Nanopore sequencing of RNA and cDNA molecules in Escherichia coli

Quantitative and Multiplexing Analysis of MicroRNAs by Direct Full-Length Sequencing in Nanopores

MicroRNAs (miRNAs) play important regulatory roles in biology. Direct sequencing of miRNAs in full-length can reveal comprehensive information on their sequences, abundance, and modifications, which, however, has yet to be achieved due to their extremely short length (∼22 nt). Herein, we developed Direct-miR-seq, a nanopore-based direct RNA sequencing (DRS) method that elongates miRNAs at both the 5' and 3' ends by ligating with custom nucleic acid adaptors to ensure full-length sequencing of miRNAs with high yield and accuracy. Compared to standard DRS, Direct-miR-seq enabled sequencing of the whole sequence of miRNAs, achieved a 26-fold sequencing yield, and exhibited reduced bias across miRNA species along with low sequencing error rates. We applied Direct-miR-seq to native RNA populations from cells and human serum to demonstrate its capability to selectively capture miRNAs of known sequences in complex RNA environments for revealing quantitative information in abundance and m6A modification at single-molecule and single-base resolution of ∼100 miRNA species in a single sequencing event. We envision that Direct-miR-seq may be translated toward a variety of biological and medical applications by sequencing miRNAs and other small RNAs.

Automation of RNA-Seq Sample Preparation and Miniaturized Parallel Bioreactors Enable High-Throughput Differential Gene Expression Studies

A powerful strategy to accelerate bioprocess development is to complement parallel bioreactor systems with an automated approach, often achieved using liquid handling stations. The benefit of such high-throughput experiments is determined by the employed monitoring procedures. To gain a molecular understanding of the microbial production strains in miniaturized parallel single-use bioreactors, we extended the at-line monitoring procedures to transcriptome analysis in a parallel approach using RNA-Seq. To perform automated RNA-Seq experiments, we developed a sample preparation workflow consisting of at-line cell disruption by enzymatic cell lysis, total RNA extraction, nucleic acid concentration normalization, and Nanopore cDNA Library preparation. The pH-controlled aerobic batch growth of Saccharomyces cerevisiae was studied with six different carbon sources (glucose, pyruvate, fructose, galactose, sucrose, and mannose) on a 11 mL scale using 24 parallel stirred tank bioreactors integrated into a liquid handling station while performing at-line sample preparation for RNA-Seq on the same deck. With four biological replicates per condition, 24 cDNA libraries were prepared over 11.5 h. Off-line Nanopore sequencing yielded 20.97 M classified reads with a Q-score > 9. Differential gene expression analysis revealed significant differences in transcriptomic profiles when comparing growth with glucose (exponential growth) to growth with pyruvate (stress conditions), allowing identification of 674 downregulated and 709 upregulated genes. Insignificant changes in gene expression patterns were measured when comparing growth with glucose and fructose, yielding only 64 differentially expressed genes. The expected differences in cellular responses identified in this study show a promising approach for transcriptomic profiling of bioreactor cultures, providing valuable insights on a molecular level at-line in a high-throughput fashion.

A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines

The human genome contains instructions to transcribe more than 200,000 RNAs. However, many RNA transcripts are generated from the same gene, resulting in alternative isoforms that are highly similar and that remain difficult to quantify. To evaluate the ability to study RNA transcript expression, we profiled seven human cell lines with five different RNA-sequencing protocols, including short-read cDNA, Nanopore long-read direct RNA, amplification-free direct cDNA and PCR-amplified cDNA sequencing, and PacBio IsoSeq, with multiple spike-in controls, and additional transcriptome-wide N6-methyladenosine profiling data. We describe differences in read length, coverage, throughput and transcript expression, reporting that long-read RNA sequencing more robustly identifies major isoforms. We illustrate the value of the SG-NEx data to identify alternative isoforms, novel transcripts, fusion transcripts and N6-methyladenosine RNA modifications. Together, the SG-NEx data provide a comprehensive resource enabling the development and benchmarking of computational methods for profiling complex transcriptional events at isoform-level resolution.

Direct RNA sequencing of the Escherichia coli epitranscriptome uncovers alterations under heat stress

Modifications of RNA, known as the epitranscriptome, affect gene expression, translation, and splicing in eukaryotes, with implications for developmental processes, cancer, and viral infections. In prokaryotes, regulation at the level of the epitranscriptome is still poorly understood. Here, we used nanopore direct RNA sequencing of Escherichia coli to study RNA modifications and their changes under heat stress. With a single sequencing reaction, we detected most known modification types in ribosomal RNA (rRNA), transfer RNA (tRNA), and messenger RNA (mRNA). RNA sequencing was complemented by a multifaceted approach that included mass spectrometry, deletion mutants, single-nucleotide polymerase chain reaction, and in vitro methylation. Known 5-methylcytidine (m5C) and N6-methyladenosine (m6A) sites in the rRNA were confirmed, but these types of modifications could not be localized in the mRNA. In response to heat stress, levels of m5C, m6A, and N6,N6-dimethyladenosine increased in the 16S rRNA. Sequencing and mass spectrometry data demonstrated a decrease in tRNA modification abundance in the anticodon loop at 45°C. In general, mRNA modifications at 37°C were enriched in the coding regions of genes associated with general metabolism and RNA processing, which shifted to genes involved in cell wall synthesis and membrane transport under heat stress. This study provides new insights into the complexity of post-transcriptional regulation in bacteria.

RIBOSS detects novel translational events by combining long- and short-read transcriptome and translatome profiling

Ribosome profiling is a high-throughput sequencing technique that captures the positions of translating ribosomes on RNAs. Recent advancements in ribosome profiling include achieving highly phased ribosome footprints for plant translatomes and more recently for bacterial translatomes. This substantially increases the specificity of detecting open reading frames (ORFs) that can be translated, such as small ORFs located upstream and downstream of the annotated ORFs. However, most genomes (e.g. bacterial genomes) lack the annotations for the transcription start and termination sites. This hinders the systematic discovery of novel ORFs in the 'untranslated' regions in ribosome profiling data. Here, we develop a new computational pipeline called RIBOSS to discover noncanonical ORFs and assess their translational potential against annotated ORFs. The RIBOSS Python modules are versatile, and we use them to analyse both prokaryotic and eukaryotic data. We present a resulting list of noncanonical ORFs with high translational potential in Homo sapiens, Arabidopsis thaliana, and Salmonella enterica. We further illustrate RIBOSS utility when studying organisms with incomplete transcriptome annotations. We leverage long-read and short-read data for reference-guided transcriptome assembly and highly phased ribosome profiling data for detecting novel translational events in the assembled transcriptome for S. enterica. In sum, RIBOSS is the first integrated computational pipeline for noncanonical ORF detection and translational potential assessment that incorporates long- and short-read sequencing technologies to investigate translation. RIBOSS is freely available at https://github.com/lcscs12345/riboss.

