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Acinetobacter baumannii, a top‐priority WHO pathogen, causes life‐threatening infections in immunocompromised patients, leading to prolonged hospitalisation and high mortality. Here, we used the Galleria mellonella model to investigate community strain C98 (Ab‐C98) virulence via transcriptomic analysis. Ab‐C98 showed greater killing and faster colonisation in larvae than the clinical reference strain (ATCC BAA1605). Genes in three iron clusters, acinetobactin, baumannoferrin and the Feo system, were significantly up‐regulated. Targeted knockout of siderophore genes (basC, bfnD, and the gene encoding isochorismatase) significantly increased the survival of infected larvae by at least 35.16%, identifying these genes as potential targets for developing anti‐virulence agents against A. baumannii. [ABSTRACT FROM AUTHOR]

Fokienia hodginsii (F. hodginsii), belonging to the genus Fokienia of the Cupressaceae. F. hodginsii has significant application value due to its wood properties and great research value in evolutionary studies as a gymnosperm. However, the genome of F. hodginsii remains unknown due to the large size of gymnosperms genome. Pacific Bioscience sequencing, Hi‐C mapping, whole‐genome Bisulfite Sequencing (BS‐Seq), long‐read isoform sequencing (Iso‐Seq), direct RNA sequencing (DRS), quantitative proteomics, and metabonomics analysis are employed to facilitate genome assembly, gene annotation, and investigation into epigenetic mechanisms. In this study, the 10G F. hodginsii genome is assembled into 11 chromosomes. Furthermore, 50 521 protein‐coding genes are annotated and determined that 65% of F. hodginsii genome comprises repetitive sequences. It is discovered that transposable element (TE)‐including introns is associated with higher expression. The DNA methylome of F. hodginsii reveals that xylem has a higher DNA methylation level compared to callus. Moreover, DRS reveals the significant alterations in RNA full‐length ratio, which potentially associated with poly(A) length (PAL) and alternative polyadenylation (APA). Finally, the morphology measurement and metabonomics analysis revealed the difference of 14 cultivars. In summary, the genomes and epigenetics datasets provide a molecular basis for callus formation in the gymnosperm family. [ABSTRACT FROM AUTHOR]

Abstract Fokienia hodginsii (F. hodginsii), belonging to the genus Fokienia of the Cupressaceae. F. hodginsii has significant application value due to its wood properties and great research value in evolutionary studies as a gymnosperm. However, the genome of F. hodginsii remains unknown due to the large size of gymnosperms genome. Pacific Bioscience sequencing, Hi‐C mapping, whole‐genome Bisulfite Sequencing (BS‐Seq), long‐read isoform sequencing (Iso‐Seq), direct RNA sequencing (DRS), quantitative proteomics, and metabonomics analysis are employed to facilitate genome assembly, gene annotation, and investigation into epigenetic mechanisms. In this study, the 10G F. hodginsii genome is assembled into 11 chromosomes. Furthermore, 50 521 protein‐coding genes are annotated and determined that 65% of F. hodginsii genome comprises repetitive sequences. It is discovered that transposable element (TE)‐including introns is associated with higher expression. The DNA methylome of F. hodginsii reveals that xylem has a higher DNA methylation level compared to callus. Moreover, DRS reveals the significant alterations in RNA full‐length ratio, which potentially associated with poly(A) length (PAL) and alternative polyadenylation (APA). Finally, the morphology measurement and metabonomics analysis revealed the difference of 14 cultivars. In summary, the genomes and epigenetics datasets provide a molecular basis for callus formation in the gymnosperm family.

ABSTRACT RNA transcripts are potential therapeutic targets, yet bacterial transcripts have uncharacterized biodiversity. We developed an algorithm for transcript prediction called tp.py using it to predict transcripts (mRNA and other RNAs) in Escherichia coli K12 and E2348/69 strains (Bacteria:gamma-Proteobacteria), Listeria monocytogenes strains Scott A and RO15 (Bacteria:Firmicute), Pseudomonas aeruginosa strains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), and Haloferax volcanii (Archaea:Halobacteria). From >5 million E. coli K12 and >3 million E. coli E2348/69 newly generated Oxford Nanopore Technologies direct RNA sequencing reads, 2,487 K12 mRNAs and 1,844 E2348/69 mRNAs were predicted, with the K12 mRNAs containing more than half of the predicted E. coli K12 proteins. While the number of predicted transcripts varied by strain based on the amount of sequence data used, across all strains examined, the predicted average size of the mRNAs was 1.6–1.7 kbp, while the median size of the 5′- and 3′-untranslated regions (UTRs) were 30–90 bp. Given the lack of bacterial and archaeal transcript annotation, most predictions were of novel transcripts, but we also predicted many previously characterized mRNAs and ncRNAs, including post-transcriptionally generated transcripts and small RNAs associated with pathogenesis in the E. coli E2348/69 LEE pathogenicity islands. We predicted small transcripts in the 100–200 bp range as well as >10 kbp transcripts for all strains, with the longest transcript for two of the seven strains being the nuo operon transcript, and for another two strains it was a phage/prophage transcript. This quick, easy, and reproducible method will facilitate the presentation of transcripts, and UTR predictions alongside coding sequences and protein predictions in bacterial genome annotation as important resources for the research community.IMPORTANCEOur understanding of bacterial and archaeal genes and genomes is largely focused on proteins since there have only been limited efforts to describe bacterial/archaeal RNA diversity. This contrasts with studies on the human genome, where transcripts were sequenced prior to the release of the human genome over two decades ago. We developed software for the quick, easy, and reproducible prediction of bacterial and archaeal transcripts from Oxford Nanopore Technologies direct RNA sequencing data. These predictions are urgently needed for more accurate studies examining bacterial/archaeal gene regulation, including regulation of virulence factors, and for the development of novel RNA-based therapeutics and diagnostics to combat bacterial pathogens, like those with extreme antimicrobial resistance.

Abstract Background Direct RNA sequencing (dRNA-seq) on the Oxford Nanopore Technologies (ONT) platforms can produce reads covering up to full-length gene transcripts, while containing decipherable information about RNA base modifications and poly-A tail lengths. Although many published studies have been expanding the potential of dRNA-seq, its sequencing accuracy and error patterns remain understudied. Results We present the first comprehensive evaluation of sequencing accuracy and characterisation of systematic errors in dRNA-seq data from diverse organisms and synthetic in vitro transcribed RNAs. We found that for sequencing kits SQK-RNA001 and SQK-RNA002, the median read accuracy ranged from 87% to 92% across species, and deletions significantly outnumbered mismatches and insertions. Due to their high abundance in the transcriptome, heteropolymers and short homopolymers were the major contributors to the overall sequencing errors. We also observed systematic biases across all species at the levels of single nucleotides and motifs. In general, cytosine/uracil-rich regions were more likely to be erroneous than guanines and adenines. By examining raw signal data, we identified the underlying signal-level features potentially associated with the error patterns and their dependency on sequence contexts. While read quality scores can be used to approximate error rates at base and read levels, failure to detect DNA adapters may be a source of errors and data loss. By comparing distinct basecallers, we reason that some sequencing errors are attributable to signal insufficiency rather than algorithmic (basecalling) artefacts. Lastly, we generated dRNA-seq data using the latest SQK-RNA004 sequencing kit released at the end of 2023 and found that although the overall read accuracy increased, the systematic errors remain largely identical compared to the previous kits. Conclusions As the first systematic investigation of dRNA-seq errors, this study offers a comprehensive overview of reproducible error patterns across diverse datasets, identifies potential signal-level insufficiency, and lays the foundation for error correction methods.

