to each manual. rRNA depletion with the riboPOOLs kit was performed according to the protocol v1.3 in the approaches for qPCR, quantity measurement by NanoDrop and Bioanalyzer and protocol v1.5 (for RNAs sequencing). As suggested by the manufacturer, Dynabeads MyOne Strep C1 (Thermo Scientific) were used. For all kits, the depleted RNA was precipitated with ethanol and resolved in 20 µL RNase-free water as above.Depletion of rRNA was checked by the Agilent 2100 Bioanalyzer (Agilent Technologies) using the Agilent RNA 6000 Pico Kit according to the manual.cysG , were determined using dilutions of genomic DNA . The amount of remaining rRNA was determined using the ΔΔCt method47.Depletion of 5S and 16S rRNA was analysed by RT-qPCR (Supplementary table 48), which follows the procedure used by Hücker et al.49. Thus, 1 µg RNA is fragmented using a Covaris E220  in a Covaris-Tube (MicroTube AFA Fiber Pre-Slit –Snap-Cap 6 × 16 mm). After an ethanol precipitation, the RNA samples were resolved in 25 µL RNase-free water. Dephosphorylation was performed in 60 µl total volume by addition of 2.0 µL Antarctic Phosphatase (NEB), 2.7 µL 10 × Antarctic Phosphatase Buffer, 0.5 µL Superase·In (Invitrogen), and RNase-free water. Samples were incubated for 30 min at 37 °C and subsequently cleaned with the miRNeasy Mini Kit (Qiagen). The dephosphorylated RNA samples were dissolved in 30 µL RNase-free water. Phosphorylation was conducted by adding 3.6 µL T4-DNA-Ligase-Buffer (ThermoFisher), 2 µL T4 PNK (NEB), and 0.5 µL Superase·In and subsequent incubation for 1 h at 37 °C. The RNA was cleaned as before. Library preparation was performed according to the TrueSeq small RNA Kit (Illumina) manual. For size selection, polyacrylamide gels were prepared as follows. Per each gel, 4.2 mL MilliQ-water treated with DEPC, 2.475 mL Rothiphorese 30NF , 0.75 mL 10 × TBE, 75 µL 10% APS, and 4.5 µL TEMED were mixed and poured. Bands were cut after staining with SYBR Gold (Invitrogen) and comparison to a standard DNA ladder  at a size range of about 27 to 40 bp. Final libraries were checked using an Agilent Bioanalyzer High Sensitivity DNA Analysis. Sequencing was performed on a MiSeq (Illumina) using a v3 cartridge for 2 × 75 cycles paired-end.The RNA was fragmented, dephosphorylated and re-phosphorylated to obtain all fragments irrespective of their initial phosphorylation status . Bioinformatic analysis of the raw sequencing reads was performed with a pipeline seamlessly connecting FastQC, Fastp, Bowtie2, and FastQ-Screen53.The genomes files used for mapping were downloaded from NCBI , MICROBExpress (ME), and riboPOOLs (RP) were compared to the discontinued old-version RiboZero (RZ) and the self-made depletion using biotinylated antisense rRNA probes . Depletions were performed in triplicates using an aliquot of the same total RNA isolated from bit Fig. A. After In a second step, specific depletion of 16S and 23S rRNAs was investigated using electrophoretic analysis  and 5S rRNA (about 120 nt). Two such samples of total RNA are shown in Fig. Since not all kits target and deplete 5S rRNA, the remaining amount of 5S and 16S present in each sample was measured using qPCR. The result was calculated for each method used based on the 5S and 16S rRNA amount in the untreated sample Fig. H. The re27. However, RP and BP have not been tested with RNA-seq. Surprisingly, the number of reads that generally mapped to the genome increased after depletion. For instance, 27% of the reads from the untreated total RNA mapped to the genome, while 46% and 60% mapped when treated with BP and RP, respectively  was found. For the untreated total RNA about 5% mapped to genes, while about 13% of the reads mapped to genes for either treatment.Sequencing data and, thus, final efficiencies in rRNA removal are available for RZ, RM and ME Comparing the distribution of the different RNA reads mapping to the genome, we found an increase for reads mapping to genes  and an even higher increase in reads mapping to tRNA. Nevertheless, whilst about 64% of the reads are mapping to rRNA genes in the untreated sample, a massive reduction of those reads is seen after treatment, e.g., about 26% for RP and about 22% for BP map to rRNA genes. This reduction in rRNA-originating reads leads to a shift towards mRNA- and tRNA-originating reads, which are therefore increased in proportion  values for gene-coding regions (CDS) were 0.91 and 0.87 when comparing untreated RNA with the sample depleted with BP and RP, respectively Fig. –S2. The In contrast to the bulk of genes, comparing weakly expressed genes  in the untreated and treated sample shows a much lower correlation. For instance, the Pearson correlation of such weakly expressed genes comparing the untreated sample with RP and BP is 0.28 and 0.33, respectively. However, this is not unexpected since the detection of a single read more or less reflects a substantial percent change for genes with such low expression values. In any case, in the untreated sample, 1731 protein-coding genes with an RPKM at or below 10 were found. Interestingly, the fraction of genes with no observable expression  is higher in the untreated sample , but lower in the treated samples, e.g., 690 and 524 for RP and BP, respectively. Thus, depletion increases the number of genes displaying detectable expression at all. Furthermore, 113 and 251 genes formerly having an RPKM ≤ 10, are now above 10 RPKM when the total RNA was depleted with RP with BP. Taken together, a general shift of more observable reads per gene for the weakly expressed genes is visible after depletion  describes similar efficiencies for the depletion of rRNAs from Salmonella species as we found here for E. coli56. Also, Ciulla et al.23, comparing RZ, ME and three further depletion setups with other strategies, showed that RZ was superior in depletion of all rRNAs at that time. Petrova et al.26 compared RZ, ME and RM using total RNA obtained from a co-culture of Pseudomonas aeruginosa and Staphylococcus aureus26. Their results regarding depletion efficiency of rRNAs with RZ, RM and ME were confirmed by our data.The differences between the efficiency of rRNA depletion of different methods tested here seem to be caused by the characteristics of their specifications. Comparing results received by RT-qPCR and Bioanalyzer data, a clear ranking of depletion efficiency can be made with RP reaching comparable results as the former RZ. Our own biotinylated probes seem to be a little less efficient compared to RP or RZ, but all of the former are more efficient than RM or ME. One main reason for the differences observed might be that RP, RZ and BP target 5S, 16S and 23S rRNAs, whereas RM and ME targeted 16S and 23S rRNA only. Despite, RM and ME are also inferior in depleting the targeted 16S and 23S rRNAs. Perhaps, this is due to the short oligonucleotides used in both kits of just around 20 nt. Additionally, it is unclear if the complete sequence of the rRNAs is covered by those probes. Hence, small fragments of rRNA, which may appear due to degradation, might not be captured efficiently and remain in the samples. Further, the hybridisation efficiency of oligonucleotides is inferior compared to longer probes. For instance, the antisense oligonucleotides used in RP are 40 nt and presumably cover the full length of each rRNA species. This increased length in the probes results in better depletion, even if degradation of rRNAs occurs. The nucleotides used in RZ and in the BP method are full-length antisense molecules of the rRNAs and are RNA-based in contrast to the (c)DNA-based probes used in RM, RP, and ME. Additionally, RNA:RNA hybrids are more stable