Advances in high-throughput sequencing technologies have enabled extensive studies of freshwater biofilms and significant breakthroughs in biofilm meta-omics. To date, however, no standardized protocols have been developed for the effective isolation of RNA from freshwater benthic biofilms. In this study, we compared column-based kit RNA extraction with five RNAzol-based extractions, differentiated by various protocol modifications. The RNA products were then evaluated to determine their integrity, purity and yield and were subjected to meta-transcriptomic sequencing and analysis. Significant discrepancies in the relative abundance of active communities and structures of eukaryotic, bacterial, archaebacterial, and viral communities were observed as direct outcomes of the tested RNA extraction methods. The column isolation-based group was characterized by the highest relative abundance of Archaea and Eukaryota, while the organic isolation-based groups commonly had the highest relative abundances of Prokaryota (bacteria). Kit extraction methods provided the best outcomes in terms of high-quality RNA yield and integrity. However, these methods were deemed questionable for studies of active bacterial communities and may contribute a significant degree of bias to the interpretation of downstream meta-transcriptomic analyses. In freshwater environments, benthic biofilms can be considered “cities of microorganisms” that attach to abiotic surfaces and embed into extracellular polymeric substances. These freshwater biofilms have been identified as major sites of carbon and nutrient cycling  and are The study of biofilm community structures and their functional attributes require a proper nucleic acid extraction, regardless of the sequencing platform or molecular analysis method. Indeed, reliable high-quality total nucleic acid (RNA) extraction is a prerequisite for recovering messenger RNA (mRNA) for gene expression studies based on next-generation sequencing, quantitative reverse transcription polymerase chain reaction (qRT-PCR) or microarrays, as low-quality total RNA may strongly compromise the experimental results and waste time, labor, and resources . In esseIt is difficult to obtain high-quality total RNA from environmental biofilm samples, as these molecules are easily degraded by intracellular or extracellular RNases even before sampling and extraction. Accordingly, the ideal method of extracting high-quality total RNA from soil and sediment samples has been debated over the last three decades . ContamiAs indicated, the high-quality and high-yield extraction of total RNA from environmental biofilms is a highly important requisite to downstream applications. However, different extraction methods may introduce variability in the composition of recovered mRNA and subsequently yield a biased sequencing result. However, very few studies have compared the effects of different total RNA extraction methods on environmental biofilm samples, and their respective recovered mRNA in terms of subsequent gene expression profile obtained via meta-transcriptome sequencing. The total RNA extraction strategies applied in this study ranged from a standardized column-based kit isolation, to five organic-based extraction methods, generating a total of six extraction groups. Hence, the objectives of this study were to (1) examine the purity, yield and integrity of total RNA extracts following six different extraction procedures; (2) assess and compare the active microbiomes associated with benthic freshwater biofilms using recovered mRNA from previously extracted total RNA from each extraction procedures; (3) identify the functional profiles of the active microbiomes resulting outcomes from each extraction procedure, and (4) analyze and compare the differential gene expression profile outcomes from the six extraction procedures performed in this study.®  extraction with different pretreatment cell disruption steps, (iii) including no cell disruption (RNAzol only group), (iv) bead-beating, (v) lysozyme, and (vi) lysozyme + bead-beating. Since the organic isolation-based groups yielded RNA with relatively low purity after initial extraction, half of the non-column-based extracted RNA samples were subjected to an additional purification step using an RNA Concentrator-25TM kit . All total RNA extracts were assessed for purity, yield and integrity, and pooled for subsequent mRNA recovery prior to metatranscriptome sequencing and bioinformatics analysis.A schematic diagram of the study design is presented in g for 10 min. The supernatants were gently removed without disturbing the biofilm pellets. The same biofilm sample was then homogenized by up and down pipetting and subsequently 400-μl aliquots of this biofilm biomass suspension was then placed in separate Eppendorf tubes. The biofilm aliquots were then flash-frozen using liquid nitrogen and stored at −80°C. One aliquot of each independent repeat was freeze-dried to obtain a dry weight measurement. The procedure for freeze drying is described as follows: the biofilm aliquot in Eppendorf tube was covered with punctured parafilm to allow water evaporation. The biofilm aliquot was then placed in a lid-less 50 ml Falcon tube, which was also placed in the freeze-dryer’s sample holder flask. The freeze dryer was adjusted to temperatures below −30°C and pressure below 0.5 mbar. The biofilm sample was dried overnight and the final product was fully lyophilized. The benthic biofilm sampling metadata, including the ambient temperature, water temperature, water pH, sampling depth, and sampling time, are provided in Submerged pebbles covered with benthic biofilms were collected from the lily pond at the Main Building of The University of Hong Kong . In total, we conducted four independent sampling procedures on different dates Cf. . For eacTo obtain an overall understanding of the microbial communities structure and active microbiome profile, it is important to employ a multiphasic approach. Here, the identification of microbial community structures utilizing genomic DNA extraction and 16S rRNA sequencing approaches were employed. Genomic DNA (gDNA) isolation from the above-described benthic biofilms and the subsequent sequencing and analysis protocols were performed as recently described , with slFollowing a cleanup step comprising the truncation of barcode and primer sequences, the paired-end reads were merged using FLASH  to obtain, indicating the number of pooled RNA extracts): RNA from column-based kit extraction (n = 8);For each extraction method, eight replicates were generated from four independent extractions to yield a total of 48 extracted RNA samples. All RNA samples were analyzed using a BioDrop Touch Duo device (No. 80-3006-61) to determine the purity and yield. A Bioanalyzer RNA 6000 device was used to assess RNA integrity. However, given the resulting poor RNA yield observed for non-column-based RNA extraction strategies  employed in this study, an extra purification step using RNA Clean & Concentrator-25 kit  was performed on half of the non-column-based RNA extracts. Hence, RNA extracts for each extraction strategy were pooled and then further sent for library construction and metatranscriptomic sequencing and analysis (n = 4); RNA from beads beating extraction (n = 4); RNA from lysozyme extraction (n = 4); RNA from cell disruption extraction (n = 4); RNA from lysozyme + beads beating extractions (n = 4). For metatranscriptomics sequencing and analysis, there were no replicates for each extraction group as they have been all pooled prior to this step to obtain sufficient yield.RNA from RNAzol Only extraction  to (2.5) here below.The Quick-RNA Fecal/Soil Microbe Microprep kit  was used according to the kit protocol, which included a cell disruption step with 0.1- and 0.5- mm beads.The RNAzol protocol was followed based on manufacturer’s instructions. RNAzol acts as a chemical lysis reagent to disrupt the outer membranes of bacterial cells.The cells were first disrupted by two alternate cycles of 40 s vortexing and 20 s rest using 0.150 to 0.212 mm glass beads , followed by standard RNAzol extraction.A 60-μl volume of lysozyme (5 mg/ml)  was added to the liquid biofilm sample, together with 30 μl of NaCl-EDTA  as the activating buffer. The sample was then vortexed for 30 s, incubated in a 37°C water bath for 2 min, and vortexed for 30 s prior to standard RNAzol extraction.To set up this equipment, a pressure regulator  was connected to a nitrogen cylinder . This procedure comprised slow compression and fast depression . In the This method combined the approaches of lysozyme and bead-beating for cell disruption, followed by RNAzol extraction. All of the extracted RNA samples were stored at −80°C.260/OD280; OD260/OD230); (B) Qubit analysis  to determine the RNA yield; and (C) Agilent 2100 Bio-analyzer analysis (Agilent Technologies) to verify RNA integrity. The significance of the results