Background: Direct RNA sequencing (dRNA-seq) on the Oxford Nanopore Technologies (ONT) platforms can produce reads covering up to full-length gene transcripts, while containing decipherable information about RNA base modifications and poly-A tail lengths. Although many published studies have been expanding the potential of dRNA-seq, its sequencing accuracy and error patterns remain understudied. Results: We present the first comprehensive evaluation of sequencing accuracy and characterisation of systematic errors in dRNA-seq data from diverse organisms and synthetic in vitro transcribed RNAs. We found that for sequencing kits SQK-RNA001 and SQK-RNA002, the median read accuracy ranged from 87% to 92% across species, and deletions significantly outnumbered mismatches and insertions. Due to their high abundance in the transcriptome, heteropolymers and short homopolymers were the major contributors to the overall sequencing errors. We also observed systematic biases across all species at the levels of single nucleotides and motifs. In general, cytosine/uracil-rich regions were more likely to be erroneous than guanines and adenines. By examining raw signal data, we identified the underlying signal-level features potentially associated with the error patterns and their dependency on sequence contexts. While read quality scores can be used to approximate error rates at base and read levels, failure to detect DNA adapters may be a source of errors and data loss. By comparing distinct basecallers, we reason that some sequencing errors are attributable to signal insufficiency rather than algorithmic (basecalling) artefacts. Lastly, we generated dRNA-seq data using the latest SQK-RNA004 sequencing kit released at the end of 2023 and found that although the overall read accuracy increased, the systematic errors remain largely identical compared to the previous kits. Conclusions: As the first systematic investigation of dRNA-seq errors, this study offers a comprehensive overview of reproducible error patterns across diverse datasets, identifies potential signal-level insufficiency, and lays the foundation for error correction methods. [ABSTRACT FROM AUTHOR]

ABSTRACT Nanopore direct RNA sequencing (DRS) enables the capture and full-length sequencing of native RNAs, without recoding or amplification bias. Resulting data sets may be interrogated to define the identity and location of chemically modified ribonucleotides, as well as the length of poly(A) tails, on individual RNA molecules. The success of these analyses is highly dependent on the provision of high-resolution transcriptome annotations in combination with workflows that minimize misalignments and other analysis artifacts. Existing software solutions for generating high-resolution transcriptome annotations are poorly suited to small gene-dense genomes of viruses due to the challenge of identifying distinct transcript isoforms where alternative splicing and overlapping RNAs are prevalent. To resolve this, we identified key characteristics of DRS data sets that inform resulting read alignments and developed the nanopore guided annotation of transcriptome architectures (NAGATA) software package (https://github.com/DepledgeLab/NAGATA). We demonstrate, using a combination of synthetic and original DRS data sets derived from adenoviruses, herpesviruses, coronaviruses, and human cells, that NAGATA outperforms existing transcriptome annotation software and yields a consistently high level of precision and recall when reconstructing both gene sparse and gene-dense transcriptomes. Finally, we apply NAGATA to generate the first high-resolution transcriptome annotation of the neglected pathogen human adenovirus type F41 (HAdV-41) for which we identify 77 distinct transcripts encoding at least 23 different proteins.IMPORTANCEThe transcriptome of an organism denotes the full repertoire of encoded RNAs that may be expressed. This is critical to understanding the biology of an organism and for accurate transcriptomic and epitranscriptomic-based analyses. Annotating transcriptomes remains a complex task, particularly in small gene-dense organisms such as viruses which maximize their coding capacity through overlapping RNAs. To resolve this, we have developed a new software nanopore guided annotation of transcriptome architectures (NAGATA) which utilizes nanopore direct RNA sequencing (DRS) datasets to rapidly produce high-resolution transcriptome annotations for diverse viruses and other organisms.

Transcriptome analysis based on high-throughput sequencing of a cDNA library has been widely applied to functional genomic studies. However, the cDNA dependence of most RNA sequencing techniques constrains their ability to detect base modifications on RNA, which is an important element for the post-transcriptional regulation of gene expression. To comprehensively profile the N6-methyladenosine (m6A) and N5-methylcytosine (m5C) modifications on RNA, direct RNA sequencing (DRS) using the latest Oxford Nanopore Technology was applied to analyze the transcriptome of six tissues in rice. Approximately 94 million reads were generated, with an average length ranging from 619 nt to 1013 nt, and a total of 45,707 transcripts across 34,763 genes were detected. Expression profiles of transcripts at the isoform level were quantified among tissues. Transcriptome-wide mapping of m6A and m5C demonstrated that both modifications exhibited tissue-specific characteristics. The transcripts with m6A modifications tended to be modified by m5C, and the transcripts with modifications presented higher expression levels along with shorter poly(A) tails than transcripts without modifications, suggesting the complexity of gene expression regulation. Gene Ontology analysis demonstrated that m6A- and m5C-modified transcripts were involved in central metabolic pathways related to the life cycle, with modifications on the target genes selected in a tissue-specific manner. Furthermore, most modified sites were located within quantitative trait loci that control important agronomic traits, highlighting the value of cloning functional loci. The results provide new insights into the expression regulation complexity and data resource of the transcriptome and epitranscriptome, improving our understanding of the rice genome.

Glucose is a major source of carbon and essential for the survival of many organisms, ranging from yeast to human. A sudden 60-fold reduction of glucose in exponentially growing fission yeast induces transcriptome-wide changes in gene expression. This regulation is multilayered, and the boundaries of transcripts are known to vary, with functional consequences at the protein level. By combining direct RNA sequencing with 5'-CAGE and short-read sequencing, we accurately defined the 5'- and 3'-ends of transcripts that are both poly(A) tailed and 5'-capped in glucose starvation, followed by proteome analysis. Our results confirm previous experimentally validated loci with alternative isoforms and reveal several transcriptome-wide patterns. First, we show that sense-antisense gene pairs are more strongly anticorrelated when a time lag is taken into account. Second, we show that the glucose starvation response initially elicits a shortening of 3'-UTRs and poly(A) tails, followed by a shortening of the 5'-UTRs at later time points. These result in domain gains and losses in proteins involved in the stress response. Finally, the relatively poor overlap both between differentially expressed genes (DEGs), differential transcript usage events (DTUs), and differentially detected proteins (DDPs) highlight the need for further study on post-transcriptional regulation mechanisms in glucose starvation. [ABSTRACT FROM AUTHOR]

Protein arginine methyltransferase 5 (Prmt5) is essential for normal B‐cell development; however, the roles of Prmt5 in tumor‐infiltrating B cells in tumor therapy have not been well elucidated. Here, we revealed that CD19‐cre‐Prmt5fl/fl (Prmt5cko) mice showed smaller tumor weights and volumes in the colorectal cancer mouse model; B cells expressed higher levels of Ccl22 and Il12a, which attracted T cells to the tumor site. Furthermore, we used direct RNA sequencing to comprehensively profile RNA processes in Prmt5 deletion B cells to explore underline mechanisms. We found significantly differentially expressed isoforms, mRNA splicing, poly(A) tail lengths, and m6A modification changes between the Prmt5cko and control groups. Cd74 isoform expressions might be regulated by mRNA splicing; the expression of two novel Cd74 isoforms was decreased, while one isoform was elevated in the Prmt5cko group, but the Cd74 gene expression showed no changes. We observed Ccl22, Ighg1, and Il12a expression was significantly increased in the Prmt5cko group, whereas Jak3 and Stat5b expression was decreased. Ccl22 and Ighg1 expression might be associated with poly(A) tail length, Jak3, Stat5b, and Il12a expression might be modulated by m6A modification. Our study demonstrated that Prmt5 regulates B‐cell function through different mechanisms and supported the development of Prmt5‐targeted antitumor treatments. [ABSTRACT FROM AUTHOR]

Soil microbes play an undeniable role in sustainable agriculture, plant health, and soil management. A deeper understanding of soil microbial composition and function has been gained through next-generation sequencing. Although soil metagenomics has provided valuable information about microbial diversity, issues stemming from RNA extraction, low RNA abundance in some microbial populations (e.g., viruses), and messenger RNA enrichment have slowed the progress of soil metatranscriptomics. A variety of soil RNA extraction methods have been developed thus far yet none of the available protocols can obtain RNA with high quality, purity, and yield for third-generation sequencing. The latter requires RNA with high quality and large quantities (with no or low contamination such as humic acids). Also, use of commercial kits for in-batch soil RNA extraction is quite expensive, and these commercial kits lack buffer composition details, which prevents the optimization of protocols for different soil types. An improved and cost-effective method for extracting RNAs from mineral and organic soils is presented in this article. An acidic sodium acetate buffer and phosphate buffer with modifications to bead beating and nucleic acid precipitation lead to higher RNA yields and quality. Using this method, we obtained almost DNA-free RNA. By using nanopore's direct RNA sequencing, the extracted contamination-free RNAs were successfully sequenced. Finally, taxonomic groups such as bacteria, fungi, archaea, and viruses were classified and profiled, and functional annotation of the datasets was carried out using an in-house customized bioinformatics workflow.