than RNA:DNA hybrids Our further investigations focused in BP and RP compared to untreated RNA. After comparing the relative mRNA reads from RNA-seq, differences between the untreated and the treated samples for both methods are observed. The varying numbers of gene-coding reads can be traced back either to varying degradation of some mRNAs during preparation or, more likely, to varying unspecific depletion of certain mRNA during the rRNA depletion. Nevertheless, our data shows a good correlation between treated and untreated samples and also an increasing amount of effective reads deriving from mRNA, especially from low expressed genes. For those genes, a shift to higher RPKM values is observed. Thus, the reduction of rRNA molecules increases their detection potential.Taken together, the self-made BP has a similar depletion efficiency compared to the former RZ Figs. , 3. In a57, but this is not commercialized yet. tRNA depletion would be a valuable target for depletion, since we found a high proportion of tRNAs present in the samples after depletion. Nevertheless, a possible disadvantage of the BP method is the somewhat lower stability of the RNA probes. In any case, also the RNA samples have to be treated with the same care in order not to degrade precious samples. Unfortunately, it was not possible to compare RNA-sequencing results of a RZ depleted probe concerning expression levels, since the former RZ kit is not available anymore. However, from our previous data (not shown) and experiments conducted here, we conclude a very similar overall performance.Finally, the BP-method can be customized to the target organism or target RNA. It might even be possible to derive antisense tRNA probes, which allow tRNA removal, as mentioned by Liu et al.54.If the user prefers a ready-to-use product, RP is a good alternative to the former RZ, with comparable efficiencies and modest bias in changing gene expression values due to the depletion procedure. The new version of RZ is enzyme based. It should be treated with some care, especially when comparing datasets derived from using the previous version with data from using the new version. It has been shown that enzyme-based kits lead to a larger bias, especially in Ribo-seq experiments All tested kits/methods are similar in price per reaction  recommend using hybridization and capture methods for rRNA depletion in RNA-seq or Ribo-seq experiments. The shift in RNA species composition increases clearly the amount of mRNA reads mapping and additionally, improves detectable expression for weakly expressed genes.Supplementary Information.


Epigallocatechin gallate (EGCG) is a major catechin found in green tea, and there is mounting evidence that EGCG is potentially useful for the treatment of coronavirus diseases, including coronavirus disease 2019 (COVID-19). Coronaviruses encode polyproteins that are cleaved by 3CL protease (the main protease) for maturation. Therefore, 3CL protease is regarded as the main target of antivirals against coronaviruses. EGCG is a major constituent of brewed green tea, and several studies have reported that EGCG inhibits the enzymatic activity of the coronavirus 3CL protease. Moreover, EGCG has been reported to regulate other potential targets, such as RNA-dependent RNA polymerase and the viral spike protein. Finally, recent studies have demonstrated that EGCG treatment interferes with the replication of coronavirus. In addition, the bioavailability of EGCG and future research prospects are discussed. The coronavirus disease 2019 (COVID-19) pandemic has impacted all aspects of society, leading to extensive investigations into remedies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus of COVID-19. As of 2021, vaccines for SARS-CoV-2 are available, but effective antiviral medicines for COVID-19 are not yet available. Since the vaccination speed is limited, additional years will be required to achieve complete herd immunity. Moreover, it is expected that novel coronavirus diseases will emerge in the future. Therefore, numerous antiviral medicines should be developed to treat or alleviate coronavirus diseases.There are four coronavirus subfamilies: alpha, beta, gamma and delta; and seven coronaviruses are known to infect human . SARS-CoGreen tea has been a popular beverage for millennia, and many reports have shown that drinking green tea has various health benefits, such as cancer prevention and treatment of infectious diseases ,5. EpigaRecently, one study examined the relationship between green tea consumption and overall COVID-19 risk, including morbidity and mortality . AlthougMany antiviral medicines have been developed to treat viral diseases, and virus-specific enzymes are major targets for drug development. For example, human immunodeficiency virus (HIV) encodes reverse transcriptase and protease, and inhibitors of these enzymes are well-known antiviral drugs for acquired immune deficiency syndrome (AIDS) . LikewisCoronavirus-specific proteases are candidate targets for viral drug development . CoronavEGCG is a major constituent of green tea, and EGCG treatment has been reported to inhibit various viruses . PreviouBecause 3CL protease is essential for coronavirus maturation, potential inhibitors of 3CL protease were sought to develop antivirals for coronavirus. Initially, SARS 3CL protease was used to screen the inhibitors using a 720-compound library, and tea components, including tannic acid and 3-isotheaflavin-3-gallate (TF2B), showed inhibitory effects against SARS 3CL protease . Several50) of EGCG for SARS 3CL protease ranged from 25 μM to greater than 100 μM, and the IC50 for SARS-CoV-2 3CL protease ranged from 0.847 μM to 16.5 μM, according to our results  is a popular target of antiviral medicines . PolypheThe SARS-CoV-2 spike glycoprotein is known to interact with the host cell angiotensin-converting enzyme 2 (ACE2) protein to initiate viral infection. Therefore, SARS-CoV-2 infection can be prevented by blocking the interaction between the viral spike protein and ACE2. Several structural studies have suggested that EGCG interacts with the SARS-CoV-2 spike proteins ,50. MoreFinally, immune modulation can be a target of EGCG in the treatment of coronavirus diseases. Patients with COVID-19 can develop acute pneumonia, which can lead to the onset of a cytokine storm resulting from the upregulation of pro-inflammatory cytokines . Since ESince EGCG treatment showed inhibitory effects on 3CL protease and ACE2 binding in vitro, EGCG was expected to inhibit coronavirus replication. However, the handling of SARS or SARS-CoV-2 requires a BSL-3/BSL-4 lab facility, and the use of these facilities is limited. For this reason, there are limited experimental infection data for SARS or SARS-CoV-2 to support the role of EGCG in coronavirus replication . 