was determined using analysis of variance (ANOVA) and SPSS Statistics software, version 24.0 .Total RNA samples were subjected to three quality control analyses prior to library construction: (A) NanoDrop analysis  to assess RNA purity . The final cDNA library preparation involved a multistep process that included purification, terminal repair, A-tailing, sequencing adapter ligation, size selection and PCR enrichment. For library QC, the library concentration was quantified using a Qubit 2.0 fluorometer and adjusted to 2 ng/μl. Next, the insert size was checked using an Agilent 2100 Bio-analyzer and quantified to a greater accuracy by quantitative PCR. The PCR products were subjected to standard quantification and purification procedures (Novogene Bioinformatics Technology). Finally, the libraries were sequenced on an Illumina HiSeq2500 platform to generate 250-bp paired-end reads. The Illumina 16S rRNA gene amplicon sequencing and metatranscriptome reads were deposited in the NCBI-Sequence Read Archive (SRA) under the following accession reference number (PRJNA594486).After the RNA sample quality assessment, the extracted total RNA was first subjected to ribosomal RNA removal using the Ribo-Zero rRNA Removal Kit . The mRNA was fragmented randomly before cDNA synthesis, which were achived using the NEBNext Ultran ≥ 10%). To further eliminating tRNA and rRNA, the remaining reads were subjected to BlastN with a minimum alignment bit score of 54, using a filtering database that comprised the complete rRNA loci and tRNA sequences of bacteria, archaea, and eukaryotes from the National Center for Biotechnology (NCBI) and SILVA databases  , as wellatabases . In totae-value ≤ 1e–5) using DIAMOND software (BlastP), while allowing for the acquisition of taxonomic ranks. According to a previous study, minimum bit score thresholds of 148, 110, and 74 can be used, respectively, for phylogenetic and functional assignments at the genus level (>80% confidence level), phylogenetic and functional assignments at the family level (>80% confidence level) and reliable function (COG) assignments (>95% confidence level)  . Phylum-e level) . The tope-value < 10–6 was used for the COG assignments. The KEGG functional annotation analysis was conducted using the KEGG Automatic Annotation Server  functional annotation analysis, homologous gene cluster analysis (eggNOG) and carbohydrate enzyme analysis (CAZy) were performed by mapping functionally annotated unigenes to different functional protein databases using BLAST software. As each mapping unigene yielded more than one outcome, BLAST Coverage Ratios (BCRs) of the reference and query genes were calculated to establish a BCR (Ref) and BCR (Que) > 40%, and these values were used to ensure biological significance. Once predicted, the unigenes were assigned to COGs  via blasn Server  and a biAn expectation-maximization (RSEM)  routine Quantitative metabolic mapping of the metatranscriptome profiles was performed by mapping the KEGG annotations of identified protein sequences into metabolic pathway maps, using the iPath v2 module . In thesThe data that support the findings of this study are available from the corresponding author upon reasonable request.First, the bacterial community profiles in freshwater benthic biofilms were assessed to provide a reference for this study. Biofilm DNA was subjected to an amplicon-based sequencing approach that targeted the 16S rRNA V3-V4 region. The generated 16S metagenomics sequence data from the sampled benthic biofilms contained 98,675 raw tags, 97,233 clean tags and 92,460 effective tags , with an average read length of 250 nucleotides . Cyanobap < 0.05, one-way ANOVA), as well as a non-significantly higher purity level and yield. Obtained values of RNA purity , yield (μg/g dry sample) and integrity values from column-based extractions were 2.07 ± 0.03, 2.13 ± 0.36, 298 ± 136, and 5.63 ± 0.48 , yield (μg/g dry sample) were found at 1.62 ± 0.04, 0.83 ± 0.11, and 302.15 ± 106.43, respectively , yield (μg/g dry sample) and integrity values for the chemically based extractions following a purification step averaged at 1.92 ± 0.13, 1.54 ± 0.31, 205.16 ± 110.28, and 2.63 ± 0.11, respectively , except for the lysozyme- and the RNAzol only groups , RNAzol only (R), bead-beating (B), lysozyme (L), pressure bomb (P), and lysozyme + beads (LB) RNA extraction strategies, respectively. In all of the treated samples, the active microbiome generally comprised bacteria, viruses, eukaryotic microbes and archaea . NotablyAt the phylum level, Proteobacteria, Cyanobacteria, Actinobacteria, Verrucomicrobia, Bacteroidetes, Actinobacteria, Planctomycetes, Firmicutes, and Nitrospirae were most abundant in the combined column- and organic isolation-based groups , followeA further comparison of inter-sample differences in the dominant 35 phyla  revealedTo further our understanding of the effects of RNA extraction methods on the ability to investigate microbial metabolism in biofilm samples, the obtained transcripts were compared with the EggNOG , KEGG F and CAZyAll of the tested samples included genes involved in energy production and conversion, post-translational modification, amino acid and energy metabolism, translation, signal transduction, cell wall/membrane/envelope biogenesis, inorganic ion transport, and metabolism . A compaA comparison of the other RNA extraction methods and their impacts on functional gene annotation revealed that the samples subjected to mechanical lysis (namely bead-beating or pressure bomb) were clustered together and had similar functional gene annotation profiles. These samples were characterized by a generally lower relative abundance of annotated gene functions relative to the other samples. The samples subjected to pressure bomb lysis method contained the highest relative abundance of genes with unknown function. The samples subjected to lysozyme or lysozyme + bead extraction had similar annotated gene function profiles and were clustered together. The samples subjected to RNA extraction with RNAzol alone exhibited a distinct functional annotation pattern, with the highest relative abundance of genes associated with extracellular structures; intracellular trafficking; amino acid transport and metabolism, defense mechanisms, secondary metabolites biosynthesis, transport and catabolism; and coenzyme transport and metabolism.Most of the genes represented in the KEGG pathway analysis were associated with metabolic pathways . In partOverall, the highest relative abundances were observed for genes encoding carbohydrate-binding modules (CBM), glycoside hydrolases (GH), and glycosyltransferases (GT) . HoweverFor the differential gene expression analysis, the relative unigene expression levels were calculated as FPKM. Here, genes differentially expressed between libraries were identified using the criteria of a corrected padj < 0.05 and log2 fold change  ≥ 1. Differential gene cluster analysis was used to determine the patterns that emerged under different experimental conditions. Each challenge–control combination produced a differential gene set, and the FPKM values of all the combined differential gene sets in each experimental group/sample were included in the cluster analysis.p value of < 0.05) were detected by comparing the gene expression levels in samples subjected to different RNA extraction strategies  to prevent RNA degradation. To date, no standard sampling and processing methods for environmental biofilms have been developed. RNA degradation can be avoided by immediately subjecting environmental biofilm samples to extraction or by shock-freezing samples for storage at −80°C until extraction is possible. Raw biofilm samples can also be stored in DNA/RNA shield  or treated with RNAlaterStaphylococcus aureus. In that study, gel electrophoresis revealed clear differences in the integrity of the extracted RNA. Although that study investigated only a single-species biofilm, the authors similarly concluded that the choice of RNA extraction method affected the RNA integrity . Thus, it is recommended to apply some RNA preservative agents during sample collection.The significant difference in the active microbiomes between the column- and organic-based isolation was foreseeable, implied by the huge difference observed in RNA integrity levels between the two major procedures. Considering the unqualified RIN performance observed in both column isolation-based group and chemical isolation-based groups in this study, future studies should optimize the sample collection and storage method prior to RNA extraction to be able to yield RNA with acceptable integrity levels that can be proceed with downstream sequencing and analysis. More specifically, it is advisable to use RNA preservatives. It has been shown that compared to the samples without preservative substances, the use of preservatives significantly increased RIN from 2.7 to 8.7 . HoweverMost importantly, the lysozyme + beads group demonstrated the best outcomes showing highest relative abundance of Bacteria among all groups, suggesting that a combination of chemical, mechanical and enzymatic lysis procedure had the best performance in breaking down bacteria cell walls and released most abundant bacteria cells. Considering that the bacterial cell walls are significantly thick in Gram-positive bacteria as it is mainly composed of peptidoglycan , insuffi293 human cells (Qiagen RNeasy kit and guanidinium-phenol (TRIzol) extraction) and two library selection schemes (poly-A enrichment and rRNA depletion) on downstream transcript abundance estimates, and found that rRNA depletion was particularly sensitive to the RNA extraction method  can be found below: National Center for Biotechnology Information (NCBI), YY collected the data. YY and OH conceived the conception or design of the work. YY and OH drafted the manuscript. YY, SR, and OH revised the manuscript. All authors analyzed and interpreted the data.