Methanotroph Methylotuvimicrobium alcaliphilum 20Z-3E as a fumarate producer: transcriptomic analysis and the role of malic enzyme

The halotolerant obligate methanotroph Methylotuvimicrobium alcaliphilum 20Z is a promising biotechnological strain that has been repeatedly tested as a producer of high-added-value polycarbon compounds. The mutant M. alcaliphilum 20Z-3E lacking two fumarases and a malic enzyme is a potential fumarate producer. The analysis of strand-specific 3'-end sequencing of mRNA did not reveal any effects of the mutations on the central metabolism of the methanotroph; however, it showed a dramatic change in the expression of putative iron transport genes, as well as some genes associated with stress response. When the strain 20Z-3E grows at low salinity under methane, some part of fumarate is formed from aspartate, since the increase in salinity results in the biosynthesis of ectoine and the decrease in fumarate concentration. However, when the strain grows on methanol, the fumarate pool is lower and does not depend on the salinity of the medium. Our results have shown that deletion of the mae gene encoding malic enzyme makes a significant contribution to the fumarate accumulation. The strain 20Z-2F with the deletion of only two genes, fumI and fumII, demonstrated delayed growth under methane in comparison with 20Z and 20Z-3E strains. The branching of the tricarboxylic acid cycle due to the adenylosuccinate shunt, as well as the presence of malic enzyme, provides metabolic flexibility to M. alcaliphilum, which allows the methanotroph to adapt to a variety of external conditions and, on the other hand, us to modify its genome to obtain valuable products.

Gene expression regulation and polyadenylation in ulcerative colitis via long-chain RNA sequencing

BACKGROUND

Ulcerative colitis (UC) is an immune-mediated chronic intestinal disease, with a pathogenesis that remains incompletely understood. The purpose of this study is to analyze the difference of gene expression between UC patients and healthy controls using Oxford Nanopore Technology's long-read RNA sequencing (ONT-RNA-seq) and to explore how alternative polyadenylation (APA) site selection contributes to UC pathogenesis.

METHODS

Colon tissue samples from UC and normal controls (NC) were collected, and total RNA was extracted and sequenced using ONT-RNA-seq technology. Various bioinformatics analyses were performed, including differential expression gene (DEG) analysis, functional enrichment analysis, APA site analysis, and prediction miRNAs and RNA binding proteins (RBPs) targets, to explore the molecular mechanism underlying UC.

RESULTS

ONT-RNA-seq analysis revealed that the expression levels of ACSF2, NPY, SLC26A3, BRINP3, and PKLPP2 were significantly lower in UC patients compared to the NC group, while the expression levels of CCL20, CCL21, CD55, IDO1, LCN2, NOS2, CCL11, OLFM4, ANXA1, REG1A, S100A9, SLPI, SPINK1, and AGR2 were significantly higher. Functional enrichment analysis showed that DEGs were closely related to immune and inflammatory responses, which in turn are related to many challenges in the diagnosis and treatment of UC. Mechanistically, APA site selection was found to contribute to the regulation of gene expression in UC, and some APA genes were identified as potential regulators of miRNAs and RBPs. Vene diagram revealed significant overlap between miRNA- and RBP-targeted genes and DEGs, suggesting that APA genes may modulate genes expression in UC through miRNA and RBP targeting. Additionally, five key APA genes--CD38, NCALD, SMIM31, GPX7, and SWAP70--were identified as potentially playing crucial role in UC pathogenesis.

CONCLUSIONS

This study provides new insights into the molecular mechanisms of UC through ONT-RNA-seq technology, especially in gene expression regulation and APA site selection.

Enhancing novel isoform discovery: leveraging nanopore long-read sequencing and machine learning approaches

Long-read sequencing technologies can capture entire RNA transcripts in a single sequencing read, reducing the ambiguity in constructing and quantifying transcript models in comparison to more common and earlier methods, such as short-read sequencing. Recent improvements in the accuracy of long-read sequencing technologies have expanded the scope for novel splice isoform detection and have also enabled a far more accurate reconstruction of complex splicing patterns and transcriptomes. Additionally, the incorporation and advancements of machine learning and deep learning algorithms in bioinformatic software have significantly improved the reliability of long-read sequencing transcriptomic studies. However, there is a lack of consensus on what bioinformatic tools and pipelines produce the most precise and consistent results. Thus, this review aims to discuss and compare the performance of available methods for novel isoform discovery with long-read sequencing technologies, with 25 tools being presented. Furthermore, this review intends to demonstrate the need for developing standard analytical pipelines, tools, and transcript model conventions for novel isoform discovery and transcriptomic studies.

Nanopore sequencing: flourishing in its teenage years

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.

Challenges in identifying mRNA transcript starts and ends from long-read sequencing data

Long-read sequencing (LRS) technologies have the potential to revolutionize scientific discoveries in RNA biology through the comprehensive identification and quantification of full-length mRNA isoforms. Despite great promise, challenges remain in the widespread implementation of LRS technologies for RNA-based applications, including concerns about low coverage, high sequencing error, and robust computational pipelines. Although much focus has been placed on defining mRNA exon composition and structure with LRS data, less careful characterization has been done of the ability to assess the terminal ends of isoforms, specifically, transcription start and end sites. Such characterization is crucial for completely delineating full mRNA molecules and regulatory consequences. However, there are substantial inconsistencies in both start and end coordinates of LRS reads spanning a gene, such that LRS reads often fail to accurately recapitulate annotated or empirically derived terminal ends of mRNA molecules. Here, we describe the specific challenges of identifying and quantifying mRNA terminal ends with LRS technologies and how these issues influence biological interpretations of LRS data. We then review recent experimental and computational advances designed to alleviate these problems, with ideal use cases for each approach. Finally, we outline anticipated developments and necessary improvements for the characterization of terminal ends from LRS data.

Direct RNA sequencing in plants: Practical applications and future perspectives

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.

A Genomic Language Model for Chimera Artifact Detection in Nanopore Direct RNA Sequencing

Chimera artifacts in nanopore direct RNA sequencing (dRNA-seq) can significantly distort transcriptome analyses, yet their detection and removal remain challenging due to limitations in existing basecalling models. We present DeepChopper, a genomic language model that precisely identifies and removes adapter sequences from base-called dRNA-seq long reads at single-base resolution, operating independently of raw signal or alignment information to effectively eliminate chimeric read artifacts. By removing these artifacts, DeepChopper substantially improves the accuracy of critical downstream analyses, such as transcript annotation and gene fusion detection, thereby enhancing the reliability and utility of nanopore dRNA-seq for transcriptomics research.

Deciphering transcript architectural complexity in bacteria and archaea

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.