50 of EGCG for coronavirus replication was relatively lower than that for 3CL protease inhibition. Since the coronavirus polyprotein contains multiple cleavage sites for 3CL protease, partial inhibition of polyprotein cleavage by EGCG may contribute to the inhibition of coronavirus replication [Bovine coronavirus is a causative virus for diarrhea in cattle, and pretreatment with EGCG significantly decreases the propagation of bovine coronavirus in host cells . Incubatlication . The inhAlthough EGCG efficiently inhibits coronavirus 3CL protease and replication in vitro, it is unknown whether EGCG can reach an effective concentration in vivo. For this reason, we conducted a literature review of the known in vivo distributions of EGCG. Although the respiratory tract is the primary site for SARS-CoV-2 infection, recent data indicate that SARS-CoV-2 also infects the gastrointestinal tract . Moreove50 for 3CL protease inhibition [Since SARS-CoV-2 is detected in both the respiratory and gastrointestinal tracts, the distribution of EGCG in the lung, intestine, and colon is summarized in hibition ,66. In phibition ,66. SincSaliva is important for the respiratory transmission of coronavirus because coronavirus is transmitted primarily through respiratory droplets, which contain saliva . When on50 values) required to effectively inhibit 3CL protease [Here, we have reviewed recent research progress on the therapeutic potential of EGCG for treating coronavirus diseases. EGCG is an abundant tea polyphenol in brewed green tea, and many reports provide evidence that EGCG can efficiently block 3CL protease, an essential enzyme for coronavirus replication ,39. Moreprotease ,66. In aprotease . Likewisprotease . These rBecause most of the EGCG data were obtained from in vitro studies, animal experiments or clinical tests are required to confirm the effects of EGCG on coronavirus diseases. Since green tea comprises EGCG as the main constituent, its extract can be used in in vivo experiments. As the safety of green tea has long been verified, an adequate amount of green tea can be directly used in in vivo experiments without toxicity concerns. These experiments will determine whether EGCG or green tea is useful for the treatment of coronavirus diseases. In addition, an epidemiological study would be useful for examining the effects of EGCG or green tea on coronavirus diseases. Although preliminary statistical results are available, the results of epidemiological studies, such as the correlation between personal green tea consumption and the risk of developing coronavirus disease, can be evaluated to determine the effects of green tea on coronavirus . We expe


Long noncoding RNAs exceeding a length of 200 nucleotides play an important role in ensuring cell functions and proper organism development by interacting with cellular compounds such as miRNA, mRNA, DNA and proteins. However, there is an additional level of lncRNA regulation, called lncRNA epigenetics, in gene expression control. In this review, we describe the most common modified nucleosides found in lncRNA, 6-methyladenosine, 5-methylcytidine, pseudouridine and inosine. The biosynthetic pathways of these nucleosides modified by the writer, eraser and reader enzymes are important to understanding these processes. The characteristics of the individual methylases, pseudouridine synthases and adenine–inosine editing enzymes and the methods of lncRNA epigenetics for the detection of modified nucleosides, as well as the advantages and disadvantages of these methods, are discussed in detail. The final sections are devoted to the role of modifications in the most abundant lncRNAs and their functions in pathogenic processes. Although almost 80% of the human genome has been transcribed, only 2% of it (mRNA) codes proteins ,2. All o5C, m6A) are present in DNA .,27.5C, mGlu, deprived of the hypermodified nucleotide mcms2U34, is a poor substrate for GluRS, exhibiting a 100-fold reduction in its specificity constant (kcat/KM). The presence of the m6A modification in mRNA regulates several molecular processes, such as transcription, pre-mRNA splicing, mRNA export and stability, as well as translation [5C modifications affect mRNA stability [H. sapiens, 28S RNAs, 10 methylated nucleosides and 95 pseudouridines were found. They are distributed over important regions, including the decoding and tRNA binding sites , the peptidyl-transferase center and the intersubunit interface, facilitating efficient and accurate protein synthesis. Disturbances in tRNA and rRNA methylation processes alter cellular functions and the deregulation of these pathways can lead to complex diseases [Abundant noncoding RNAs, such as transfer RNAs, ribosomal RNAs and spliceosomal RNAs are modified and depend on the modifications for their biogenesis and function. tRNA is one of the most extensively modified RNAs with, on average, 13 modifications per molecule . It is wtability , mRNA cotability . The knotability . Moreovetability . In H. sdiseases ,40.In this review, we present the characteristics, detection methods and the role of the modified nucleotides present in long noncoding RNAs. We also discuss the influence of lncRNA modifications on the development of mammals and neoplastic processes. There are three groups of protein involved in modifying RNA metabolism ,28. The 6A) is one the most abundant RNA modifications, occurring in divergent members of the RNA family such as mRNA, rRNA, tRNA, snRNA and also lncRNA. It is usually present in several sites per transcript [6A modification is connected with the methylase complex (writer). Core MTase heterodimer complexes comprise of a methyl transferase such as 3 (METTL3) and a methyltransferase, such as 14 (METTL14) [6A modification levels [6A in RNA. RBM15/15B interacts with METTL3 in a WTAP-dependent manner and mediates the binding of the complex to specific RNA sites [6A in coding RNAs, METTL16 can methylate both coding and noncoding RNAs [6A writer, as well as the reader [6-methyl adenosine (manscript . In humaMETTL14) ,45,46,47METTL14) . AdditioMETTL14) ,50,51, KMETTL14) , the zinMETTL14) , the RNAMETTL14) ,54,55. Tn levels ,49,56. SNA sites ,57. ReceNA sites ,59,60,61ing RNAs . While te reader ,64.6A modification has two specific erasers, FTO and ALKBH5 [6A to N6-hydroxymethyladosine or N6-formyladenosine, which are chemically unstable and can hydrolyze to the final adenine product [Like DNA and histone modifications pathways, the md ALKBH5 ,65. FTO  product ,67,68. A product . Both de product ,71,72. F product , while A product . Whereas6A modification sites are recognized by “reader” proteins to generate functional signaling. The YT521-B homology (YTH) domain-containing protein family are the most predominant m6A readers and directly bind to the m6A-modified RNA bases. The human YTH domain containing protein family consists of five proteins, namely, YTHDF1–3 and YTHDC1–2, which are conserved in mammalian genomes [6A located in the 5′UTR region of mRNA and is involved in cap-independent translation [6A modification [6A switch”, which means m6A alters the local structure of mRNA or lncRNA, to facilitate the binding of HNRNPs for biological regulation [6A readers include the insulin-like growth factor 2 mRNA binding protein (IGF2BP) family, which was reported to regulate the stability of m6A methylated RNAs [m genomes . YTHDC1  genomes ,77,78. Y genomes ,80. More genomes ,81. The nslation ,83,84. Hfication ,86. Thisgulation . Other mted RNAs ,88,89.5C)5-methyl cytidine (m was found in both DNA and RNA. Two writer m5C methyltransferases (MTases) have been shown to catalyze the m5C modification of eukaryotic RNA. However, their substrate specificity and cellular functions are not completely understood [5C formation in mRNAs is mainly catalyzed by the NSUN2 type RNA methyltransferase [5C methylation promotes the export of mRNA from the nucleus to the cytoplasm in an ALYREF-dependent manner. The RNA binding protein, ALYREF is an m5C reader and is necessary for the nuclear export of m5C-modified mRNAs. Unlike m6A demethylases, it lacks an enzyme that specifically converts m5C to C. Recently, it has been proven that the ten-eleven translocation (TET 1–3) proteins, a family of 5-methylcytosine dioxygenases, catalyze the successive oxidation of m5C to the final product, 5-hydroxymethylcytosine (hm5C), and can therefore be classified as eraser proteins [derstood ,91. Morederstood ,93, wherderstood . The NSUderstood . In 2017nsferase . NSUN2-mproteins . The TETproteins . Moreoveproteins ,98. The proteins . HoweverPseudouridine (Ψ) is a ubiquitous modified nucleotide, mainly found in rRNA, tRNA and ncRNA [nd ncRNA . The estnd ncRNA . As a rend ncRNA ,102.Pseudouridine writers, called pseudouridine synthases (PUSs), recognize substrates and catalyze the isomerization of U to Ψ, without the need for cofactors B 42,100100,103. 