The expanding field of epitranscriptomics might rival the epigenome in the diversity of biological processes impacted. In recent years, the development of new high-throughput experimental and computational techniques has been a key driving force in discovering the properties of RNA modifications. Machine learning applications, such as for classification, clustering or de novo identification, have been critical in these advances. Nonetheless, various challenges remain before the full potential of machine learning for epitranscriptomics can be leveraged. In this review, we provide a comprehensive survey of machine learning methods to detect RNA modifications using diverse input data sources. We describe strategies to train and test machine learning methods and to encode and interpret features that are relevant for epitranscriptomics. Finally, we identify some of the current challenges and open questions about RNA modification analysis, including the ambiguity in predicting RNA modifications in transcript isoforms or in single nucleotides, or the lack of complete ground truth sets to test RNA modifications. We believe this review will inspire and benefit the rapidly developing field of epitranscriptomics in addressing the current limitations through the effective use of machine learning. [ABSTRACT FROM AUTHOR]

Trypanosomatids are single-cell eukaryotic parasites. Unlike higher eukaryotes, they control gene expression post-transcriptionally and not at the level of transcription initiation. This involves all known cellular RNA circuits, from mRNA processing to mRNA decay, to translation, in addition to a large panel of RNA-interacting proteins that modulate mRNA abundance. However, other forms of gene regulation, for example by lncRNAs, cannot be excluded. LncRNAs are poorly studied in trypanosomatids, with only a single lncRNA characterized to date. Furthermore, it is not clear whether the complete inventory of trypanosomatid lncRNAs is known, because of the inherent cDNA-recoding and DNA-amplification limitations of short-read RNA sequencing. Here, we overcome these limitations by using long-read direct RNA sequencing (DRS) on nanopore arrays. We analyze the native RNA pool of the two main lifecycle stages of the African trypanosome Trypanosoma brucei, with a special emphasis on the inventory of lncRNAs. We identify 207 previously unknown lncRNAs, 32 of which are stage-specifically expressed. We also present insights into the complexity of the T. brucei transcriptome, including alternative transcriptional start and stop sites and potential transcript isoforms, to provide a bias-free understanding of the intricate RNA landscape in T. brucei. [ABSTRACT FROM AUTHOR]

The covalent modification of RNA molecules is a pervasive feature of all classes of RNAs and has fundamental roles in the regulation of several cellular processes. Mapping the location of RNA modifications transcriptome-wide is key to unveiling their role and dynamic behaviour, but technical limitations have often hampered these efforts. Nanopore direct RNA sequencing is a third-generation sequencing technology that allows the sequencing of native RNA molecules, thus providing a direct way to detect modifications at single-molecule resolution. Despite recent advances, the analysis of nanopore sequencing data for RNA modification detection is still a complex task that presents many challenges. Many works have addressed this task using different approaches, resulting in a large number of tools with different features and performances. Here we review the diverse approaches proposed so far and outline the principles underlying currently available algorithms. [ABSTRACT FROM AUTHOR]

Over the past decade, nanopore sequencing has experienced significant advancements and changes, transitioning from an initially emerging technology to a significant instrument in the field of genomic sequencing. However, as advancements in next-generation sequencing technology persist, nanopore sequencing also improves. This paper reviews the developments, applications, and outlook on nanopore sequencing technology. Currently, nanopore sequencing supports both DNA and RNA sequencing, making it widely applicable in areas such as telomere-to-telomere (T2T) genome assembly, direct RNA sequencing (DRS), and metagenomics. The openness and versatility of nanopore sequencing have established it as a preferred option for an increasing number of research teams, signaling a transformative influence on life science research. As the nanopore sequencing technology advances, it provides a faster, more cost-effective approach with extended read lengths, demonstrating the significant potential for complex genome assembly, pathogen detection, environmental monitoring, and human disease research, offering a fresh perspective in sequencing technologies., Competing Interests: Conflict of interest The authors have declared no competing interests., (Copyright © 2024. Published by Elsevier Ltd.)

The transcriptome serves as a bridge that links genomic variation to phenotypic diversity. A vast number of studies using next-generation RNA sequencing (RNA-seq) over the last 2 decades have emphasized the essential roles of the plant transcriptome in response to developmental and environmental conditions, providing numerous insights into the dynamic changes, evolutionary traces, and elaborate regulation of the plant transcriptome. With substantial improvement in accuracy and throughput, direct RNA sequencing (DRS) has emerged as a new and powerful sequencing platform for precise detection of native and full-length transcripts, overcoming many limitations such as read length and PCR bias that are inherent to short-read RNA-seq. Here, we review recent advances in dissecting the complexity and diversity of plant transcriptomes using DRS as the main technological approach, covering many aspects of RNA metabolism, including novel isoforms, poly(A) tails, and RNA modification, and we propose a comprehensive workflow for processing of plant DRS data. Many challenges to the application of DRS in plants, such as the need for machine learning tools tailored to plant transcriptomes, remain to be overcome, and together we outline future biological questions that can be addressed by DRS, such as allele-specific RNA modification. This technology provides convenient support on which the connection of distinct RNA features is tightly built, sustainably refining our understanding of the biological functions of the plant transcriptome., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Despite being a major human pathogen, limited studies have reported RNA modifications in Acinetobacter baumannii . These post-transcriptional modifications play crucial regulatory roles in bacteria and have also been shown to modulate bacterial virulence. Using nanopore sequencing, we characterized RNA modifications in a virulent A. baumannii strain (Ab-C98) under free-living (mid-exponential phase in vitro culture) and during an early stage of infection (3 h post-infection) in Galleria mellonella larvae. Analysis revealed that m 5 C methylations are essential for ribosome synthesis, while m 6 A and Ψ are involved in metabolic pathways and translation processes. Iron-chelating genes exbD (m 5 C and m 6 A) and feoB (m 6 A and Ψ) and RNA polymerase subunit rpoC (m 6 A and Ψ) were selectively modified during infection. This first transcriptome-wide study highlights the potential regulatory roles of m 5 C, m 6 A and Ψ modifications in A. baumannii during infection.