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 results showed that there was no significant difference in signal counts of the RNA Pol II CTD (S5) between the different types of fish at the same stages, including RCC, CC, 2nF1, and 4nAT, which means that the number of transcriptionally active sites on germ cell chromosomes was not affected by the increase in chromosome number. Similarly, RNA-seq analysis indicated that in the levels of chromosomes and 10-kb regions in the genome, there were no significant changes in the highly active sites in RCC, 2nF1, and 4nAT. These findings suggest that at the beginning of tetraploid origin, the active transcriptome site of 4nAT in the testis was conserved in the regions of the genome compared to that in RCC and 2nF1. In conclusion, 4nAT shared a similar gene expression model in the regions of the genome with RCC and 2nF1 with significantly different expression levels.Polyploidy occurs naturally in fish; however, the appearance of these species is an occasional and gradual process, which makes it difficult to trace the changes in phenotypes, genotypes, and regulation of gene expression. The allotetraploid hybrids (4nAT) of red crucian carp  × common carp  generated from interspecies crossing are a good model to investigate the initial changes after allopolyploidization. In the present study, we focused on the changes in the active sites of the testicular transcriptome of the allotetraploid by localization of RNA Pol II CTD YSPTSPS (phospho S5) using immunofluorescence and RNA-seq data  Populus hybrids, changes in the expression of E3 ubiquitin ligase BIG BROTHER and growth-regulating factor were associated with organ size and leaf growth in allopolyploids  × common carp ♂ , numerous chimeric genes and mutations were found, suggesting genomic incompatibilities that participate in the regulation of transcriptional changes  was obtained by artificial fertilization. Subsequently, the continuous artificial fertilization of the hybrids could produce allotetraploid  (DNA-directed RNA polymerase polypeptide A (POLR2A) is the largest catalytic subunit of RNA polymerase II (RNAP II) and contains a carboxy terminal domain (CTD) composed of 52 heptapetide repeats of Tyr1–Ser2–Pro3–Thr4–Ser5–Pro6–Ser7, which is essential for polymerase activity . CTD phoed 4nAT) . Thus, ted 4nAT) .In the present study, we used allodiploids as a diploid hybrid control to discuss the profile of global genomic transcriptional activities in allotetraploids. RNA Pol II CTD (S5) activities at the chromosome level were detected by immunofluorescence, and the staining signals were calculated for allodiploid and allotetraploid. The activated transcription sites in the genome were identified using transcriptomic data from the testes of allodiploid and allotetraploid. These results provide new insights for understanding the changes in transcriptional activity under allopolyploidization.1, and 4nAT aged 1 year were collected from the State Key Laboratory of Developmental Biology of Freshwater Fish . After euthanizing with buffered tricaine methanesulfonate (MS-222), one part of the testes from the fish was collected for testicular section preparation, and the other parts were excised for preparation of gonadal cell chromosomes. The experimenters were certified under a professional training course for laboratory animal practitioners from the Institute of Experimental Animals, Hunan, China. All experiments were approved by the Institutional Animal Care and Use Committee of Hunan Normal University .Male RCC, CC 2nFThe kidney and testis tissues were used to detect RNA Pol II CTD (S5) activities at the chromosome level. After adaption for 3 days, the fish were injected with concanavalin (10 μg/g body weight). Two hours post injection with colchicine (5 μg/g body weight), the kidney tissues were collected and treated with 0.075 M KCl for 60 min at room temperature. Then, the tissues were fixed with 3:1 methanol–acetic acid and dropped to precooling sections following staining with 4% Giemsa for 60 min. The separated chromosomes were blocked using 5% goat serum for 30 min at room temperature and incubated with polyclonal antibody against RNA Pol II CTD  after washing three times with phosphate-buffered saline (PBS). The signals were then detected using an Alexa Fluor 488-conjugated goat anti-rabbit IgG antibody , and 4′,6-diamidino-2-phenylindole (DAPI) was used to stain the chromosomes. The chromosomes and positive signals were analyzed using a Leica inverted DMIRE2 microscope image system , and images were captured using CW4000 FISH software (Leica).The testis samples were first fixed using Bouin’s fixating solution for 24 h and then dehydrated using graded ethanol solutions . Subsequently, the tissues were treated twice with xylene and embedded in paraffin. The 6-μm-thick tissues were prepared for the sections and stained with hematoxylin and eosin.For immunohistochemistry, the paraffin sections were dewaxed with xylene and rehydrated using graded ethanol solutions . Antigen retrieval was performed using citrate buffer  and treated with 10% hydrogen peroxidase in methanol. The sections were then blocked using 5% goat serum for 30 min at room temperature, followed by incubation with polyclonal antibody against RNA Pol II CTD  at 4°C overnight. After washing three times with PBS, the sections were incubated with sheep anti-rabbit/rat secondary antibody–horseradish peroxidase  and stained with diaminobenzidine.1, and 4nAT were used, and the testes were collected following total RNA isolation using TRIzol Reagent  according to the instructions of the manufacturer. Total RNA was analyzed on a 1.2% agarose gel, and a NanoDrop 2000 spectrophotometer  was used to evaluate the quality and concentration. In addition, the RNA integrity number (RIN) value from the Agilent 2100 Bioanalyzer  was used to determine the quality. Only samples with RIN > 8 were used for the following experiments. The sequenced cDNA libraries were constructed using TruSeqTM RNA Sample Prep Kit  and sequenced on an Illumina HiSeq 6000 platform. All data were deposited in the Sequence Read Archive (SRA) database under the accession numbers SRR14463341, SRR14463346, and SRR1573262.Transcriptomic activities were determined using RNA-seq data. Briefly, three mature individuals from RCC, 2nF1 while the clean reads of testes from 2nF1 and 4nAT were mapped to the genomes of RCC and CC2 using hierarchical indexing for spliced alignment of transcripts (HISAT) ] were filtered, and low-quality reads  were removed. The genomes of RCC and CC were used to examine transcriptomic activities at the chromosome level. The clean reads of testes from RCC were mapped to the genome of RCC, (HISAT) . The regAll data are presented as the mean ± standard deviation. One-way analysis of variance followed by Tukey’s test was used to compare the means between different fishes. All statistical analyses were performed using SPSS .The RNA Pol II CTD (S5) localization in the nucleus of somatic cells at different cell cycle stages of RCC was analyzed by immunofluorescence. When mitotic chromosomes agglutinated, the signals and chromosomes did not colocalize and spread throughout the nucleus, with 38–76 signals . At the 1, and 4nAT following the meiotic process. Immunofluorescence analysis confirmed that RNA Pol II CTD (S5) was expressed in the nuclei of spermatocytes at different stages, with the positive signals varying in number. Small RNA Pol II CTD (S5) agglomerates and accumulations were detected during the prophase of meiosis I, and the number of signals decreased during the meiotic process and completely disappeared in sperm. There was no significant difference in the different types of fish during the division cycle of meiosis, with similar numbers of signals in the same stages. In all four species, 20–40 signals were present in the cells at the prophase of meiosis I  could be detected