Comparison of direct cDNA and PCR-cDNA Nanopore sequencing of RNA from Escherichia coli isolates

Whole-transcriptome (long-read) RNA sequencing (Oxford Nanopore Technologies, ONT) holds promise for reference-agnostic analysis of differential gene expression in pathogenic bacteria, including for antimicrobial resistance genes (ARGs). However, direct cDNA ONT sequencing requires large concentrations of polyadenylated mRNA, and amplification protocols may introduce technical bias. Here we evaluated the impact of direct cDNA- and cDNA PCR-based ONT sequencing on transcriptomic analysis of clinical Escherichia coli. Four E. coli bloodstream infection-associated isolates (n=2 biological replicates per isolate) were sequenced using the ONT Direct cDNA Sequencing SQK-DCS109 and PCR-cDNA Barcoding SQK-PCB111.24 kits. Biological and technical replicates were distributed over eight flow cells using 16 barcodes to minimize batch/barcoding bias. Reads were mapped to a transcript reference and transcript abundance was quantified after in silico depletion of low-abundance and rRNA genes. We found there were strong correlations between read counts using both kits and when restricting the analysis to include only ARGs. We highlighted that correlations were weaker for genes with a higher GC content. Read lengths were longer for the direct cDNA kit compared to the PCR-cDNA kit whereas total yield was higher for the PCR-cDNA kit. In this small but methodologically rigorous evaluation of biological and technical replicates of isolates sequenced with the direct cDNA and PCR-cDNA ONT sequencing kits, we demonstrated that PCR-based amplification substantially improves yield with largely unbiased assessment of core gene and ARG expression. However, users of PCR-based kits should be aware of a small risk of technical bias which appears greater for genes with an unusually high (>52%)/low (<44%) GC content.

Direct nanopore RNA sequencing of umbra-like virus-infected plants reveals long non-coding RNAs, specific cleavage sites, D-RNAs, foldback RNAs, and temporal- and tissue-specific profiles

The traditional view of plus (+)-strand RNA virus transcriptomes is that infected cells contain a limited variety of viral RNAs, such as full-length (+)-strand genomic RNA(s), (-)-strand replication intermediate(s), 3' co-terminal subgenomic RNA(s), and viral recombinant defective (D)-RNAs. To ascertain the full complement of viral RNAs associated with the simplest plant viruses, long-read direct RNA nanopore sequencing was used to perform transcriptomic analyses of two related umbra-like viruses: citrus yellow vein-associated virus (CY1) from citrus and CY2 from hemp. Analysis of different timepoints/tissues in CY1- and CY2-infected Nicotiana benthamiana plants and CY2-infected hemp revealed: (i) three 5' co-terminal RNAs of 281 nt, 442 nt and 671 nt, each generated by a different mechanism; (ii) D-RNA populations containing the 671 fragment at their 5'ends; (iii) many full-length genomic RNAs and D-RNAs with identical 3'end 61 nt truncations; (iv) virtually all (-)-strand reads missing 3 nt at their 3' termini; (v) (±) foldback RNAs comprising about one-third of all (-)-strand reads and (vi) a higher proportion of full-length gRNAs in roots than in leaves, suggesting that roots may be functioning as a gRNA reservoir. These findings suggest that viral transcriptomes are much more complex than previously thought.

Analysis of bacterial transcriptome and epitranscriptome using nanopore direct RNA sequencing

Bacterial gene expression is a complex process involving extensive regulatory mechanisms. Along with growing interests in this field, Nanopore Direct RNA Sequencing (DRS) provides a promising platform for rapid and comprehensive characterization of bacterial RNA biology. However, the DRS of bacterial RNA is currently deficient in the yield of mRNA-mapping reads and has yet to be exploited for transcriptome-wide RNA modification mapping. Here, we showed that pre-processing of bacterial total RNA (size selection followed by ribosomal RNA depletion and polyadenylation) guaranteed high throughputs of sequencing data and considerably increased the amount of mRNA reads. This way, complex transcriptome architectures were reconstructed for Escherichia coli and Staphylococcus aureus and extended the boundaries of 225 known E. coli operons and 89 defined S. aureus operons. Utilizing unmodified in vitro-transcribed (IVT) RNA libraries as a negative control, several Nanopore-based computational tools globally detected putative modification sites in the E. coli and S. aureus transcriptomes. Combined with Next-Generation Sequencing-based N6-methyladenosine (m6A) detection methods, 75 high-confidence m6A candidates were identified in the E. coli protein-coding transcripts, while none were detected in S. aureus. Altogether, we demonstrated the potential of Nanopore DRS in systematic and convenient transcriptome and epitranscriptome analysis.

Enhancing transcriptome expression quantification through accurate assignment of long RNA sequencing reads with TranSigner

Recently developed long-read RNA sequencing technologies promise to provide a more accurate and comprehensive view of transcriptomes compared to short-read sequencers, primarily due to their capability to achieve full-length sequencing of transcripts. However, realizing this potential requires computational tools tailored to process long reads, which exhibit a higher error rate than short reads. Existing methods for assembling and quantifying long-read data often disagree on expressed transcripts and their abundance levels, leading researchers to lack confidence in the transcriptomes produced using this data. One approach to address the uncertainties in transcriptome assembly and quantification is by assigning the long reads to transcripts, enabling a more detailed characterization of transcript support at the read level. Here, we introduce TranSigner, a versatile tool that assigns long reads to any input transcriptome. TranSigner consists of three consecutive modules performing: read alignment to the given transcripts, computation of read-to-transcript compatibility based on alignment scores and positions, and execution of an expectation-maximization algorithm to probabilistically assign reads to transcripts and estimate transcript abundances. Using simulated data and experimental datasets from three well-studied organisms - Homo sapiens, Arabidopsis thaliana, and Mus musculus - we demonstrate that TranSigner achieves accurate read assignments, obtaining higher accuracy in transcript abundance estimation compared to existing tools.

Quantitative profiling N1-methyladenosine (m1A) RNA methylation from Oxford nanopore direct RNA sequencing data

With the recent advanced direct RNA sequencing technique that proposed by the Oxford Nanopore Technologies, RNA modifications can be detected and profiled in a simple and straightforward manner. Majority nanopore-based modification studies were devoted to those popular types such as m6A and pseudouridine. To address current limitations on studying the crucial regulator, m1A modification, we conceived this study. We have developed an integrated computational workflow designed for the detection of m1A modifications from direct RNA sequencing data. This workflow comprises a feature extractor responsible for capturing signal characteristics (such as mean, standard deviations, and length of electric signals), a single molecule-level m1A predictor trained with features extracted from the IVT dataset using classical machine learning algorithms, a confident m1A site selector employing the binomial test to identify statistically significant m1A sites, and an m1A modification rate estimator. Our model achieved accurate molecule-level prediction (Average AUC = 0.9689) and reliable m1A site detection and quantification. To show the feasibility of our workflow, we conducted a study on in vivo transcribed human HEK293 cell line, and the results were carefully annotated and compared with other techniques (i.e., Illumina sequencing-based techniques). We believed that this tool will enabling a comprehensive understanding of the m1A modification and its functional mechanisms within cells and organisms.