6A modification, specific Ψ eraser or reader proteins have not yet been identified. This is due to the high stability of the C–C bond and the inability of the potential eraser proteins to cleave it, what is necessary for them to exchange Ψ for U. Furthermore, the lack of reader proteins that specifically bind to Ψ means it is difficult for proteins to identify the more subtle modification, which results in the C–N bond being replaced by a C–C bond, between uracil and ribose [6A and m5C, the reader and the eraser proteins have been identified [Alternatively, the RNA-independent pathway relies upon the direct recognition of targets by PUS complexes, often at conserved structural or sequence motifs ,110. In d ribose . In humad ribose ,110,111.entified ,27. It iInosine (I) differs from adenine in that it possesses a carbonyl group instead of an amino group at position 6 of the purine ring. This modification only occurs in the double-stranded regions of mRNA, tRNA, rRNA, and ncRNAs and is catalyzed by the writer protein, adenosine deaminase acting on RNA (ADAR). In vertebrates, a family of three ADAR proteins, ADAR1 p and DNA-32P(A/m6A)Cp, which migrate as 117/116 mers on denaturing gel. The labeled band is excised from the gel, digested with nuclease P1 into mononucleotides containing 5′ phosphate, and then the m6A modification status is determined by TLC [6A, m5C, Ψ, and possibly other unknown modified nucleotides, in several coding and noncoding RNAs. The method is laborious and with low throughput and it may be possible to substitute it with ultra-performance LC–MS methods (UPLC–MS) [The study of RNA modification started in 1957 when the first modified nucleoside, pseudouridine, was discovered in bulk yeast RNA, using paper chromatography . The firtography ,123. Usid by TLC . This meUPLC–MS) ,125.6A mapping strategies were based on the immunoprecipitation of modified RNA molecules, using m6A-specific antibodies coupled to the subsequent NGS sequencing. In the following procedures, m6A Seq and MeRIP-Seq, ncRNA is fragmented to a size of about 200 nucleotides and immunoprecipitated by a m6A specific antibody, attached to the magnetic beads. Then, the RNA separated with a magnet is subjected to a second round of m6A immunoprecipitation. The resulting RNA pool, which is highly enriched with m6A-containing RNAs, is used for library construction and NGS sequencing [6A detection technique, miCLIP [6A mark in the RNA chain and cross-linked using UV light, with a wavelength of 254 nm. miCLIP allows for a high-resolution detection of m6A in RNAs.The high-throughput mquencing ,126. Bot, miCLIP ,128,129,6A nucleotide in RNA, using an indirect approach, is difficult because few chemical reagents modify the methyl group. However, NOseq, a method for the detection of m6A in RNA after chemical deamination by nitrous acid, has recently been introduced [The detection of the mtroduced . Nitroustroduced .5C or Ψ in RNAs. Reverse transcription, which is utilized in the next step, enables the detection of the modification sites [5C modification sites in RNA, i.e., the bisulfite conversion of cytidine to uridine has been applied successfully to determine the presence of this modified nucleotide in DNA [5C modified cytosine is resistant to bisulfite cytosine deamination. Thus, simply comparing the NGS sequences of RNA molecules subjected to bisulfite treatment with those that remain untreated, should pinpoint the modification sites [5C libraries, which are ready for sequencing. A disadvantage in the detection of m5C present in RNA using bisulfite is that a large amount of RNA is initially required to compensate for the high losses caused by this reagent. Moreover, other modifications or double-stranded regions may be resistant to bisulfite treatment, especially under the milder reaction conditions required to maintain RNA integrity. Therefore, this method often requires additional confirmation with the aforementioned direct methods used for the detection of m6A modifications—MeRIP and miCLIP. They differ in the application of m5C-specific antibodies [The indirect approach, in which chemical compounds selectively react with the modified ribonucleotides, was also used during the detection of mon sites ,120. Thee in DNA . The meton sites ,134,135.tibodies .5C-methyltransferases (m5C-MTases), NSUN2 and NSUN4 [5C-MTases to form irreversible covalent bonds with target residues, the resulting stable enzyme–RNA complexes are suitable for immunoprecipitation and mapping. This is also the case with the AZA-seq methodology, in which the “suicide inhibitor” nucleotide analog of 5-azacytidine is incorporated into cellular RNA and “traps” m5C-MTases for pulldown and sequencing [An alternative approach, which has been termed the “suicide enzyme trap”, has been employed to characterize the substrates of the following mnd NSUN4 ,138. By quencing .Determining the Ψ sites in the RNA chain requires indirectly analyzing this modification using carbodiimide chemistry. The chemical typically used for this is 1-cyclohexyl-(2-morpholinoethyl) carbodiimide metho-p-toluene sulfonate (CMCT), which reacts with guanosine, uridine and pseudouridine nucleosides. However, in alkaline conditions (pH 10.4), only Ψ–CMCT adducts are stable ,141. TheRecently, Pan et al. developed a method that uses a CMC-Ψ-induced RT stop with an additional step of site-specific ligation, followed by PCR, to generate two unique PCR products, that correspond to the modified and unmodified uridine. The modification is visualized in the PCR products using gel electrophoresis .1 digestion [1 specifically cleaves RNA after guanosine or inosine but is inhibited by guanosine glyoxal/borate adducts. The cleavage of glyoxal-modified RNA creates RNA fragments that carry inosine at their termini, as an input for sequencing. A method similar to the direct approach, used to determine inosine modifications, called inosine chemical erasing (ICE), was developed. [The editing events are typically identified using the direct detection method, by comparing the cDNA sequences with the corresponding genomic DNA sequence . The ediigestion ,151. RNaveloped. ,153. ICEveloped. .5C modification in DNA and RNA and the m6A modification in DNA [NGS methods based on short-read sequencing have difficulty in determining the modification patterns of the entire transcript sequence. Recently, a direct modification detection method, called nanopore sequencing, has been developed ,156,157.n in DNA . The Epin in DNA ,155. Then in DNA . The gre6A, m5C, Ψ and I sequencing studies was performed, highlighted the total amount of modifications in lncRNA, as well as the number of individual lncRNAs, that contain the respective modified nucleotide. The results were as follows: m6A—(13357 modifications/12348 lncRNAs); m5C—(9965 modifications/1072 lncRNAs); Ψ—(162 modifications/150 lncRNAS); I—(11726 modifications/3374 lncRNAs) [cis acting or trans acting [cis acting lncRNAs recruit factors, either to the site of lncRNA transcription or to adjacent loci and involve lncRNA XIST and lncRNA H19 [ANRIL is included in cis and in trans gene regulation [It is estimated that human cells have over 50,000 lncRNA molecules coded in genes. Some of them contain introns and are spliced by the same machinery as pre-mRNAs . Many malncRNAs) ,162. ThelncRNAs) . lncRNAss acting . The ciscRNA H19 ,166. Tragulation .XIST gene and involved in X chromosome inactivation [6A sites in XIST repeat regions have been identified. Patil and colleagues have shown that m6A formation in XIST, as well as in cellular mRNAs, is mediated by RBM15 and RBM15B, which bind the m6A-methylation complex and recruit it to specific sites in RNA [6A methylation complex [XIST is a 17.5 kb capped, spliced and polyadenylated nucleotide transcript, transcribed from the tivation ,169. Duetivation . In humas in RNA . Additio complex . These dMany pathways contribute to the control of gene expression during development. Polycomb repressive complex (PRC2) and XIST are associated with gene repression in various developmental processes, such as X chromosome inactivation and genomic imprinting. 