in the spermatocytes of RCC, CC, 2nFeiosis I , 2–5 sigeiosis I , and 8–1eiosis I . In the Statistical analysis showed that in interphase cells from kidney tissue in RCC, the highest number of RNA Pol II CTD (S5) signals was found compared to other types of cells. The number of RNA Pol II CTD (S5) signals in the dividing cells was significantly lower. Along with the development of germ cells, the signal counts decreased in the following order: prophase I, metaphase I, spermatids, and sperm. Statistics of the signal numbers in somatic and germ cells of all species are shown in 1 was arrested during meiosis, which was accompanied by a large number of primary spermatocytes with meiotic disorders, and stained positive. Meanwhile, the testis of 2nF1 had some spermatogonia that stained positive, and its early primary spermatocytes and apoptotic cells were negative  was specifically expressed in the spermatogonia and some spermatocytes, conferring the different species with different positive antibody characteristics as they were in different developmental states. In testes from 1-year-old RCC, there were a large number of spermatids and sperm, and only several spermatocytes at the early prophase stage were positive . The devnegative . The 1-ynegative .1 and 4nAT, the fishes contained subgenomes, including the RCC and CC genomes. Clean reads were mapped to the two genomes. In hybrid 2nF1, the clean reads were mapped to 37,318 genes from RCC and 23,372 genes from CC  was highly expressed in spermatogonia and some early primary spermatocytes of 4nAT, and in spermatogonia and some primary spermatocytes of 2nF1. This means that all experimental fish basically followed the regulation of cellular transcription activity expression according to the developmental program of germ cells; that is, the expression of RNA Pol II CTD (S5) was high in the interphase stage, low in the mitotic stage, and not expressed in sperm. Based on these results, we can also conclude that the RNA Pol II CTD (S5) protein expression in fish testes was conserved despite fish ploidy or fertility. Although it is expressed in some primary spermatocytes in 2nF1, it is only expressed in spermatocytes with meiotic disorders, with the early primary spermatocytes being negative. These results imply the abnormal development of germ cells in 2nF1 and require further investigation. Therefore, RNA Pol II CTD (S5) protein is a good marker for distinguishing the developmental status of germ cells  proteins showed sites with high transcriptional activities, such as dot-like signals in the nuclei of mammalian cells. The RNA Pol II CTD (S5) signals have been visualized in cription . In thiscription . Similar1 and 4nAT. Chr3 and Chr30 from RCC were among the top three chromosomes in 2nF1 and 4nAT, suggesting that the transcriptional activities did not change significantly even when the chromosome doubled. In the 10-kb region, the highest expression regions were similar among the three fishes. For example, the site Chr20:24810001-24820001 from RCC chromosomes had the highest expression levels in the three fishes. Similar to other animals, gene expression is regulated from transcriptional initiation to RNA processing  signals in the testes, the sites of active transcription were determined using RNA-seq data. At the chromosome level, the highest expression was observed in similar chromosomes and regions between 2nFocessing . During gulation . Cis-regcription . In hybrcription . A previcription . The preme shock . Hybridime shock . This mame shock .Taken together, the results of the present study present the comparison of transcriptional activities at the genomic level in diploid and tetraploid fishes. It was indicated that allotetraploids and diploids had no significant changes in transcriptional activities by RNA Pol II CTD (S5) signal determination and analysis of RNA-seq data from the testes. Based on the results, a comparative analysis of allotetraploid fish was performed globally, which provides new insight for future investigation at the molecular level on the mechanisms of genome duplication and polyploidization in fishes.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The animal study was reviewed and approved by the fish were treated humanely following the regulations of the Administration of Affairs Concerning Experimental Animals for the Science and Technology Bureau of China.CZ and SL designed the study and carried out the analyses. YZ, LZu, YS, HZ, WH, and QL performed the technical process. CZ, YZ, LZu, and LZo prepared and drafted the manuscript. RZ, KL, and CT involved in material preparation. All authors have read and approved the final manuscript.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.


In addition, we will also provide an overview for the cellular functions of other RNA modifications, including m5C and m1A. Furthermore, we will also discuss the roles of RNA modifications within the context of disease etiologies and highlight recent advances in the development of therapeutics that target RNA modifications. Elucidating these context-specific functions will increase our understanding of how these modifications become dysregulated during disease pathogenesis and may provide new opportunities for improving disease prevention and therapy by targeting these pathways.Chemical modifications of RNA molecules regulate both RNA metabolism and fate. The deposition and function of these modifications are mediated by the actions of writer, reader, and eraser proteins. At the cellular level, RNA modifications regulate several cellular processes including cell death, proliferation, senescence, differentiation, migration, metabolism, autophagy, the DNA damage response, and liquid-liquid phase separation. Emerging evidence demonstrates that RNA modifications play active roles in the physiology and etiology of multiple diseases due to their pervasive roles in cellular functions. Here, we will summarize recent advances in the regulatory and functional role of RNA modifications in these cellular functions, emphasizing the context-specific roles of RNA modifications in mammalian systems. As m Accordis (CGCs) . Increass (CGCs) .Mettl3 resulted in increased expression of pro-apoptotic proteins in several cancer cell lines, emphasizing that METTL3 can function as a negative regulator of apoptosis  signaling pathway, which prostate cancer cells are dependent on for survival , resulting in the induction of ER stress and apoptosis in cardiomyocyte cells  of Gata3, a tumor suppressor, resulting in decreased GATA3 expression and promoted resistance to apoptosis  cells had no effect on the apoptosis rate; rather, knockdown of Fto resulted in increased apoptosis in hGCs , an oncometabolite produced by mutant IDH1/2 enzymes . Fto depmulation . Decrease arrest . The trepoptosis . In breaanscript . In meland Sox10 . Demethyng genes .6A readers in mediating cell death. One study found that YTHDF2 negatively regulates apoptosis in TNBC  that has been found to promote proliferation , WTAP promoted the mRNA stability of Cdk2, a regulator of cell cycle control over the G1/S and S/G2 transition, by directly binding to the Cdk2 transcript at the 3′-UTR  and increased NSCLC proliferation  in vivo . Mechaniechanism . Furthert manner .6A eraser FTO is well-studied within the context of cancer. In leukemia, FTO promoted the proliferation of AML cells by reducing m6A levels at the 3′-UTR of Asb2 and 3′ and 5′-UTR of Rara, two mediators of hematopoiesis and differentiation, resulting in decreased ASB2 and RARA protein expression , which led to decreased expression of YTHDF2 . Decreasd Map4k4 . Activatd Map4k4 .6A machinery in cell fate decisions. Future studies should be centered on understanding the dynamic nature of m6A in initiating cellular senescence and quiescence, as well as the changes in m6A that are needed for the cell to re-enter the cell cycle. Elucidating the roles of m6A machinery in cell fate decisions has broad-standing implications in understanding stem cell biology, cancer stem cell formation and maintenance, and cell cycle control.A current gap in knowledge in this field revolves around our understanding of the m6A in differentiation. Outside of hematopoiesis, m6A has been found to be a critical regulator in stem cell fate, neuronal development, and skin development. The role of m6A in development and stem cell biology is reviewed extensively elsewhere , which mediates early-stage hematopoietic stem and progenitor cell (HSPC) differentiation  accumulation in the bone marrow, suggesting that HSC differentiation was unable to progress without METTL3 or m6A  resulted in increased aNSC proliferation and differentiation through aberrant activation of the STAT3 pathway, resulting in inhibited neurogenesis and dysregulated neuronal development  showed increased adipogenic differentiation -promoting transcription factor Sox4  of EMT-associated transcription factor Snail, resulting