Co-transcriptional gene regulation in eukaryotes and prokaryotes

Many steps of RNA processing occur during transcription by RNA polymerases. Co-transcriptional activities are deemed commonplace in prokaryotes, in which the lack of membrane barriers allows mixing of all gene expression steps, from transcription to translation. In the past decade, an extraordinary level of coordination between transcription and RNA processing has emerged in eukaryotes. In this Review, we discuss recent developments in our understanding of co-transcriptional gene regulation in both eukaryotes and prokaryotes, comparing methodologies and mechanisms, and highlight striking parallels in how RNA polymerases interact with the machineries that act on nascent RNA. The development of RNA sequencing and imaging techniques that detect transient transcription and RNA processing intermediates has facilitated discoveries of transcription coordination with splicing, 3'-end cleavage and dynamic RNA folding and revealed physical contacts between processing machineries and RNA polymerases. Such studies indicate that intron retention in a given nascent transcript can prevent 3'-end cleavage and cause transcriptional readthrough, which is a hallmark of eukaryotic cellular stress responses. We also discuss how coordination between nascent RNA biogenesis and transcription drives fundamental aspects of gene expression in both prokaryotes and eukaryotes.

Construction of a Full-Length Transcriptome of Western Honeybee Midgut Tissue and Improved Genome Annotation

Honeybees are an indispensable pollinator in nature with pivotal ecological, economic, and scientific value. However, a full-length transcriptome for Apis mellifera, assembled with the advanced third-generation nanopore sequencing technology, has yet to be reported. Here, nanopore sequencing of the midgut tissues of uninoculated and Nosema ceranae-inoculated A. mellifera workers was conducted, and the full-length transcriptome was then constructed and annotated based on high-quality long reads. Next followed improvement of sequences and annotations of the current reference genome of A. mellifera. A total of 5,942,745 and 6,664,923 raw reads were produced from midguts of workers at 7 days post-inoculation (dpi) with N. ceranae and 10 dpi, while 7,100,161 and 6,506,665 raw reads were generated from the midguts of corresponding uninoculated workers. After strict quality control, 6,928,170, 6,353,066, 5,745,048, and 6,416,987 clean reads were obtained, with a length distribution ranging from 1 kb to 10 kb. Additionally, 16,824, 17,708, 15,744, and 18,246 full-length transcripts were respectively detected, including 28,019 nonredundant ones. Among these, 43,666, 30,945, 41,771, 26,442, and 24,532 full-length transcripts could be annotated to the Nr, KOG, eggNOG, GO, and KEGG databases, respectively. Additionally, 501 novel genes (20,326 novel transcripts) were identified for the first time, among which 401 (20,255), 193 (13,365), 414 (19,186), 228 (12,093), and 202 (11,703) were respectively annotated to each of the aforementioned five databases. The expression and sequences of three randomly selected novel transcripts were confirmed by RT-PCR and Sanger sequencing. The 5' UTR of 2082 genes, the 3' UTR of 2029 genes, and both the 5' and 3' UTRs of 730 genes were extended. Moreover, 17,345 SSRs, 14,789 complete ORFs, 1224 long non-coding RNAs (lncRNAs), and 650 transcription factors (TFs) from 37 families were detected. Findings from this work not only refine the annotation of the A. mellifera reference genome, but also provide a valuable resource and basis for relevant molecular and -omics studies.

Single-Cell Sequencing Technology and Its Application in the Study of Central Nervous System Diseases

The mammalian central nervous system consists of a large number of cells, which contain not only different types of neurons, but also a large number of glial cells, such as astrocytes, oligodendrocytes, and microglia. These cells are capable of performing highly refined electrophysiological activities and providing the brain with functions such as nutritional support, information transmission and pathogen defense. The diversity of cell types and individual differences between cells have brought inspiration to the study of the mechanism of central nervous system diseases. In order to explore the role of different cells, a new technology, single-cell sequencing technology has emerged to perform specific analysis of high-throughput cell populations, and has been continuously developed. Single-cell sequencing technology can accurately analyze single-cell expression in mixed-cell populations and collect cells from different spatial locations, time stages and types. By using single-cell sequencing technology to compare gene expression profiles of normal and diseased cells, it is possible to discover cell subsets associated with specific diseases and their associated genes. Therefore, scientists can understand the development process, related functions and disease state of the nervous system from an unprecedented depth. In conclusion, single-cell sequencing technology provides a powerful technology for the discovery of novel therapeutic targets for central nervous system diseases.

Sequencing accuracy and systematic errors of nanopore direct RNA sequencing

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.

The Applications of Nanopore Sequencing Technology in Animal and Human Virus Research

In recent years, an increasing number of viruses have triggered outbreaks that pose a severe threat to both human and animal life, as well as caused substantial economic losses. It is crucial to understand the genomic structure and epidemiology of these viruses to guide effective clinical prevention and treatment strategies. Nanopore sequencing, a third-generation sequencing technology, has been widely used in genomic research since 2014. This technology offers several advantages over traditional methods and next-generation sequencing (NGS), such as the ability to generate ultra-long reads, high efficiency, real-time monitoring and analysis, portability, and the ability to directly sequence RNA or DNA molecules. As a result, it exhibits excellent applicability and flexibility in virus research, including viral detection and surveillance, genome assembly, the discovery of new variants and novel viruses, and the identification of chemical modifications. In this paper, we provide a comprehensive review of the development, principles, advantages, and applications of nanopore sequencing technology in animal and human virus research, aiming to offer fresh perspectives for future studies in this field.

Exploring the transcriptional landscape of phage-host interactions using novel high-throughput approaches

In the last decade, powerful high-throughput sequencing approaches have emerged to analyse microbial transcriptomes at a global scale. However, to date, applications of these approaches to microbial viruses such as phages remain scarce. Tailoring these techniques to virus-infected bacteria promises to obtain a detailed picture of the underexplored RNA biology and molecular processes during infection. In addition, transcriptome study of stress and perturbations induced by phages in their infected bacterial hosts is likely to reveal new fundamental mechanisms of bacterial metabolism and gene regulation. Here, we provide references and blueprints to implement emerging transcriptomic approaches towards addressing transcriptome architecture, RNA-RNA and RNA-protein interactions, RNA modifications, structures and heterogeneity of transcription profiles in infected cells that will provide guides for future directions in phage-centric therapeutic applications and microbial synthetic biology.