5C marks were also detected. The presence of m5C methylation in the XIST transcript prevents the binding of the PRC2 in vitro. In Xist lncRNA, the presence of pseudouridylation and A–I editing sites has been confirmed, however, their roles are unknown at this stage so far [PRC2 binds with high affinity to the 5′-end region of XIST called the repeat A-region . This fue so far ,171. 6A modification sites. Moreover, a modification of the m6A site in MALAT1 mediates the m6A switch, which allows for the HNRNPC (reader) protein to be bound to a U-rich tract in the strand opposite to the m6A modification site [6A modification regulates the binding of proteins to MALAT1 lncRNA. The recent analysis of MeRIP seq data revealed thousands of m6A switches, which are involved in alternative RNA splicing and abundance [6A modifications in MALAT1 are important to the metastatic capacity of esophageal cancer cells, both in vitro and in vivo [6A mark in MALAT1 by the YTHDC1 reader protein plays a critical role in maintaining the composition of nuclear speckles and their genomic binding sites. Interestingly, the phenotypes induced by MALAT1-m6A deficiency could be largely rescued both in vitro and in vivo, by artificially tethering YTHDC1 onto MALAT1. In addition, MALAT1 lncRNA is subject to post-transcriptional m5C modification; five m5C sites been found to regulate chromatin-related roles in other lncRNAs, such as HOTAIR and XIST [The metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) gene is located at chromosome 11q13 and encodes a 7.9 kb transcript. MALAT1 is a highly modified lncRNA, carrying multiple mion site . Thus, tbundance . The MALbundance ,63. This in vivo . They aland XIST . Althougand XIST ,170.HOX transcript antisense RNA (HOTAIR) lncRNA is a transcript of the antisense strand of the hoxC gene, which is spliced and polyadenylated [6A sites were identified, with a single site (A783) being consistently methylated. HOTAIR interacts with the nuclear m6A reader YTHDC1 at the methylated A783 and at additional sites [6A sites mediates high HOTAIR levels. Additionally, m6A-dependent YTHDC1–HOTAIR interactions are required for gene repression, independent of the expression level and chromatin recruitment. The previous results demonstrate that site-specific cytosine methylation occurs in lncRNA HOTAIR [enylated  Within Hal sites . LocalizA HOTAIR . The metA HOTAIR . It is t6A modifications [6A marks in its 3′-end region, which are required for the binding of let-7 miRNA. It has been proposed that the presence of m6A in lincRNA1281 can act as a m6A-switch for specific RNA binding proteins, which will eventually regulate their interaction with let-7 miRNA. However, the identity of such proteins has not yet been discovered. A similar mechanism has already been proposed for the binding of the HuR (ELAVL1) protein and miRNAs, to the mRNAs encoding developmental regulators in mESCs.Yang et al. identified the cytoplasmic long intergenic noncoding RNA 1281 (lincRNA 1281), whose function is regulated by mications . This liications . Notably6A levels in lncRNA H19. The RNA binding protein immunoprecipitation (RIP) assay showed that METTL3 and METTL14 can directly bind with lncRNA H19. The m5C modification in lncRNAH19 can increase its stability [5C-modified lncRNA H19 can be specifically bound by G3BP1, a well-known oncoprotein, which results in MYC accumulation. NSUN2 was shown to methylate lncRNA H19 and affect its stability. The Ras-GTPase-activating protein-binding protein 1 (G3BP1) was confirmed to bind methylated lncRNAH19, based on the presence of NSUN2. lncRNA H19 has two editing sites, and their presence increases the lncRNA stabilization energy by 3 kcal/mol [H19, an imprinted lncRNA with a size of 2.3 kb, plays an important role in embryonic development . The knotability . Furtherkcal/mol .sra1 gene, whose size ranges from 0.7 to 0.9 kb. It is a dual-function RNA, which acts as both an lncRNA and an mRNA [6A modifications in lncRNA SRA, of an unknown function [The human steroid receptor RNA activator (SRA) is a transcript of the  an mRNA . lncRNA  an mRNA . Currentfunction . In a sufunction ,181. As 6A, m5C and Ψ nucleosides [6A PVT1 lncRNA modification regulates epidermal stemness via its interaction with the MYC protein [6A methylation is an important regulator of this process. Moreover, the RNA m6A modification mediated by the METTL3/METTL14 complex (The human plasmacytoma variant translocation 1 (PVT1 lncRNA) is a large locus, which is longer than 30 kb and is located at 8q24.21. It serves an oncogenic role in a variety of malignant tumors, such as colorectal cancer . PVT1 lnleosides . Recentl protein . The sug complex A regulatInformation available in the literature suggests that lncRNA epigenetics play a role in gene regulation through various mechanisms. First, the modification of lncRNAs may change their structure and affect their interactions with proteins, like in the case of lncRNA. Second, the modification of lncRNAs could mediate transcription repression . Third,


Small double-strand RNA (dsRNA) molecules can activate endogenous genes via an RNA-based promoter targeting mechanism. RNA activation (RNAa) is an evolutionarily conserved mechanism present in diverse eukaryotic organisms ranging from nematodes to humans. Small activating RNAs (saRNAs) involved in RNAa have been successfully used to activate gene expression in cultured cells, and thereby this emergent technique might allow us to develop various biotechnological applications, without the need to synthesize hazardous construct systems harboring exogenous DNA sequences. Accordingly, this thematic issue aims to provide insights into how RNAa cellular machinery can be harnessed to activate gene expression leading to a more effective clinical treatment of various diseases. Small interfering RNAs (siRNAs) and microRNAs (miRNAs), key regulators of gene expression, are recognized as small double-stranded RNA (dsRNA) molecules ,2,3. TheIn this review, we present recent advances and challenges in the therapeutic applications of saRNAs.saRNA-mediated locus-specific gene activation has been studied in neural cells. Based on many studies, two models of locus-specific gene activation have been reported, promoter-targeted duplex RNA activating and natural antisense disruption, leading to changes in chromatin structure ,14,15,20Spinal muscular atrophy (SMA) is another example of a neuromuscular disorder . InsuffiWe believe that the next step for clinical translation of RNAa therapeutics for the treatment of various neurodegenerative and neurodevelopmental disorders is the development of novel drug delivery systems.RNAa-mediated locus-specific activation of gene transcription has been reported in cardiovascular cells ,38,39. IRecently, RNA-based therapeutics have gained more