in YTHDF1-mediated increases in SNAIL translation and EMT progression  mRNA resulted in increased MTCH2 protein expression, resulting in increased adipogenesis in longissimus dorsi muscle cells taken from both lean Landrace-breed pigs and obese Jinhua-breed pigs  is an active area of study. The role of m6A in modulating these pathways will add new insights into the DDR machinery.Elucidating the communication between m6A and DNA Pol κ were rapidly recruited to sites of DNA damage (Mettl3 in HeLa and U2OS cells exposed to UV radiation resulted in decreased cyclobutene pyrimidine dimer (CPD) removal, a major UV damage product,  cells also resulted in decreased CPD removal upon UVB irradiation  pathway, as treatment with an inhibitor of SUV40H1/H2, which are NHEJ-specific enzymes, had no effect on m6A recruitment , which were induced by X-ray radiation or Zeocin treatment, a chemical that induces DSBs, METTL3 was activated and phosphorylated at S43 by the key DDR kinase ATM, which then localized to DNA damage sites . At thesA hybrid . Accordi process . YTHDC1  hybrids . The DNA hybrids .6A-dependent manner was not explored  (In addition to mdiation) . Howeverdiation) .2O2 treatment, the m6A eraser FTO increased the mRNA stability of DNA repair pathway genes, including Hspa1a (Hsp70), in osteoblasts  involves the formation of biological condensates containing aggregates of proteins or nucleic acids within the cell . BiophysYthdf1 or Ythdf3 prevented stress granule (SG) formation , which are believed to be necessary for YTHDC1’s role in LLPS . In MEF,densates . AdditioML cells . In thisML cells . Further complex . The rol complex .6A is critical for LLPS and stress granule formation remains controversial. One study found that m6A on mRNAs promoted YTHDF1-3 partitioning into phase-separated structures  model in neurons found that m5C-methylated sites were increased upon OGD/R  in U87 glioma cells in an m5C-dependent manner  levels  levels . Furthernslation . Additioycolysis . Taken tlic fate .Chen et al. found that m5C was localized to DSBs upon ROS-induced DNA damage, and is present at DNA-damage-induced DNA-RNA hybrids  can function as an m1A 28S rRNA methyltransferase, and that inhibition of NML results in decreased proliferation  for METTL3 using a high throughput drug screen  (5C regulation (5C or other mechanisms (mget YBX1 . Shibata (pYBX1) . Increas (pYBX1) . TAS0612 (pYBX1) . Everoli (pYBX1) . Accordi (pYBX1) . Howevergulation . Azacytigulation . Howevergulation . Howeverchanisms .Wang et al. recently identified thiram as a potential candidate compound that selectively inhibits m1A writer complex TRMT6/TRMT61A (in vitro, and decreased tumor growth in vivo (/TRMT61A . Thiram  in vivo . However in vivo .Compound HUHS015 has been identified as an ALKBH3 inhibitor . As prevWhile the roles of RNA modifications have been extensively studied for several cellular functions, there remain several areas of interest that are not well-established and require further examination.Two areas of interest that remain open areas of research include evaluating the roles of RNA modifications in mediating specialized forms of cell death and within LLPS. In the area of cellular death, the role of RNA modifications has been well-studied in terms of apoptosis. However, emerging evidence suggests that RNA modifications may be important in mediating specialized forms of cell death including ferroptosis, pyroptosis, or other mechanisms of specialized cell death . UnderstFurthermore, as previously mentioned, LLPS remains an emerging field of research. The field of LLPS encompasses the intersection of cell biology and biophysics; not only are the biophysical mechanisms by which these condensates form an active area of interest, but more recently, increased attention has been placed on detailing the role these condensates play within cellular processes. Increasing our understanding of RNA modifications in this process will aid in understanding the function and necessity of LLPS in mediating cellular functions.6A, within mammalian cellular processes is another gap of knowledge within the field of epitranscriptomics that remains critical to address. For example, while there are several studies that have identified cellular functions for pseudouridine in Drosophila, few studies have been done to explore the role of pseuoduridine in mammalian cellular functions (The roles of other RNA modifications, other than munctions .Another area of interest that requires further study is understanding the cell-type specific function of the role of RNA modification in cellular functions. As demonstrated, not only do RNA modifications differ across cell types, but they can also differ across contexts, including across differentiation states and in response to stress. Understanding the relevance and pervasiveness of RNA modifications in these processes, and how different cell types adopt distinct mechanisms for RNA modifications across these functions, remains an important area of research.In addition, due to the prevalence of RNA modifications in diverse cellular functions, the dysregulation of RNA modifications contributes to the etiology of several diseases. RNA modifications have been found to contribute to the pathologies of several diseases including cancer, diabetes, cardiovascular diseases, and developmental and neurological diseases. Increasing our understanding of the distinct roles that RNA modifications play in these cellular processes will allow for an increased understanding of disease etiology. While there are no therapeutics currently in clinical use that target RNA modifications, an increased understanding of their roles in disease etiology may contribute to the development of therapeutics that aim to selectively target this epitranscriptomic re-wiring.


Ribosome profiling reveals the translational dynamics of mRNAs by capturing a ribosomal footprint snapshot. Growing evidence shows that several long non-coding RNAs (lncRNAs) contain small open reading frames (smORFs) that are translated into functional peptides. The difficulty in identifying bona-fide translated smORFs is a constant challenge in experimental and bioinformatics fields due to their unconventional characteristics. This motivated us to isolate human adipose-derived stem cells (hASC) from adipose tissue and perform a ribosome profiling followed by bioinformatics analysis of transcriptome, translatome, and ribosome-protected fragments of lncRNAs. Here, we demonstrated that 222 lncRNAs were associated with the translational machinery in hASC, including the already demonstrated lncRNAs coding microproteins. The ribosomal occupancy of some transcripts was consistent with the translation of smORFs. In conclusion, we were able to identify a subset of 15 lncRNAs containing 35 smORFs that likely encode functional microproteins, including four previously demonstrated smORF-derived microproteins, suggesting a possible dual role of these lncRNAs in hASC self-renewal. Long non-coding RNAs (lncRNAs) are generically described as sequences longer than 200 nucleotides (nt) without the ability to encode proteins. Many lncRNAs have properties similar to mRNAs in that they are transcribed by RNA polymerase II, capped, and polyadenylated ,2,3. How2+ uptake into the sarcoplasmic reticulum in skeletal muscle [Human adipose-derived stem cells (hASC) have the ability to self-renew and differentiate into adipocytes, osteoblasts, and chondrocytes. These cells appear as an excellent source for the study of stem cell fate and as a robust source for use in regenerative medicine ,18,19. Tl muscle . In oppol muscle . MeanwhiAgainst this background our goal is to identify translated smORFs within lncRNAs in hASC. To address this question, we proposed the identification of smORFs in lncRNAs through ribosome profiling experiments followed by deep sequencing (Ribo-seq) and transcriptomic and translatomic  analysis. In conclusion, we verified ribosomal occupancy in many lncRNAs consistent with the translation of smORFs; however, further experimental studies are required to provide evidence for the translation and function of these microproteins.Human adipose-derived stem cells were obtained from adipose tissue from lipoaspirate samples of three female donors aged between 20 and 48 years . We rand2 under constant shaking. Next, the cell suspension was filtered through a 100 µm then a 40 µm mesh filter  and centrifuged. The pellet was treated with a hemolysis buffer to remove contaminating erythrocytes. The cells obtained were washed and plated at a density of 1 × 105 cells/cm2 in T75 culture flasks in DMEM supplemented with 10% FBS, penicillin (100 units/mL), and streptomycin (100 µg/mL) in humid incubator at 37 °C and 5% CO2. The culture medium was changed twice a week, and all of the experiments were performed with cell cultures at passages 4 to 6. Cell characterization was performed according to the minimal criteria