Tail-tape-fused virion and non-virion RNA polymerases of a thermophilic virus with an extremely long tail

Thermus thermophilus bacteriophage P23-45 encodes a giant 5,002-residue tail tape measure protein (TMP) that defines the length of its extraordinarily long tail. Here, we show that the N-terminal portion of P23-45 TMP is an unusual RNA polymerase (RNAP) homologous to cellular RNAPs. The TMP-fused virion RNAP transcribes pre-early phage genes, including a gene that encodes another, non-virion RNAP, that transcribes early and some middle phage genes. We report the crystal structures of both P23-45 RNAPs. The non-virion RNAP has a crab-claw-like architecture. By contrast, the virion RNAP adopts a unique flat structure without a clamp. Structure and sequence comparisons of the P23-45 RNAPs with other RNAPs suggest that, despite the extensive functional differences, the two P23-45 RNAPs originate from an ancient gene duplication in an ancestral phage. Our findings demonstrate striking adaptability of RNAPs that can be attained within a single virus species.

Direct Analysis of HIV mRNA m6A Methylation by Nanopore Sequencing

The post-transcriptional processing and chemical modification of HIV RNA are understudied aspects of HIV virology, primarily due to the limited ability to accurately map and quantify RNA modifications. Modification-specific antibodies or modification-sensitive endonucleases coupled with short-read RNA sequencing technologies have allowed for low-resolution or limited mapping of important regulatory modifications of HIV RNA such as N6-methyladenosine (m6A). However, a high-resolution map of where these sites occur on HIV transcripts is needed for detailed mechanistic understanding. This has recently become possible with new sequencing technologies. Here, we describe the direct RNA sequencing of HIV transcripts using an Oxford Nanopore Technologies sequencer and the use of this technique to map m6A at near single nucleotide resolution. This technology also provides the ability to identify splice variants with long RNA reads and thus, can provide high-resolution RNA modification maps that distinguish between overlapping splice variants. The protocols outlined here for m6A also provide a powerful paradigm for studying any other RNA modifications that can be detected on the nanopore platform.

The Use of Nanopore Sequencing to Analyze the Chloroplast Transcriptome Part II: Bioinformatic Analyzes and Virtual RNA Blots

Nanopore sequencing of full-length cDNAs offers unprecedented details of the plastid RNA metabolism. After the generation of the nanopore reads, several bioinformatic steps are required to analyze the data. In this chapter, we describe in a few simple command lines the processing and mapping of the reads as well as the generation of virtual Northern blots as a simple and familiar way to visualize Nanopore sequencing data.

The Use of Nanopore Sequencing to Analyze the Chloroplast Transcriptome Part I: Library Preparation

Global understanding of plastid gene expression has always been impaired by its complexity. RNA splicing, editing, and intercistronic processing create multiple transcripts isoforms that can hardly be resolved using traditional molecular biology techniques. During the last decade, the wide adoption of RNA-seq-based techniques has, however, allowed an unprecedented understanding of all the different steps of chloroplast gene expression, from transcription to translation. Current strategies are nonetheless unable to identify and quantify full length transcripts isoforms, a limitation that can now be overcome using Nanopore Sequencing. We here provide a complete protocol to produce, from total leaf RNA, cDNA libraries ready for Nanopore sequencing. While most Nanopore protocols take advantage of the mRNA polyA tail we here first ligate an RNA adapter to the 3' ends of the RNAs and use it to initiate the template switching reverse transcription. The cDNA is then prepared and indexed for use with the regular Oxford Nanopore v14 chemistry. This protocol is of particular interest to researchers willing to simultaneously study the multiple post-transcriptional processes prevalent in the chloroplast.

An optimized workflow of full-length transcriptome sequencing for accurate fusion transcript identification

Next-generation sequencing has revolutionized cancer genomics by enabling high-throughput mutation screening yet detecting fusion genes reliably remains challenging. Long-read sequencing offers potential for accurate fusion transcript identification, though challenges persist. In this study, we present an optimized workflow using nanopore sequencing technology to precisely identify fusion transcripts. Our approach encompasses a tailored library preparation protocol, data processing, and fusion gene analysis pipeline. We evaluated the performance using Universal Human Reference RNA and human adenocarcinoma cell lines. Our optimized nanopore sequencing workflow generated high-quality full-length transcriptome data characterized by an extended length distribution and comprehensive transcript coverage. Validation experiments confirmed novel fusion events with potential clinical relevance. Our protocol aims to mitigate biases and enhance accuracy, facilitating increased adoption in clinical diagnostics. Continued advancements in long-read sequencing promise deeper insights into fusion gene biology and improved cancer diagnostics.

Uncovering the temporal dynamics and regulatory networks of thermal stress response in a hyperthermophile using transcriptomics and proteomics

IMPORTANCE

Extreme environments provide unique challenges for life, and the study of extremophiles can shed light on the mechanisms of adaptation to such conditions. Pyrococcus furiosus, a hyperthermophilic archaeon, is a model organism for studying thermal stress response mechanisms. In this study, we used an integrated analysis of RNA-sequencing and mass spectrometry data to investigate the transcriptomic and proteomic responses of P. furiosus to heat and cold shock stress and recovery. Our results reveal the rapid and dynamic changes in gene and protein expression patterns associated with these stress responses, as well as the coordinated regulation of different gene sets in response to different stressors. These findings provide valuable insights into the molecular adaptations that facilitate life in extreme environments and advance our understanding of stress response mechanisms in hyperthermophilic archaea.

Leptospira transcriptome sequencing using long-read technology reveals unannotated transcripts and potential polyadenylation of RNA molecules

IMPORTANCE

Leptospirosis, caused by the spirochete bacteria Leptospira, is a zoonotic disease of humans and animals, accounting for over 1 million annual human cases and over 60,000 deaths. We have characterized operon transcriptional units, identified novel RNA coding regions, and reported evidence of potential posttranscriptional polyadenylation in the Leptospira transcriptomes for the first time using Oxford Nanopore Technology RNA sequencing protocols. The newly identified RNA coding regions and operon transcriptional units were detected only in the pathogenic Leptospira transcriptomes, suggesting their significance in virulence-related functions. This article integrates bioinformatics, infectious diseases, microbiology, molecular biology, veterinary sciences, and public health. Given the current knowledge gap in the regulation of leptospiral pathogenicity, our findings offer valuable insights to researchers studying leptospiral pathogenicity and provide both a basis and a tool for researchers focusing on prokaryotic molecular studies for the understanding of RNA compositions and prokaryotic polyadenylation for their organisms of interest.