Nanopore direct RNA sequencing (DRS) provides the direct access to native RNA strands with full-length information, shedding light on rich qualitative and quantitative properties of gene expression profiles. Here with NanoTrans, we present an integrated computational framework that comprehensively covers all major DRS-based application scopes, including isoform clustering and quantification, poly(A) tail length estimation, RNA modification profiling, and fusion gene detection. In addition to its merit in providing such a streamlined one-stop solution, NanoTrans also shines in its workflow-orientated modular design, batch processing capability, all-in-one tabular and graphic report output, as well as automatic installation and configuration supports. Finally, by applying NanoTrans to real DRS datasets of yeast, Arabidopsis, as well as human embryonic kidney and cancer cell lines, we further demonstrate its utility, effectiveness, and efficacy across a wide range of DRS-based application settings., Competing Interests: Conflict of interest The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

RNA transcripts are potential therapeutic targets, yet bacterial transcripts have uncharacterized biodiversity. We developed an algorithm for transcript prediction called tp.py using it to predict transcripts (mRNA and other RNAs) in Escherichia coli K12 and E2348/69 strains (Bacteria:gamma-Proteobacteria), Listeria monocytogenes strains Scott A and RO15 (Bacteria:Firmicute), Pseudomonas aeruginosa strains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), and Haloferax volcanii (Archaea:Halobacteria). From >5 million E. coli K12 and >3 million E. coli E2348/69 newly generated Oxford Nanopore Technologies direct RNA sequencing reads, 2,487 K12 mRNAs and 1,844 E2348/69 mRNAs were predicted, with the K12 mRNAs containing more than half of the predicted E. coli K12 proteins. While the number of predicted transcripts varied by strain based on the amount of sequence data used, across all strains examined, the predicted average size of the mRNAs was 1.6-1.7 kbp, while the median size of the 5'- and 3'-untranslated regions (UTRs) were 30-90 bp. Given the lack of bacterial and archaeal transcript annotation, most predictions were of novel transcripts, but we also predicted many previously characterized mRNAs and ncRNAs, including post-transcriptionally generated transcripts and small RNAs associated with pathogenesis in the E. coli E2348/69 LEE pathogenicity islands. We predicted small transcripts in the 100-200 bp range as well as >10 kbp transcripts for all strains, with the longest transcript for two of the seven strains being the nuo operon transcript, and for another two strains it was a phage/prophage transcript. This quick, easy, and reproducible method will facilitate the presentation of transcripts, and UTR predictions alongside coding sequences and protein predictions in bacterial genome annotation as important resources for the research community.IMPORTANCEOur understanding of bacterial and archaeal genes and genomes is largely focused on proteins since there have only been limited efforts to describe bacterial/archaeal RNA diversity. This contrasts with studies on the human genome, where transcripts were sequenced prior to the release of the human genome over two decades ago. We developed software for the quick, easy, and reproducible prediction of bacterial and archaeal transcripts from Oxford Nanopore Technologies direct RNA sequencing data. These predictions are urgently needed for more accurate studies examining bacterial/archaeal gene regulation, including regulation of virulence factors, and for the development of novel RNA-based therapeutics and diagnostics to combat bacterial pathogens, like those with extreme antimicrobial resistance., Competing Interests: The authors declare no conflict of interest.

RNA modifications are a common occurrence across all domains of life. Several chemical modifications, including N6-methyladenosine, have also been found in viral transcripts and viral RNA genomes. Some of the modifications increase the viral replication efficiency while also helping the virus to evade the host immune system. Nonetheless, there are numerous examples in which the host's RNA modification enzymes function as antiviral factors. Although established methods like MeRIP-seq and miCLIP can provide a transcriptome- wide overview of how viral RNA is modified, it is difficult to distinguish between the complex overlapping viral transcript isoforms using the short read-based techniques. Nanopore direct RNA sequencing (DRS) provides both long reads and direct signal readings, which may carry information about the modifications. Here, we describe a refined protocol for analyzing the RNA modifications in viral transcriptomes using nanopore technology. [ABSTRACT FROM AUTHOR]

The epitranscriptomics of the SARS-CoV-2 infected cell reveals its response to viral replication. Among various types of RNA nucleotide modifications, the m6A is the most common and is involved in several crucial processes of RNA intracellular location, maturation, half-life and translatability. This epitranscriptome contains a mixture of viral RNAs and cellular transcripts. In a previous study we presented the analysis of the SARS-CoV-2 RNA m6A methylation based on direct RNA sequencing and characterized DRACH motif mutations in different viral lineages. Here we present the analysis of the m6A transcript methylation of Vero cells (derived from African Green Monkeys) and Calu-3 cells (human) upon infection by SARS-CoV-2 using direct RNA sequencing data. Analysis of these data by nonparametric statistics and two computational methods (m6anet and EpiNano) show that m6A levels are higher in RNAs of infected cells. Functional enrichment analysis reveals increased m6A methylation of transcripts involved in translation, peptide and amine metabolism. This analysis allowed the identification of differentially methylated transcripts and m6A unique sites in the infected cell transcripts. Results here presented indicate that the cell response to viral infection not only changes the levels of mRNAs, as previously shown, but also its epitranscriptional pattern. Also, transcriptome-wide analysis shows strong nucleotide biases in DRACH motifs of cellular transcripts, both in Vero and Calu-3 cells, which use the signature GGACU whereas in viral RNAs the signature is GAACU. We hypothesize that the differences of DRACH motif biases, might force the convergent evolution of the viral genome resulting in better adaptation to target sequence preferences of writer, reader and eraser enzymes. To our knowledge, this is the first report on m6A epitranscriptome of the SARS-CoV-2 infected Vero cells by direct RNA sequencing, which is the sensu stricto RNA-seq. [ABSTRACT FROM AUTHOR]

Abstract Alternative splicing is a widespread phenomenon, which generates multiple isoforms of the gene product. Reproductive development is the key process for crop production. Although numerous forms of alternative splicing have been identified in model plants, large-scale study of alternative splicing dynamics during reproductive development in rice has not been conducted. Here, we investigated alternative splicing of reproductive development of young panicles (YP), unfertilized florets (UF) and fertilized florets (F) in rice using direct RNA sequencing, small RNA sequencing, and degradome sequencing. We identified a total of 35,317 alternative splicing (AS) events, among which 67.2% splicing events were identified as novel alternative splicing events. Intron retention (IR) was the most abundant alternative splicing subtype. Splicing factors that differentially expressed and alternatively spliced could result in global alternative splicing. Global analysis of miRNAs-targets prediction revealed that alternative spliced transcripts affected miRNAs’ targets during development. Degradome sequencing detected only 6.8% of the differentially alternative splicing transcripts, suggesting a productive transcripts generation during development. In addition, alternative splicing isoforms of Co-like, a transcription factor, interacted with Casein kinase 1-like protein HD1 (CKI) examined in luciferase assay, which could modulate normal male-floral organs development and flowering time. These results reveal that alternative splicing is intensely associated with developmental stages, and a high complexity of gene regulation.

The epitranscriptomics of the SARS-CoV-2 infected cell reveals its response to viral replication. Among various types of RNA nucleotide modifications, the m6A is the most common and is involved in several crucial processes of RNA intracellular location, maturation, half-life and translatability. This epitranscriptome contains a mixture of viral RNAs and cellular transcripts. In a previous study we presented the analysis of the SARS-CoV-2 RNA m6A methylation based on direct RNA sequencing and characterized DRACH motif mutations in different viral lineages. Here we present the analysis of the m6A transcript methylation of Vero cells (derived from African Green Monkeys) and Calu-3 cells (human) upon infection by SARS-CoV-2 using direct RNA sequencing data. Analysis of these data by nonparametric statistics and two computational methods (m6anet and EpiNano) show that m6A levels are higher in RNAs of infected cells. Functional enrichment analysis reveals increased m6A methylation of transcripts involved in translation, peptide and amine metabolism. This analysis allowed the identification of differentially methylated transcripts and m6A unique sites in the infected cell transcripts. Results here presented indicate that the cell response to viral infection not only changes the levels of mRNAs, as previously shown, but also its epitranscriptional pattern. Also, transcriptome-wide analysis shows strong nucleotide biases in DRACH motifs of cellular transcripts, both in Vero and Calu-3 cells, which use the signature GGACU whereas in viral RNAs the signature is GAACU. We hypothesize that the differences of DRACH motif biases, might force the convergent evolution of the viral genome resulting in better adaptation to target sequence preferences of writer, reader and eraser enzymes. To our knowledge, this is the first report on m6A epitranscriptome of the SARS-CoV-2 infected Vero cells by direct RNA sequencing, which is the sensu stricto RNA-seq.