attention in cancer therapy due to their enormous potential to selectively target previously undruggable genes and gene expression modulators. Unlike RNAi, which mostly targets sense transcripts, RNAa, as an alternative and promising new therapeutic strategy, can activate gene expression in a natural manner by targeting antisense transcripts or promoter regions ,54,55,56saRNAs can exert their anticancer effects through induction of cell cycle arrest, cellular senescence, proliferation inhibition, apoptosis induction, metastasis suppression, and multidrug resistance reversal . AlthougIn the past few years, a steadily increasing number of clinical and preclinical studies have been performed, using various saRNA-based therapies for the treatment of a multitude of different diseases .Due to their potential involvement in human disorders, strong efforts have been undertaken to develop new therapeutic agents applying a RNAa strategy. For instance, two companies in the USA, RNAa Therapeutics and OPKO-CURNA, are investigating therapeutic approaches based on RNA activation. Of note, mipomersen, an oligonucleotide targeting apolipoprotein B, was approved by the FDA in January 2013, but received a negative opinion from a European Medicines Agency panel . RNA-actTo improve the medicinal properties and potential in vivo applications of saRNAs, two steps must be taken. First, novel nanoparticle-based drug delivery systems must be developed to increase the drug accumulation in the targeted tissue and also address the aforementioned challenges in the therapeutic application of saRNAs. To date, different delivery systems have been developed for the delivery of saRNAs. Recently, lipid-based nanoparticles (LNPs) have attracted worldwide attention. LNP-based delivery systems face serious limitations such as toxicity, low thermodynamic stability, poor efficiency of encapsulation, and leaking challenges . To overThe second step for the development of effective saRNA therapeutics relies on tailoring site-specific chemical modifications of saRNAs. For instance, blocking the 5′-OH of the passenger strand and modifications to the 2′ backbone  has been demonstrated to reduce its off-target potential and increase endonuclease resistance and serum stability, respectively ,58,100. RNAa-based drugs have gained great attention in the past few years owing to their high potential in treating various disorders. However, delivery challenges slow down the clinical translation of this new class of therapeutic agents. Enzymatic digestion, low cellular uptake, poor endosomal escape, off-target effects, and fast clearance from the bloodstream have necessitated optimization of not only the RNAa molecules but also of the delivery systems. Many non-viral delivery systems have been designed and developed for the delivery of RNAa-based therapeutic systems. Nanoparticle-based delivery systems have several advantages including high functionalization and targeting capacity and ease of large-scale development, which make them a promising delivery system for medical applications. For instance, several studies demonstrated that PEGylation of different materials such as PEI can enhance their circulation time and reduce hemolysis and serum opsonization. Chemical modifications of RNA molecules herald a new era in the development of these cutting-edge RNA-based therapeutics. However, these modifications might be limited due to the occurrence of severe side effects and functionality reduction, which are topics that urgently need to be addressed.Future applications of RNAa-based therapeutics will significantly advance due to the progress in the development of drug delivery vehicles, reduction of the off-targeting problem, and huge large-scale synthesis capacity that will be offered by pharmaceutical companies. The combinatorial strategy using RNAa with chemotherapeutic drugs also could be a new strong treatment modality for different types of diseases.


The widespread implementation of mass sequencing has revealed a diverse landscape of small RNAs derived from larger precursors. Whilst many of these are likely to be byproducts of degradation, there are nevertheless metabolically stable fragments derived from tRNAs, rRNAs, snoRNAs, and other non-coding RNA, with a number of examples of the production of such fragments being conserved across species. Coupled with specific interactions to RNA-binding proteins and a growing number of experimentally reported examples suggesting function, a case is emerging whereby the biological significance of small non-coding RNAs extends far beyond miRNAs and piRNAs. Related to this, a similarly complex picture is emerging of non-canonical roles for the non-coding precursors, such as for snoRNAs that are also implicated in such areas as the silencing of gene expression and the regulation of alternative splicing. This is in addition to a body of literature describing snoRNAs as an additional source of miRNA-like regulators. This review seeks to highlight emerging roles for such non-coding RNA, focusing specifically on “new” roles for snoRNAs and the small fragments derived from them. Since discovering the functions of structural non-coding RNAs (ncRNAs) such as rRNAs and tRNAs in the 1950s, it has been apparent that RNAs do not simply serve as intermediaries in the direction of protein production ,3,4,5. AGiven the plethora of transcripts and degradation products within cells, assigning function to products of RNA processing is not simple. However, there is a growing body of evidence to demonstrate functional significance of smaller RNAs that are derived from larger non-coding precursors, and it is clear that in many cases one cannot dismiss the potential for these small RNAs to regulate biological processes. tRNAs are one such example, considered for decades to only be responsible for facilitating the addition of amino acids to growing polypeptide chains, but now known to generate tRNA-derived fragments that perform essential gene regulatory functions such as gene silencing, epigenetic inheritance, and ribosome biogenesis ,22,23,24Small nucleolar RNAs (snoRNAs) were discovered in mammalian cells in 1960, where their localization suggested a possible link to ribosomal RNAs (rRNAs), another class of ncRNA discovered several decades prior ,29. It wSnoRNAs represent an ancient genetic lineage, present in both Archaryotes and Eukaryotes, which maintain an extraordinary degree of sequence conservation within the structural motifs by which snoRNAs are classified . The twoThe first class of snoRNA, C/D box snoRNAs, are characterized by the presence of two conserved sequence motifs, box C (RUGAUGA) and box D (CUGA), near the 5′ and 3′ termini, respectively ,34,37. TThe second class of snoRNA, H/ACA snoRNAs, are characterized by the presence of a 3′ (ACA) tail and two hairpin structures connected by a hinge region bearing a conserved (ANANNA) motif  ,34,39,44The third subfamily of snoRNAs, scaRNAs, are localized in sub-nuclear regions known as Cajal bodies on account of an additional Cajal body localization motif (UGAG) . scaRNAsAll three families of snoRNA not only fine-tune the ribosomes and spliceosomes by expanding the chemical repertoire of RNA to facilitate RNA–protein and RNA–RNA interactions but also protect the target RNAs from nucleolytic degradation ,39,47. WGAS5 and SNHG1, from which eleven and nine snoRNAs are respectively derived [Typically, snoRNAs are transcribed from introns, usually embedded in genes that code for proteins related to ribosome biogenesis and function, thus providing a mechanism that ensures that ribosomes and associated snoRNAs are present in the correct