Current technical advancements in plant epitranscriptomic studies

The growth and development of plants are the result of the interplay between the internal developmental programming and plant-environment interactions. Gene expression regulations in plants are made up of multi-level networks. In the past few years, many studies were carried out on co- and post-transcriptional RNA modifications, which, together with the RNA community, are collectively known as the "epitranscriptome." The epitranscriptomic machineries were identified and their functional impacts characterized in a broad range of physiological processes in diverse plant species. There is mounting evidence to suggest that the epitranscriptome provides an additional layer in the gene regulatory network for plant development and stress responses. In the present review, we summarized the epitranscriptomic modifications found so far in plants, including chemical modifications, RNA editing, and transcript isoforms. The various approaches to RNA modification detection were described, with special emphasis on the recent development and application potential of third-generation sequencing. The roles of epitranscriptomic changes in gene regulation during plant-environment interactions were discussed in case studies. This review aims to highlight the importance of epitranscriptomics in the study of gene regulatory networks in plants and to encourage multi-omics investigations using the recent technical advancements.

Membrane-Vesicle-Mediated Interbacterial Communication Activates Silent Secondary Metabolite Production

Most bacterial biosynthetic gene clusters (BGCs) are "silent BGCs" that are expressed poorly or not at all under normal culture conditions. However, silent BGCs, even in part, may be conditionally expressed in response to external stimuli in the original bacterial habitats. The growing knowledge of bacterial membrane vesicles (MVs) suggests that they could be promising imitators of the exogenous stimulants, especially given their functions as signaling mediators in bacterial cell-to-cell communication. Therefore, we envisioned that MVs added to bacterial cultures could activate diverse silent BGCs. Herein, we employed Burkholderia multivorans MVs, which induced silent metabolites in a wide range of bacteria in Actinobacteria, Bacteroidetes and Proteobacteria phyla. A mechanistic analysis of MV-induced metabolite production in Xenorhabdus innexi suggested that the B. multivorans MVs activate silent metabolite production by inhibiting quorum sensing in X. innexi. In turn, the X. innexi MVs carrying some MV-induced peptides suppressed the growth of B. multivorans, highlighting the interspecies communication between B. multivorans and X. innexi through MV exchange.

Profiling the polyadenylated transcriptome of extracellular vesicles with long-read nanopore sequencing

BACKGROUND

While numerous studies have described the transcriptomes of extracellular vesicles (EVs) in different cellular contexts, these efforts have typically relied on sequencing methods requiring RNA fragmentation, which limits interpretations on the integrity and isoform diversity of EV-targeted RNA populations. It has been assumed that mRNA signatures in EVs are likely to be fragmentation products of the cellular mRNA material, and the extent to which full-length mRNAs are present within EVs remains to be clarified.

RESULTS

Using long-read nanopore RNA sequencing, we sought to characterize the full-length polyadenylated (poly-A) transcriptome of EVs released by human chronic myelogenous leukemia K562 cells. We detected 443 and 280 RNAs that were respectively enriched or depleted in EVs. EV-enriched poly-A transcripts consist of a variety of biotypes, including mRNAs, long non-coding RNAs, and pseudogenes. Our analysis revealed that 10.58% of all EV reads, and 18.67% of all cellular (WC) reads, corresponded to known full-length transcripts, with mRNAs representing the largest biotype for each group (EV = 58.13%, WC = 43.93%). We also observed that for many well-represented coding and non-coding genes, diverse full-length transcript isoforms were present in EV specimens, and these isoforms were reflective-of but often in different ratio compared to cellular samples.

CONCLUSION

This work provides novel insights into the compositional diversity of poly-A transcript isoforms enriched within EVs, while also underscoring the potential usefulness of nanopore sequencing to interrogate secreted RNA transcriptomes.

Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research

The oral microbiota has an enormous impact on human health, with oral dysbiosis now linked to many oral and systemic diseases. Recent advancements in sequencing, mass spectrometry, bioinformatics, computational biology, and machine learning are revolutionizing oral microbiome research, enabling analysis at an unprecedented scale and level of resolution using omics approaches. This review contains a comprehensive perspective of the current state-of-the-art tools available to perform genomics, metagenomics, phylogenomics, pangenomics, transcriptomics, proteomics, metabolomics, lipidomics, and multi-omics analysis on (all) microbiomes, and then provides examples of how the techniques have been applied to research of the oral microbiome, specifically. Key findings of these studies and remaining challenges for the field are highlighted. Although the methods discussed here are placed in the context of their contributions to oral microbiome research specifically, they are pertinent to the study of any microbiome, and the intended audience of this includes researchers would simply like to get an introduction to microbial omics and/or an update on the latest omics methods. Continued research of the oral microbiota using omics approaches is crucial and will lead to dramatic improvements in human health, longevity, and quality of life.

Methodologies for bacterial ribonuclease characterization using RNA-seq

Bacteria adjust gene expression at the post-transcriptional level through an intricate network of small regulatory RNAs and RNA-binding proteins, including ribonucleases (RNases). RNases play an essential role in RNA metabolism, regulating RNA stability, decay, and activation. These enzymes exhibit species-specific effects on gene expression, bacterial physiology, and different strategies of target recognition. Recent advances in high-throughput RNA sequencing (RNA-seq) approaches have provided a better understanding of the roles and modes of action of bacterial RNases. Global studies aiming to identify direct targets of RNases have highlighted the diversity of RNase activity and RNA-based mechanisms of gene expression regulation. Here, we review recent RNA-seq approaches used to study bacterial RNases, with a focus on the methods for identifying direct RNase targets.

Current concepts, advances, and challenges in deciphering the human microbiota with metatranscriptomics

Metatranscriptomics refers to the analysis of the collective microbial transcriptome of a sample. Its increased utilization for the characterization of human-associated microbial communities has enabled the discovery of many disease-state related microbial activities. Here, we review the principles of metatranscriptomics-based analysis of human-associated microbial samples. We describe strengths and weaknesses of popular sample preparation, sequencing, and bioinformatics approaches and summarize strategies for their use. We then discuss how human-associated microbial communities have recently been examined and how their characterization may change. We conclude that metatranscriptomics insights into human microbiotas under health and disease have not only expanded our knowledge on human health, but also opened avenues for rational antimicrobial drug use and disease management.

Challenges in identifying mRNA transcript starts and ends from long-read sequencing data

Long-read sequencing (LRS) technologies have the potential to revolutionize scientific discoveries in RNA biology, especially by enabling the comprehensive identification and quantification of full length mRNA isoforms. However, inherently high error rates make the analysis of long-read sequencing data challenging. While these error rates have been characterized for sequence and splice site identification, it is still unclear how accurately LRS reads represent transcript start and end sites. Here, we systematically assess the variability and accuracy of mRNA terminal ends identified by LRS reads across multiple sequencing platforms. We find substantial inconsistencies in both the start and end coordinates of LRS reads spanning a gene, such that LRS reads often fail to accurately recapitulate annotated or empirically derived terminal ends of mRNA molecules. To address this challenge, we introduce an approach to condition reads based on empirically derived terminal ends and identified a subset of reads that are more likely to represent full-length transcripts. Our approach can improve transcriptome analyses by enhancing the fidelity of transcript terminal end identification, but may result in lower power to quantify genes or discover novel isoforms. Thus, it is necessary to be cautious when selecting sequencing approaches and/or interpreting data from long-read RNA sequencing.