Turnover of messenger RNAs (mRNAs) is a highly regulated process and serves to control expression of RNA molecules and to eliminate aberrant transcripts. Profiling mRNA decay using short-read sequencing methods that target either the 5' or 3' ends of RNAs, overlooks valuable information about the other end, which could provide significant insights into biological aspects and mechanisms of RNA decay. Oxford Nanopore Technology (ONT) is rapidly emerging as a powerful platform for direct sequencing of native, single-RNA molecules. However, as currently designed, the existing ONT platform is unable to sequence the very 5' ends of RNAs and is limited to polyadenylated molecules. Here, we present a detailed step-by-step experimental protocol for True End-to-end RNA Sequencing (TERA-Seq), a new method that addresses ONT's limitations, allowing accurate representation and characterization of RNAs at the level of single molecules. TERA-Seq describes both poly- and non-polyadenylated RNA molecules and accurately identifies their native ends by ligating uniquely designed adapters to the 5' ends (5TERA), the 3' ends (TERA3), or both ends (5TERA3) that are sequenced along with the transcripts., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The cap is a 7-methylguanosine attached to the first messenger RNA (mRNA) nucleotide with a 5'-5' triphosphate bridge. This conserved eukaryotic modification confers stability to the transcripts and is essential for translation initiation. The specific mechanisms that govern transcript cytoplasmic longevity and translatability were always of substantial interest. Multiple works aimed at modeling mRNA decay mechanisms, including the onset of decapping, which is the rate-limiting step of mRNA decay. Additionally, with the recent advances in RNA-based vaccines, the importance of efficient synthesis of fully functional mRNAs has increased. Non-capped mRNAs arising during in vitro transcription are highly immunogenic, and multiple approaches were developed to reduce their levels. Efficient and low-cost methods for elimination of non-capped mRNAs in vitro are therefore essential to basic sciences and to pharmaceutical applications. Here, we present a protocol for heterologous expression and purification of catalytically active recombinant Xrn1 from Thermothelomyces (Myceliophthora) thermophilus (Tt_Xrn1). We also describe protocols needed to verify the enzyme quality., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Direct sequencing of single molecules through nanopores allows for accurate quantification and full-length characterization of native RNA or complementary DNA (cDNA) without amplification. Both nanopore-based native RNA and cDNA approaches involve complex transcriptome procedures at a lower cost. However, there are several differences between the two approaches. In this study, we perform matched native RNA sequencing and cDNA sequencing to enable relevant comparisons and evaluation. Using Saccharomyces cerevisiae, a eukaryotic model organism widely used in industrial biotechnology, two different growing conditions are considered for comparison, including the poly-A messenger RNA isolated from yeast cells grown in minimum media under respirofermentative conditions supplemented with glucose (glucose growth conditions) and from cells that had shifted to ethanol as a carbon source (ethanol growth conditions). Library preparation for direct RNA sequencing is shorter than that for direct cDNA sequencing. The sequence characteristics of the two methods were different, such as sequence yields, quality score of reads, read length distribution, and mapped on reference ability of reads. However, differential gene expression analyses derived from the two approaches are comparable. The unique feature of direct RNA sequencing is RNA modification; we found that the RNA modification at the 5′ end of a transcript was underestimated due to the 3′ bias behavior of the direct RNA sequencing. Our comprehensive evaluation from this work could help researchers make informed choices when selecting an appropriate long-read sequencing method for understanding gene functions, pathways, and detailed functional characterization.

Background Recent studies have disclosed the genome, transcriptome, and epigenetic compositions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the effect of viral infection on gene expression of the host cells. It has been demonstrated that, besides the major canonical transcripts, the viral genome also codes for noncanonical RNA molecules. While the structural characterizations have revealed a detailed transcriptomic architecture of the virus, the kinetic studies provided poor and often misleading results on the dynamics of both the viral and host transcripts due to the low temporal resolution of the infection event and the low virus/cell ratio (multiplicity of infection [MOI] = 0.1) applied for the infection. It has never been tested whether the alteration in the host gene expressions is caused by aging of the cells or by the viral infection. Findings In this study, we used Oxford Nanopore's direct cDNA and direct RNA sequencing methods for the generation of a high-coverage, high temporal resolution transcriptomic dataset of SARS-CoV-2 and of the primate host cells, using a high infection titer (MOI = 5). Sixteen sampling time points ranging from 1 to 96 hours with a varying time resolution and 3 biological replicates were used in the experiment. In addition, for each infected sample, corresponding noninfected samples were employed. The raw reads were mapped to the viral and to the host reference genomes, resulting in 49,661,499 mapped reads (54,62 Gbs). The genome of the viral isolate was also sequenced and phylogenetically classified. Conclusions This dataset can serve as a valuable resource for profiling the SARS-CoV-2 transcriptome dynamics, the virus–host interactions, and the RNA base modifications. Comparison of expression profiles of the host gene in the virally infected and in noninfected cells at different time points allows making a distinction between the effect of the aging of cells in culture and the viral infection. These data can provide useful information for potential novel gene annotations and can also be used for studying the currently available bioinformatics pipelines. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a complex strategy for the transcription of viral subgenomic mRNAs (sgmRNAs), which are targets for nucleic acid diagnostics. Each of these sgmRNAs has a unique 5′ sequence, the leader–transcriptional regulatory sequence gene junction (leader–TRS junction), that can be identified using sequencing. High-resolution sequencing has been used to investigate the biology of SARS-CoV-2 and the host response in cell culture and animal models and from clinical samples. LeTRS, a bioinformatics tool, was developed to identify leader–TRS junctions and can be used as a proxy to quantify sgmRNAs for understanding virus biology. LeTRS is readily adaptable for other coronaviruses such as Middle East respiratory syndrome coronavirus or a future newly discovered coronavirus. LeTRS was tested on published data sets and novel clinical samples from patients and longitudinal samples from animal models with coronavirus disease 2019. LeTRS identified known leader–TRS junctions and identified putative novel sgmRNAs that were common across different mammalian species. This may be indicative of an evolutionary mechanism where plasticity in transcription generates novel open reading frames, which can then subject to selection pressure. The data indicated multiphasic abundance of sgmRNAs in two different animal models. This recapitulates the relative sgmRNA abundance observed in cells at early points in infection but not at late points. This pattern is reflected in some human nasopharyngeal samples and therefore has implications for transmission models and nucleic acid–based diagnostics. LeTRS provides a quantitative measure of sgmRNA abundance from sequencing data. This can be used to assess the biology of SARS-CoV-2 (or other coronaviruses) in clinical and nonclinical samples, especially to evaluate different variants and medical countermeasures that may influence viral RNA synthesis. [ABSTRACT FROM AUTHOR]

Abstract Background SARS-CoV-2, a positive-sense RNA virus in the family Coronaviridae, has caused a worldwide pandemic of coronavirus disease 2019 or COVID-19. Coronaviruses generate a tiered series of subgenomic RNAs (sgRNAs) through a process involving homology between transcriptional regulatory sequences (TRS) located after the leader sequence in the 5′ UTR (the TRS-L) and TRS located near the start of ORFs encoding structural and accessory proteins (TRS-B) near the 3′ end of the genome. In addition to the canonical sgRNAs generated by SARS-CoV-2, non-canonical sgRNAs (nc-sgRNAs) have been reported. However, the consistency of these nc-sgRNAs across viral isolates and infection conditions is unknown. The comprehensive definition of SARS-CoV-2 RNA products is a key step in understanding SARS-CoV-2 pathogenesis. Methods Here, we report an integrative analysis of eight independent SARS-CoV-2 transcriptomes generated using three sequencing strategies, five host systems, and seven viral isolates. Read-mapping to the SARS-CoV-2 genome was used to determine the 5′ and 3′ coordinates of all junctions in viral RNAs identified in these samples. Results Using junctional abundances, we show nc-sgRNAs make up as much as 33% of total sgRNAs in cell culture models of infection, are largely consistent in abundance across independent transcriptomes, and increase in abundance over time during infection. By assessing the homology between sequences flanking the 5′ and 3′ junction points, we show that nc-sgRNAs are not associated with TRS-like homology. By incorporating read coverage information, we find strong evidence for subgenomic RNAs that contain only 5′ regions of ORF1a. Finally, we show that non-canonical junctions change the landscape of viral open reading frames. Conclusions We identify canonical and non-canonical junctions in SARS-CoV-2 sgRNAs and show that these RNA products are consistently generated by many independent viral isolates and sequencing approaches. These analyses highlight the diverse transcriptional activity of SARS-CoV-2 and offer important insights into SARS-CoV-2 biology.