proportions ,55. Othe derived ,56,57  and other members of the RNA-induced silencing complex (RISC) of which the miRNA is the targeting component .The canonical miRNA biogenesis pathway has been established for some time, involving two enzymatic reactions catalyzed respectively within the nucleus and cytoplasm by the Drosha and Dicer enzymes, each functioning within multi-component protein complexes ,71. AddiThis is particularly apparent with the nucleus, where cell fractionation has revealed the presence of abundant mature, fully processed miRNAs  and the In close parallel to snoRNAs, for decades tRNAs also had a largely single and well-defined role—in this case, mediating the transport of amino acids during translation to the growing polypeptide chain . Also, iInterestingly, and of direct relevance to this review, next-generation sequencing has also revealed the generation of smaller tRNA-derived fragments (tRFs) . Though tRFs broadly fall into four classes, depending on their size and the region from which they are derived . tRF-1 mDifferent tRF sizes and termini suggest different processing mechanisms , whilst Further indicating tRF functionality was the observation that knockdown of tRF-Gly-GCC (tRF-GG) represses genes that are associated with the expression of endogenous retroviral element (ERVL) . AlthougAdditionally, there are literally hundreds of studies purporting that dysregulation of tRFs is related to cancers of various types ,109,110;GAS5, a host gene for multiple snoRNAs that influence apoptosis and the cell cycle [One of the first indications that snoRNAs could play important roles beyond those for which they are traditionally known came with the initial observation that the human snoRNA h5sn2 is downregulated in meningiomas compared with normal brain tissue . Thereafll cycle . Similarll cycle .Several studies have also ascribed roles for snoRNAs within other cancer-associated signaling pathways, such as PI3K/AKT, which plays a pivotal role in cell differentiation, proliferation, and survival . Though Cancer stem cells present challenges to the elimination of cancers on account of their capacity to self-renew, differentiate, and seed tumors . IncreasAs demonstrated by the examples above, the dysregulation of snoRNA expression is prevalent in various cancers . CoupledThough historically snoRNAs are known to facilitate psuedouridylation and methylation of rRNA and snRNA, emerging studies suggest that additional types of modifications, or different RNA targets for modification, also exist . For exaPost-transcriptional modification of tRNAs are also prevalent at the anticodon wobble position and at the position 3′ to the anticodon triplet that stabilizes the mRNA–tRNA interaction . The cytIn addition to non-coding RNAs, high-throughput sequencing of ligated RNAs also reveals interactions between snoRNAs and mRNAs, such as SNORD83B, an orphan snoRNA that stabilizes the levels of target mRNAs . Although the full mechanism remains uncharacterized, direct base pairing between the snoRNA and its target mRNAs is required .snoRNAs have also been implicated in regulating alternative splicing of mRNAs , such asIn addition to guiding a more diverse array of post-transcriptional modification or regulating alternative splicing, snoRNAs also participate in the 3′-processing of mRNAs. In an attempt to better understand poly(A) site selection, it was revealed that a subset of snoRNAs is associated with the mammalian 3′-end processing complex, with snoRNAs interacting with Fip1, a component of the cleavage and polyadenylation specificity factor (CPSF) . One of As is reported with tRNAs, high-throughput sequencing has revealed that snoRNAs are also processed to generate smaller fragments, of which at least a portion do not appear to be simple degradation products. The evidence to support this claim, other than a trickle of reports of functional effects of sdRNAs described later in this section, is that sdRNA expression is often conserved across species  and thatOn the whole, sdRNAs are classifiable into several categories based upon their origin and length: H/ACA box snoRNAs generate 20–24 nt sized fragments mainly derived from the 3′ end ,25, wherOne obvious possible function for sdRNAs is as a novel source of miRNAs, as was initially reported looking at small RNAs co-immunoprecipitating with AGO1 and AGO2 in human embryonic kidney 293 cells (HEK293) . One of SnoRNAs are also a reported source of piRNAs, a class of non-coding RNA 26–31 nt in size that associate with AGO-related PIWI proteins and that are involved in the degradation of transposon RNA and the epigenetic regulation of gene expression . In one The functionality of sdRNAs remains an unresolved question, though there are intriguing suggestions of functional roles. For example, SNORD115 was found to regulate the splicing of HTR2C  to produThe mechanism, or mechanisms, that generate smaller fragments from longer snoRNAs remain little understood; however, it has been demonstrated that at least some sno-RNA-derived miRNAs (such as that derived from ACA45) are DICER-dependent . AdditioIt has been reported that the production of sdRNAs increases during non-optimal or stress conditions, suggesting potential roles in stress regulation. Consistent with this, the sdRNAs produced under these conditions are associated with ribosomes, suggesting yet unidentified roles of sdRNAs in translation. This is an intriguing possibility given that translation typically decreases under stress conditions ,158. AgaIn addition to the DICER/DGCR8-associated pathways that one may expect for a small non-coding RNA, recent studies have also implicated the involvement of FUS (fused in sarcoma/translocated in liposarcoma) in the generation of sdRNAs ,162. FUSFor decades, the known functions of snoRNAs were limited to the post-transcriptional modification of RNAs associated with translation. However, previously unexpected roles for these molecules have been reported; the intricacies of which are still being discovered . In addiVarious studies suggest that the non-canonical functions of snoRNAs may be facilitated by the metabolically stable fragments they give rise to . Deep seThe interest in this emerging area of molecular biology is both in the nature of the “new” mechanisms that are regulated by snoRNAs and sdRNAs and in the breadth of genes that are subject to regulation. Are we looking at unexpected roles for a handful of snoRNAs regulating a few dozen genes, or does the work we discuss here represent the first insights into a new frontier for molecular discovery?At this stage, it is impossible to answer this question; however, there are several factors that at least suggest the possibility that non-canonical functions of snoRNAs could represent a larger tool of gene regulation than is currently appreciated. First, snoRNAs and sdRNAs are abundant, yet frequently overlooked in sequencing data where experimental and bioinformatic tools are poorly developed to either capture or analyze such RNAs. Second, snoRNAs are seemingly capable of multiple interactions, both in terms of the assembly of non-canonical snoRNPs and in their capacity to interact with target transcripts across imperfect binding interfaces. Coupled with the existence of several hundred orphan snRNAs , these lines of evidence are collectively suggestive of important non-canonical roles.This has ramifications both in increasing our understanding of molecular and gene regulatory pathways and in the application of non-invasive biomarkers, where snoRNA/sdRNA dysregulation has already been widely reported in cancer but is yet to factor into clinical decision making.