Sourcing Phage-Encoded Terminators Using ONT-cappable-seq for SynBio Applications in Pseudomonas

Efficient transcriptional terminators are essential for the performance of genetic circuitry in microbial SynBio hosts. In recent years, several libraries of characterized strong terminators have become available for model organisms such as Escherichia coli. Conversely, terminator libraries for nonmodel species remain scarce, and individual terminators are often ported over from model systems, leading to unpredictable performance in their new hosts. In this work, we mined the genomes of Pseudomonas infecting phages LUZ7 and LUZ100 for transcriptional terminators utilizing the full-length RNA sequencing technique "ONT-cappable-seq" and validated these terminators in three Gram-negative hosts using a terminator trap assay. Based on these results, we present nine terminators for E. coli, Pseudomonas putida, and Pseudomonas aeruginosa, which outperform current reference terminators. Among these, terminator LUZ7 T50 displays potent bidirectional activity. These data further support that bacteriophages, as evolutionary-adapted natural predators of the targeted bacteria, provide a valuable source of microbial SynBio parts.

In-depth Temporal Transcriptome Profiling of Monkeypox and Host Cells using Nanopore Sequencing

The recent human Monkeypox outbreak underlined the importance of studying basic biology of orthopoxviruses. However, the transcriptome of its causative agent has not been investigated before neither with short-, nor with long-read sequencing approaches. This Oxford Nanopore long-read RNA-Sequencing dataset fills this gap. It will enable the in-depth characterization of the transcriptomic architecture of the monkeypox virus, and may even make possible to annotate novel host transcripts. Moreover, our direct cDNA and native RNA sequencing reads will allow the estimation of gene expression changes of both the virus and the host cells during the infection. Overall, our study will lead to a deeper understanding of the alterations caused by the viral infection on a transcriptome level.

Detection of Streptococcus pyogenes M1UK in Australia and characterization of the mutation driving enhanced expression of superantigen SpeA

A new variant of Streptococcus pyogenes serotype M1 (designated 'M1_UK') has been reported in the United Kingdom, linked with seasonal scarlet fever surges, marked increase in invasive infections, and exhibiting enhanced expression of the superantigen SpeA. The progenitor S. pyogenes 'M1_global' and M1_UK clones can be differentiated by 27 SNPs and 4 indels, yet the mechanism for speA upregulation is unknown. Here we investigate the previously unappreciated expansion of M1_UK in Australia, now isolated from the majority of serious infections caused by serotype M1 S. pyogenes. M1_UK sub-lineages circulating in Australia also contain a novel toxin repertoire associated with epidemic scarlet fever causing S. pyogenes in Asia. A single SNP in the 5' transcriptional leader sequence of the transfer-messenger RNA gene ssrA drives enhanced SpeA superantigen expression as a result of ssrA terminator read-through in the M1_UK lineage. This represents a previously unappreciated mechanism of toxin expression and urges enhanced international surveillance.

An Introduction to Nanopore Sequencing: Past, Present, and Future Considerations

There has been significant progress made in the field of nanopore biosensor development and sequencing applications, which address previous limitations that restricted widespread nanopore use. These innovations, paired with the large-scale commercialization of biological nanopore sequencing by Oxford Nanopore Technologies, are making the platforms a mainstay in contemporary research laboratories. Equipped with the ability to provide long- and short read sequencing information, with quick turn-around times and simple sample preparation, nanopore sequencers are rapidly improving our understanding of unsolved genetic, transcriptomic, and epigenetic problems. However, there remain some key obstacles that have yet to be improved. In this review, we provide a general introduction to nanopore sequencing principles, discussing biological and solid-state nanopore developments, obstacles to single-base detection, and library preparation considerations. We present examples of important clinical applications to give perspective on the potential future of nanopore sequencing in the field of molecular diagnostics.

Analysis of Fowl Adenovirus 4 Transcriptome by De Novo ORF Prediction Based on Corrected Nanopore Full-Length cDNA Sequencing Data

The transcriptome of fowl adenovirus has not been comprehensively revealed. Here, we attempted to analyze the fowl adenovirus 4 (FAdV-4) transcriptome by deep sequencing. RNA samples were extracted from chicken LMH cells at 12, 18 or 26 h post-FAdV-4 infection, and subjected to Illumina strand-specific RNA-seq or nanopore full-length PCR-cDNA sequencing. After removing the reads of host cells, the data of FAdV-4 nanopore full-length cDNAs (transcripts) were corrected with reads from the Illumina RNA-seq, mapped to the viral genome and then used to predict viral open reading frames (ORFs). Other than 42 known ORFs, 39 novel ORFs were annotated to the FAdV-4 genome. Different from human adenovirus 5, one FAdV-4 ORF was often encoded by several transcripts, and more FAdV-4 ORFs were located on two exons. With these data, 18 major transcription start sites and 15 major transcription termination sites were defined, implying 18 viral promoters and 15 polyadenylation signals. The temporal cascade of viral gene transcription was observed in FAdV-4-infected cells, with six promoters possessing considerable activity in the early phase. Unexpectedly, four promoters, instead of one major late promoter, were engaged in the transcription of the viral genus-common genes on the forward strand. The clarification of the FAdV-4 transcriptome laid a solid foundation for the study of viral gene function, virulence and virus evolution, and it would help construct FAdV-4 as a gene transfer vehicle. The strategy of de novo ORF prediction could be used to parse the transcriptome of other novel adenoviruses.

Transcriptome profiling for precision cancer medicine using shallow nanopore cDNA sequencing

Transcriptome profiling is a mainstay of translational cancer research and is increasingly finding its way into precision oncology. While bulk RNA sequencing (RNA-seq) is widely available, high investment costs and long data return time are limiting factors for clinical applications. We investigated a portable nanopore long-read sequencing device (MinION, Oxford Nanopore Technologies) for transcriptome profiling of tumors. In particular, we investigated the impact of lower coverage than that of larger sequencing devices by comparing shallow nanopore RNA-seq data with short-read RNA-seq data generated using reversible dye terminator technology (Illumina) for ten samples representing four cancer types. Coupled with ShaNTi (Shallow Nanopore sequencing for Transcriptomics), a newly developed data processing pipeline, a turnaround time of five days was achieved. The correlation of normalized gene-level counts between nanopore and Illumina RNA-seq was high for MinION but not for very low-throughput Flongle flow cells (r = 0.89 and r = 0.24, respectively). A cost-saving approach based on multiplexing of four samples per MinION flow cell maintained a high correlation with Illumina data (r = 0.56-0.86). In addition, we compared the utility of nanopore and Illumina RNA-seq data for analysis tools commonly applied in translational oncology: (1) Shallow nanopore and Illumina RNA-seq were equally useful for inferring signaling pathway activities with PROGENy. (2) Highly expressed genes encoding kinases targeted by clinically approved small-molecule inhibitors were reliably identified by shallow nanopore RNA-seq. (3) In tumor microenvironment composition analysis, quanTIseq performed better than CIBERSORT, likely due to higher average expression of the gene set used for deconvolution. (4) Shallow nanopore RNA-seq was successfully applied to detect fusion genes using the JAFFAL pipeline. These findings suggest that shallow nanopore RNA-seq enables rapid and biologically meaningful transcriptome profiling of tumors, and warrants further exploration in precision cancer medicine studies.