established by the International Society of Cellular Therapy [The hASC isolation was performed as previously described . In shor Therapy .6 cells) was treated with 100 µg/mL cycloheximide for 10 min at 37 °C. Cells were detached with trypsin, washed with PBS, and incubated in the lysis buffer  for 10 min on ice. Cell lysate was centrifuged , and the supernatant was carefully collected into a new tube. Next, the sample was incubated with a nuclease (Benzonase) for 10 min at 25 °C to produce ribosome RNA footprints (RNA-protected fragments). The nuclease digestion was inhibited with RNaseOUT (Invitrogen™), and lysates were loaded and pelleted into an ultracentrifuge tube over 2 mL of 1 M sucrose cushion by ultracentrifugation at 39,000 rpm  at 4 °C for 2 h. The supernatant was removed, and RNA was purified and submitted to electrophoresis (TBE-urea 6% gel) to recover the ribosome-protected RNA fragments of approximately 30 nucleotides. Concentration and size distribution were determined on a Bioanalyzer DNA chip   . Ribo-seThe Ribo-seq raw data were first subjected to quality control checking with FastQC (v.0.11.2). As previously described , the repFor the analysis of the RNA-seq raw data, fastq files of the Total and Polysomal Fractions of undifferentiated hASC were downloaded and subjected to quality control checking as described above. Low-quality reads and adaptor sequences were removed as previously described. Next, reads were mapped to genome build hg19 using HISAT2 (v.2.2.1) , and feaOther statistics and functional analyses were performed with R (v.3.5.2), including graphical representations. Principal Component Analysis (PCA) and raw reads profile plots were performed using deepTools (v.3.2.1) .p-value < 0.01 and FDR < 0.01 (1%).The Gene Ontology (GO) analysis of the protein-coding genes was performed with PANTHER (Released 20200728), using a cut-off criterion of Prediction of RNA minimum free-energy of secondary structures formation was calculated with RNAfold (v.2.4.14) . RNAfoldPredictions of the putative microprotein localization were performed using DeepLoc 1.0. In short, DeepLoc 1.0 uses a recurrent neural network that processes protein sequences and identifies protein regions important for subcellular localization .Ribosome profiling followed by next-generation sequencing (Ribo-seq) maps the position of translating ribosomes over the transcriptome by combining ribosome footprint and deep sequencing. This is possible due to the action of nuclease treatment, resulting in ribosome-protected fragments (RPFs) with a size of around 30 nt ,49. We pp < 2.2 × e−16) (p < 3.77 × e−16), lower GC-content  and fewer exons  (p < 2.2 × e−16) (p < 2.2 × e−16) . Our sequenced ribosomal footprints show a characteristic and well-documented length distribution ,50, wher × e−16) A, which  × e−16) B–D. Besi × e−16) E, which  × e−16) E. Regard × e−16) F. Taken To deepen our analysis of lncRNA translation, we used the RNA-seq data of Total and Polysomal fractions of undifferentiated hASC to compare with the generated Ribo-seq data. First, just to have a broader view, we performed a Gene Ontology (GO) analysis of the highest expressed protein-coding genes in these datasets, being identified as the most relevant pathways related to the developmental process in the Ribo-seq, cotranslational protein targeting to membrane in the total RNA-seq, and translation initiation in the polysomal RNA-seq . As statConsidering only the 99 common lncRNAs identified in our datasets , we perf2+ retention capacity [Four smORFs of identified lncRNAs have previously been confirmed as coding for microproteins ,54,55,56capacity . Moreovecapacity . We prevcapacity , which icapacity . Furthercapacity   after a dermolipectomy procedure, followed by sequencing in a distinct high-throughput plataform . Using tHuman adipose-derived stem cells hold great promise in regenerative medicine due to their simple isolation procedure, yield, and proliferative capacity, and, above all, due to their paracrine effects on the injured site. This paracrine effect is directly related to the release of specific proteins and extracellular vesicles containing different biomolecules ,63,64,65Ribosome profiling successfully identifies ribosome occupancy in lncRNAs, shedding light on the possible translation of smORFs. However, the following techniques must be combined to guarantee the existence of these microproteins: ribosome profiling, total and polysomal RNA-seq, mass spectrometry (MS)-based proteomics/peptidomics, in vitro and in vivo translation, immunofluorescence, and functional biochemistry, as well as molecular assays ,67,68,69Over the past years, distinct groups have used experiments and proteogenomics analysis to discover microproteins quantitatively, demonstrating microproteins derived from 5′ untranslated regions (5′UTR) and 3′ untranslated regions (3′UTR) of mRNAs and also from smORFs within lncRNAs ,72,73,74Here, we were able to identify several translated smORFs within lncRNAs in hASC. As shown in Similarly, we demonstrated the presence of translated smORFs in lncRNAs SNHG8, SNHG16, and MIR22HG. Recently, mitochondrial microproteins derived from smORFs in lncRNAs SNHG8 and SNHG16 were demonstrated by immunofluorescence of FLAG-tagged microproteins, while their function and mechanism of action remain unknown . RegardiAs mentioned previously, the discovery of microproteins has a significant impact on molecular and cellular biology as well as medicine. Huang et al. demonstrated a microprotein (named MP31) encoded from 5′UTR of PTEN mRNA and localized in mitochondria, which limits lactate–pyruvate conversion. Recombinant MP31 administered intraperitoneally penetrated the blood–brain barrier and inhibited glioblastoma xenografts, establishing its tumor-suppressing activity and, in turn, clinical use . SimilarHere, we begin this journey of discovering new microproteins in hASC, showing the ribosome occupancy in lncRNAs, with future perspectives to characterize these possible small proteins. Microproteins may play important roles in adult stem cell self-renewal, differentiation, and paracrine effects.In summary, using the state-of-the-art ribosome profiling technique followed by next-generation sequencing (Ribo-seq) of hASC isolated from liposuction (liquid WAT) or dermolipectomy (solid WAT) and bioinformatics analysis of different sequenced fractions , we were able to identify a subset of lncRNAs with ribosome occupancy in smORFs, which may indicate a translational capacity and coding potential of functional microproteins.


Copper-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry has been used to label NAD+-capped RNAs (NAD-RNAs) for their identification. However, copper-caused RNA fragmentation/degradation interferes with the analysis. We developed the NAD tagSeq II method for transcriptome-wide NAD-RNA analysis based on copper-free, strain-promoted azide-alkyne cycloaddition (SPAAC) click chemistry. This method was used to compare NAD-RNA and total transcriptome profiles in Escherichia coli. Our study reveals genome-wide alterations in E. coli RNA NAD+ capping in different growth phases and indicates that NAD-RNAs could be the primary form of transcripts from some genes under certain environments.Some RNAs in both prokaryotes and eukaryotes were recently found to contain the NAD +)-capped RNAs (NAD-RNAs) indicate that prokaryotes and eukaryotes employ noncanonical RNA capping to regulate gene expression. Two methods for transcriptome-wide analysis of NAD-RNAs, NAD captureSeq and NAD tagSeq, are based on copper-catalyzed azide-alkyne cycloaddition (CuAAC) click chemistry to label NAD-RNAs. However, copper ions can fragment/degrade RNA, interfering with the analyses. Here we report development of NAD tagSeq II, which uses copper-free, strain-promoted azide-alkyne cycloaddition (SPAAC) for labeling NAD-RNAs, followed by identification of tagged RNA by single-molecule direct RNA sequencing. We used this method to compare NAD-RNA and total transcript profiles of Escherichia coli cells in the exponential and stationary phases. We identified hundreds of NAD-RNA species in E. coli and revealed genome-wide alterations of NAD-RNA profiles in the different growth phases. Although no or few NAD-RNAs were detected from some of the most highly expressed genes, the transcripts of some genes were found to be primarily NAD-RNAs. Our study suggests that NAD-RNAs play roles in linking nutrient cues with gene regulation in E. coli.Recent findings regarding nicotinamide adenine dinucleotide (NAD RNAs r 5′ end –10. LateAD-RNAs) –14.