Third-generation sequencing techniques have become increasingly popular due to their capacity to produce long, high-quality reads. Effective comparative analysis across various samples and sequencing platforms is essential for understanding biological mechanisms and establishing benchmark baselines. However, existing tools for long-read sequencing predominantly focus on quality control (QC) and processing for individual samples, complicating the comparison of multiple datasets. The lack of comprehensive tools for data comparison and visualization presents challenges for researchers with limited bioinformatics experience. To address this gap, we present Giraffe (https://github.com/lrslab/Giraffe_View), a Python3-based command-line tool designed for comparative analysis and visualization across diverse samples and platforms. Giraffe facilitates the assessment of read quality, sequencing bias, and genomic regional methylation proportions for both DNA and direct RNA sequencing reads. Its effectiveness has been demonstrated in various scenarios, including comparisons of sequencing methods (whole genome amplification vs. shotgun), sequencing platforms (Oxford Nanopore Technology, ONT vs. Pacific Biosciences, PacBio), tissues (kidney marrow with and without blood), and biological replicates (kidney marrows)., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Nanopore direct RNA sequencing (DRS) enables the capture and full-length sequencing of native RNAs, without recoding or amplification bias. Resulting data sets may be interrogated to define the identity and location of chemically modified ribonucleotides, as well as the length of poly(A) tails, on individual RNA molecules. The success of these analyses is highly dependent on the provision of high-resolution transcriptome annotations in combination with workflows that minimize misalignments and other analysis artifacts. Existing software solutions for generating high-resolution transcriptome annotations are poorly suited to small gene-dense genomes of viruses due to the challenge of identifying distinct transcript isoforms where alternative splicing and overlapping RNAs are prevalent. To resolve this, we identified key characteristics of DRS data sets that inform resulting read alignments and developed the nanopore guided annotation of transcriptome architectures (NAGATA) software package (https://github.com/DepledgeLab/NAGATA). We demonstrate, using a combination of synthetic and original DRS data sets derived from adenoviruses, herpesviruses, coronaviruses, and human cells, that NAGATA outperforms existing transcriptome annotation software and yields a consistently high level of precision and recall when reconstructing both gene sparse and gene-dense transcriptomes. Finally, we apply NAGATA to generate the first high-resolution transcriptome annotation of the neglected pathogen human adenovirus type F41 (HAdV-41) for which we identify 77 distinct transcripts encoding at least 23 different proteins., Importance: The transcriptome of an organism denotes the full repertoire of encoded RNAs that may be expressed. This is critical to understanding the biology of an organism and for accurate transcriptomic and epitranscriptomic-based analyses. Annotating transcriptomes remains a complex task, particularly in small gene-dense organisms such as viruses which maximize their coding capacity through overlapping RNAs. To resolve this, we have developed a new software nanopore guided annotation of transcriptome architectures (NAGATA) which utilizes nanopore direct RNA sequencing (DRS) datasets to rapidly produce high-resolution transcriptome annotations for diverse viruses and other organisms., Competing Interests: The authors declare no conflict of interest.

Fast and accurate identification of microbial pathogens is critical for the proper treatment of infections. Traditional culture‐based diagnosis in clinics is increasingly supplemented by metagenomic next‐generation‐sequencing (mNGS). Here, RNA/cDNA‐targeted sequencing (meta‐transcriptomics using NGS (mtNGS)) is established to reduce the host nucleotide percentage in clinic samples and by combining with Oxford Nanopore Technology (ONT) platforms (meta‐transcriptomics using third‐generation sequencing, mtTGS) to improve the sequencing time. It shows that mtNGS improves the ratio of microbial reads, facilitates bacterial identification using multiple‐strategies, and discovers fungi, viruses, and antibiotic resistance genes, and displaying agreement with clinical findings. Furthermore, longer reads in mtTGS lead to additional improvement in pathogen identification and also accelerate the clinical diagnosis. Additionally, primary tests utilizing direct‐RNA sequencing and targeted sequencing of ONT show that ONT displays important potential but must be further developed. This study presents the potential of RNA‐targeted pathogen identification in clinical samples, especially when combined with the newest developments in ONT. [ABSTRACT FROM AUTHOR]

The covalent modification of RNA molecules is a pervasive feature of all classes of RNAs and has fundamental roles in the regulation of several cellular processes. Mapping the location of RNA modifications transcriptome-wide is key to unveiling their role and dynamic behaviour, but technical limitations have often hampered these efforts. Nanopore direct RNA sequencing is a third-generation sequencing technology that allows the sequencing of native RNA molecules, thus providing a direct way to detect modifications at single-molecule resolution. Despite recent advances, the analysis of nanopore sequencing data for RNA modification detection is still a complex task that presents many challenges. Many works have addressed this task using different approaches, resulting in a large number of tools with different features and performances. Here we review the diverse approaches proposed so far and outline the principles underlying currently available algorithms. [ABSTRACT FROM AUTHOR]

Abstract Fast and accurate identification of microbial pathogens is critical for the proper treatment of infections. Traditional culture‐based diagnosis in clinics is increasingly supplemented by metagenomic next‐generation‐sequencing (mNGS). Here, RNA/cDNA‐targeted sequencing (meta‐transcriptomics using NGS (mtNGS)) is established to reduce the host nucleotide percentage in clinic samples and by combining with Oxford Nanopore Technology (ONT) platforms (meta‐transcriptomics using third‐generation sequencing, mtTGS) to improve the sequencing time. It shows that mtNGS improves the ratio of microbial reads, facilitates bacterial identification using multiple‐strategies, and discovers fungi, viruses, and antibiotic resistance genes, and displaying agreement with clinical findings. Furthermore, longer reads in mtTGS lead to additional improvement in pathogen identification and also accelerate the clinical diagnosis. Additionally, primary tests utilizing direct‐RNA sequencing and targeted sequencing of ONT show that ONT displays important potential but must be further developed. This study presents the potential of RNA‐targeted pathogen identification in clinical samples, especially when combined with the newest developments in ONT.