The Baker Lab at the OHSU School of Dentistry: leveraging bioinformatics and molecular biology to discover how the bacteria that live in our mouth impact human health and disease

The microorganisms living in the human oral cavity, collectively known as the oral microbiota, play a critical role in not only oral health, but systemic and overall health. The Baker Lab leverages emerging technologies in bioinformatics and molecular biology to answer fundamental questions regarding the ecology, physiology, and pathogenesis of the oral microbiota. We use a microbial 'omics approach, which has included pioneering the use of nanopore sequencing on saliva and oral bacterial RNA. The resulting work discovered novel bacterial species and biosynthetic pathways which impact the ecology of the oral microbiota and its relationship to human disease. This article will briefly define the oral microbiota. It will also summarize how bioinformatics and 'omics-based research have revolutionized oral health research. The article will then provide a broad summary of our past, present and future research and educational programs.

Opportunities and Challenges to Profile mRNA Modifications in Escherichia coli

mRNA methylation is an important regulator of many physiological processes in eukaryotes but has not been studied in depth in prokaryotes. Working with bacterial mRNA is challenging because it lacks a poly(A)-tail. However, methods for detecting RNA modifications, both sequencing and mass spectrometry, rely on efficient preparation of mRNA. Here, we compared size-dependent separation by electrophoresis and rRNA depletion for enrichment of Escherichia coli mRNA. The purification success was monitored by qRT-PCR and RNA sequencing. Neither method allowed complete removal of rRNA. Nevertheless, we were able to quantitatively analyze several modified nucleosides in the different RNA types. We found evidence for stress dependent RNA modification reprofiling in rRNA, but also several modified nucleosides in the mRNA enriched fractions showed significant changes.

Circular Whole-Transcriptome Amplification (cWTA) and mNGS Screening Enhanced by a Group Testing Algorithm (mEGA) Enable High-Throughput and Comprehensive Virus Identification

Metagenomic next-generation sequencing (mNGS) offers a hypothesis-free approach for pathogen detection, but its applicability in clinical diagnosis, in addition to other factors, remains limited due to complicated library construction. The present study describes a PCR-free isothermal workflow for mNGS targeting RNA, based on a multiple displacement amplification, termed circular whole-transcriptome amplification (cWTA), as the template is circularized before amplification. The cWTA approach was validated with clinical samples and nanopore sequencing. Reads homologous to dengue virus 2 and chikungunya virus were detected in clinical samples from Bangladesh and Brazil, respectively. In addition, the practicality of a high-throughput detection system that combines mNGS and a group testing algorithm termed mNGS screening enhanced by a group testing algorithm (mEGA) was established. This approach enabled significant library size reduction while permitting trackability between samples and diagnostic results. Serum samples of patients with undifferentiated febrile illnesses from Vietnam (n = 43) were also amplified with cWTA, divided into 11 pools, processed for library construction, and sequenced. Dengue virus 2, hepatitis B virus, and parvovirus B19 were successfully detected without prior knowledge of their existence. Collectively, cWTA with the nanopore platform opens the possibility of hypothesis-free on-site comprehensive pathogen diagnosis, while mEGA contributes to the scaling up of sample throughput.

IMPORTANCE Given the breadth of pathogens that cause infections, a single approach that can detect a wide range of pathogens is ideal but is impractical due to the available tests being highly specific to a certain pathogen. Recent developments in sequencing technology have introduced mNGS as an alternative that provides detection of a wide-range of pathogens by detecting the presence of their nucleic acids in the sample. However, sequencing library preparation is still a bottleneck, as it is complicated, costly, and time-consuming. In our studies, alternative approaches to optimize library construction for mNGS were developed. This included isothermal nucleic acid amplification and expansion of sample throughput with a group testing algorithm. These methods can improve the utilization of mNGS as a diagnostic tool and can serve as a high-throughput screening system aiding infectious disease surveillance.

Development of ONT-cappable-seq to unravel the transcriptional landscape of Pseudomonas phages

RNA sequencing has become the method of choice to study the transcriptional landscape of phage-infected bacteria. However, short-read RNA sequencing approaches generally fail to capture the primary 5' and 3' boundaries of transcripts, confounding the discovery of key transcription initiation and termination events as well as operon architectures. Yet, the elucidation of these elements is crucial for the understanding of the strategy of transcription regulation during the infection process, which is currently lacking beyond a handful of model phages. We developed ONT-cappable-seq, a specialized long-read RNA sequencing technique that allows end-to-end sequencing of primary prokaryotic transcripts using the Nanopore sequencing platform. We applied ONT-cappable-seq to study transcription of Pseudomonas aeruginosa phage LUZ7, obtaining a comprehensive genome-wide map of viral transcription start sites, terminators, and complex operon structures that fine-regulate gene expression. Our work provides new insights in the RNA biology of a non-model phage, unveiling distinct promoter architectures, putative small non-coding viral RNAs, and the prominent regulatory role of terminators during infection. The robust workflow presented here offers a framework to obtain a global, yet fine-grained view of phage transcription and paves the way for standardized, in-depth transcription studies for microbial viruses or bacteria in general.

Ubiquitous mRNA decay fragments in E. coli redefine the functional transcriptome

Bacterial mRNAs have short life cycles, in which transcription is rapidly followed by translation and degradation within seconds to minutes. The resulting diversity of mRNA molecules across different life-cycle stages impacts their functionality but has remained unresolved. Here we quantitatively map the 3’ status of cellular RNAs in Escherichia coli during steady-state growth and report a large fraction of molecules (median>60%) that are fragments of canonical full-length mRNAs. The majority of RNA fragments are decay intermediates, whereas nascent RNAs contribute to a smaller fraction. Despite the prevalence of decay intermediates in total cellular RNA, these intermediates are underrepresented in the pool of ribosome-associated transcripts and can thus distort quantifications and differential expression analyses for the abundance of full-length, functional mRNAs. The large heterogeneity within mRNA molecules in vivo highlights the importance in discerning functional transcripts and provides a lens for studying the dynamic life cycle of mRNAs.