+ as the first nucleotide, in place of adenosine triphosphate (ATP), during transcription initiation   , 15–20. tability , 15. How+ with an alkyne followed by copper-catalyzed azide-alkyne cycloaddition (CuAAC) to label NAD-RNAs with biotin. Biotin-conjugated RNAs are then enriched by streptavidin resin to make a cDNA library that is sequenced and quantified for enrichment of tagged RNAs. Using NAD captureSeq, 53 NAD-RNAs were identified from E. coli  was found that differed from the NAD+ (m/z = 664.1164) observed from the reaction without ADPRC and matched the expected mass of a transglycosylation product replacing nicotinamide with 3-azido-1-propanol . The result indicates that ADPRC is indeed capable of catalyzing the transglycosylation reaction of NAD-RNA with 3-azido-1-propanol.NAD captureSeq and NAD tagSeq label NAD-RNAs by first using ADPRC to catalyze the transglycosylation reaction that replaces the nicotinamide of the NAD cap with an alkynyl alcohol and then using CuAAC for conjugation with an azide-linked tag. To adapt SPAAC to NAD tagSeq or NAD captureSeq, an azide moiety, instead of an alkyne moiety, needs to replace the nicotinamide of NAD-RNA in the ADPRC-catalyzed reaction A. The st+ fragments were quantified using mass spectrometry. It was found that 99.34% (±0.16%) and 99.41% (±0.21%) of the original NAD-RNAs were alkyne modified and azide modified in the presence of 4-pentyn-1-ol and 3-azido-1-propanol, respectively . The results showed that ADPRC could catalyze the transglycosylation of NAD-RNAs with 3-azido-1-propanol as efficiently as with 4-pentyn-1-ol.We compared the ADPRC-catalyzed transglycosylation reaction of the 38-nt NAD-RNA with 3-azido-1-propanol or 4-pentyn-1-ol. After the reaction, the RNA samples were purified and digested with nuclease P1. The alkyne- and azide-modified NADWe then used SPAAC to label the 38-nt NAD-RNA with a synthetic 16-nt RNA tag A and B. E. coli cellular RNAs showed severe RNA fragmentation as compared with SPAAC tagging , such as Ap4A, at the 5′ end  reaction between the sulfhydryl group of the dpCoA cap and the DBCO of the RNA tag. This assumption was verified by the observation that there was no ligation product if the 38-nt dpCoA-RNA was reacted with iodoacetic acid (IAA), a sulfhydryl group blocking reagent, prior to SPAAC tagging  was subjected to SPAAC tagging with the 16-nt RNA-DBCO tag. A small portion of the m7GpppA-RNA was found to be tagged  after incubation with 4-pentyn-1-ol and 3-azido-1-propanol, respectively, in the presence of ADPRC . These results indicate that ADPRC can act on m7G-capped RNAs, although weakly. It is plausible that some NAD-RNAs in eukaryotes previously identified through the ADPRC-catalyzed labeling process might be false signals from m7G-mRNAs. Therefore, for using ADPRC in CuAAC- or SPAAC-based tagging to identify NAD-RNAs in eukaryotic RNA samples, an m7G-mRNA depletion step needs to be introduced to reduce noise from m7G-mRNAs before the ADPRC-catalyzed reaction is carried out, as shown by Hu et al.  or 7 h . We used one nanopore flow cell to sequence each sample. For the initial trial to compare SPAAC and CuAAC tagging, two RNA samples from the stationary phase were tagged by CuAAC and SPAAC, respectively, and sequenced by nanopore sequencing. The overall sequence read length obtained through SPAAC tagging was much greater than that through CuAAC tagging (Datasets S1 and S2). The NAD-RNA–producing genes identified by CuAAC were generally identified using SPAAC tagging, but the gene number and the NAD-RNA read member were far fewer than those identified using SPAAC . The result indicated that SPAAC tagging offers a much higher sensitivity and generates more accurate information on the whole sequences of NAD-RNAs than CuAAC. Further experiments were carried out by using the SPAAC-based NAD tagSeq II method. We included three biological replicates for both exponential and stationary phases, except for ADPRC− samples which had two biological replicates.The RNA samples were extracted from  tagging C. A totaSI Appendix, Fig. S5). Approximately 30 to 50% of the reads were rRNAs. These mapped sequencing reads are listed in Dataset S2. After removing rRNA reads, tagged reads accounted for 15,783 of the 3,412,676 reads (0.46%) in the six ADPRC+ samples. For the four ADPRC− samples, 151 of the 1,470,713 reads (0.01%) contained the tag RNA sequence. In each ADPRC− sample, generally no more than a single read from any gene was found to have the tag sequence. The exception is the ssrA transcript likely because of its very high abundance, for which 18 of its 315,450 transcripts (0.006%) contained the tag sequence. The results indicate that the noise level from this assay was very low. It also indicates that dpCoA-RNAs, if any, which might be tagged without ADPRC were extremely rare under our growth conditions and/or were not efficiently tagged in this assay.We obtained 0.49 to 1.0 million sequencing reads for each sample (Dataset S2). Although there was some overlap between the genes from which NAD-RNAs were detected in both the exponential and stationary phases, there were distinct subsets of genes that produced NAD-RNAs only in one phase  from the exponential phase cells and 11,795 of the 1,982,114 reads (0.6%) from the stationary phase cells were identified as NAD-RNA reads . Seventy-nine of them were identified as high-confidence NAD-RNAs in both phases, bringing the total number of high-confidence NAD-RNAs to 279. On average, 5.3% of the transcripts from the 229 NAD-RNA–producing genes in the stationary phase and around 2.0% of the 129 NAD-RNA–producing genes in the exponential phase were NAD capped, respectively (Dataset S3).The NAD-RNA–producing genes in each sample were filtered using the following criteria: 1) at least 0.2% of the transcripts from the gene were NAD-RNAs, which is about 20 times the noise level from the ADPRC− samples; and 2) there were at least two NAD-RNA reads detected from each gene. The criteria are based not on statistics but rather on our assumption that if a very small portion of transcripts from a certain gene is NAD capped, the NAD-RNAs might be produced incidentally and might not have a significant role in gene regulation. If a NAD-RNA species met the above criteria in at least two out of the three replicates, we considered it a high-confidence NAD-RNA. Using these criteria, a total of 129 genes in the exponential phase and 229 in the stationary phase were found to produce high-confidence NAD-RNAs (ectively C. Among Dataset S3). The remaining 8 NAD-RNAs were not detected, likely because the cognate genes were expressed at a very low level under our conditions. The low transcript levels for five of these eight genes could also be due to their smaller transcripts (<107 nt) which might be partially removed by the RNA Clean kit or could not be sequenced by nanopore sequencing. The smallest read detected in our analysis (not including the tag sequence) was 98 nt.The previous report using the NAD captureSeq method identified 49 NAD-RNAs from late exponential phase cells of the K-12 strain , the samWe selected seven NAD-RNAs  identified in our analysis for validation through the biotin labeling/capturing approach used in NAD captureSeq. Total RNA samples were labeled with biotin through CuAAC and SPAAC tagging. Tagged RNAs were enriched using streptavidin beads and subjected to reverse transcription-PCR analysis. As shown in + capping in E. coli is dependent on the transcription start site (TSS) and promoter sequences . Most of the high-confidence NAD-RNAs were from moderately to lowly expressed genes (Dataset S3). The result further indicates that although some NAD-RNAs might be incidentally produced, most of the NAD-RNAs were produced selectively from certain genes.It is known that NADequences , 15. The+ capped. In the exponential phase cells, the transcripts with the highest NAD+ modification were from several protein-coding genes with the highest ratio of NAD-RNAs/total transcript at 38% , 55% (sibE), and 52% (sibC) of their total transcripts detected as NAD-RNAs . These st at 38% . The relNAD-RNAs . On the Dataset S4). The 229 genes in the stationary phase were overrepresented in the GO terms of negative and positive regulation of transcription, negative regulation of translation and biosynthetic processes, energy production, and responses to abiotic stresses (Dataset S4). Many genes that produced a high percentage/level of NAD-RNAs in the stationary phase are known to be involved in response to energy depletion and other abiotic stresses, growth inhibition, and persistence/antibiotics resistance. We quantified cellular ATP and NAD+ levels in the exponential phase and the stationary phase. The ATP level was ∼2.5-fold lower, whereas the NAD+ level was slightly higher in the stationary phase than in the exponential phase .The genes producing high-confidence NAD-RNAs in the exponential and/or stationary phases were subjected to gene ontology (GO) enrichment analysis. The 129 NAD-RNA–producing genes in the exponential phase are mostly enriched in the GO terms of metabolic and energy generation processes  in their total transcript levels between the exponential phase and stationary phase. Strikingly, among the 279 high-confidence NAD-RNA–producing genes, 208 (75%) displayed differential expression between the two phases (Dataset S5). The result indicates that most of the NAD-RNA–producing genes showed significant alteration in their transcript levels under the different growth phases. We then analyzed any correlation between the changes in the NAD-RNA and total transcript levels for these 279 genes under the two different growth conditions. It was found that an increase in the NAD-RNA level was generally associated with an increase in the total transcript level from the same gene (with a correlation coefficient of 0.69)  displayed differential expression, which was defined by statistically significant difference (adjusted of 0.69) F.