Summary: The Human Genome Project opened an era of (epi)genomic research, and also provided a platform for the development of new sequencing technologies. During and after the project, several sequencing technologies continue to dominate nucleic acid sequencing markets. Currently, Illumina (short-read), PacBio (long-read), and Oxford Nanopore (long-read) are the most popular sequencing technologies. Unlike PacBio or the popular short-read sequencers before it, which, as examples of the second or so-called Next-Generation Sequencing platforms, need to synthesize when sequencing, nanopore technology directly sequences native DNA and RNA molecules. Nanopore sequencing, therefore, avoids converting mRNA into cDNA molecules, which not only allows for the sequencing of extremely long native DNA and full-length RNA molecules but also document modifications that have been made to those native DNA or RNA bases. In this review on direct DNA sequencing and direct RNA sequencing using Oxford Nanopore technology, we focus on their development and application achievements, discussing their challenges and future perspective. We also address the problems researchers may encounter applying these approaches in their research topics, and how to resolve them. Public summary: • Nanopore-seq can dissect native DNA/RNA molecules from any organisms at unlimited length • A wide variety of algorithms greatly increase the accuracy of signal decoding in Nanopore-Seq • Nanopore-Seq significantly facilitates genome assembly and structural variant calling, and can simultaneously detect base modifications • These advantages ensure its great potentials in future medical and agricultural practices

Short-read, high-throughput sequencing (HTS) methods have yielded numerous important insights into microbial ecology and function. Yet, in many instances short-read HTS techniques are suboptimal, for example, by providing insufficient phylogenetic resolution or low integrity of assembled genomes. Single-molecule and synthetic long-read (SLR) HTS methods have successfully ameliorated these limitations. In addition, nanopore sequencing has generated a number of unique analysis opportunities, such as rapid molecular diagnostics and direct RNA sequencing, and both Pacific Biosciences (PacBio) and nanopore sequencing support detection of epigenetic modifications. Although initially suffering from relatively low sequence quality, recent advances have greatly improved the accuracy of long-read sequencing technologies. In spite of great technological progress in recent years, the long-read HTS methods (PacBio and nanopore sequencing) are still relatively costly, require large amounts of high-quality starting material, and commonly need specific solutions in various analysis steps. Despite these challenges, long-read sequencing technologies offer high-quality, cutting-edge alternatives for testing hypotheses about microbiome structure and functioning as well as assembly of eukaryote genomes from complex environmental DNA samples. [ABSTRACT FROM AUTHOR]

Alternative splicing is a widespread phenomenon, which generates multiple isoforms of the gene product. Reproductive development is the key process for crop production. Although numerous forms of alternative splicing have been identified in model plants, large-scale study of alternative splicing dynamics during reproductive development in rice has not been conducted. Here, we investigated alternative splicing of reproductive development of young panicles (YP), unfertilized florets (UF) and fertilized florets (F) in rice using direct RNA sequencing, small RNA sequencing, and degradome sequencing. We identified a total of 35,317 alternative splicing (AS) events, among which 67.2% splicing events were identified as novel alternative splicing events. Intron retention (IR) was the most abundant alternative splicing subtype. Splicing factors that differentially expressed and alternatively spliced could result in global alternative splicing. Global analysis of miRNAs-targets prediction revealed that alternative spliced transcripts affected miRNAs' targets during development. Degradome sequencing detected only 6.8% of the differentially alternative splicing transcripts, suggesting a productive transcripts generation during development. In addition, alternative splicing isoforms of Co-like, a transcription factor, interacted with Casein kinase 1-like protein HD1 (CKI) examined in luciferase assay, which could modulate normal male-floral organs development and flowering time. These results reveal that alternative splicing is intensely associated with developmental stages, and a high complexity of gene regulation. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A) is the most abundant internal messenger RNA (mRNA) modification, contributing to the processing, stability, and function of methylated RNAs. Methylation occurs in the nucleus during pre-mRNA synthesis and requires a core methyltransferase complex consisting of METTL3, METTL14, and WTAP. During herpes simplex virus (HSV-1) infection, cellular gene expression is profoundly suppressed, allowing the virus to monopolize the host transcription and translation apparatus and antagonize antiviral responses. The extent to which HSV-1 uses or manipulates the m6A pathway is not known. Here, we show that, in primary fibroblasts, HSV-1 orchestrates a striking redistribution of the nuclear m6A machinery that progresses through the infection cycle. METTL3 andMETTL14 are dispersed into the cytoplasm, whereas WTAP remains nuclear. Other regulatory subunits of the methyltransferase complex, along with the nuclear m6A-modified RNA binding protein YTHDC1 and nuclear demethylase ALKBH5, are similarly redistributed. These changes require ICP27, a viral regulator of host mRNA processing that mediates the nucleocytoplasmic export of viral late mRNAs. Viral gene expression is initially reduced by small interfering RNA (siRNA)-mediated inactivation of the m6A methyltransferase but becomes less impacted as the infection advances. Redistribution of the nuclear m6A machinery is accompanied by a wide-scale reduction in the installation of m6A and other RNAmodifications on both host and viral mRNAs. These results reveal a far-reaching mechanism by which HSV-1 subverts host gene expression to favor viral replication. [ABSTRACT FROM AUTHOR]

Abstract Background Alternative polyadenylation is commonly examined using cDNA sequencing, which is known to be affected by template-switching artifacts. However, the effects of such template-switching artifacts on alternative polyadenylation are generally disregarded, while alternative polyadenylation artifacts are attributed to internal priming. Results Here, we analyzed both long-read cDNA sequencing and direct RNA sequencing data of two organisms, generated by different sequencing platforms. We developed a filtering algorithm which takes into consideration that template-switching can be a source of artifactual polyadenylation when filtering out spurious polyadenylation sites. The algorithm outperformed the conventional internal priming filters based on comparison to direct RNA sequencing data. We also showed that the polyadenylation artifacts arise in cDNA sequencing at consecutive stretches of as few as three adenines. There was no substantial difference between the lengths of poly(A) tails at the artifactual and the true transcriptional end sites even though it is expected that internal priming artifacts have shorter poly(A) tails than genuine polyadenylated reads. Conclusions Our findings suggest that template switching plays an important role in the generation of spurious polyadenylation and support the need for more rigorous filtering of artifactual polyadenylation sites in cDNA data, or that alternative polyadenylation should be annotated using native RNA sequencing.

Abstract Current technologies for targeted characterization and manipulation of viral RNA primarily involve amplification or ultracentrifugation with isopycnic gradients of viral particles to decrease host RNA background. The former strategy is non-compatible for characterizing properties innate to RNA strands such as secondary structure, RNA–RNA interactions, and also for nanopore direct RNA sequencing involving the sequencing of native RNA strands. The latter strategy, ultracentrifugation, causes loss in genomic information due to its inability to retrieve unassembled viral RNA. To address this, we developed a novel application of current nucleic acid hybridization technologies for direct characterization of RNA. In particular, we modified a current enrichment protocol to capture whole viral native RNA genomes for downstream RNA assays to circumvent the abovementioned problems. This technique involves hybridization of biotinylated baits at 500 nucleotides (nt) intervals, stringent washes and release of free native RNA strands using DNase I treatment, with a turnaround time of about 6 h 15 min. RT-qPCR was used as the primary proof of concept that capture-based purification indeed removes host background. Subsequently, capture-based purification was applied to direct RNA sequencing as proof of concept that capture-based purification can be coupled with downstream RNA assays. We report that this protocol was able to successfully purify viral RNA by 561- to 791-fold. We also report that application of this protocol to direct RNA sequencing yielded a reduction in human host RNA background by 1580-fold, a 99.91% recovery of viral genome with at least 15× coverage, and a mean coverage across the genome of 120×. This report is, to the best of our knowledge, the first description of a capture-based purification method for assays that involve direct manipulation or characterisation of native RNA. This report also describes a successful application of capture-based purification as a direct RNA sequencing strategy that addresses certain limitations of current strategies in sequencing RNA viral genomes.

An increasing number of viruses are continuously being found in a wide range of organisms, including fungi. Recent studies have revealed a wide viral diversity in microbes and a potential importance of these viruses in the natural environment. Although virus exploration has been accelerated by short-read, high-throughput sequencing (HTS), and viral de novo sequencing is still challenging because of several biological/molecular features such as micro-diversity and secondary structure of RNA genomes. This study conducted de novo sequencing of multiple double-stranded (ds) RNA (dsRNA) elements that were obtained from fungal viruses infecting two Fusarium sambucinum strains, FA1837 and FA2242, using conventional HTS and long-read direct RNA sequencing (DRS). De novo assembly of the read data from both technologies generated near-entire genomic sequence of the viruses, and the sequence homology search and phylogenetic analysis suggested that these represented novel species of the Hypoviridae, Totiviridae, and Mitoviridae families. However, the DRS-based consensus sequences contained numerous indel errors that differed from the HTS consensus sequences, and these errors hampered accurate open reading frame (ORF) prediction. Although with its present performance, the use of DRS is premature to determine viral genome sequences, the DRS-mediated sequencing shows great potential as a user-friendly platform for a one-shot, whole-genome sequencing of RNA viruses due to its long-reading ability and relative structure-tolerant nature.