Cellular RNA levels typically fluctuate and are influenced by different transcription rates and RNA degradation rates. However, the understanding of the fundamental relationships between RNA abundance, environmental stimuli, RNA activities, and RNA age distributions is incomplete. Furthermore, the rates of RNA degradation and transcription are difficult to measure in transcriptomic experiments in living organisms, especially in studies involving humans. A model based on activity demands and RNA age was developed to explore the mechanisms of RNA level fluctuations. Using single-cell time-series gene expression experimental data, we assessed the transcription rates, RNA degradation rates, RNA life spans, RNA demand, accumulated transcription levels, and accumulated RNA degradation levels. This model could also predict RNA levels under simulation backgrounds, such as stimuli that induce regular oscillations in RNA abundance, stable RNA levels over time that result from long-term shortage of total RNA activity or from uncontrollable transcription, and relationships between RNA/protein levels and metabolic rates. This information contributes to existing knowledge. Detected cellular RNA levels usually fluctuate. The understanding of the fundamental relationships between RNA level fluctuations, the rates of RNA degradation and transcription, environmental stimuli, RNA activities, and RNA age distributions is incomplete. In the present research, we developed a model based on the demands of RNA (related to intrinsic and/or extrinsic information), RNA age , transcription, and RNA degradation to explain the mechanism underlying intracellular RNA level fluctuations. We also explored applicability of the model for analysing dynamic processes between interacting biomolecules, such as the relationship between RNA and protein level fluctuations. Using single-cell time-series gene expression experimental data, we assessed some biological parameters, such as transcription rates, RNA degradation rates, and RNA life spans. This model could also predict RNA levels under simulation backgrounds, such as stimuli that induce regular oscillations in RNA abundance, stable RNA levels over time that result from long-term shortage of total RNA activity or from uncontrollable transcription, and relationships between RNA/protein levels and metabolic rates. This information contributes to existing knowledge and provides a new perspective for future studies. Mechanisms underlying the maintenance of specific RNA levels in a given cell are a target of transcriptomics studies –3. DetecLittle is known about the relationship between the supply and demand of RNA. Excess or deficiency in RNA can be harmful –18. ReguRNAs are queued along the DNA template for production by RNA polymerase. The term “RNA age”, which specifies how long an RNA has existed since its initial transcription, was previously used in our study in a gene expression model ; later, Transcription and RNA degradation rates are key parameters that lead to fluctuations in RNA levels ,30. CellIn the present research, we developed a model based on the demands of RNA (related to intrinsic and/or extrinsic information), RNA age , pulse transcription, and RNA degradation to explain the mechanism underlying intracellular RNA level fluctuations. We also explored applicability of the model for analysing dynamic processes between interacting biomolecules, such as the relationship between RNA and protein level fluctuations. The aim of this study was to provide explanations for some transcriptomic phenomena and to provide a new perspective for future studies.2 and median absolute percentage error (MdAPE) of the model were a good fit for experimental values, thus, this model was reasonable to use to explore biological parameters contained in these experimental data. Transcription rates, RNA degradation rates, RNA demands, RNA life spans, accumulated transcription levels, and accumulated RNA degradation levels were calculated. Analysis of fluctuations in the levels of Saccharomyces cerevisiae HSP26 mRNA  A letter containing a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).Important additional instructions are given below your reviewer comments.Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.Thank you again for your submission. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.Sincerely,Quan ZouGuest EditorPLOS Computational BiologyIlya IoshikhesDeputy EditorPLOS Computational Biology***********************Please revise the manuscript carefully.Reviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: The authors developed a simulation model based on activity demands and RNA age to explore the mechanisms of RNA level fluctuations. The model used single-cell time series gene expression experimental data to determine the model parameters. The model was also able to predict RNA levels under simulation backgrounds, such as oscillation in RNA abundance, stable RNA levels and the relationship between RNA and protein levels and metabolic rates. The manuscript may benefit from the following revisions.1. The axes of the figures need to be labeled.2. How are the parameters for the two-unit model that’s used to explain the relationship between RNA and protein dynamics determined? Is there any difference with the exhaustive search method used for the RNA level model?3. Figure 7 needs more elaboration in the main text.Reviewer #2: In this study, the authors proposed a model to explain the mechanism underlying intracellular RNA level fluctuations. The overall framework of the model seems to be logical and up to the task. I would like to raise some general points regarding this manuscript:1. Are there any references to support the definition of the age of a biomolecule used in this study?2. Page 18, the formula of degradation coefficient s should be provided3. R scripts for plotting should also provide4. The Font in Figure 7 is too small to read. The authors are suggested to update this Figure5. A brief description of the relationship between cellular protein levels and mRNA abundance is necessary, although it is summarised in the reported data Reviewer #3: In this study, Xu et al. proposed a computational model with pre-defined parameters to explore the mechanisms of RNA fluctuation in living cells. The authors showed that the model fits well to the real experimental data and can explain RNA level fluctuations in response to different stimuli. Generally, the study provides some novel insights and looks interesting to me. However, I have the following concerns need to be addressed:- As my understanding, the authors fitted the parameters of their model using single-cell experimental data and showed that the parameters can predict values of the real experimental values well: “ R2 of each gene was over 0.9, indicating that the model predicted a good fit with these experimental values (line103-104)”. First, what’s the R2 here mean? The authors should make it clear to the reader how they evaluate the consistency. Second, it is not clear how they fit the parameters, usually one should fit the parameters in some data and see how it predict previous unseen data to show the performance. Here, I guess the parameters for different genes are different, so it is practical to leave some data points of certain gene out for cross-validation? If they just fit the parameters using all the data points and then predict the values, it’s not enough to make the statement “the model predicted a good fit with these experimental values”.- The authors show three examples representing regular, partially regular and irregular fluctuations, which is good. However, to show the robustness of a computational model, it needs to be tested on data set at large scale. Considering that it may be difficult to perform a systematic evaluation in the current study, the author can at least provide one more example for each category in addition to the current one example. I found the data used in the study are from very old publications, is there any newer single-cell data available in larger scale?- In line 490-493, the authors mentioned that “We used the data provided by these studies to verify the outputs of model simulations”. Yet, no details are provided about how they verify the outputs using the experimental data.- Some figures, for examples, figure 2a, 3a, 4a, are hard to understand according to the figure legends, is it an example or just a schematic plot? The meaning of x-axis and y-axis is unclear. Further explanations about these figures in the legend are required. Fonts in figure 7a are too small.- The writings of the manuscript seem unbalanced, I found the “Discussion” part interesting to read while the “Results” part very descriptive and boring. I would suggest that the authors put some of their own interpretations after describing the data in the “Results” instead of putting them in the “Discussion”.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Computational Biologydata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: Yes**********what does this mean?). If published, this will include your full peer review and any attached files.PLOS authors have the option to publish the peer review history of their article  computational code underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data or code —e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #3: YesFigure Files:https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, Data Requirements:http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example in PLOS Biology see here: Reproducibility:https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocolsTo enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at  8 Jun 2021Attachment2021-6-8-responses to the reviewers.docxSubmitted filename: Click here for additional data file. 17 Jun 2021Dear Dr. XU,We are pleased to inform you that your manuscript 'A model explaining mRNA level fluctuations based on activity demands and RNA age' has been provisionally accepted for publication in PLOS Computational Biology.Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Computational Biology. Best regards,Quan ZouGuest EditorPLOS Computational BiologyIlya IoshikhesDeputy EditorPLOS Computational Biology***********************************************************Reviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: By this revision, the authors have addressed the concerns raised in the review.Reviewer #2: The authors addressed my commentsReviewer #3: The authors have addressed all my concerns, and I think the manuscript is acceptable for publication.**********Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data or code —e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: NoneReviewer #2: YesReviewer #3: Yes**********what does this mean?). If published, this will include your full peer review and any attached files.PLOS authors have the option to publish the peer review history of their article  1223-442824 | ploscompbiol.org | @PLOSCompBiolPLOS Computational Biology | Carlyle House, Carlyle Road, Cambridge CB4 3DN | United Kingdom