+ cap. At the 3′ ends, ∼47% of the NAD-mRNAs and 53% of non–NAD-mRNAs contained the predicted stop codon sequence  and responses to abiotic stimuli. NAD-RNAs might play a role in the reciprocal connection between nutritional cues and gene expression as indicated from NAD+ capping of mitochondrial RNAs in eukaryotes . DNA oligos were synthesized by Beijing Genomics Institute. RNA oligos were synthesized from Integrated DNA Technologies (IDT). All other reagents were purchased from commercial sources and used without further purification.4A-RNA, and 50-nt NAD-RNA were produced through in vitro transcription according to the method described previously .The 38-nt NAD-RNA, 38-nt pA-RNA, 38-nt pppA-RNA, 38-nt FAD-RNA, 38-nt dpCoA-RNA, 38-nt ppA-RNA, 38-nt Apeviously , with miRNA oligos used as the tags were synthesized at IDT. Their sequences are as follows: 5′- rGrArArCrCrUrGrArArCrCrUrGrArArC-azide-3′ for 16-nt-RNA-azide, 5′-rGrArArCrCrUrGrArArCrCrUrGrArArC-DBCO-3′ for 16-nt-RNA-DBCO, and 5′-rCrCrUrGrArArCrCrUrGrArArCrCrUrGrArArCrCrUrGrArArCrCrUrGrArArCrCrUrGrArArCrCrU-DBCO-3′ for 39-nt-RNA-DBCO.The reaction was carried out in 50 μL of solution containing 100 mM Tris⋅HCl, pH 8.0, 10 mM iodoacetic acid, 500 ng 38-nt NAD-RNAs, or dpCoA-RNAs and 50 units of murine RNase inhibitor (NEB) at 37 °C for 15 min. The RNAs were purified with RNA clean kit (Zymo) following the manufacturer’s instructions.2, 200 ng RNA, 100 units of murine RNase inhibitor (NEB), 0.425 μM ADP ribosyl cyclase (Sigma), and either 10 μL 4-pentyn-1-ol (for CuAAC) or 10 μL 3-azido-1-propanol (for SPAAC) for 1 h at 37 °C. The reaction was stopped by adding 100 μL phenol/chloroform  (Invitrogen). The RNA sample was purified with chloroform extraction and ethanol precipitated. The CuAAC was performed by incubating the RNA in a 50-μL reaction containing 50 mM Hepes, pH 7.0, 5 mM MgCl2, 15 μM 16-nt RNA-azide, 1 mM CuSO4, 0.5 mM THPTA, 2 mM sodium ascorbate, and 15 μM 16-nt RNA-azide at 25 °C for 30 min. The RNA was ethanol precipitated and dissolved with RNase-free H2O. The SPAAC was performed by incubating the RNA in a 10-μL reaction containing 155.2 mM NaCl, 2.97 mM Na2HPO4, 1.06 mM KH2PO4, pH 7.4, 10 units of murine RNase inhibitor (NEB), and 75 μM 16-nt RNA-DBCO  for 2 h at 37 °C. An equal volume of 2× RNA loading solution (NEB) was added to the RNA samples. After incubation at 95 °C for 5 min, the RNAs were resolved on a 15% denaturing polyacrylamide gel and stained, followed by visualization using the ChemiDoc imaging system (Bio-Rad). Note that the tagging efficiency might differ under different reaction conditions, such as the concentration of tag RNAs and ADPRC and other conditions.The reaction was carried out in 50 μL of solution containing 50 mM Hepes, pH 7.0, 5 mM MgClE. coli K-12 stain MG1655  was grown in Luria-Bertani (LB) broth under aeration at 37 °C. An overnight culture was diluted 1:100 into fresh medium and grown to an OD600 of 0.32 for the log-phase sample or to an OD600 of 2.7 (after 7 h of incubation) for the stationary phase sample.SI Appendix, Supplementary Methods.Total RNA was extracted according to the method described by Winz et al. . The detSI Appendix, Supplementary Methods.Size selection was conducted using the RNA Clean kit (Zymo) according to the manufacturer’s instructions. The detailed method is described in 2, 45 μg cellular RNA, 10 μL of 3-azido-1-propanol (Sigma), 0.85 μM ADP ribosyl cyclase (Sigma), and 100 units of murine RNase inhibitor (NEB) was incubated for 30 min at 37 °C. The reaction was stopped by adding 100 μL phenol/chloroform  (Invitrogen). The mixture was centrifuged at 12,000 × g for 5 min at 4 °C. The upper phase was collected and mixed with 100 μL chloroform. After centrifugation, the upper phase was gently collected and mixed at a 1:3 ratio with 100% ethanol and a 0.1× volume of 3 M NaOAc (pH 5.4). The RNA sample was incubated for 30 min at −20 °C and then centrifuged at 14,000 × g for 20 min at 4 °C. The pellet was washed twice with 400 μL 75% ethanol, air dried, and dissolved in 10 μL RNase-free H2O. SPAAC was performed by incubating the RNA in a 30-μL reaction containing 155.2 mM NaCl, 2.97 mM Na2HPO4, 1.06 mM KH2PO4, pH 7.4, 30 units of murine RNase inhibitor (NEB), and 33.3 μM 39-nt-RNA-DBCO at 37 °C for 2 h. The RNA sample was mixed at a 1:3 ratio with ethanol and a 0.1× volume of 3 M NaOAc (pH 5.4). The RNA was pelleted by centrifugation at 14,000 × g for 20 min at 4 °C. The pellet was washed twice with 400 μL 75% ethanol, air dried, and dissolved in 40 μL RNase-free H2O.A 100-μL reaction containing 50 mM Hepes, pH 7.0, 5 mM MgCl7GpppA-capped RNA was subjected to ADPRC reaction using 4-pentyn-1-ol as substrate, following the procedure for tagging of in vitro transcribed RNAs mentioned above. Then CuAAC-based biotin labeling was performed following the procedure as described . The RNA sample was incubated for 30 min at −20 °C and then subjected to centrifugation at 14,000 × g for 20 min at 4 °C. The RNA sample was separated on a 10% denaturing polyacrylamide gel electrophoresis gel and transferred to a positively charged nylon membrane Hybond-N (Amersham Pharmacia Biotech) and probed with horseradish peroxidase (HRP)-conjugated Streptavidin (Thermo Scientific). The signal was detected using ECL Western Blotting Substrate (Pierce) and blot image was acquired using Chemidoc XRS+ Imager (Bio-Rad).The 200 ng of 38-nt mescribed . UnreactSI Appendix, Supplementary Methods for details).Removal of 16S and 23S rRNAs was performed using MICROBExpress kit (Invitrogen) which includes binding solution, capture oligonucleotides, and derivatized magnetic beads , 200 μM dithiothreitol, 6 µg acetylated bovine serum albumin (BSA), 10% glycerol, 4 μg RNA, 1 mM ATP, 60 units of murine RNase inhibitor (NEB), and 100 units of yeast poly(A) polymerase (MCLAB) was incubated for 20 min at 37 °C. The reaction was stopped by adding RNA binding solution and the RNA sample was purified with RNA Clean kit (RCC-5) (Zymo) following the manufacturer’s instructions.A 60-μL reaction containing 20 mM Tris⋅HCl, pH 7.0, 600 μM MnClFor each RNA sample, 1 μg poly(A)-tailed RNA was used to prepare a library using the Nanopore Direct RNA Sequencing Kit (RNA-0002) following the manufacturer’s instructions (Oxford Nanopore Technologies). Each library was loaded onto a flow cell (R9.4) and sequenced on the sequencing device GridION. Base calling was conducted using Guppy software (Oxford Nanopore Technologies).2HPO4, 1.06 mM KH2PO4, pH 7.4, 30 units of murine RNase inhibitor (NEB), and 3.3 mM biotin-PEG4-DBCO (Sigma) at 37 °C for 1 h. Unreacted biotin-PEG4-DBCO and biotin-PEG3-azide were removed by adding 100 μL phenol/chloroform  (Invitrogen). The mixture was centrifuged at 12,000 × g for 5 min at 4 °C. The upper phase was collected and mixed with 100 μL chloroform. After centrifugation, the upper phase was gently collected and mixed at a 1:3 ratio with 100% ethanol and a 0.1× volume of 3 M NaOAc (pH 5.4). The RNA sample was incubated for 30 min at −20 °C and then centrifuged at 14,000 × g for 20 min at 4 °C. The pellet was washed twice with 400 μL 75% ethanol, air dried, and dissolved in 300 μL buffer containing 50 mM Tris⋅HCl, 0.5 M LiCl, 1 mM EDTA, pH 7.5. The RNA solution was incubated with 500 μg magnetic Streptavidin C1 beads (Invitrogen) 37 °C for 30 min and the beads were washed with RNase-free water. The RNAs were eluted by incubating the beads in 80 μL elution buffer containing 50 mM Tris⋅HCl, pH 7.5, 95% formamide, 10 mM EDTA, and 2 mM biotin at 65 °C for 5 min. The RNA was ethanol precipitated and reversed transcribed using PrimeScript RT Master Mix (Takara). PCR was performed using PCR primers .A total of 100 μg total RNA and IAA-treated 100 μg total RNA were subjected to ADPRC reaction using 4-pentyn-1-ol and 3-azido-propanol as substrate, respectively, following the procedure as tagging of in vitro-transcribed RNAs. Then CuAAC-based biotin labeling was performed following the procedure as described . SPAAC-bE. coli strain K-12 substrain MG1655 . GO enrichment analysis was performed using the binomial test in the PANTHER database    was usedThe DESeq2 package  was adopSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary FileSupplementary File