Genes involved in disease resistance are some of the fastest evolving and most diverse components of genomes. Large numbers of nucleotide-binding, leucine-rich repeat (NLR) genes are found in plant genomes and are required for disease resistance. However, NLRs can trigger autoimmunity, disrupt beneficial microbiota or reduce fitness. It is therefore crucial to understand how NLRs are controlled. Here, we show that the RNA-binding protein FPA mediates widespread premature cleavage and polyadenylation of NLR transcripts, thereby controlling their functional expression and impacting immunity. Using long-read Nanopore direct RNA sequencing, we resolved the complexity of NLR transcript processing and gene annotation. Our results uncover a co-transcriptional layer of NLR control with implications for understanding the regulatory and evolutionary dynamics of NLRs in the immune responses of plants.

An increasing number of viruses are continuously being found in a wide range of organisms, including fungi. Recent studies have revealed a wide viral diversity in microbes and a potential importance of these viruses in the natural environment. Although virus exploration has been accelerated by short-read, high-throughput sequencing (HTS), and viral de novo sequencing is still challenging because of several biological/molecular features such as micro-diversity and secondary structure of RNA genomes. This study conducted de novo sequencing of multiple double-stranded (ds) RNA (dsRNA) elements that were obtained from fungal viruses infecting two Fusarium sambucinum strains, FA1837 and FA2242, using conventional HTS and long-read direct RNA sequencing (DRS). De novo assembly of the read data from both technologies generated near-entire genomic sequence of the viruses, and the sequence homology search and phylogenetic analysis suggested that these represented novel species of the Hypoviridae , Totiviridae , and Mitoviridae families. However, the DRS-based consensus sequences contained numerous indel errors that differed from the HTS consensus sequences, and these errors hampered accurate open reading frame (ORF) prediction. Although with its present performance, the use of DRS is premature to determine viral genome sequences, the DRS-mediated sequencing shows great potential as a user-friendly platform for a one-shot, whole-genome sequencing of RNA viruses due to its long-reading ability and relative structure-tolerant nature. [ABSTRACT FROM AUTHOR]

Foot-and-mouth disease (FMD) is a severe and extremely contagious viral disease of cloven-hoofed domestic and wild animals, which leads to serious economic losses to the livestock industry globally. FMD is caused by the FMD virus (FMDV), a positive-strand RNA virus that belongs to the genus Aphthovirus, within the family Picornaviridae. Early detection and characterization of FMDV strains are key factors to control new outbreaks and prevent the spread of the disease. Here, we describe a direct RNA sequencing method using Oxford Nanopore Technology (ONT) Flongle flow cells on MinION Mk1C (or GridION) to characterize FMDV. This is a rapid, low cost, and easily deployed point of care (POC) method for a near real-time characterization of FMDV in endemic areas or outbreak investigation sites. Key features • Saves ~35 min of the original protocol time by omitting the reverse transcription step and lowers the costs of reagents and consumables. • Replaces the GridION flow cell from the original protocol with the Flongle, which saves ~90% on the flow cell cost. • Combines the NGS benchwork with a modified version of our African swine fever virus (ASFV) fast analysis pipeline to achieve FMDV characterization within minutes. Graphical overview Schematic of direct RNA sequencing of foot-and-mouth disease virus (FMDV) process, which takes ~50 min from extracted RNA to final loading, modified from the ONT SQK-RNA002 protocol (Version: DRS_9080_v2_revO_14Aug2019)., Competing Interests: Competing interestsThe authors declare no conflicts of interest., (©Copyright : © 2024 The Authors; This is an open access article under the CC BY 4.0 license.)

Nonsense-mediated mRNA decay (NMD) is a system that controls the quality of mRNA transcripts in eukaryotes by degradation of aberrant transcripts in a pioneer round of translation. In mammals, NMD targets one-third of mutated, disease-causing mRNAs and ∼10% of unmutated mRNAs, facilitating appropriate cellular responses to environmental changes [1]. In plants, NMD plays an important role in development and regulating abiotic and biotic stress responses [2]. The transcripts with premature termination codons (PTCs), upstream ORFs or long 3′-UTRs can be targeted to NMD. It was shown that alternative splicing plays a crucial role in regulation of NMD triggering, for example, by the introduction of a PTC in transcripts. Therefore, the correct identification of mRNA isoforms is a key step in the study of the principles of regulation of the cell transcriptome by the NMD pathway. Here, we performed long-read sequencing of Physcomitrella (Physcomitrium patens) mutant smg1Δ line 2 native transcriptome by Oxford Nanopore Technology (ONT). The smg1Δ is a knockout (KO) mutant deficient in SMG1 kinase is a key component of NMD system in plants and animals [3]. RNA was isolated with Trizol from 5 day old protonemata and sequenced using kit SQK-RNA002, flow cells FLO-MIN106 and a MinION device (Oxford Nanopore Technologies Ltd., UK (ONT)) in three biological repeats. Basecalling was performed with Guppy v.4.0.15. The presented transcriptomes give advantages in the identification and functional characterization of RNA transcripts that are direct targets of the Nonsense-mediated mRNA decay system.

It has been known for a few decades that transcripts can be marked by dozens of different modifications. Yet, we are just at the beginning of charting these marks and understanding their functional impact. High-quality methods were developed for the profiling of some of these marks, and approaches to finely study their impact on specific phases of the RNA life-cycle are available, including RNA metabolic labeling. Thanks to these improvements, the most abundant marks, including N6-methyladenosine, are emerging as important determinants of the fate of marked RNAs. However, we still lack approaches to directly study how the set of marks for a given RNA molecule shape its fate. In this perspective, we first review current leading approaches in the field. Then, we propose an experimental and computational setup, based on direct RNA sequencing and mathematical modeling, to decipher the functional consequences of RNA modifications on the fate of individual RNA molecules and isoforms.

The direct RNA sequencing platform offered by Oxford Nanopore Technologies allows for direct measurement of RNA molecules without the need of conversion to complementary DNA, fragmentation or amplification. As such, it is virtually capable of detecting any given RNA modification present in the molecule that is being sequenced, as well as provide polyA tail length estimations at the level of individual RNA molecules. Although this technology has been publicly available since 2017, the complexity of the raw Nanopore data, together with the lack of systematic and reproducible pipelines, have greatly hindered the access of this technology to the general user. Here we address this problem by providing a fully benchmarked workflow for the analysis of direct RNA sequencing reads, termed MasterOfPores. The pipeline starts with a pre-processing module, which converts raw current intensities into multiple types of processed data including FASTQ and BAM, providing metrics of the quality of the run, quality-filtering, demultiplexing, base-calling and mapping. In a second step, the pipeline performs downstream analyses of the mapped reads, including prediction of RNA modifications and estimation of polyA tail lengths. Four direct RNA MinION sequencing runs can be fully processed and analyzed in 10 h on 100 CPUs. The pipeline can also be executed in GPU locally or in the cloud, decreasing the run time fourfold. The software is written using the NextFlow framework for parallelization and portability, and relies on Linux containers such as Docker and Singularity for achieving better reproducibility. The MasterOfPores workflow can be executed on any Unix-compatible OS on a computer, cluster or cloud without the need of installing any additional software or dependencies, and is freely available in Github (https://github.com/biocorecrg/master_of_pores). This workflow simplifies direct RNA sequencing data analyses, facilitating the study of the (epi)transcriptome at single molecule resolution.